动议 · 2026-05-06 · 届国会 15
人工智能（AI）转型不容无就业式增长（主辩论）
人工智能（AI）转型不容无就业式增长（主辩论）
5月6日国会续辩职总秘书长黄志明提出的"人工智能转型不容无就业式增长"动议，约20名议员发言，是第15届国会迄今最具分量的AI辩论。动议要求承认AI的经济变革力量，把增长锚定在公平、韧性与人人有机会，装备工人与企业，确认新加坡不容无就业增长。执政党与工运议员聚焦岗位重设计、公司培训委员会（CTC）与新设的三方就业理事会；工人党议员全数支持动议但另提结构方案：严燕松倡全民AI股权基金（成年公民每年500新元分红加在职培训基金），Andre Low主张无收入上限的裁员保险、再培训税收抵免与"AI收益审计"，Kenneth Tiong呼吁高端AI工具全民可及。人力部长陈诗龙驳斥工人党方案是"和解金"而非赋权，引人力部调查称采用AI企业仅约6%裁员，承诺研究提高求职者援助收入门槛并推动更早裁员通报。朝野最终均表态支持动议。
关键要点
- • 约20名议员发言近7小时，朝野全数表态支持动议，但在政策工具上针锋相对
- • 工人党提全民AI股权基金（成人每年500新元分红）与无收入上限裁员保险
- • 陈诗龙引人力部调查：采用AI企业仅约6%裁员，七成已见生产力提升
- • 政府允研究提高求职者援助收入门槛，推动雇主在员工离职前通报裁员
政府拒绝以现金再分配为主的保障路线，坚持"投资于人"：通过技能与劳动力发展局、三方就业理事会和企业劳动力转型配套让工人随AI增长共同进步，承诺"保不住每一份工作，但会保护每一个工人"。
工人党议员支持动议本身，但批评现行求职者援助计划门槛过低、递减设计逼工人仓促就业，主张无收入上限的裁员保险、全民AI股权基金、再培训税收抵免与强制性AI转型通知等结构性保障。
AI就业冲击已升为国家级议程：政府明确以三方机制而非立法保障应对AI转型，公共资助将与工人成果挂钩，求职者援助计划门槛与裁员通报制度料将检讨增强。
“你们两位的提案都不是赋权。在我看来，那是一种和解金——认定大规模岗位流失不可避免，我们能做的最多只是减轻冲击。”
参与人员 (12)
完整译文（中文）
Hansard 原始记录 · 2026-06-09
（程序文本）恢复就问题进行的辩论[2026年5月5日]，（程序文本）
（程序文本）本院——（程序文本）
[(议事文本)1. 承认新技术特别是人工智能(AI)的变革力量推动新加坡经济发展的下一阶段；(议事文本)]
（程序文本）2. 强调新加坡的人工智能驱动增长方案必须以公平、韧性和全民机会为基础；（程序文本）
[(议事文本)3. 决心为工人和企业提供装备和支持，以抓住新机遇并共同前进；以及(议事文本)]
（程序文本）4. 确认经济进展必须保持包容性，新加坡不能出现无就业增长，因为每一名工人都很重要。（程序文本）
（程序文本）问题再次提出。（程序文本）
下午12时32分 议长：Mark Lee 先生。
Mark Lee 先生（委任议员）：议长先生，基于我的同事、全国职工总会（NTUC）秘书长Ng昨晚所做的演讲，我想着重关注这项议案如何在企业层面真正实现。
先生，防止无就业增长不能仅依靠工人支持来实现。它还必须融入企业转型的方式、岗位重新设计的方式以及我们的体系支持企业自信前行的方式。
历史表明，在技术变革时期，赢家不是那些试图保护现有商业模式的企业，而是那些充分理解自身基础优势并能够将其重新部署到新领域的企业。Fujifilm就是一个例子。它没有通过试图销售更多胶片来渡过胶片行业的崩溃，而是基于材料、光学和成像技术的能力，进入了护肤、诊断和医疗保健技术领域。
在新加坡已具有优势的行业——先进制造业、物流和连通性、金融和医疗保健——人工智能并非在替代产业本身，而是改变了价值在产业内创造的方式。这是新加坡现在需要的思维方式。我们的任务不是逐一保留现有的每一份工作。我们的任务是帮助我们的企业和劳动力识别他们的优势，适应这些变化，并携手进入增长的下一阶段。
我的发言将分为三个部分：首先，人工智能如何实际上为企业创造价值；其次，它对就业和工作者的影响；第三，我们如何能构建一个更清晰的企业入口和一座更宽的桥梁，使企业和工作者能够共同渡过转变。
议长先生，企业采纳人工智能是因为它能带来可衡量的成果。证据已经显现。在客户服务领域，生成式人工智能将生产力提高了约15%，在经验较少的工作者中获益更大。企业在软件工程方面也看到了两位数的增长，而在运营和供应链中，人工智能正在改善预测、减少浪费并优化库存和物流。
其次，人工智能不仅仅改进工作。它重新配置工作。全球证据表明，人工智能的采纳越来越集中在高技能工作者中，企业在由人工智能支持的较小、更有经验的团队周围重新组织工作。这造成了双重风险：首先，生产力收益可能更多地流向已经处于领先地位的人，加剧不平等；其次，它有可能侵蚀职业生涯的底层。
如果入门级职位减少过快，工作者通过经验积累判断力的传统途径将被打破。企业可能仍然需要中层能力，但较少有工作者会有机会培养这种能力。这是一个结构性问题。
与此同时，新角色正在涌现，包括将人工智能集成到工作流程中、验证输出、重新设计工作和将领域知识转化为解决方案。DBS和Mastercard等公司正在使用人工智能来处理日常查询并大规模个性化响应，将人工代理释放出来从事更高价值的工作。我们在中小企业（SME）中也看到同样的情况。例如，护肤公司MTM Labo使用名为Hana的人工智能工具来支持多语言客户咨询，使其团队能够专注于更复杂的、高接触度的互动。
这是一个重要观点。人工智能在思虑周全的部署下，不仅仅是替代工作。它改变了工作的性质，并能提高人类工作的价值。
但采纳并非即插即用。它需要集成到工作流程中、流程重新设计以及与商业战略的协调。这是许多企业，特别是中小企业，在将人工智能转化为实施时面临的挑战所在。如果我们不解决这个问题，能力将集中在较大的企业和更高技能的工作者中。差距将扩大。这一结果将直接违背这项议案的精神。
然而，我们也必须谨慎对待如何应对这些变化。
我理解Ng先生要求提早通知裁员以更好地支持工作者的良好初衷。但如果企业还没有准备好重新设计工作或以不同的方式安置工作者，仅提早通知是无法解决问题的。
如果人工智能正在重新组织工作，也许更加重要的更好解决方案不是我们是否在失业后更早介入，而是在失业成为必要之前足够早地介入。我们应该将重点从管理裁员转向使所有企业都能够重新设计工作和对工人进行再培训，使得他们的转变和劳动力调整同时进行，而不是在转变之后。
这引出了我的第三点——我们如何架起前路的桥梁？一座足够宽阔使许多人都能通过的桥梁，而非仅供少数人通过的桥梁。
最近推出的企业劳动力转型计划（Enterprise Workforce Transformation Package）是正确方向上的一步。在新加坡工商联合会（SBF）和新加坡全国雇主协会（SNEF）作为项目合作伙伴的情况下，企业可以获得咨询支持来重新设计流程和工作角色，并利用SkillsFuture劳动力发展补助金（SkillsFuture Workforce Development Grant）进行咨询、劳动力技术采纳和能力建设。这是一个有意义的转变。
然而，目前，企业仍在应对多项计划、多个机构和多个审批流程，在速度最为重要的时刻放缓了采纳。但我很欣慰听到Tan部长昨晚所说，SkillsFuture新加坡和劳动力新加坡将合并为技能和劳动力发展局（Skills and Workforce Development Agency），旨在解决这个问题。
但我们能否为帮助企业做更多的事呢？
这涉及我讨论的实用性的第一个方面。前进的一种方式是，人工智能补助和计划采用更加综合的方式，使企业可以通过单一界面获得这种支持，而不是应对多个机构，并灵活地部署它，无论是用于基本实施、订阅还是实验，而无需重复的审批层次，就像SkillsFuture企业信用钱包（SkillsFuture Enterprise Credit wallet）一样。
对于规模更大或更复杂的定制项目，也可能有理由提供更多的前期支持，以便企业在进行长期投资时不受现金流的制约。
与此同时，我们必须认识到人工智能的采纳涉及实验。并非每个项目都会成功。如果企业尽管真诚努力仍然受到惩罚，我们有可能会阻碍创新。如果我们希望企业果断行动，对失败的合理容忍将是必要的。
第二个维度是规模化能力建设。经验丰富的人工智能专业人士的人才库仍然很小且竞争激烈。如果我们对引进外国人工智能人才过于限制，我们将减缓整个经济的能力建设。因此，我们为打造宽广桥梁所做的努力也必须意味着保持我们的人才管道开放。不仅是为了引进人才，而且要让这些人才在各企业和行业间进行技能交叉流动。
对于中小企业，我们可以考虑的一个领域是提供有针对性的灵活性，以引入超越现有人力资源限制的专门AI专业知识。这可以是有时间限制的、按申请基础进行的，并配备一些措施防止滥用。
第三个维度是通过我们的高等教育学院（IHLs）。高等教育学院可以更刻意地定位为应用AI的执行平台，特别是通过以研究生课程为中心的卓越中心。许多研究生，包括外国人才，带有丰富的行业经验和技术深度。与本地本科生配对时，形成了一个实用的能力转移模式。如果以真实的中小企业和部门问题为中心，这些团队可以超越概念验证工作，开发可部署的解决方案。
这实现了几个目标。它降低了中小企业的实验成本，同时促进了国际和本地人才之间的交叉融合，并创建了一个初创企业的管道，以新加坡为中心，专注于解决真实的行业需求。
这个模式也有助于应对职业发展阶梯断层的问题。随着入门级途径变窄，让学生参与真实问题解决可以更早地建立能力。与此同时，它强化了我们学生的批判性思维，使他们准备好质疑和验证AI，而不是仅仅依赖AI。
第四个维度是行业赋能。今天，许多公司在孤立地试图解决类似的AI问题。这导致了努力的重复、更高的实验成本和更缓慢的采用。
行业协会和商会在结构上处于解决这个差距的位置。它们在政府政策和企业级行为的界面处运作，可以将国家AI战略转化为特定部门的实施。它们可以充当协调平台，识别共同的行业问题，汇聚需求，并与解决方案供应商和高等教育学院合作，开发与实际工作流程和职位相符的综合、可部署的解决方案。
让我举例说明。新加坡商人联合会正在开发一个AI工具，以帮助企业理解自由贸易协定的原产地规则，以及在商品出口到海外时如何申请优惠关税待遇。这是一个行业主导方法如何减少重复和提高效率的例子。
对于许多中小企业，挑战也在于应用能力。企业想知道应该优先考虑哪些问题，谁可以帮助以及如何在不过度成本或风险的情况下进行。
新加坡中华总商会（SCCCI）与信息通信媒体发展局（IMDA）联合推出的AI体验计划作为支持数字企业蓝图的举措，清楚地说明了这一点。它被过度申请是因为中小企业正在寻求有指导的入口点。
同样，SCCCI的AI赋能计划允许中小企业定义真实问题，并与南洋理工学院、新加坡理工学院、淡马锡理工学院和新加坡科技设计大学（SUTD）的学生合作开发解决方案。中小企业获得了可行的解决方案。学生获得了相关的经验。知识在整个系统中传播。有了适当的支持和资金，行业协会和商会可以成为加速各部门AI采用的平台。
最后，议长先生，第五个也是最重要的维度是人力资本。AI驱动增长的成功将不仅由我们部署多少工具决定，还由我们引导多少工人度过这种变化决定。
我同意吴先生的观点，无论是由于AI还是行业整合而被替换的工人在过渡期间都需要更强的支持。但我们也应该考虑该支持如何构建。
今天，许多都遵循'先培训后安置'方法，其中工人首先被重新培训，然后被支持找工作。实际上，这可能是不确定的。没有工人想被裁员，花几个月时间培训，然后仍然面临下一份工作的不确定性。因此，我们应该更刻意地朝着'先安置后培训'模式前进。如果另一家公司准备接纳一名被替换的工人，即使适应不是立即的，我们应该直接支持这种过渡。这可以通过向接纳企业提供临时工资支持来完成，类似于工作支持计划（JSS）的精神，但以行业过渡基金为中心，使公司有动力优先招聘然后进行在岗培训。
这缩短了工人的不确定性期间，同时给公司信心接纳和培养新人才。这也是行业协会和商会以及工会可以发挥协调作用的地方——识别有需求的公司，并将其与面临风险的工人相匹配。
最后，议长先生，开放的桥梁必须是道德和社会契约，该契约的核心是信任。工人必须将AI视为赋能工具，而不是威胁。如果AI被视为消除工作或关闭途径的工具，采用将减缓，不是因为公司缺乏技术，而是因为缺乏信任。
如果信任被打破，我们可能会无意中创造一个双输的结果，即政府干预更受限制的关于AI采用的劳动监管，提高长期成本并减少企业的灵活性。因此，必须通过AI的部署方式、工作的重新设计以及工人如何度过变化来刻意建立信任。
先生，我是一个商人，我加入支持我的工会兄弟吴先生在这项动议中的号召，因为我相信这体现了为新加坡服务良好的真正三方合作精神。
我们不能说每个工人都重要，然后让工人独自度过这种过渡。企业必须领导重新设计工作和投资于其人民。工人必须向前迈进并适应。政府必须确保系统使两者都能够。只有这样，工人和企业才能共同进步。
议长先生，这项动议反映了新加坡决心正确处理这个问题。让我们采取积极的道路共同合作，尽早建立信任，并确保AI扩展机会而不是缩小机会。先生，我强烈支持这项动议。[掌声。]
议长：Saktiandi Supaat先生。
下午12点49分 Saktiandi Supaat先生（Bishan-Toa Payoh）：议长先生，在我开始之前，我想声明我在新加坡的一家银行、金融机构工作。我还是电力和天然气雇员工会（UPAGE）和物流和供应链工会（SCEU）的顾问。
议长先生，我首先要感谢全国工人大会秘书长兼议员吴庆铭先生提出这项重要动议，并阐述了需要一个新的AI驱动增长契约，该契约将工人置于我们转变的中心，以公平、韧性和全民机会为基础。
我将专注于我们如何建立一个更具包容性的AI经济，其中增长不仅强劲，而且广泛共享。
AI不再是新兴的；它已经在重塑我们的工作和生活方式。除了众所周知的AI工具，我在与UPAGE和SCEU的合作中，以及最近人力资源政府议会委员会对SMRT、NTUC Finest at Punggol和Chye Thiam Maintenance Pte Ltd的学习之旅中亲眼见证了这一点。
在不同的部门，电力和天然气、供应链、运输、零售、食品和饮料（F&B）、清洁和设施管理，所有这些都在工作流程中嵌入AI、自动驾驶车辆（AVs）和机器人，提高生产力，创建新工作，为现有工人重新设计角色。
现在存在AI创新和应用的全球竞争。并且越来越相信那些早期和果断行动的经济体和公司将捕获最大价值。
但议长先生，正如本议院一直强调的那样，经济成功必须是包容性的。经济成功不仅仅是增长，而是其利益如何广泛分享。不均匀的增长不是新加坡应该遵循的模式。除了我们通过税收措施和有针对性的援助实施的再分配措施外，我们必须培养一种持久的心态，以确保AI驱动的增长是包容性的。
AI的使用引发了许多工人的关注。例如，AI会夺走我的工作吗？它会导致无工作增长吗？
根据全国工人大会每年进行的新加坡经济情感调查，AI会替代他们的工作或当前职位的恐惧对专业人士、经理和技术人员（PMETs）和入门级求职者更为明显。对于非PME和低薪员工，关注程度较低可能是因为他们不广泛使用AI工具，并且不了解AI将如何影响他们的工作机会，而不是因为不存在AI破坏风险。
这些关注得到全球工作重组的新闻以及AI在不同部门和职业间采用不均衡的加强。
尊敬的议长先生，让我用我所在的金融部门的具体例子来说明这种不均衡。在新加坡的银行业，人工智能不再是新兴技术，而是已经深度融入并成为生产力的核心驱动力。在整个部门，我们本地的银行正在运营和客户服务中部署自动化，特别是在劳动密集型和重复性流程中。这些不是试验性用例；它们正在改变整个价值链上的工作方式。
人工智能现在被用于运营中，如处理、结算和合规，以及通过支持更快速和更一致承保的机器学习模型进行信用评估。它甚至开始——好吧，我不会说是开始；它已经在招聘中发挥更大的作用，特别是在初始筛选中。
但这种影响并不是均匀的。日常文秘和处理工作受影响最大，而招聘正在转向数据、人工智能、网络安全和治理方面的更高技能岗位。与此同时，监管正在维持对风险、合规和审计监督角色的需求。
但最重要的是，更复杂的工作仍然需要人类的判断。处理细微的客户问题、管理关系和做出判断决策不能轻易自动化。因此，许多职位不是在消失而是在演变。例如，信用官员正在转向解释和监督，而客服中心的角色正在转向体验、升级和建立信任。所以，我们看到的不是大规模的工作替代，而是工作中任务的重新配置。
尊敬的议长先生，虽然许多人工智能讨论关注PMETs，但我们不能忽视熟练的技工和我们的蓝领工人。我们的电工、技术人员和维护工人是必不可少的。人工智能无法独自修理电梯或维护地铁系统。随着我们的经济变得更加数字化，这些角色将变得更加复杂，而不是更简单。实际上，它们是高度掌握的职业。
如果人工智能提高了对技能的溢价，我们也必须提高对掌握技能的认可方式。但除了认可之外，我们还必须重新思考如何建立掌握技能。当人工智能改变工作的执行方式时，我们也必须重新思考如何传输技能。
如今，我们的许多行业转型地图（ITMs）指导部门增长和劳动力发展。但它们在很大程度上是为前人工智能时代设计的。更新这些框架可能是有价值的，以明确说明人工智能如何改变学徒制和在职培训途径。这个问题以前在这个议会中提出过，值得重新关注。
特别是，我们应该考虑是否需要在ITMs之外建立行业培训连续性地图，以确保即使人工智能承担更多常规任务，我们也继续维持深度熟练的人类工人的强大管道，特别是在掌握技能、判断力和动手专业知识无法被替代的角色中。
如今，这在熟练的技行业中不那么明显。这就是为什么我在上次供应委员会中也提议了一个国家技工大师认证框架，以认可进展、奖励深厚技能并整合人工智能能力。
如果我们做对了，人工智能不会掏空中等技能工作，而是会提升它们。这也将进一步帮助提升我们技术教育学院（ITEs）和理工学院的熟练毕业生。
尊敬的议长先生，鉴于人工智能的巨大机遇和风险，作为增长引擎的人工智能需要有利于工人和公民的合理政策。阿拉伯联合酋长国和芬兰等国家已经采纳了协调一致的国家人工智能战略，结合政府领导、企业采用和劳动力发展。
在新加坡，我们已经采取了重要步骤。2026年预算宣布了由总理劳伦斯·黄领导的国家人工智能委员会的建立，以及通过企业创新计划为企业提供激励措施，并通过SkillsFuture和TechSkills Accelerator为工人提供支持。
我想提供一些建议，以更有效地装备工人和企业，确保没有工人掉队。
首先，我们必须使人工智能成为生活的常态。我们必须超越培训途径和时间受限的人工智能工具访问。虽然我欢迎通过政府和NTUC倡议提供临时访问，但我们必须思考在订阅初始阶段之后会发生什么。
许多更强大的人工智能工具需要持续的订阅。随着时间推移，这可能会在能够定期使用这些工具的人和无法使用的人之间造成分裂。如果不加以解决，我们冒着在人工智能'有者'和'无者'之间创造新形式不平等的风险。
由于对人工智能工具的访问直接影响生产力、学习和收入潜力，不平等的访问将转化为不平等的结果。因此，我们应该考虑如何确保持续和可负担的访问，特别是对低收入工人、自由职业者、技工和小企业。
可能的方法包括基础级别的补贴性访问，类似于数字连接，与行业伙伴的分层或基于群体的定价，通过社区中心、图书馆和培训中心的共享访问，以及确保接收人工智能支持的雇主也向工人提供访问权限。
尊敬的议长先生，如果人工智能是包容性增长的力量，获取权不能是特权，必须被广泛共享。在数字时代，获取人工智能可能会变得像获取互联网一样基本。我们必须确保没有新加坡人因价格原因被排除在那个未来之外。
推动采用的一种方式是让政府成为有用人工智能工具的'第一客户'，并缓解与人工智能转型相关的担忧。启用人工智能的系统可以为利用政府服务的公民提供更快和更实用的回应。随着人工智能系统持续向新加坡人提供有用的结果和快速建议，对人工智能和人工智能采用的信心将增长。
在这一背景下，我也想承认政府为支持工人适应以人工智能塑造的经济、保持就业为中心成果并缓解工作焦虑所做的努力。
因此，需要承认，例如，在M³和焦点地区4（FA4）框架下，马来/穆斯林社区的就业成果已经在规模和有针对性支持下实现。在2022年至2025年间，新加坡劳动力部和NTUC的就业和就业能力研究所（e2i）协助了超过29,000名马来/穆斯林求职者，其中超过19,000人成功获得就业。
与此同时，通过M³和FA4下的社区途径，超过6,000名求职者获得了接触，其中超过500人成功就业，包括需要更持续支持的求职者。这反映了我们国家就业系统的广度和我们社区为中心的干预的深度。基于此，FA4工作流将加强其对支持工人适应以人工智能塑造的经济的关注，保持就业为中心成果。
我很高兴NTUC将通过NTUC的e2i与MENDAKI紧密合作，加强职业转换，特别是对于从校园过渡到职业的年轻成人。这些年轻成人可能在对工作关联性和人工智能驱动的岗位流失的高度不确定中进入劳动力市场。这包括通过与高等教育机构（IHL）合作并整合e2i的职业服务、工作匹配和雇主网络来加强早期职业途径，使新毕业生为变化中的劳动力市场做好更充分的准备。
对于服务不足的马来/穆斯林工人，作为初步步骤，MENDAKI和NTUC的e2i联合试点了社区环境中的Langkah Digital AI研讨会，并计划在今年进一步扩大规模；我计划参加其中一些研讨会。总的来说，这些有意的就业相关干预将有助于确保人工智能的生产力收益不会导致无就业增长，而是为新加坡人赋能，跨越生命各阶段，适应、保持就业能力并充满信心地进步，得到NTUC、其伙伴和更广泛的劳动力运动的支持。因此，我鼓励我们的社区利用这些举措进行技能提升。
第二，我们必须关注支持人工智能的基础设施。新加坡已经投资于强大的数字基础设施。诸如Singpass这样的系统已经允许安全交易，包括具有法律约束力的流程，例如持久授权书。下一步是通过应用程序编程接口（APIs）增强互操作性，以便更多服务可以无缝集成。
当服务集成时，人工智能可以显著提高效率和用户体验。与此同时，我们必须对数据共享框架和安全港进行调整，以便数据可以被负责任地使用而不会阻碍创新。
第三，我们必须确保雇主重新设计工作流程以有意义地嵌入人工智能。议员Mark Lee已经提到了这一点。单独的培训是不够的。虽然企业劳动力转型计划提供了有用的支持，但它倾向于覆盖已经倾向于转变的大公司。我们需要采取进一步的行动。
一种可能性是推出"人工智能双语"认证，针对雇主而不仅仅是工人和求职者。虽然它可以是自愿"选择加入"的基础，比如BCA的绿色建筑认证计划或TAFEP的公平雇用徽章，但该认证可以与某些其他利益或配额关联，以激励公司主动参与。与现有的自愿计划一样，这可以与激励措施联系起来，以鼓励更广泛的参与。
第四，我们必须支持传统雇主的员工、技工、低工资工人和平台工人。人工智能可以充当个人助手，增强生产力和收入。例如，技工可以使用人工智能工具生成报价单、发票和客户回应；低工资工人可以使用人工智能进行日程安排和财务规划；平台工人可以优化跨平台的路线和工作，增加自主权。政府是否有可能投资于此类工具并提供时间有限的访问权，以便这些工人能够体验其实际好处？
最后，我们必须认识到并非所有工人都有相同的能力适应人工智能。时间限制、照顾责任和人生阶段挑战影响参与培训。我们应该向前推进，促进灵活学习；将培训融入工作；并加强跨部门流动性。这确保我们的劳动力保持灵活、流动和包容。尊敬的议长先生，请允许我现在用马来语发言。
(用马来文)：【请参阅《方言演讲》。】我们希望每一位工人都能获得他们所需的支持以提升技能，不被人工智能的持续进步所甩在身后。通过与马来/穆斯林工人的互动，许多人将人工智能视为一个机遇，但也担忧他们无法跟上这种快速的技术进步。
这种担忧是有效的。人工智能正在改变我们的工作方式。特别是PMET开始提出疑问：我的技能仍然相关吗？我能适应这些变化吗？根本问题是：这个人工智能经济中还有我的位置吗，还是我会被甩在身后？
作为经济韧性委员会的联合主席，与万里扎尔博士合作，我们的目标明确——通过以开放和准备的态度拥抱人工智能转变，来建设和加强我们社区的经济韧性。我们希望的增长能创造机会并赋能工人，而不是取代他们。
我们将评估经济战略审查委员会将阐述的经济转变的影响，识别新的行业和增长机会，以及了解我们如何能够鼓励马来/穆斯林社区更广泛地参与这些领域。同时，我们正在制定有针对性的战略，以加强社区在经济转变倡议中的参与，确保参与能够在所有阶层——从青年到专业人士和企业家——中得到深化。
在马来/穆斯林社区中，这项工作已经开始，并必须通过M³（现更名为M³+）来加强。让我分享一些由马来/穆斯林机构所进行的努力的例子，以提升我们社区的人工智能素养。
我们看到了令人鼓舞的倡议。在新加坡伊斯兰宗教理事会（MUIS）及清真寺，人工智能素养计划帮助社区理解负责任地使用技术。IftaSG倡议在法特瓦研究中运用人工智能。鼓励深思熟虑的人工智能整合的计划也已向伊斯兰宗教教师提供，以实现更丰富和更有意义的伊斯兰学习体验。
在新加坡伊斯兰学者和宗教教师协会（PERGAS），人工智能培训通过多项计划为伊斯兰宗教教师配备数字技能，这些计划包括《多样性驱动的伊斯兰学者技能提升》、《人工智能加速器挑战赛》和《伊斯兰学者企业家人工智能》。
在穆斯林专业人士协会，针对在职专业人士，《学习圈：关于生成式人工智能的一切》计划将在本月举行。该计划将探讨生成式人工智能如何重塑我们的工作方式，以及专业人士如何开始在其日常角色中有意义地应用它。
在MENDAKI，MENDAKI成就计划（MAP）现在使用Khanmigo和KiteSense Luminee等人工智能工具来提高来自弱势背景学生的学习成果。这体现了确保技术进步成为促进社区社会流动和包容性增长催化剂的承诺。
Abdul Kadir bin Abdul Rahman先生是一位科学和数学领域的资深教育工作者，他很好地展现了如何将三十年的深厚经验与当代创新相结合。作为MAP计划的培训师，他是运用人工智能技术改善学习质量的坚定倡导者。他指出一个重要的变化是学生提问意愿的提高——这促进了更具互动性和支持性的学习环境。
此外，MENDAKI的Langkah Digital倡议提供人工智能就绪工作坊、实践培训和技能提升计划，帮助个人理解和应用人工智能于日常生活和工作中。MENDAKI与新加坡科技设计大学（SUTD）等机构建立合作伙伴关系，开启了人工智能、设计和应用型学习的机会——使我们的社区不仅仅是技术消费者，而是能够掌握技术的主体。
这表明人工智能可以成为社会流动的催化剂——如果我们确保获取机会和资源被广泛共享的话。但并非每个人都从同一起点出发。有些人拥有机会、支持性环境和学习时间。有些人则面临约束——无论是时间、家庭责任还是信心不足。这就是为什么我们的方法必须具有包容性。培训必须易于获取、切合实际且有用，以便每个个人都有机会与这些变化相适应并取得进展。最终，人工智能经济中的成功不仅由技术衡量，而是由我们确保每个公民都能够充满信心和希望地向前发展的程度来衡量。
（英文）：议长先生，人工智能将带来破坏和机遇。如果管理得当，它可以提高生产力，为所有人扩大机会。但如果管理不善，它可能加剧不平等。
我们必须确保人工智能推动的不仅仅是增长，而是包容性增长。如果我们处理得当，人工智能不会分裂我们的劳动力，而是会加强它。
通过这样做，我们将更新这份人工智能驱动增长的契约。在这份契约中，每个新加坡人，无论是用代码工作还是用双手工作，都在我们的经济中有一席之地、有一个角色、有一个未来。我衷心支持这项议案，议长先生。
主席：杨女士。
下午1时09分 杨婉玲议员(榜鹅)：议长先生，不久前，我在榜鹅的一个红绿灯处时，一辆自动驾驶穿梭车驶过。我不是唯一观看的人。在我身旁，司机和行人都抬起了头——既有好奇心，也有一种更加安静的情感。一种低沉的嗡鸣般的焦虑，伴随着一丝敬畏。在他们的眼睛后面，有一个非常人性的问题：这对我意味着什么？
那个场景一直留在我心里。人工智能和自动驾驶技术正在改变我们工作、生活和娱乐的方式，速度比人类有史以来看到的任何技术都要快。因此，本议院今天必须回答的问题不是这些技术如何工作，而是我们在做什么——具体地、有意地——以确保我们的工人的生活和生计不被落下。
议长先生，这就是这项动议的真正含义。我想对此讲话，不仅仅是给出保证，而是提出一个计划。一个为我们工人的计划，一个为我们工会成员的计划，一个为坐在旁听席上支持我们这项动议的兄弟姐妹们的计划。
这种转变已经在静静地发生，无处不在。在樟宜机场，自动行李拖车在航站楼之间运送行李。在滨海堤坝服务路，自动清扫机清扫树叶和垃圾。在巴西班让码头，无人自动导引车在货场之间运输集装箱。我们的第一批创造收益的自动驾驶巴士服务计划在今年下半年在两条路线上运行。
技能提升理所当然地处于最前沿。但工作重新设计同样至关重要，以重新设计现有工作以适应新现实，创建新的工作类型，并在人工智能改变工作周期时支持工人的过渡。要使工作重新设计真正产生效果，它必须是一个真正的自下而上的努力，以工人和他们真实的工作流程为中心。让我详细说明。
首先，有意地咨询工人，以真正了解他们的工作。作为全国运输工人工会(NTWU)执行秘书，我亲眼看到过三方合作有效运作时的样子。我们的管理合作伙伴SBS运输、SMRT和其他公司一直在为我们的巴士车长和技术人员做准备，以应对人工智能、电动车(EV)和自动驾驶车(AV)的到来。雇主提供技能提升和培训。政府在这一过程中支持公司和工人。工会则做我们最擅长的事：在工作现场认真倾听工人的真实需求。
正是这种地面层面的倾听提出了我们本来会忽视的问题。即使我们朝着到2030年我们巴士车队的50%成为电动车的目标前进，我们的巴士车长指出电动车培训存在重要缺陷。与使用镜子的传统巴士不同，电动车使用数字监视器，我们的车长告诉我们关于时间延迟、眩光、眼疲劳，更严重的情况下还有恶心。他们要求更长的培训和准备时间。工会与我们的三方合作伙伴一起推动了这一点，问题得到了解决。
议长先生，这是任何顾问报告都不会提出的反馈。但它直接影响巴士设计、驾驶员安全和乘客体验。工人比任何人都更了解他们的工作。这是我们必须继续利用的资源。
为了应对我们的第一批自动驾驶巴士服务，全国运输工人工会(NTWU)去年调查了约500名巴士车长和技术人员。三分之一的人对自动驾驶车会影响他们工作表示担忧——工作保障是最大的担忧，其次是对降薪的恐惧。这不足为奇。这些是全球运输工人所共有的情感。然而，我们调查对象中有三分之一仍然相信司机将继续发挥重要作用。
因此，我们进行了更深入的调查。我们与巴士车长坐在一起，要求他们向我们讲述他们一天的工作，不是他们的职位描述说的，而是他们实际做的。
他们告诉我们的话颠覆了我们的假设。从纸面上看，我们假设驾驶是巴士车长工作的核心，也许占他们任务的80%。我们的车长告诉我们，这更接近20%。其他80%——帮助老年乘客安全上车、管理车厢拥挤、缓解冲突局面、给乘客指路、成为车上冷静和令人放心的存在，甚至告诉乘客只能在坐着时进行歌唱表演——这些是任何自动驾驶车都无法替代的深层人性化责任。
这有深远的影响。如果我们按照关于巴士车长角色的纸面假设行动，我们会误判工作规模、技能要求和薪酬结构——为工人创造不公平的结果，同时为组织带来人力资源(HR)规划灾难。正确确定职位描述不是一种官僚行为。这是所有工作重新设计的基础。
议长先生，工会和三方就业委员会将继续进行地面工作。但我们不能独自做这件事，如果我们认真对待大规模的工作重新设计的话。我呼吁政府为此提供适当的资源：资助对实际工作角色和工作流程进行系统研究和制图，以便工作重新设计建立在实地真实而不仅仅是假设的基础上。
议长先生，我的第二点是：要使人工智能转型成功，工人和客户必须处于关于人工智能能为工人和企业带来什么的重新想象过程的中心。不是事后咨询。不是被告知已经做出的决定。从一开始就要处于中心。
AI将改变我们所知的工作。但它确切地会落在哪里——哪些任务、哪些角色、哪些行业——没有人能完全预测。这正是为什么重新想象的过程如此重要。我们不能等到尘埃落定。我们必须与工人们一起建设、准备，是的，大胆地梦想一个由人工智能驱动的工作场所会是什么样子。我从访问正在进行转型的公司中学到的最重要经验是：当你早期且真诚地让工人参与时，他们不会抵制变化。他们会推动它。
议长先生，让我给你介绍信任中心（Trusted Hub）。一家新加坡中小企业，经营25年，从事数据处理业务，在其核心，这实际上正是人工智能所在。回到2001年，信任中心处理来自公众成员的政府提交；堆堆叠叠的纸张；复印机、传真机、打印机。快进到2026年，同样的业务，或多或少相同的客户，但工作方式完全不同。人工智能现在处理大部分数据，减轻了他们员工的负担。
当我访问时印象深刻的不是技术。是人。因为信任中心将他们的工人作为利益相关者——而不是乘客——纳入了重新想象的过程，他们的大多数员工已经提升自己来编程AI代理，为公司创造企业和创新价值。公司中最年长的AI代理程序员？一位60多岁的绅士。自学的。当你不低估你的工人时，这就是会发生的。
我以前在这个议院谈过FairPrice在榜鹅海滨购物中心的未来商店，它在国际贸易展上被推荐为超市未来模型，并作为技术如何能使我们工人的工作更好、更容易、更安全的生活展示。它用人们可以亲身体验和看到的证据而不是言语来驱散恐惧。
但是让它成功的不是人工智能。是过程。工人和工会塑造和设计了系统，而不是继承它。正因为如此，员工不仅接受了变化，他们拥有了它。
我想要的是更多这样的。明天的商店、明天的公交车枢纽、明天的餐厅、明天的诊所。活的试验台，允许重新想象不仅在公司内部发生，而且在整个集群和我们的社区中发生，以便有关工作场所人工智能的对话可以公开、坦诚和富有想象力地进行，而不是恐惧。
很像我的榜鹅居民看着我们的自主穿梭车滑过，有一种低调的焦虑，是的，但绝对夹杂着一丝敬畏。
虽然明天工作场所的形状仍在形成中，但有一点是清楚的。将工人和工作流程放在转型中心不是可选的，这是方法。实践中是什么样子的？
这是Chye Thiam Maintenance公司向自愿接受扫地机器人培训的工人提供200美元培训津贴，使转型成为工人选择的东西，而不是对他们做的事情。
这是Grab与工会合作，评估AV穿梭车安全驾驶员是否能够承受持续警惕的整个8小时班次，因为工人福利是设计的一部分，而不是事后考虑。
这是一位英国企业家开始称他的AI机器人为AI员工，以提醒自己和他的团队，AI不是关于取代人，而是关于改变角色。
这些不是宏大的姿态。它们是小的、有意的、但非常重要的行为，正常化了工作场所中的AI，并使其成为工人可以看到自己在其中兴旺而不是被取代的东西。这涉及负责任的雇主、进步的员工，当然还有支持和培养的政府。这是三方制，这是为什么三方就业理事会对于组织如此重要，从一开始就定下正确的基调，关于AI如何在日常公司生活中被嵌入和奖励。
议长先生，这是对AI取代的无根据恐惧的真正答案——不是保证，而是证据。证据表明，当工人被视为共同创造者时，转型更快，采纳更强，结果对每个人都更好。
三方就业理事会有利于在每个层级推动这项重新想象工作，通过公司培训委员会（CTC）、集群层级的CTC女王蜜蜂、跨行业的行业AI提升计划。我们的女王蜜蜂可以带上他们的承包商生态系统，就像FairPrice在他们的未来商店中所做的那样。工会将做我们最擅长的：与工人和管理部门一起走过前面的路是什么样子，以及沿途出现了什么新角色。
但议长先生，这真的需要投资和意图。我呼吁政府为行业的行业AI提升计划提供资金——零售、物流、医疗——具有与已经开始指导我们公共运输AV路线图相同的故意性。工人应该知道的不仅是AI即将到来，而且是下一个试验台在哪里，新工作会是什么样子，以及如何到达那里。清晰度不是奢侈品。对于站在那个十字路口的工人来说，这是一切。
议长先生，我的第三点是这样的：即使是管理最好的AI过渡也会看到工作消失，一些职业发现他们所做的任务被AI接管。这是诚实的事实。我们不应该用乐观主义来掩盖它。因此，过渡支持必须是真实的、必须是及时的，必须到达最需要它的人。
我们欠我们的工人一个在他们跌得太远之前抓住他们并尽快让他们回到一份好工作的系统。那个系统必须从工作重新设计开始。不是事后考虑，而是作为第一道防线。如果我们很好并及早重新设计工作，我们减少了需要被抓住的工人数量。最好的过渡支持是使悬崖从一开始就更短的支持。
这就是为什么我们发送给企业的信号如此重要。AI赠款必须与强制性工作重新设计要求相关联，生产力增益与工人成果相关联。如果这些企业无法留住我们的工人，这些公司应该被要求提前通知政府他们无法留住的人员，以便这些失业工人可以得到e2i和我们新成立的三方就业理事会的协助。这将向工人保证新加坡的AI过渡不会导致无就业增长，我们将过渡时间保持到新的好工作尽可能短。
议长先生，我为我们总理在2026年预算中关于AV过渡将被仔细管理、与平台工人协会和我们的驾驶员进行密切协商的保证感到欣慰。作为全国出租车协会和全国私人雇车协会的顾问，我想直接谈论这个问题。用普通话，请议长。
（用普通话）：[请参阅本地语言演讲。]我们的出租车和私人雇车驾驶员已经在竞争激烈且燃料成本很高的环境中航行。看到AV在榜鹅运营，听到自主公交车试点的消息，他们不禁心中充满了一种平静的、未言明的担忧。他们不要求我们停止技术进步——但他们需要的不仅仅是保证。他们需要清晰的方向感。
自主车辆的地理围栏将如何逐步扩展？时间表是什么？新的角色，如远程操作员和安全主管，正在出现。我希望愿意的驾驶员将获得支持并获得培训机会，以便他们可以过渡到这些新职位。对于那些还不能进行这种过渡的人，我也希望新成立的技能和劳动力发展局将花时间更仔细地了解他们的需求——因为他们不是一个同质群体，不能被视为一体。
这不仅仅是一个涉及平台驾驶员的问题。我们的技术人员和工匠用他们的双手保持新加坡运转，但在关于AI的对话中，他们常常是无形的。他们的贡献长期以来一直没有得到足够的认可。
我很高兴人力资源部（MOM）已经开始在这个领域推动努力，从电气贸易开始。我们必须继续努力为工匠建立更有希望和更受尊重的职业道路，同时利用AI增强他们的能力——而不是取代他们的判断。
（用英文）：议长先生，最容易受到AI破坏的工人往往是缓冲最少的——储蓄最少、灵活性最少、等待系统跟上他们的时间最少。这就是为什么我们的反应必须是全面的三方制。雇主和平台伙伴必须随着他们的商业模式演变而加倍努力，而不是退缩。这意味着继续参与过渡支持、共享培训成本、覆盖机会成本，以及在就业和就业后途径中支持工人。
工会将做我们一直做的事情，走进现场、倾听，并与我们的工人一起塑造生计机会，我们将继续'jaga rumah'——通过关注其他司法管辖区正在做的事情，从中国关于AI替换本身不是解雇理由的互联网法院裁定到加州对AV上人类安全操作员的要求。这些是世界各地确定边界所在的信号。新加坡必须从中学习，在必要时，走在它们前面。政府必须围绕需要它的人设计过渡支持，而不是围绕行政上方便的东西。这是我们必须坚持的标准。
议长先生，我将以三项对政府的呼吁作为结论。
给时间。工作重新设计不能仓促。它需要与工人坐在一起，了解他们的工作真正是什么，而不仅仅是工作描述说的，当第一个答案被证明不完整时回到现场，就像我们在公交车长那样做的。公司需要得到支持，而不仅仅是被推入其中。
在重新想象方面给予帮助。大多数公司，尤其是我们的中小企业，无法单独做到这一点。我期待政府提供实际的便利、框架和资金，使工作重新设计成为可能。我期待我们的领先企业、我们的女王蜜蜂，站出来、分享已经完成的工作，并将他们的行业带进来。停留在一个公司内的转型是只有一半完成的转型。
让NTUC成为联系纽带。我们的工会、我们的e2i、我们的三方就业理事会——我们已经在现场、在公司中、通过我们的CTC，与工人和雇主每天坐在一起。我们有需要许多年才能建立的信任。我们的劳动运动已经为成为这一过渡的结缔组织做好了准备，将失业工人与重新设计的角色相匹配，提倡公平待遇，并让每个人（包括我们自己）负起责任。SWDA和我们的机构必须以此为基础。
议长先生，我回想起那个在榜鹅滑过的自主穿梭车。看着它的工人们不是要求我们停止它。他们要求我们确保当它向前发展时，他们也向前发展。这是我们欠他们的答案。不仅仅是一个承诺；一个计划。
我相信，实现没有失业增长的AI转变是可能的。这不是因为技术会自动解决，而是因为我们会这样做。如果我们妥善咨询工人，让他们参与重新想象他们的工作，并通过确实能惠及最需要帮助的人的转型支持来支持这一点，我们就能做到。我支持这项动议。
主席：吉亚姆先生。
下午1时28分 杰拉尔德·詹燕松先生（阿裕尼）：我声明我的利益冲突——我是一家为培训提供商提供软件的公司的所有人和董事。
议长先生，我们面临对劳动力的结构性威胁。数十年来，新加坡的经济模式建立在这样的前提之上：高学历和高技能的劳动力将掌握繁荣未来的钥匙，并成为抵御经济风暴的缓冲。然而，我们现在正处于一个范式转变的时期，人工智能不仅在增强人类能力，而且在许多方面正在取代它。与过去经济周期不同——那时的动荡可以作为创意破坏的一个插曲而被消除——人工智能有望成为我们经济和社会关系发生根本转变的先兆。进一步推进这一概念，它甚至会影响政府在个人与社会之间进行调解所发挥的角色。
今天，我们必须认识到劳动力经济力量的本质正在改变。即使生产率飙升，如果我们不解决这个问题，也将导致固化的下层和中产阶级失去经济代理权。这种关注在Jasmine Sun为《纽约时报》撰写的评论文章中得到表达，她指出了旧金山共识——人们越来越认识到高度暴露于AI职业的年轻工人招聘已经在下降。她提醒我们存在形成永久性下层阶级的风险，其中技术的收益集中在少数人手中。
并非所有证据都指向灾难。美国国家经济研究局2025年的工作论文发现，暴露于较高AI的任务确实经历了劳动力需求的减少。然而，迄今为止，整体就业影响一直很温和，因为生产率的增长抵消了一些流离失所。同样，麻省理工学院的Danielle Li和斯坦福大学的Erik Brynjolfsson在《季度经济学杂志》上发表的研究发现，生成式AI工具使工人生产率提高了近15%，其中经验较少的工人收益最大，从而表明AI可以是阶梯，而不仅仅是活板门。
应该注意的是，这些研究检查了早期和控制的部署。随着代理AI同时在整个行业扩展，分配后果可能比早期生产率研究所建议的更严重和更迅速。
我们无法确定新加坡走的是哪条轨迹。风险的不对称要求我们为更难的情景做准备，而不是更容易的情景。
这种关切得到了AI革命的建筑师的共鸣。2021年，OpenAI首席执行官Sam Altman在其博客文章《一切的摩尔定律》中预测，AI会将权力从劳动力转向资本，声称如果公共政策不相应适应，大多数人会比今天的情况更糟。至关重要的是，Altman并非宿命论者。他主张主动重新分配AI驱动的财富，包括给予公民经济中的股权，可以使这成为广泛繁荣的转变。
同样，Anthropic首席执行官Dario Amodei指出，民主的健康基于普通人通过创造经济价值而拥有杠杆，这是他在2024年的文章《爱的机器》中表达的观点。
这种杠杆的侵蚀是一个令人深感关切的前景，需要大胆而结构性的政策回应。新加坡处于独特的位置来领导这一回应，并捕捉AI为我们人民所呈现的真实经济机会。作为一个拥有高学历劳动力、强有力机构和资本充足的主权财富基金的小型开放经济体，与许多大国相比，我们拥有迅速和结构性地采取行动的工具。
但这个机会窗口不会无限期地保持开放。虽然成本套利使离岸外包具有吸引力，但AI可能会侵蚀这一优势——不是通过将这些工作带回来，而是通过使小型新加坡专业人士团队能够完成曾经需要数百名离岸工人的工作。机会不在于传统意义上的回岸，而在于在国内集中更高价值的协调和监督角色，其中信任、机构质量和接近决策者最为重要。
AI的平等化潜力超越了白领工作。一名英语困难的蓝领工人可以用母语口述，让AI实时呈现为专业文档，使他们能够专注于自己的工艺而不是语法。AI应该是一个平等化工具，提升技术大师，而不是分层我们劳动力的楔子。AI工具还可以通过使小型超高效团队创造巨大价值并扩展，以最少的人力实现全球范围，来推动新一代本地初创企业。
因此，新加坡必须走在这一转变的前沿，同时确保利益流向所有公民。这需要受过培训、拥有技能并善于利用AI工具和创新的工人和企业家，并赋予他们的员工也能这样做的能力。
我们目前重新培训新加坡人的努力常常受到低效用外部培训计划陷阱的阻碍，这些计划产生的认证在AI驱动的经济中缺乏现实世界的价值。这些计划让培训提供商获利，同时让工人掌握经济价值甚微的技能。这种错位存在创造两速经济的风险，其中资本所有者和技术集成公司将那些陷入传统就业慢速道的人留下，导致社会凝聚力的根本侵蚀，并增加长期结构性失业的风险。
为了解决这一问题，我提议建立一个国家AI公平基金。该基金是维护我们社会契约完整性的必要保障。这是一个战略性的盈余转移，从从AI中获益巨大的企业转向新加坡人，以促进我们的集体稳定。
在我解释基金用途后不久，我将详细说明精确的融资机制。我建议基金按两个不同的支柱进行组织。
第一个是社会红利，收入作为直接支付分配给每个成年新加坡公民。我提议初始公民红利为每个成年公民500美元，随着基金贡献的增长而向上扩展。这在设计上是温和的。它不是为了替代收入，而是为了提供一个切实的信号，即每个新加坡人都在我们的共同未来中拥有所有权。
根据我们目前的公民人口，这将每年花费约15亿美元——或少于去年预算盈余的10%——并为每个新加坡家庭提供有意义的回报。这将充当社会底线，确保国家数字繁荣的收益为所有人提供切实的心理平安和尊严。
随着工作性质的演变，这一红利将为家庭提供额外的缓冲。它还使新加坡能够获得AI的全面生产率优势，而不会过度加剧社会不平等。
可以辩称，社区发展委员会（CDC）代金券已经这样做，但那些完全是自由裁量的。我提议的社会红利是一个结构性权利——收据的函数，而不是财政情绪在那一刻碰巧是什么。这个区别对于规划其未来的家庭来说意义重大。
基金的另一部分将专用于掌握基金，这将是一个雇主主导的在职培训（OJT）模式，将培训从课堂移出，进入每个企业。
我提议掌握基金为任何进入或转换到AI增强角色的新加坡公民提供掌握学徒工资，覆盖其总薪资的50%，以中位工资为上限，为期六个月。这奖励了工人的适应努力，同时降低了企业在这个不稳定市场中聘用、培训和留住人才的障碍。
认识到许多中小企业缺乏设计结构化OJT计划的能力，我建议基金也融资一个专家OJT顾问库。这些在OJT设计方面经验丰富的顾问将在企业之间轮换，以构建根据每个企业具体需求定制的OJT蓝图。这将帮助中小企业填补人才缺口，同时也解决为市场新进入者创建培训和学徒计划新阶梯的需求。
此外，我建议向雇主提供导师学分，以补偿高级员工用于结构化指导的时间，将我们的工作场所变成真正的掌握学院，并确保技能与经济的实际需求保持相关。
掌握基金应提供给在新加坡成立和以新加坡为基地的所有商业实体和社会，包括微型企业。应密切监控资金的使用，以确保其确实有助于每个企业内的AI掌握。我估计掌握基金的年成本约为14.2亿美元。
让我列出融资细节。
第一个来源是对年度利润超过1亿美元的企业的公司所得税率边际提高两个百分点。通过关注这些公司，我们从那些最能通过AI而不是人数驱动增长的公司获取自动化盈余。无论是全球科技公司还是传统巨头，这些企业都处于将收入与劳动力脱钩的最前沿。这项税收增加将每年产生约15亿美元，确保创纪录效率的收益被回收到国家AI公平基金中，造福所有新加坡人。
第二个来源是针对性地增加我们投资回报的利用。我提议将预算中纳入的最大净投资回报从50%提高到52.5%，额外的2.5%直接流入基金。根据目前的估计，这将每年筹集约14.5亿美元。
我们的主权财富实体GIC和淡马锡一直是进入AI领域的早期行动者，投资于Anthropic等基础公司，并与Microsoft、BlackRock和Nvidia一起承诺数十亿美元用于AI基础设施合作。由于这些全球投资从全球范围内劳动力自动化中获利，我们只需将这些收益的一小部分回收到我们自己的劳动力中。
转移2.5%并非激进的要求。这确保了我们的储备不仅能提供财务稳定性，还能为每位新加坡人提供长期的经济自主权。
当我们展望未来时，我们不能简单地假设失业工人会像在以往的技术革命中那样顺利地转向新角色。蒸汽机没有取代人类的判断力，但人工智能可能会这样做。这正是为什么被动技能再培训是不够的，为什么需要社会红利的财务保障。转向创业、护理工作、技工、体育和艺术等自动化程度较低的工作的工人不仅需要培训，还需要时间和安全保障来做出这种转变。
当然，会出现我们还无法想象的新工作，但我们必须建立一个足够强大的系统来支持我们的人民，即使这些工作的出现速度比我们希望的要慢，或分布不够均匀。国家人工智能平等基金为新加坡人提供了财务缓冲，使他们能够自信地进行这些转变。
在今年的拨款委员会辩论期间，我提议了青年工资信用计划——针对聘用年轻新加坡工人的雇主的有针对性的工资补贴。国家人工智能平等基金将这一逻辑扩展到对所有在人工智能转变和其他技术破坏中应对的新加坡人的更广泛的长期框架。
议长先生，国家人工智能平等基金是我们数字时代社会契约的更新。我们不能让人工智能成为分裂我们社会的楔子。相反，我们必须利用它成为我们国家历史上最伟大的平等化力量。通过建立社会红利和精通基金，我们给予每位新加坡人在我们数字繁荣中的直接利益和保持领先的资源。
让我们的目标是确保随着机器变得更加有能力，我们的人民变得更加安全。通过现在采取行动，我们能够确保技术进步为每位新加坡人的尊严和经济自主权服务。先生，我支持这项动议。
议长先生：Poh Li San女士。
下午1时43分 Poh Li San女士（Sembawang West选区）：议长先生，在这次会议中，实际上在过去几次会议中，很少有演讲没有提及人工智能时代。政府也谈了很多全球中断将如何影响我们的娱乐、工作和生活。
在政策制定中，总是存在二元选择：乘上人工智能浪潮或被淹没并落后。这是霍布森的选择，答案是显而易见的。但我们不能针对虚假的对手来论证。新加坡是一个小型、开放的、数字化连接的经济体。人工智能将成为经济生活的事实。
政府表示将增长我们的经济、支持我们的企业和照顾我们的工人。但是，部委的政策制定与实地实施之间存在差异。
在街道层面，人工智能转变看起来令人生畏、昂贵，对许多中年工人来说，是一个焦虑和困惑的地方。这是第一波变化，可能也是最艰难的。政府、企业、工会和工人必须共同努力度过这一波浪潮。
在转变期间，一些工作会消失，但新的工作也会出现。如果由市场决定，只有最强大、最适合和最有能力的受益。在一个经济丛林法则不受阻碍地运作的城市中，让我们坦诚地说，人工智能转变将使一些人受益，但不是所有人。这种增长不会导致所有人的生活更加美好和繁荣。
但这不是市场的工作。这是我们的工作；我们在这个议会中的所有人都必须将市场的力量引向我们的目标：为新加坡人创造更多高价值工作并重新培训失业工人，但要以满足企业利润需求的方式进行，以便我们的经济能够继续长期增长。我们过去通过满足两方利益的解决方案建立了新加坡，我们必须在未来再次这样做。
让我具体谈论人工智能可以造福我们工人的两种方式。
我们过去说人民是新加坡的唯一资源。我们现在是一个超高龄社会，总生育率为0.87。我们的资源池在萎缩。人力资源现在是大多数企业的关键瓶颈和成本驱动力，特别是中小企业，它们雇用了70%的本地劳动力。如果企业关闭，更多工人将失去工作，即使那些不受人工智能威胁的人也是如此。
在过去的十年中，我们的企业面临日益恶化的劳动力短缺。2025年Manpower集团最新的人才短缺调查显示，亚太地区近五分之四的雇主在寻找熟练人才方面存在困难，77%报告了困难。特别是，许多新加坡人不能或不愿做的工作由非新加坡人完成。
但我们对外国工人的依赖是有限的，包括政治和社会限制。我们需要人工智能驱动的机器人来替代外国工人，那些没有新加坡人愿意做或能做的工作。例如，建筑、海事和航空部门的重型工作，这些工作暴露于变暖气候的恶劣环境中。这对我们来说将是改变游戏规则的。
下一个前沿是物理生成人工智能或具体化人工智能。最近，生成人工智能技术已与物理系统集成，使机器能够与现实世界互动并适应现实世界。它使机器人能够通过模拟和将智能从数字模型转移到现实硬件来学习复杂任务，如操纵和导航。简单地说，能够思考甚至感知的机器人和类人机器可以被部署在非结构化的和动态的环境中，以协助或甚至替代人类工人。
最近几个月，Dexterity AI、Figure AI和Unitree Robotics等公司已经展示了它们在人工智能驱动的机器人和类人机器在专业角色中的能力。
与像ChatGPT这样在互联网上搜索以训练其模型的生成人工智能工具不同，物理生成人工智能工具需要在特定背景的环境中为它们将要做的角色和任务进行训练。随着时间的推移，这些物理人工智能能力将成熟并可供面临人力短缺的企业使用。这些人工智能驱动的机器人可以帮助我们的企业克服人力约束、降低成本并提高盈利能力。
物理人工智能机器人擅长重复任务，但无法替代每一个角色。重新设计为人机混合团队的工作和流程将成为新常态。老年人和女性可以加入改变后的劳动力——重复的、重型任务由机器人完成，复杂的监督角色由人类执行。这将是一个新的自由和赋权的模式，今天无法想象但在不久的将来将成为现实。
新加坡人可以被培养成机器人的监督者。将为年轻工程师和技术人员创建新的高价值工作角色，如这些人工智能机器人的设计、建造和维护。
如果他们愿意，更多新加坡人可以在更晚的年龄退休，因为他们的角色将变得不那么体力要求。老年人和女性可以加入以前由那些有更强身体能力的人主导的行业。而且机器人也不携带任何社会包袱。
议长先生，向人工智能驱动的机器人的过渡是我的工作领域，这是我们正在努力实现的愿景——为企业解决真实的问题并提升工人的生活质量。我强烈地认为，我们的人工智能转变应该专注于为我们的产业定制物理生成人工智能解决方案，以帮助每位新加坡人在这个赋权的旅程上。
总理Lawrence Wong为我们的国家人工智能战略概述了四个关键支柱。特别是，在先进制造和运输连接部门，人工智能驱动的机器人将确实是力量倍增器。
我们为这种转变做好准备了吗？还没有。我们为此已经做好了充分准备，但我们必须快速行动。我建议采取以下六个步骤。
第一，工会应该预测哪些类型的工作和部门处于风险中，以及可能失业的工人数量。
第二，人力部应该为受影响的工人资助再培训，以为他们准备其他角色或其他产业。
第三，工人也应该站出来，学习新技能并对新工作机会持开放态度。
第四，教育部（MOE）和IHLs应该重新设计学术课程，以使学生远离已经被人工智能占领的领域。所有IHLs学生都应该学习与其学科相关的人工智能工具。
五，贸易及工业部应吸引更多世界一流的物理生成式人工智能公司在新加坡设立总部，并吸引人才进行研究与开发（R&D）。
六，企业应愿意与人工智能公司合作，以自动化和重新设计工作流程、改革工作职位并创建人机混合团队。议长先生，我想用马来语分享几点意见。
（用马来语）：【请参考民族语言演讲。】议长先生，新加坡的人工智能转型必须由政府、企业、工会和工人共同管理，以避免收益不均。物理人工智能可以缓解劳动力短缺，并将工作重塑为人机混合团队。通过工作重新设计、员工技能提升和教育改革，工人可以进入更高价值的职位，而企业可以通过更高的生产力实现增长。
为了支持这一转型，政府的支持和监管至关重要，以资助工人再培训、创造高价值工作、吸引领先的人工智能企业，并确保人工智能被道德地用于广泛的社会利益。
（用英语）：在不久的将来，一个新的人工智能生态系统将出现。技术公司创造人工智能解决方案，企业拥有它们，工人们利用它们。
但政府必须制定规则。人工智能必须被用作善的力量，而不是用于犯罪和有害的活动。建立人工智能使用的伦理规范将决定我们的社会是从人工智能中受益，还是被其奴役。
但关于人工智能还有一个更深层的道德问题。人工智能是人造的；它本身没有内在的善，没有固有的价值。我们在这个议院的议员有责任引导人工智能在市场中的使用方向，不仅要禁止犯罪行为，更要推进公平、善良和正义的使用。我们必须确保人工智能转型不仅仅创造增长，而是创造就业、惠及工人、加强企业并提升社区。议长先生，我也想用普通话来总结我的观点。
（用普通话）：【请参考民族语言演讲。】议长先生，新加坡的人工智能转变需要政府、企业、工会和工人的协调努力，以确保企业和员工都能受益，并支持和协助受影响的人。这包括提供再培训和扩大教育范围，创造高价值工作，使更多新加坡人能够尽快适应这些变化。
物理AI（结合生成式AI的机器人）可以通过在建筑、航空和海事等行业承担艰苦危险的工作来缓解劳动力短缺，同时将工作角色转变为人机协作模式。
我想提议几项关键步骤来支持AI转型：
首先，企业应该自动化并重新设计工作；其次，工会应该标记处于风险中的职位；第三，工人应该继续学习；第四，政府应该制定清晰的AI规则。国家转型不应仅仅为了追求更高的经济增长，而应确保社会各阶层都能受益。
（以英文发言）议长先生，我起身发言的动议要求我们确认AI转型'不能导致无就业增长'。这个'不能'不是经验预测，也不是空洞的修辞。这是政治决心。
自由市场中的AI可能或可能不会成为我们人民自由和赋能的新模式。是我们的决心让它成为如此。议长先生，我支持动议。[掌声。]
议长：低安德烈先生。
下午1时57分 低武杨·安德烈先生（非选区议员）：议长先生，提交给这个议院的动议呼吁一项不会落下新加坡工人的AI转型。总理、劳工首长、整个政府在过去几个月都说过同样的话；这就是他们的意图。我今天下午想要审视的是，我们拥有的政策框架是否足以满足我们被要求确认的承诺。
议长先生，企业做出的每一次人工智能部署，本质上是一项选择。企业可以使用人工智能让现有员工变得更有能力、更富有生产力、比以前更有价值，或者用人工智能完全不需要这些工人。经济学的简记法将此称为增强与自动化的对比：增强是指人工智能与工作者并肩工作，自动化是指人工智能替代他们。
斯坦福大学经济学家埃里克·布林约尔松是人工智能与劳动力市场领域的主要学术声音之一，他提出了一个令人信服的论点：在没有有意政策调向相反方向的自由市场中，激励机制系统性地倾向于自动化。企业发现部署人工智能来替代工人比重新培训他们更容易、更便宜。税收制度、劳动力市场机构、资本成本结构都倾斜了竞争环境。即使增强随着时间的推移会创造更多的总价值、更多的好工作、更广泛的繁荣和更公平的收益分配，但无指导系统的默认轨迹是自动化。
政府选择并宣布的方向是增强。今天摆在我们面前的议案假定了增强。昨天本议院的劳工首长用他自己的话表达了同样的承诺——不是人工智能代替工人，而是人工智能为工人工作。
这一哲学方向在议会两边已经确定。实质问题是我们的政策框架是否与之相符。
目前有三个地方的架构校准不当。三个地方，在当今，制度尽管作出了相反的承诺，仍在允许自动化。
劳工部长昨天表示，人工智能也在重塑高端专业人士、经理和行政人员(PME)职位，例如医生、律师和会计师。总理表达了同样的观点——人工智能将影响新加坡的专业人士、经理和技术人员(PMETs)，他们花费多年建立了专业职业，现在被告知脚下的地面在移动。
上周在五一劳动节集会上，总理陈振声表示，'我们可能无法保护每一份工作，但我们将保护每一个工人。'问题是政府选择的工具——SkillsFuture求职者支持计划——是否能够兑现这一承诺。总理将求职者支持计划称为'新加坡方式'，是相比工人党(WP)首选的冗余保险更实用、更符合新加坡特色的替代方案。这是对新加坡传统的倒读。
议长先生，劳工部长昨天在议会中表示，过渡期间的财政支持不是福利，而是对工人成果的投资。按照这个标准，这一传统一直以来就建立在正是这种投资之上。中央公积金(CPF)、MediShield Life、MediSave，这些都是全民缴费计划，在生活的重大风险发生时支付。每一项都覆盖每一个工人，因为它所保险的风险可能会影响每一个工人。这就是新加坡方式。
求职者支持计划并非建立在这一传统基础之上。它是一项以税收为资金来源的补助金，以裁员前收入为门槛，在设计上更接近于经济援助而非风险保险。按目前的配置，它在六个月内以递减的月度分期支付最多6,000元，首月为1,500元，最后三个月每月为750元，并且仅向被裁员前月收入为5,000元或以下的工作者提供。
劳动部长昨日在本议院承认该上限排除了面临人工智能时代相同失业风险的PMEs，并提议将符合条件的上限提高到接近PMEs中位总收入水平。
如果采纳该提案，这是向工人党长期主张的方向迈进。但Ng先生的提案只是移动这条线，我们的提案是将其移除。提高上限让更多工作者进入该计划，但不改变该计划对他们的作用。对于确实符合上限资格的工作者，递减支付传达了一个信息：从高金额开始并逐步减少的支付不是一个缺陷。这是一个倒计时。倒计时会推动工作者接受第一个工作机会，而非正确的选择。
人力部的数据本身告诉我们为什么这很重要。在去年最后一个季度中被裁员的居民中，43.6%的PMETs在六个月内没有找到新工作。这是求职者支持计划无法应对的群体。而在那些在六个月内找到工作的人中，大约十人中有四人的工资低于以前。所以，他们接受了可用的工作，而非他们经验相称的工作。我们大多数人都经历过，你在职业阶梯上爬得越高，找到下一份工作的时间就越长。
议长先生，一个被六个月倒计时推入他们不想要的低薪工作的PMET已经经历了政府框架本应阻止的自动化结果，虽然附带了微小的缓冲。提高上限只是扩大了该群体，但不会缩短倒计时。
议长先生，工人党对裁员保险计划的提案建立在新加坡实际的传统基础之上。我们支付最后一次所领工资的40%，没有收入上限，也没有递减机制。它由雇主和雇员缴款资助，采用与中央公积金相同的模式，并覆盖所有为该计划缴款的工作者，包括劳动部长已认定为风险最大的专业人士，因为它所保险的风险不止于$5,000、$7,600或议会可能设定的任何其他上限。
总理说我们必须保护每一位工作者。政府选择的工具没有做到。工人党的做到了。
议长先生，当一家公司考虑进行重大人工智能部署时，它面临两条道路：一条道路是保留现有员工并对他们进行再培训，使其与人工智能并肩工作；另一条道路则是裁员，精简运营，引进规模更小、懂人工智能的劳动力。前者是增强，后者是自动化。
但我们的税法对处于决策关头的公司说了什么？目前的框架奖励活动。它奖励人工智能资本支出。它奖励培训支出。这些都是值得奖励的事情，但目前的框架所没有做到的是奖励这一选择本身。
裁减现有员工并培训较少新员工的公司获得与保留和重新培训现有员工的公司相同的财政待遇。购买人工智能来替代工人的公司获得与购买人工智能来增强工人的公司相同的财政待遇。
税法在这个选择关口沉默无语。
正如布朗森先前所指出的，在选择关口沉默无语并非在后果上保持中立。当税法不主动奖励员工保留时，潜在的经济学会使公司倾向于裁员。毕竟，劳动力是资产负债表上最昂贵的一项，而劳动力成本是永久性的，这与一次性培训成本不同。在市场无干预的情况下，公司会选择裁员。
昨天，黄先生在本议院为CTC框架进行了辩护，将其作为将企业转型与工人进步挂钩的机制，并提议通过新成立的三方就业委员会进行扩展。
CTC在项目层面为与其合作的公司运作，附带补助金资金。扩大其覆盖范围会扩大补助金模式，但不会改变每家公司都在其中运作的更广泛财政体系结构，无论其是否在CTC计划内。正是这种更广泛的财政体系结构塑造了首席财务官在决策点上的财务决策。
二月在本议院，我提议推出再培训税收抵免，这是一种仅适用于能够证明他们已将现有员工保留在人工智能增强职位中而非裁员的公司的扣除。正是这一缺失的有条件部分将在公司必须做出决策的确切时刻为其提供财政信号。这项再培训税收抵免将奖励积极的选择，而不仅仅是投资人工智能。
本议案的第四部分确认经济进步必须保持包容性。这是关于分配的承诺，而不仅仅是增长。我的同事Gerald Giam提议建立一个国家人工智能公平基金来从结构上实现这一承诺。我今天提议的工具是任何再分配机制（包括Giam先生的）需要运作的诊断工具。因为增强战略的第三个条件要真正实现就是验证。
议长先生，增强最终是一个可测试的主张。它做出了一个预测，即在人工智能与工人并肩部署的部门中，工资将跟随这些工人帮助创造的生产率增长。如果这个预测成立，政府所采纳的框架就正如宣传的那样得到了实现。如果这些部门的生产率提高了，但工资并未随之增长，那么所实现的就不是增强，无论我们用什么语言来描述它。
目前，我们很少有机制，也很少有系统的方式来区分究竟发生了哪种情况。
政府正在四个国家人工智能使命部门——先进制造、连接、金融和医疗保健进行大规模严肃的公共资金投资。公共资金通过CTC补助、新成立的三方就业委员会、技能和劳动力发展局以及各种企业转型计划流入这些部门和其他部门。这些是适当的投资，但公共投资产生了相应的公众问责责任。公共资金流向之处，公众有权知道产出是什么以及流向何人。
因此，我要求的是一个有针对性的透明机制，即年度人工智能收益审计，最初专门针对四个国家人工智能使命进行范围界定，向议会报告来自国家支持的人工智能投资的生产率收益如何在工资和资本回报之间分配。随着时间推移，其范围和覆盖面可以扩大。
二月在我的预算演讲中，我将其定义为分配问题。今天，随着本议案在议院面前要求我们确认经济进步必须保持包容性，我再次提议将其视为更根本的东西。人工智能收益审计是议会可用的最直接工具，以测试政府选择的增强方向是否真正得到实现。如果收益与工人分享，审计将说明这一点，框架将有证据支持其主张。如果没有，我们将在差距变成鸿沟之前、在本议案从政策陈述变成希望陈述之前了解到这一点。
议长先生，增强和自动化之间的选择不是一天做出的。它每天都由我们运行的计划架构、我们维持的税法和我们选择收集的数据所做出。无论议院今天说什么，那个架构将继续代表我们做出选择。
目前，我的立场是该架构将工人推向第一份可得到的工作，而不是合适的工作。我们的税法对于在重新培训工人和保留他们之间的选择关口没有任何肯定的表述，我们也没有建立任何机制来判断公共人工智能投资的收益是否惠及了那些该投资以其名义进行的人。这就是我支持本议案的原因。我敦促政府为其提供所需的架构，以便我们能够确保没有工人被遗忘。感谢您，议长先生。
议长：哈米德·拉扎克博士。
下午2点10分 哈米德·拉扎克博士（西海岸-裕廊西）：议长先生，我声明我是一家私人骨科诊所的业主，该诊所已工会化，我也是卫生服务雇主工会（HSEU）的顾问。
我起来支持本议案——无失业增长的人工智能过渡。人工智能已经来临。这不是试点；它已经在成为一个平台。
先生，我们的问题不是我们是否采用人工智能。我们会采用。更宽泛的问题是我们是否在增长的同时不遗弃我们的工人。在接下来的十年里，新加坡应该被评判的不是我们部署人工智能的速度有多快，而是我们在多大程度上将采用转化为更好的工作、更好的工资和工作场所更强的信任。
我今天以三个身份发言：作为一名专业人士、作为一位家长和作为倾听居民意见的议员。
首先，是专业上的焦虑。许多专业人士、经理、执行人员和技术人员（PMETs），他们不害怕技术，他们对不确定性感到不安，因为人工智能很少替代整个工作。它拆解任务，它压缩团队，它改变雇主的招聘对象。当你看不到你的角色如何演变时，焦虑就会增加。
第二，是为人父母的焦虑。今天的父母问非常简单的问题：我的孩子会有一个公平的开始吗？入门级工作会是什么样子？如果入门级工作萎缩，那么谁来培训下一代？
第三，是居民的焦虑，这是最实际的。职业中期的工人担心失业。照顾者担心时间。许多人不能只停止工作去培训或再培训。他们不是在要求保障。他们只是要求公平的机会和一个他们可以驾驭的体系。
议长先生，我们应该坦率地对待人工智能。人工智能是聪明的，但它不是智慧的。它可能产生幻觉，它可能听起来自信，但仍然是错误的。因此，未来不应该是人与人工智能竞争。它应该是人与人工智能一起工作，进行判断、进行验证和承担责任。
本议案不仅仅是关于技术。它涉及信任、工作重新设计和整个工人旅程。信任将决定这种采用是否会成功。如果工人将人工智能视为监控，信任就会减弱，最终破裂。当信任破裂时，采用将放缓，收益将不可持续。
总理黄女士谈到了保护每一位工人，并扩展实际的三方工具，如用于人工智能过渡的CTC。这是我们应该加倍推进的方向，我在这方面提议四个实际举措。
首先，技能必须是一条路径，而不是菜单。SkillsFuture是一项重大的国家资产。但在实地，许多工人告诉我这一点。它很有用，但也令人不堪重负。课程太多，徽章太多，信号太少。
因此，问题现在不仅仅是获取。它是导航。工人不应该需要滚动数小时来猜测什么真正对他或他的下一份工作重要。因此，我建议我们按部门、按职位策划更清晰的人工智能相关路径，具有明确的前门和明确的雇主认可。我们可以考虑为那些选择支持人工智能驱动增长的优先课程的人提供额外激励，特别是当有明确的雇主需求时。这可能意味着更高的补助金层级或与结果挂钩的支持，如完成加面试、实习或根据设计和可行性确定的再部署路径。
第二，将人工智能采用与工作重新设计挂钩。许多议员都谈过这一点。如果我们资助采用，我们应该问，任务将如何改变，工人将如何被重新部署，性能测量将如何继续保持公平？生产率必须体现为对我们的工人更好的工作，并最终体现为更好的工资，而不仅仅是人员数量的减少。
这不是为了惩罚。这是为了务实。这是我们三方伙伴可以通过提供剧本、模板和咨询支持来帮助的地方，这样中小企业就不会被丢下独自应对。
第三，为专业部门（如诊所、律师事务所、会计师事务所）提高人工智能就绪度。许多是小型机构，PMET密集且时间紧张。他们想采用人工智能，但担心安全、机密性、责任和信任。
一个已在本议院分享的实用模式已经在医疗保健领域显现。今年4月，HSEU和GP+合作社签署了一项协议，为基层诊所员工进行人工智能意识培训，并帮助基层诊所采用技术和重新设计工作流程，由CTC方式和CTC补助支持。我近距离观察了这一伙伴关系。价值在于使采用在务实、负责任的基础上进行，并以工作重新设计为锚点，而不仅仅是工具推广。
我希望我们能将这种基于集群、CTC风格的方式扩展到其他专业部门，包括法律和会计，以便较小的执业机构能够从不确定性转向就绪状态，具有明确的治理标准和工人保护。
对于我们的工人，当需要被识别时，支持应该开始。这意味着更快的工作匹配、适应现实生活日程的模块化培训和负责任过渡的实际指导。实际上，结构化的指导和明确的下一步减少了焦虑，因为它使工人从等待转变为行动。议长先生，我现在将用泰米尔语发言。
（用泰米尔语）：【请参阅方言发言。】尊敬的议长，许多人在谈论人工智能时感到担忧。他们担心工作可能会消失，技能的价值可能会下降，以及孩子的未来可能会发生什么。这些担忧是真实的。问题也很困难，但我们的反应不是害怕。
人工智能发展迅速，但人类的仁慈、信任、正义感、创意、语言、文化——所有这些都不能完全被任何机器取代。人工智能可以计算；但人类的联系、人类的判断和人类的责任将始终与我们同在。因此，我们必须将自己从恐惧的道路转向机会的道路。人工智能的兴起并不意味着人类不再被需要。相反，它更清楚地表明了人类必须做什么真正重要的任务。
在这方面，人文学科很重要；语言技能很重要；文化细微差别很重要；社会理解很重要。医疗保健、护理、教育、社会服务、咨询和涉及与人直接接触的工作——这些是人工智能无法替代的领域。
泰米尔语和泰米尔文化在这一努力中是一种支持；我们的文学培养人类的感情。我们的文化加强了社会责任。这是我们的力量。所以，这是我们必须告诉年轻人的：拥抱人工智能，但也要发展人类的能力。
学习不仅仅是认证。这是一条道路、一个信念、一个未来计划。当增长到来时，就业机会必须伴随而来。变革的支持也必须伴随而来。所以，不要害怕。让我们有信心。
（用英语）：议长先生，无失业增长必须意味着一件事。工人能够感受到的增长，无论是工资、尊严还是明确的下一步。
所以，我提出一个治理标准。测试不是我们有多少项目。测试是工人是否能够快速看到正确的路线，为了正确的工作，在正确的时间。父母是否能对孩子的起点和未来感到自信，以及公民的旅程是否感到无缝。
如果我们保持这个方向，并以三方决心完善交付，新加坡可以有效、负责任和快速地部署人工智能，同时加强信任和保护尊严。基于这些观察，议长先生，我支持这项动议。
议长：何挺如女士。
下午2时19分 何挺如女士（后港）：议长先生，新加坡对人工智能的方式经常被国际机构和咨询公司（如BCG）以及杰出人士（如国际货币基金组织（IMF）总裁克里斯塔利娜·格奥尔基耶娃）引用。
我们的技术基础设施和提升工人技能的举措是我们计划如何应对这项新的、快速发展的技术所呈现的中断和机会的关键部分。
然而，我们也必须认识到并采取行动应对另一个不舒适的现实。新加坡是最容易受到人工智能中断影响的经济体之一。国际估计表明，发达经济体中约60%的工人从事高度暴露于人工智能的工作。对于新加坡，这个比例似乎明显更高。因为我们是一个高技能、以服务为导向的枢纽，国际货币基金组织的估计表明，我们本地劳动力中约有77%高度暴露于人工智能中断，我们的过渡可能比许多其他经济体更剧烈和更尖锐。
人工智能如何根本上重新配置我们的劳动力市场？这可以通过三个不同的转变来理解。
首先，许多现有工作将从内部进行转变。人工智能正在或已经接管日常信息处理任务——起草、摘要、数据提取和标准化分析。管理人员、卫生专业人员和法律专业人员已经在使用人工智能工具来处理这些类型的任务，从而释放出用于判断、复杂问题解决和人际互动的时间。
第二，一些工作将被取代。在经济学家所说的高暴露、低互补角色中，人工智能可以自行执行大多数核心任务，保持人类参与的理由更少。文职支持工作者和许多商业和行政助理专业人员，其工作围绕日常文档、基本处理和标准化客户查询，面临最高风险，他们的职位可能会缩小甚至消失。代理人工智能技术和模型的进步只是加剧了这一影响。在英国，一些金融机构（如投资银行）因为人工智能的自动化能力而重新审视了他们对某些角色新毕业生的招聘。
第三，人工智能也将创造新的工作和新的需求。我们已经看到对人工智能工程师、数据科学家和人工智能产品专家的需求上升，但也看到了金融、医疗保健、物流和教育各领域数据精通专业人员的需求。这些新角色往往提供更高的工资，但仅适用于能够提供正确的技术和互补人类技能组合的工人。
是的，确实，人工智能工作转变已经到来，我们正处于重大中断之中。然而，影响不会在所有行业均匀分布，也不会对我们的社会和经济产生均匀影响。目前，人工智能中断在白领工人中最强烈，尤其是入门级职位。与历史上影响蓝领工作的以前技术中断不同，今天的人工智能将最多影响认知、白领角色——呼叫中心代理、行政官员或初级业务支持执行官，其工作日围绕标准流程、常规报告和脚本响应构建，处于人工智能可以执行几乎所有核心任务的角色。
在这样高暴露、低互补的白领角色中，雇主可以合并职位、放缓招聘或重新设计工作，以确保更少的人期望使用人工智能做更多工作作为简单理由。如果我们不解决这个问题，人工智能的好处将最终只由一小部分工人获得。
研究表明，生产力和财富收益可能会不成比例地落入那些最有利用人工智能能力的人身上。高技能工作创造的一个有证明的经济效应是本地服务需求增加。来自主要科技中心（包括旧金山）的研究表明，每个高端工作都与本地服务部门（如零售和食品服务）中约四个工作的创造相关。
即使这样的溢出效应产生更多工作，这些工作对脆弱工人的质量和可用性对我来说不太确定。在新加坡，较低工资和日常密集的角色更可能由脆弱工人群体持有，他们也可能面临自动化造成的更大失业风险。
国际机构（包括国际货币基金组织和世界银行）指出，在没有政策干预的情况下，人工智能可能会加剧收入不平等。人工智能驱动增长的溢出效应对低收入工人的益处程度仍然不确定。我们需要新加坡特定的研究，模型化这些分配影响，并将这些数据公开提供，以通知更针对性的政策反应。
我们还必须记住，新加坡人已经感受到房价上升和基本服务成本更高的压力。这些压力是真实的。随着我们作为一个小的、开放的经济体，严重依赖资本流入，这些压力已经建立了一段时间。人工智能的影响会推动进一步的不平等财富积累吗？因此，问这个问题是公平和迫切的：人工智能驱动的经济活动是否会无意中增加日常成本压力？
除了广泛的经济压力，我们必须转向这一过渡的人性面。随着工作继续被重新塑造，工人继续升级技能，我们不能将那些面临系统性障碍的人留下，因为我们的国家朝着人工智能就绪的未来前进。其中包括残疾人、妇女、低收入新加坡人，以及年轻毕业生。
人工智能可能会对残疾人引入新的歧视形式。由于人工智能算法通常通过模式识别进行训练，它们基于数据集中的常见模式做出判断。因此，如果使用有偏见的历史数据来为人工智能进行培训，例如招聘流程，人工智能可能会加强对残疾人的工作申请和任何其他在历史上在这个领域代表不足的群体的偏见。
女性工人也面临被人工智能边缘化的风险增加。2024年国际货币基金组织关于新加坡劳动力市场的报告发现，女性在人工智能密集的科学、技术、工程和数学（STEM）角色中代表不足，在具有人工智能工程技能的工人中也是如此。STEM中的女性占入门级职位的29%，管理职位的24.4%，但仅占C级职位的12.12%。总的来说，这意味着她们在被认为是人工智能安全面的方面代表不足。因此，她们在人工智能补充高技能工作的地方受益的位置会更差。此外，2026年3月发布的国际劳工组织数据发现，由女性主导的职业暴露于GenAI风险的可能性几乎是由男性主导的职业的两倍，在查看高自动化风险时显示了更强的差异。
总的来说，这造成了双重劣势。女性工作者不太可能从人工智能的益处中受益，同时更容易面临失业风险。简言之，女性面临更高的风险，机会也更少。
对于我们的年轻毕业生来说，人工智能对工作岗位的重塑带来了新的不确定性。初级工作岗位的流失给Z世代带来了两难困境。虽然公司仍在寻求为经验丰富的职位招聘专业人士，但由于工作岗位被人工智能吸收，年轻毕业生获得此类经验的机会减少了。
2025年，超过20%的毕业生无法获得全职永久职位，较2023年增加了近5%，超过60%的毕业生称求职变得困难，年轻毕业生对找到全职工作感到更加焦虑是很自然的。
最近的研究表明，仅仅意识到人工智能增强或威胁一个人工作的潜力就可能加重职业倦怠，主要是通过加剧工作者的工作不安全感和情感疲惫。
虽然人工智能通常与白领工作的中断有关，但易受伤害的工作者和家庭也面临巨大风险。
对人工智能工具和培训的不平等获取可能会加剧现有的劣势。那些缺乏家庭资源或有利于学习新技能的家庭环境的人可能会发现自己落后更多。如果不予解决，这将冒着代际不平等加剧的风险。
衡量人工智能对新加坡超越经济产出的影响，这一切对新加坡意味着什么？就在过去的一周，我们见证了《婚姻和生育重启工作组》的启动。人工智能进步对我们的出生率有什么影响？经济不安全已经被年轻新加坡人列为延迟或放弃生育的原因，但障碍不仅仅是财务问题。工作不确定性侵蚀了对未来的稳定感和信心，以及有足够稳固基础建立家庭和扎根的感觉。如果由人工智能驱动的中断加深了这种更广泛的不安全感，我们可以合理预期对我们本已悲剧性低迷的总生育率的进一步下行压力。
政府必须采取更有针对性的措施，确保所有工作者，无论其性别、年龄、职业、收入和无障碍需求如何，都为人工智能造成的中断做好充分准备，以减轻因裁员而面临财务压力的易受伤害工作者的负担。这将最大限度地减少随着人工智能替代变得更加普遍，失业对工作者及其家庭造成的不确定性和代价。
为了确保我们的政策有效，我们需要更多公共数据来衡量人工智能对我们劳动力市场的中断。例如，我们如何衡量人工智能项目的成功。
根据我在今年2月24日提出的议会问题的后续跟进，我注意到人工智能学徒计划目前通过三个主要指标进行评估：一是培训的从业者总人数；二是参加人工智能学徒计划的毕业生中从事人工智能工程相关职位的百分比；三是项目质量的完成和监督。这是一个很好的开始，但它们并没有告诉我们人工智能项目和中断对社会不同群体的影响。这些措施侧重于吞吐量而不是公平性。我们需要关于项目完成后两到三年内人工智能职位的工资轨迹、工作质量和保留率的数据。我们需要更多数据。
首先，应该更详细地公开参与者数据档案。这可以包括以前的职业、培训前的收入等级、年龄、性别、教育程度和残疾状况。这使我们能够看到参与者来自何处。高接触、低互补职位，或已有的高互补职位。这将表明易受伤害的群体是否甚至已经开始参与。
其次，更准确地衡量人工智能在更广泛劳动力市场中的中断可以采取暴露互补性映射的形式，从而理解职位是否具有高暴露和低互补性，并建立一个调整框架来跟踪不同人口群体的失业、工资变化和工作质量。这类数据为政府提供了人工智能如何影响不同社区的更清晰图景，以便可以将支持指向最需要的地方。
我现在转向关于我们的年轻人如何应对人工智能挑战的一些想法。
如果人工智能替代了大量初级职位，年轻工作者可能会发现建立传统上推进到高级职位所需的基础经验的机会减少。我们国家的一个解决方案可能是更好地鼓励和支持青年创业。这将使他们能够独立获得宝贵的技能，而不是等待被成熟公司录用。
这种方法建立在已经打开的大门基础上。人工智能通过部署用于建立网站、分析数据、运营营销甚至自动化后台办公任务大大降低了创业障碍。我们有许多初创企业计划，如赠款和训练营，但这些举措是否为新兴公司的完整生命周期提供了充分的持续长期支持？
此外，我们的赠款架构仍然以里程碑为重点且受项目约束，鼓励合规性而非竞争。我们需要一种文化和框架，承认失败初创企业的价值，或支持创始人主导的网络随时间推移的发展。借鉴其他创业中心的经验教训，哪些因素阻碍了新加坡建立对创业者更有利的可持续生态系统的能力？
首先，我们必须继续建立可持续的非正式网络，使创业文化自我维持。我们目前的网络通常是基于项目且时间有限的，偏向于短期指导。然而，研究表明，基于相互选择和亲和力的非正式导师关系远比行政配对更有效。如果导师关系仅与短期赠款相关联，我们的年轻人可能会错失从基于信任的指导中获得的益处，这种指导可以在例如硅谷看到。在硅谷和深圳等领先的创业中心，非正式创始人网络一直是一个关键但经常被忽视的成功驱动因素。它们促进了知识共享、供应链联系以及从锚定公司衍生的新企业。
新加坡可以从中获益良多。虽然我们有Grab和Block 71等锚定企业，但亚洲开发银行指出，我们的生态系统落后于他人，因为我们的合作仍然是政策驱动的，而不是有机集群的。我们如何能够减少对创始人的行政负担，以确保他们不会过度忙于达到赠款里程碑，而是专注于建立他们生存所需的市场竞争力以应对人工智能驱动的中断。
一种可能是将正式报告限制在赠款结束时，而不是更频繁地进行，以达到平衡。新加坡还必须更好地利用我们的锚定企业。Grab、Sea和Singtel等公司拥有深厚的技术专长和产业网络储备，这些储备在很大程度上仍被锁定在公司内部。
我们能否使用有针对性的税收抵免或同行发展项目的共同投资配对，以鼓励锚定企业为早期阶段创始人运营结构化导师和衍生项目？这将使有机网络能够在现有卓越储备周围形成，而不是寄希望于政府赠款周期会这样做。
私营部门必须发挥主导作用，政府的角色应从召集人和守门人转变为催化剂。这就是我们如何开始从工业内部发展创业体系的方式。
我们还必须学会重视失败。新加坡的经济强调和社会一致性文化使我们有时害怕失败。经合组织(OECD)2018年的一项研究发现，与任何其他参与国家相比，新加坡学生对失败的恐惧更大。然而，创业意味着对失败的宽容。创始人必须在信息不完整的情况下做出决定，有意义的创新必须有某种失败的自由作为支撑。我们必须把失败视为垫脚石而不是污点，否则我们最终会扼杀我们试图建立的生态系统，并使我们的年轻人在中断时代缺乏茁壮成长的能力。
我们可以通过开始我们自己朝着更好的创业空间的过渡，鼓励实验并将创业失败正常化为增长和经验来实现这一点。
失败应该是垫脚石，而不是死胡同。我们在学校内开始了这一过渡，我们必须摆脱完美分数，在学校内进行创业项目，让学生了解初创企业的内部运作。我们还应该展示失败的项目，以表彰它们的附加价值。
新加坡目前的破产框架也可以重新审视，以更好地支持创业者。目前，失败的创始人面临与任何其他破产者相同的限制，包括旅行禁令、董事资格取消和无自动豁免，无论其失败是真正风险承担还是财务不当行为的结果。我们能否探索为真实创业失败设立的专门途径，允许创始人更快获得豁免，更快恢复董事身份，并将其经验视为有价值的而不是负债？这不是为了使失败没有后果，而是为了确保一个诚实的赌注出错的代价不会永久阻止我们最富进取心的年轻新加坡人再次尝试。
最后，我也希望我们利用我们在应对人工智能过渡中积累的经验，在区域和全球范围内发挥作用，因为其他经济体也试图应对这种中断。
新加坡拥有强大的地位，我们已经有意决定在全球人工智能治理议程设定方面发挥领导作用。我们的管理者角色必须超越框架范围，我们必须发挥自己的作用以解决近期数据反映的人工智能开发和使用中的全球不平衡。世界银行2025年数据显示，尽管仅占全球人口的17%，但高收入国家占Notable AI模型的87%、人工智能初创企业的86%和风险基金资本融资的91%。对易受伤害的群体和全球南方在人工智能领域严重代表不足的情况，有合理的担忧。作为负责任的世界公民，我们可以发挥自己的作用来解决这个问题。
最近，我们已经开始通过《海狮项目》为东南亚语言量身定制开发人工智能工具，认识到发展中世界的许多地区冒着被基于西方数据的人工智能系统抛弃的风险。我们应该以此为基础，倡导跨东南亚国家联盟(东盟)的公平人工智能获取，向缺乏开发自己框架能力的国家出口我们的治理专长，并确保管理人工智能的规则不仅反映强势者的利益，也反映许多人的需求。
这不仅仅是抽象的外交政策和雄心。它对国内的就业有直接影响。新加坡在全球人工智能生态系统中的地位使我们有能力塑造人工智能工具在该地区如何被构建、部署和采用。我们应该有意地使用这种杠杆。当我们的研究人员——
议长：何女士，你还有一分钟。
何婷茹女士：当我们的研究人员开发出能够跨越东南亚语言的人工智能系统时，我们就创造了可以部署在我们自己的服务部门、医院和学校的工具。当我们的公司在人工智能采用方面领先时，我们就为新技能、新角色和新产业创造了需求，而我们的工人可以接受培训进入其中。
我们必须确保新加坡人在这些技术的开发中有一席之地，而不仅仅是被动接收在别处做出的决定。我们的全球人工智能领导力最终是为确保答案是前者的投资。这种方法最终还具有为新加坡创造更多工作和机会的额外好处，这将是真正的涓滴效应。我支持这项动议。
议长先生：叶鸿翁先生。
下午2时39分 Yip Hon Weng议员（Yio Chu Kang）：议长先生，我声明我在一家全球投资公司工作，从事生态系统劳动力战略。
近日来，一架飞机一直在旧金山上空盘旋，拉着一条写着'停止招聘人类'的横幅。相同的信息出现在城市各地的广告牌和公交车站亭上，还伴随着诸如'AI员工时代已经到来'这样的标语。这个活动是AI初创公司Artisan的作品。这不仅仅是一个营销噱头。它反映了一种担忧，即工作的未来可能会将人们排除在外，而不是赋能他们。
我起立支持这项议案，因为这不能是新加坡的做法。人工智能不能成为向工人发出他们可被替代的信号。在我在淡马锡的工作中，我看到了技术如何扰乱各个行业，我想预先阐述我的主要论点。要实现不造成失业的增长，企业人工智能的采用不能仅仅是购买技术。它必须遵循一条经过深思熟虑的路线：我们必须首先建立人工智能素养；利用这种素养推动工作流程和职位的重新设计；并确保这种改革为我们的工人带来切实的、共同的成果。
让我先提出一个重要观察。在淡马锡生态系统中,许多公司已在投资AI。工具正在部署,试点项目在增加。但我们看到的真实制约因素不是技术、计算能力或资本。而是劳动力的准备度。我们不缺乏技术。我们缺乏的是转型。
在我们与20多家淡马锡投资组合公司合办的人工智能素养工作坊中，我们清楚地看到，碎片化的人工智能素养仍然是主要瓶颈。我们正与首席人力资源官和首席技术官密切合作，以弥合采纳与实际价值创造之间的差距。从根本上说，这是一个技能匹配问题。在技能供应滞后的地方，机会不会消失，它只是转向其他地方。
我们正在讨论的人工智能转型具有结构性、全球性，且在加速进行。原本需要数周才能完成的任务现在只需数小时，很快就将只需数分钟甚至数秒。变化不再以线性方式进行，而是以指数方式进行。在这种背景下，采纳已不再是可选的。在新加坡，虽然大企业在与遗留系统和繁重的合规要求作斗争，而中小企业则面临资本和带宽的严重制约，但两者都面临同样的含义：不采纳人工智能的企业将难以保持竞争力。
但如果AI的采纳是必要的，破坏是不可避免的。我们必须清楚地认识到，如果这一转变管理不当，工人将面临的风险。一方面，随着AI降低许多任务的成本，对这些任务的需求可能会扩大而非收缩。经济学家将此称为「杰文斯就业效应」，其中效率不会导致工作减少，反而导致新形式工作的增加。我们之前见过这种情况。ATM减少了日常任务，但扩大了银行业务。文字处理器提高了产出，并将工作转向更高价值的岗位。人工智能可能会遵循同样的模式。
但实际情况往往呈现K形结果。有经验且具备AI能力的工作者获得不成比例的收益，而缺乏这些能力的人，特别是初级工作者，面临落后的风险。因此，问题不在于AI是否创造增长。而在于这种增长流向谁。真正的风险不在于AI替代工作。而在于它大规模替代机会。一名工作者可能保持就业，但会面临职业发展放缓和经验的无声流失。我们的任务不是否认这种颠覆。我们的任务是对其进行治理。
议长先生，如果我们要有效地治理这种颠覆，辩论必须转向。仅仅观察企业是否采纳人工智能是不够的。我们必须对采纳后发生的情况进行问责。问题很简单。工人在转型后是否比之前的生活更好？我们必须追问：工作和工作流程是否被重新设计？收益是否得到共享？如果人工智能提高了产出，但削弱了生计，那不是转型，而是排斥。我们必须确保公共资金不为此提供补贴。
因此，我请问政府：我们能否为支持计划建立明确的条件约束？如果公共补助资金正在资助企业转向，难道不应该明确将这些补助与全国性、以人为中心的评分卡相挂钩？一份追踪新增岗位净数、工作流程重新设计的规模、工资改善、员工保留和技能提升的评分卡。如果我们认真对待无失业增长，我们的采纳指标就必须超越简单计数岗位，转向衡量职业发展。
从我们在淡马锡的AI素养工作中，我们了解到企业迫切需要关于领导力、工作重新设计、成果衡量、信任和治理的指导。企业无法单独应对。
这就是我们的劳工运动、NTUC、e2i和工会发挥作用的地方。我们必须授权他们提供这样的指导，确保工会领导人和企业管理层坐在一起，同时规划企业的科技路线图和工人的再培训计划。如果公司需要关于工作重新设计和共同成果的指导，我们的三方合作伙伴必须就在现场与他们一起。
最近宣布的三方就业委员会是及时之举，但必须积极弥合企业级转型与工人级成果之间的差距。因为真正的挑战不是向企业引入人工智能，而是将工人纳入这一转型。
这将我们带到这一转变的中心挑战：人工智能不仅仅是一个技术倍增器，而是一个领导力倍增器。
领导者必须真正相信人工智能的变革潜力，并以身作则使用它，引导其应用，带动员工跟上。AI可以写作、设计和优化。但它无法行使判断力、建立信任或在不确定性中引领人们。这一责任仍属人类。
议长先生，雇主有着关键的责任，但如果没有正确的领导力，采纳AI最简单的方式就是简单地裁减人员。我们已经看到这种矛盾在全球上演。我们看到亚马逊在2026年初宣布裁减16,000个职位，同时进一步倚重AI以提高企业效率。
当人工智能主要作为削减人员的战略推出时，它会引发恐惧。当作为能力提升战略推出时，它会建立信任。这种恐惧的故事长期以来一直在我们的工作场所上演，甚至在拥有人工智能工具的员工中也是如此。
当生成式人工智能刚开始流行时，一些员工积极主动地自行探索人工智能来提高工作效率，但将其保密。他们担心如果透露新获得的生产力来源，最终会被裁员或在没有额外补偿的情况下被分配更多工作。当缺乏信任且收益不被分享时，员工隐藏他们的能力，而不是分享他们。
真正的转型需要领导者采取长期视角。企业必须预期工人过渡到新的工作方式时出现短期生产率滞后，并且必须为实验创造空间。然而，我们必须承认，许多在这个充满挑战的经济环境中与高运营成本相抗争的企业没有充足的时间。
我询问该部：我们如何能更好地帮助公司应对这些短期时滞，确保员工再培训所需时间的成本不会成为裁员的借口？
议长先生、各位，当雇主引领这一转变时，有一个我们必须清晰认识的结构性转变——在工作重新设计之前，我们必须进行工作流程重新设计。
我们要求工人改变，但系统保持不变。人工智能跨越各个职能和领域，重新想象流程如何相连以及价值如何产生。这种对整个过程的重塑必须在各个角色本身被重新设计之前进行。
然而，我们当前的政策方针中存在一个重大缺口。如今，我们的国家支持在很大程度上专注于个人工作重新设计。我们要求工人适应新的工作范围，但遗留的公司流程保持不变。
因此，AI通常被叠加到过时的工作流程中，其中存在数据孤岛和碎片化。生产力停滞，沮丧感上升。员工抵制变革并非因为顽固，而是因为在破碎的工作流程中使用先进的AI工具深感沮丧。
所以，我请问政府和我们的三方伙伴：我们能否扩大支持计划，明确关注工作流程重新设计？我们如何能为企业提供专业知识和资金，首先重新设想他们的跨职能流程？如果我们理顺工作流程，员工自然会看到这项技术的价值，将惯性转变为适应的热情。
议长先生，即使有最好的工作流程，扰乱仍然会发生。一些工人将失去工作，一些岗位的变化速度将比预期更快。我们经常指向SkillsFuture和职业转换计划等现有措施。但这是一个残酷的事实——如果这些措施足够，我们的工人为什么仍然深感焦虑?
答案是，人工智能冲击以前所未有的速度发展，工作者担心我们的社会保障网无法足够快地跟上它。
我问政府：我们如何严格追踪现有措施的速度和有效性，特别是对失业工人的财政支持，以确保它们确实能够快速响应？
对于留任的工人来说，基本的AI能力将不再是竞争优势。这将成为继续竞争的必要条件。任务是帮助工人从仅仅是AI用户转变为AI指挥者，即那些知道如何精选、引导和验证AI输出的工人。
这引出了我对我们劳动力管道的一个关键担忧。如果AI自动化了草稿、总结和初步分析，我们的初级工作会怎样？如果年轻毕业生无法获得真正的第一份工作和他们需要的导师指导，他们将永远无法获得早期队伍依靠的基础经验来成长，我们将面临失去未来劳动力的风险。
我问政府：我们如何与雇主和行业领袖合作来保护和重新设计初级职位途径，使我们的青年能够发展成为明天AI指挥者所需的专业判断力？
总之，议长先生，让我回到我开始的地方。在淡马锡生态系统中，我们看到公司正在投资AI、试点新工具并推进转型。但决定性的制约因素不是技术。而是劳动力是否做好了准备。
我与我们淡马锡公司的首席技术官分享了这个故事。一家工厂大力投资了新机器。它们更快、更聪明、更高效。但生产力下降了，不是因为技术失败，而是因为人被落下了。
在另一条线上，该公司做了不同的事情。他们没有替换工人，而是对他们进行了再培训。机器操作员成为了数据读者。技术人员成为了问题解决者。改变的不是设备。而是使用它的人的能力和信心。不久，故障率下降了。想法来自于车间。曾经害怕变化的工人开始领导它。相同的机器。相同的工厂。但一个非常不同的未来。
这就是教训。技术可能会设定步伐。但人决定了方向。在AI转型中，精通而不仅仅是采用，决定了这个方向是否包容性。
这把我们带到了摆在我们面前的动议。一个不产生失业的AI转型不仅仅是关于创造工作。它是关于确保工人与技术一起进步，而不是落后。它是关于将生产力转化为进步。它是关于将创新转化为共享成果。
如果采用建立能力，那么精通必须建立优势。如果工作被重新设计，那么技能必须深化。如果创造了增长，那么它必须被广泛共享。
但这不会自己发生。它需要协调。它需要领导。它需要信任。这就是新加坡具有独特优势的地方。我们的三方合作模式，其中政府、雇主和工人一起行动，给了我们不仅能够对变化做出反应，而且能够塑造它的能力。这是我们的秘密武器。
当企业投资时，工人必须被装备好。当工作被重新设计时，工人必须被纳入。当发生破坏时，支持必须是可信的。因为这不仅是技术转型，它是劳动力转型。建立三方就业理事会是确保这种对齐在实践中发生的重要一步。
技术会发展。市场会适应。但我们必须明确我们正在建设的未来。它不能是一个说"停止拥有人类"的未来。它必须是一个说"投资于人"的未来。我们的工人是否进步是我们必须一起做出的选择，有意图地和果断地。谢谢你，我支持这项动议。[掌声。]
议长：Jamus Lim助理教授。
下午2时54分 Jamus Jerome Lim助理教授(盛港)：议长先生，我在今天辩论中的贡献很直接。我主张，如果我们的目标是保护劳动力免受可能由经济范围内拥抱AI导致的失业，那么我们今天的努力应该主要集中在促进新招聘的政策上，而不是那些专注于减少失业或推动再培训的政策。
解释很简单。证据表明，迄今为止，由于AI导致的当前工人的失业是温和且局限的，而新工人的招聘放缓已经明显，甚至可能会加速。
原则上，AI的后果可能会在劳动力市场的两端产生影响。它可能会减少企业的招聘动力，从而降低新工作机会的总数，或者它可能会提高公司的招聘频率或诱使工人离职。
招聘放缓源于当AI工具允许公司廉价有效地替换他们以前需要招聘人工工作者来完成的工作职能时。这在初级职位尤其如此，因为新毕业生缺乏经验，新员工通常被分配的相对直接的繁琐工作使这个群体价值较低，更容易被机器替代。
但正如许多观察者，包括本院的议员已经指出的，这是一个先有鸡还是先有蛋的问题。如果我们不让新工人进入我们的公司，我们肯定不能期望他们获得必要的经验和特定工作技能，使他们在职业中期成为有价值的专业人士。
相比之下，当AI工具表明某些角色不再需要时，就会发生失业，因为它们可以由AI很好地复制。以前由人类完成的任务被替换，如果公司内没有其他地方可以重新分配给这个人，或者这个人被证明太昂贵，那么他们被解雇。
从积极方面来看，AI可能会为失业工人开辟在其他地方追求职业的新机会，要么因为他们获得了在市场上使他们更有价值的AI相关技能，要么因为他们可能可以自己创业。
但目前，来自全球研究的信息很清楚。虽然迄今为止几乎没有失业的证据，但有充分迹象表明招聘出现了下降。这在暴露于AI的部门中的情况如此，特别是在生成式AI如ChatGPT出现后，随着代理AI的成熟，这可能会加速。对于职业初期、初级工人来说，前景特别危险。即使被雇用，这类工人也往往获得较低的薪资。
这背后的原因是直观的。AI主要替代机械、可重复和明确定义的任务，这些任务主要由初级员工执行。公司仍然看重高级员工的成熟度和经验，总的来说，宁愿削减招聘并重新分配他们原本忠诚的员工，也不愿让他们离职。
先生，这些趋势在我们的本地劳动力市场中也是可见的。迄今为止，AI对这里的失业贡献不大。MOM的最新劳动力市场报告显示，自2023年以来，总体裁员人数保持稳定，失业率约为2%，自2022年以来变化不大。
在回应关于PMET部门的问题时，人力部高级议会秘书黄成俊也指出，在金融和信息通讯等受AI影响的部门中，PMET的裁员人数仍然很低，去年最后一个季度仅为960人。此外，黄高级议会秘书也指出，这些部门在同一时期的空缺职位数量很大——大约是其10倍。这可能会被解释为新招聘的劳动力市场健康稳健，但我对此持谨慎态度。这是因为正如任何求职者都会告诉你的——有一个职位不等于有一份工作。这些工作必须被填补，最好是由正在寻找工作的新加坡人来填补。
这是画面不太乐观的地方。最新的毕业生就业调查显示，在几乎每个研究领域中，成功找到工作的毕业生比例都有所下降，大约每四个毕业生中就有一个无法获得全职就业。
在回应提交的议会问题时，部长李智隆指出，下降是由于后疫情招聘激增，我们看到的只是早期趋势的平均回归。
我不太乐观。根据我的计算，虽然疫前和2020年毕业生的永久就业率平均在70%左右，但在十年前左右，这个数字接近85%，这明显要好得多。
虽然青年失业率在2020年代比前两十年要低，但诚然，在世界其他地方，自2022年以来也稳步上升了大约一个百分点。与以往新职位吸收率遵循经济周期的情况不同，新加坡经济目前实际上处于扩张状态。
从需求方面，也有报告称一些雇主对招聘新员工持谨慎和不情愿的态度，尽管幸运的是这些目前似乎是少数。此外，这种悲观的图景也掩盖了更多令人困扰的病态现象。许多新加坡工人可能不得不接受不能充分利用他们技能和才能的机会。这种不匹配在汇总数据中没有得到很好的反映。
想象一下拥有本地大学高级学位的毕业生，却仍然被迫从事外卖配送工作；或者在顶尖海外大学学习多年的学生，自回国以来反复遭到雇主的拒绝。或者有账单和需要赡养的年幼家庭的有经验的中期职业专业人士，尽管按照建议进行了技能提升，但在就业市场上连续数月无功而返。我相信议会中的其他议员在我们每周的民众接待会上会看到类似的案例。事实上，NTUC和MOM最近发表的两项研究证实了这些例子。
过度资格现象在职业早期人群中最为突出，而非自愿不充分就业与自愿不充分就业者之间的差距在30岁以下人群中最大。加之全球经济政策不确定性的大环境，我们本地劳动力市场可能正进入所谓的招聘「大犹豫」时代，这一现象也在世界其他地方被观察到。
如果我们的目标是，如该动议的标题所表明的那样，避免无就业增长，那么自然而然，我们应该优先考虑那些针对劳动力市场招聘的政策。让我列举几个。
首先，我们可以改善激励机制，鼓励公司聘用应届毕业生。正如我在今年供应委员会讨论中所分享的那样，这需要将现有的毕业生行业见习计划（GRIT）项目扩展到全国范围，成为跨部门的全国实习倡议。年轻工作者可以自由地将其SkillsFuture学分用于与愿意接纳他们的公司合作的有薪学徒制和实习项目。
企业，特别是中小企业，应该能够向人力部(MOM)提交关于在职培训的可信提案，人力部随后将利用已为企业预留的SkillsFuture企业培训券和其他补贴计划来抵消企业录用这些学员的成本。我的荣幸朋友Gerald Giam也为此目的提议了一个AI精通基金，这与我在这里提出的建议是互补的。
第二，这样的短期项目，我指的是六个月到一年，学徒制和实习也应该纳入明确的就业路径，以员工的合理表现为条件，除非由于经济情况的变化向雇主授予豁免。
这些实习生应当按照《就业法》被视为员工，并获得同等的法律保护和权益，包括最少年假，但GRIT实习生目前并未获得这些待遇。
第三，我们可以在高等教育最后一年、学生进入职场之前，加强社交技能培训的提供，包括沟通、同理心、判断力、人脉建设和远见等方面。研究表明，当工作需求不仅要求完成认知任务，还需要人与人工智能之间进行迭代协作时，人工智能对员工的补充作用最为明显。但我们的毕业生往往在学校期间专注于追求学术能力，导致他们在这些接口职能方面的准备严重不足。
第四，如果我们确实坚守我们的信念——即希望我们的毕业生专注于获得能力而非认证，正如教育部(MOE)在支持我们自主大学中可堆积式微凭证途径方面所明确表示的那样，以及最近的研究所证实的那样——那么我们应该言行一致，在公共部门中取消那些坚持要求文凭或学位的招聘要求，只要能力能够通过其他方式得到证明。这可以通过一系列微凭证来证明技能，或者候选人在面试阶段通过现场演示来证明。
先生，人工智能是一种通用技术。如同之前所有的通用技术一样，人工智能可能会摧毁和创造同样数量的工作岗位，但当我们面对这一转变的前沿时，我们必须为那些受此次推出影响最大的人群奠定基础，至少目前来说，这些人群显然是我们的年轻入门级员工。我们需要有针对性的政策来帮助克服在招聘他们时的巨大犹豫。这就是我们确保AI的增长承诺不被数百万失业工作的恐惧所掩盖的最佳方式。
议长先生：Neo Kok Beng博士。
下午3时06分 Dr Neo Kok Beng（指定议员）：议长先生，我曾经在哈佛肯尼迪学院担任创新政策访问教授十年，目前我仍在复旦大学担任创新管理访问教授。
人工智能就是我们真正所说的颠覆性技术，这是我博士研究的课题。这是范式转变，当你说范式转变时，意味着它从一个产业，或者说完全从一个产业转变到其他领域，这实际上会摧毁旧的工作方式。
让我给你举个例子。上周，我访问了Science Park的一家AI初创企业，所以我们讨论了在几个媒体项目上的合作，而我在这个容纳20人的房间里只看到了两个人。所以，我问首席执行官，'你们所有的员工在哪里？'他说，嗯，他们从不来办公室，但他们在工作。我说，'你什么时候看到他们？'他说，'嗯，我上周看到他们了，那时网络宕机了，没有通讯。由于宽带宕机，他们回来检查他们的agents，看看是否真的在工作？'所以，我问，'你怎么知道它们真的在工作？'答案是，'实际上，他们随时产生代码，一直，24/7。'所以，他拥有agents，它们在24/7工作。所以，我说，'你怎么衡量生产力？'我问了一个问题，'自那以来，你们替代或完成了多少任务或工作，相当于工程师或编码工作人员，自去年以来？'答案是五。所以，与去年和今年相比，这个人有agents为他工作，他完成了五个人的任务。
我们可以从两个角度来看：一是这家公司生产力极高；另一个需要看的是，我们少了五个工作岗位。
你会选哪一个？好吧，如果你是CEO，你就知道该怎么选。如果你是NTUC秘书长，我就不太确定了。
所以，我问了下一个问题。他碰巧正在为扩展业务招聘潜在员工，所以我问他，「你对这个正在读计算机硕士的人怎么看？他是否达标？」他的回答是，「根据我与他的讨论，他的回答表明他在当前技术方面落后两年。」
落后两年，我就想，天哪，所以当这个人毕业时，也许明年，他会怎样呢？技术总是领先他两年。
因此，这意味着我们是否应该将这个人置于实际工作环境中，基本上就是实习和在职实训，或者当这个人毕业后，他真的需要加快在当前能力上的进度，因为AI技术发展速度太快。所以，说真的，这是一场海啸。
就个人而言，我参与了一些小型非政府组织的工作。我们正在进行一个重点项目，用来监测独自生活的老年人，这样如果他们发生任何情况，我们都能了解。我们实际上在使用人工智能，因为这些老年人中大多数说方言，所以我们使用小型机器人伴侣，这些伴侣具有理解方言的能力，可以监测他们。这非常好，因为很难让照顾者去进行监测和探访这些人。
因此，这是人工智能真正非常有用的一个方面。机器人AI真的非常有用，这样我们就可以处理新加坡人不想做或可能不太适合做的工作。
我从事的另一个项目是成像，利用人工智能进行磁共振成像。我们改日再讨论此事。
问题在于工作场所体验现在变化很大。那么，我们、员工、现有人员、PMEs或工人是否拥有继续从事这份工作的技能。我实际上很高兴劳工运动推出了CTCs。这是将人工智能引入工作场所或与企业合作的一个很好的机制。我很高兴为此有这样的补助金。
但问题是我们如何界定能力素质？一些议员谈到工作流程重新设计、流程重新设计——但我们如何知道最后他们是否具备能力？工作场所的能力素质水平在哪里？因此，我认为新机构SWDA应该能够与劳工运动部门合作来界定这些能力素质。
但这些能力我们还能如何利用？它们是固定于工作场所的吗；也就是说，一个工作场所、一家公司？还是具有可迁移性的？
那么，也许我们可以考虑让专业机构参与，使得每个级别或每个能力级别的资质——无论是可堆积式的还是微凭证——都能获得行业认证和认可。这样一来，这个人在其整个职业生涯中都能拥有可转移的资质。
人工智能已经是大势所趋。与大多数员工一样，起初我——我不会说怀疑，但不愿意改变我的工作方式。但现在，我认为我别无选择。所以过去一年里，我一直在使用它。甚至我的妻子也要使用AI生成视频和图片，虽然她是艺术家，喜欢画画——但它已经成为她生活的一部分了。
这是一场巨大的变革浪潮，我支持这项动议。正如我在新加坡工程师协会理事会成员的自愿工作中曾做过的那样，我正是那个实际上提议与劳动运动合作建立青年工程师领导力计划的人，其中包括高级和全球项目。我认为工程机构和专业机构可以与工会合作，对所有这些计划进行认证，为工人开辟职业发展途径。
议长先生：Eileen Chong女士。
下午3时15分 Ms Eileen Chong Pei Shan（非选区议员）：谢谢主席。请用中文。
（以中文发言）：【请参阅书面记录。】议长先生，我同意动议中提出的许多观点，其中包括确保在人工智能转型中没有任何一名工人被遗漏的承诺。
然而，要实现这一愿景，我们还需要分享采用人工智能带来的收益，并确保未来的工人能够继续保持竞争力，领先于形势。目前，当采用技术来提高生产力时，往往是雇主受益。我提议升级《灵活工作安排指南》，赋予其法律约束力，这样可以确保员工也能享受人工智能生产力的收益。
当人工智能提高了生产力和工作效率时，我们应该鼓励工人利用节省下来的时间与家人在一起、休息、参加活动以及建立与他人的关系。
此外，明天的工人——即我们学校中今天的孩子——已经开始在课堂上接触人工智能。一些家长对在小学四年级引入人工智能是否太早提出了疑虑。神经科学家也指出，过早或过度使用人工智能和技术可能会使学习变得太容易，从而剥夺孩子发展深度学习能力的机会。
处于成长阶段的儿童应该学习如何思考、提出问题和做出判断。因此，我呼吁政府追踪并定期报告人工智能在我们学校的采用对不同年龄学生认知发展的影响。
在人工智能时代，独立思考和判断是人工智能无法替代的技能。这些正是我们应该传授给下一代的东西，使他们无论世界如何变化都能保持竞争力和韧性。
（以英文发言）：议长先生，我赞同动议中阐述的价值观：增长必须具有包容性，每名工人都很重要，在人工智能转型中任何人都不应被遗漏。确保没有人被遗漏不仅仅是确保就业增长。这要求我们致力于分享人工智能驱动的生产力收益。这也要求我们确保未来几代的工人能够在一个由人工智能和其他可能尚未被发明的技术所定义的时代蓬勃发展。
议长先生，关于人工智能驱动的经济转型的大部分讨论都集中在工人需要提升技能并保持相关性的必要性上。虽然这些努力至关重要，但它们没有回答另一个同样重要的问题：我们如何确保人工智能生产力红利的公平分配？
目前，雇主是默认的受益者。他们从相同人数的更高产出或更少人数的相同产出中获益。这样的生产力提高不会自动成为员工的收益。没有经过刻意的政策设计，它们往往只会是雇主的收益。
与工人分享人工智能生产力红利的一种方式是通过时间。在三月份人力部委员会供应辩论期间，我为灵活工作安排被赋予法律约束力提出了案例。要求灵活工作的权利与拥有灵活工作的权利并不相同。我们不应该依赖于将行动负担放在员工身上的指南，而这些员工最无法承受这种负担。
我想在今天重申对灵活工作立法的呼吁。随着我们讨论人工智能转型如何能使新加坡人受益，这变得更加显著。由于人工智能产生了真实的生产力收益，新加坡工人是否会以节省下来的时间而不仅仅是更高产出的形式分享这些收益的问题，市场本身无法回答。这必须是设计出来的。
在实际中，更多的时间意味着什么呢？它意味着能够陪伴孩子、做的不仅仅是支付补习课费用的父母。它意味着更少的照顾者必须在工作和需要照顾的家庭成员之间做出选择。它也意味着休息，真正的休息，在一个61%的员工感到疲惫、39%的工人不愿上班的国家。这些不是软性的结果。这些是人类能力得到补充和维持的条件。
政府和三方伙伴关系会承诺在塑造人工智能时代政策时将工人福祉与雇主收益和经济增长并列优先考虑吗？如果会，我敦促政府首先通过赋予灵活工作安排法律约束力来开始。
当人工智能使公司生产力更高时，工人应该对人工智能节省出来的时间拥有有意义的、可执行的权利。时间来休息和从事人工智能无法复制的那种人类联系，而我们的生育率告诉我们这方面我们正在短缺。
议长先生，现在我想转向对我们长期成功最重要的一群新加坡人。如果我们说每名工人都很重要，那么我们必须关注还不在劳动力中的工人。我说的是现在坐在我们学校课堂上的孩子，其中有些坐在上面的走廊里。
现在，我们小学四年级的10岁孩子正在被介绍人工智能工具。虽然当然有教师监督和护栏措施到位，但我们也应该提出一个更基本的问题。这种早期接触是在建立他们在人工智能世界中茁壮成长的能力，还是在建立对人工智能驱动工具的早期依赖？一些家长已经在询问。小学四年级太早了吗？真正的收益是什么？更重要的是，权衡是什么？
这些不仅仅是父母的焦虑。神经科学家也提出了严肃的问题。在他的著作《数字幻象》中，神经科学家杰瑞德·霍瓦斯博士提出了一个应该让我们停下来思考的观点。当技术使思考变得太容易时，学习的深度就消失了。人工智能是终极的卸载工具。它以最少的用户输入进行阅读、写作和计算。但我们的孩子还不是想要卸载和提高生产力的专家。他们是学习者，学习需要付出努力。它需要人工智能被设计来消除的认知摩擦。
如果我们的孩子开始在10岁时卸载他们的思考，他们就不会发展出发现错误、提出有意义问题或形成独立观点所需的心理肌肉。那么，我们所说的人工智能驱动的个性化学习可能会变成定制的舒适。因为它是无摩擦的，所以感觉起来像是进步，但它可能会绕过我们试图支持的认知发展。
这让我想起了我今天早些时候提出的一个关切：人工智能使用中的公平悖论。我很欣赏李灿烈部长关于教育部如何通过家长门户网站主动与家长沟通并分享指导的观点，指导他们如何在家更好地支持孩子。但并不是新加坡的每个孩子都有一位在家且具有数字素养、有时间根据指导行动、且有能力在课堂外支持孩子学习的家长。来自弱势背景、获得的家长指导较少、进行的非屏幕充实活动较少的儿童可能最终会更多依赖人工智能，而不是更少。
对于回家到一个人手不足的家庭，没有人来重新引导、提问或监督的孩子来说，人工智能将始终产生答案，始终减少摩擦，始终使思考变得更容易。这不是赋能。如果人工智能依赖侵蚀了它旨在补充的认知发展，那么风险最大的孩子就是我们尽力支持的孩子。
议长先生，我的同事詹姆斯·林副教授在最近的预算辩论中指出，强者和弱者大学生之间的差距不再在于他们在书面作业中提交的内容，而在于他们愿意质疑和思考超越脚本的意愿。这些能力是在多年中建立或未建立的。如果我们在10岁时取代这种努力，我们的孩子不能简单地在大学时下载它。如果做最多无监督人工智能卸载的孩子是那些已经拥有这些能力较少的孩子，那么我们不是在缩小差距。我们在扩大它——更早。
一份由布鲁金斯学会在今年1月发布的全球研究发现，人工智能在教育中的最大风险是在关键发展年份中取代费力思考。有趣的是，该研究中接受调查的65%的学生将认知发展的破坏列为人工智能使用的首要风险。孩子们自己能感受到这种差异。
议长先生，我不是建议我们不在学校使用人工智能工具。我是建议我们遵循证据，而不是炒作。生成式人工智能作为公众已经不到四年。我们还没有关于它如何影响孩子大脑的长期数据。我们不应该让技术周期的速度超过我们的孩子应得的关怀。
我也欣赏部长今早提供的更新，由A*STAR进行的新加坡纵向早期发展研究（SG LEADS）将扩大以收集数据，帮助我们理解新加坡儿童的人工智能使用模式以及人工智能使用如何影响他们的学习和幸福成果。我希望这也将包括在教育中使用人工智能工具对我们儿童认知发展的影响，包括它们对他们的执行功能和批判性思维、阅读理解和持续独立努力能力等技能的影响。我们必须确保通过给他们提供一个将始终相关的工具来为我们的孩子为我们无法预测的世界做准备：一个强大而独立的思想。
这份动议正确地呼吁新加坡对人工智能驱动增长的方法以公平、韧性和所有人的机会为基础。我同意。这就是为什么我今天谈论了人工智能转型挑战我们保护的两个关键事项：时间和思想。
对于今天的工人，我们应该为灵活工作的权利立法，以便生产力收益被收回作为休息、照顾和联系的时间。对于我们的孩子，未来的工人，我们必须保护学习所需的认知摩擦，确保我们在培养独立的思想，能够在不求助于数字拐杖的情况下解决困难问题。人工智能转型不仅仅是经济事件。它可能是一代人中最重要的机会，让我们问我们将如何利用技术返还给我们的时间和能力来建立什么样的社会。议长先生，我支持这项动议。
议长先生：维克拉姆·奈尔先生。
下午3时26分 维克拉姆·奈尔（新民）：议长先生，我支持这项动议。人工智能已经在重塑我们的经济。它正在提高生产力、启动新的商业模式并加强我们的全球竞争力。对于新加坡来说，这是一个重要机会。但除了这些益处外，还有一个真实的关切——我们如何确保我们的工人不会比他们能适应的速度更快地被取代？
在人类历史过程中，经济增长与新工作的创造相关联。例如，当国家经历工业化时，随着产业开放，为各地的人创造了新的工作。当然，经济增长也可能不仅仅来自劳动力的增加，也来自生产力的增加。这也是应该受欢迎的，因为它为那些正在工作的人创造了更高薪的工作。新加坡已从这两种趋势中受益。
在这样的背景下，对人工智能的概念关切是简单的：它会增加生产力这么多以至于明显更少的工作将被需要？这的含义是拥有工作的人少得多或那些控制资本的人将获得更高生产力的所有益处，而大量人将失业。本质上，赢家将获得更多，失败者的数量将更大。
如果我们看一下其他国家的发展，我们会看到政府开始做出回应。他们这样做不是通过阻止技术变革，而是通过采取适度的保护措施，以确保随着人工智能的采用增加，工人得到公平对待。
一个我希望讨论的领域是人工智能在招聘流程中的应用。例如，在欧盟，最近通过的《人工智能法案》认可，用于就业的人工智能系统，如那些涉及招聘、评估和绩效监控的系统，可能会显著影响劳动者的生计。因此，这些系统被归类为「高风险」，需要满足包括偏见测试、透明度披露和人类监督等要求。
这补充了《通用数据保护条例》第22条，根据该条款，个人有权不受仅基于自动化处理所做的决定的约束，该决定对其产生法律效力或严重影响其。在就业环境中，这意味着重要的决定（如招聘或解雇）不能仅由算法做出，而必须有有意义的人类参与。
在纽约市，《自动就业决策工具法案》要求对在招聘或晋升中使用的人工智能系统进行定期的偏见审计，并在使用此类工具时告知申请人。
虽然这些不是直接防止失业的法律，但它们确实确保与就业相关的决定不会以不透明或无法问责的方式依赖人工智能做出。它们还促进公平性，并有助于防止自动化决策中的无意歧视。
同时，在德国和法国等国家，劳动法要求雇主在裁员前遵循结构化的程序，包括与员工代表协商、提前通知以及努力对工人进行再培训或调岗。我们的全国职工总会（NTUC）正在与我们这里的雇主进行类似的活动。这些要求可能不是人工智能特有的，但它们有助于确保过渡以结构化和负责任的方式进行管理。
议长先生，这些例子表明，政府不是阻止技术变革，而是认识到立法可以提供防护措施，并确保公司在采用人工智能时，以充分顾及对工人影响的方式进行。这对于维持雇主和工人之间的信任特别重要。如果工人感到决定是透明地作出的，并且有相应的保护措施到位，他们就更有可能支持而不是抵制新技术的采用。
对于新加坡，我们可以考虑在涉及人工智能的就业决定中，是否应该对人类监督有更明确的期望。虽然许多雇主已经采纳了这样的做法，但将这一原则正式化可以帮助确保整个行业的一致性。我们还可以探索工人是否应该拥有更明确的透明度权利，包括了解何时使用人工智能系统来评估其工作表现或影响关于其就业决定的权利。
此外，值得考虑是否应该强化对负责任劳动力转型的期望。当重大技术变革严重影响就业时，可以鼓励雇主提供结构化支持，例如再培训机会或员工重新部署途径。
归根结底，重要的是要认识到，仅有立法是不够的，必须由健全的机构、积极的雇主和愿意适应和学习的工人来加以补充。我们的目标应该是维持一个这样的系统：企业保持创新和竞争力，工人感到安全并得到支持，机遇随着时间不断扩大。
这引导我进入第二点——我们可以为最可能受到人工智能影响的工作做什么。人工智能在执行日常和基于规则的任务方面特别有效。因此，行政工作等领域的职位，以及涉及初级分析的职位，更容易面临被替代。
然而，问题不仅仅在于这些工作可能会消失。更重要的是，这些职位常常是进入劳动力市场的切入点，为工人提供进步所需的经验和技能。如果这些机会减少，工人可能会发现随着时间推移建立职业生涯变得更加困难。
从这个意义上讲，风险不仅是失业，还包括职业发展道路的逐步侵蚀。长期来看，这可能导致这样的局面：个人从入门级职位升迁到更高技能和更高薪酬职位变得越来越困难。
因此，除了一般的再培训，我们的重点还应该放在促进实际的职业转变上。应该支持工作者进入相邻职位，在这些职位中他们现有的技能仍然可以得到应用并进一步发展。这使职业转变对工作者更加可行，特别是对职业中期的工作者。
同时，公司可以受到鼓励重新设计工作，使人工智能补充而非替代人类工作者。例如，虽然日常任务可以自动化，但需要判断力、沟通能力和问题解决能力的工作应该保留并加强。这样，人工智能就成为提高生产力的工具，而不是劳动力的替代品。
在实际操作层面，采用人工智能的雇主可以被鼓励及早为受影响的工人识别相邻岗位，并为其提供结构化的重新部署途径。这可能包括短期、针对性强的培训模块或工作重新设计，使工人能够逐步建立新的胜任能力。
这些措施有助于确保工人不会突然失去工作，而是通过一个有管理的过渡期得到引导，在这个过程中他们的技能和在各自组织内的角色得以保留。工会、政府和雇主可以共同合作为此制定一个框架。
关于创意产业（包括音乐、文学创作和表演），我们应该考虑是否需要立法或进一步的保护，以应对受版权保护的材料被用于人工智能训练的问题，以及对这一问题的救济应该完全由私法处理，还是政府有必要建立一个框架来保护此类材料。这可能包括对个人形象和声音的权利。如果完全由私法处理，只有资源充足的个人才能采取行动处理此事项，而如果存在这样的框架，个人艺术家、作家和其他创意工作者可能能够从这类保护中受益。
新加坡多年来成功应对了许多经济转型。每一次，我们都将对变革的开放态度与对社会流动性和共同进步的承诺相结合。
向人工智能驱动的经济转变将是另一项这样的考验。这将要求我们在创新与保护之间取得谨慎的平衡。如果我们深思熟虑地应对，我们可以确保人工智能成为机遇之源，并且增长保持包容性。我支持这项动议。
议长：法德里·法兹先生。
下午3时35分 法德利·法兹议员（阿裕尼）：议长先生，今日议案恰当地认识到AI的变革力量，并肯定AI驱动的经济增长必须保持包容性。
我的演讲包含三个主要观点。首先，我们必须保护工人的经济地位，并防止人工智能的经济果实仅仅流向拥有人工智能模型或生产支持人工智能硬件的人。其次，我们必须确保人工智能抗御型就业途径对新加坡人保持可行性。第三，也是最重要的是，我们必须坚持技术应该服务于人类而不是相反的理念，因为归根结底，目标不仅仅是没有失业的增长。它是在不失去我们作为人类和新加坡人身份的情况下的增长。
先生，议案陈述的第二项促请国会强调，新加坡关于人工智能驱动增长的方针必须以公平、韧性和全民机遇为基础，而第四项要求国会确认经济进展必须保持包容性，新加坡不应出现无就业增长。
这些是极其重要的目标，因为如果人工智能的兴起管理不当，它不仅可能代表技术性颠覆，还可能代表劳动力和资本之间的权力重新配置。例如，上月，Meta宣布将记录其在美国的每一位员工的按键记录和工作流程。整个工作日期间将不时截图。所有这些数据将形成用于训练AI系统的数据集，这些系统有朝一日可能会取代这些员工。其他公司很快可能会效仿。
虽然这在美国正在进行，但我们在新加坡应该问：Meta等公司是否应该被允许在没有任何明确保障的情况下以这种方式采集员工数据？关于如何采集和使用此类数据，不应该有更强的保护措施吗？工作者不应该对由其自身数据创造的价值拥有权益吗？
如果我们未能解决这些问题，我们将冒着浑浑噩噩地走向这样一个未来的风险：财富和权力集中在少数几家科技巨头手中，这些企业越来越多地使用人工智能来接管之前由其员工完成的工作。这些公司将继续成为经济增长的引擎，投资于规模日益扩大的数据中心和性能不断提升的半导体芯片，这些投资继续推动国内生产总值的增长。
作为一个国家，新加坡可能通过我们在这些科技公司中的股份以及与其的伙伴关系而获益。然而，我们必须确保这些利益（主要流向资本所有者）不会以劳动力为代价。这些发展带来了真实的风险，即被替代的工人可能会看到他们的经济力量逐步被侵蚀，大量工人将不得不竞争数量更少的低薪工作机会。
我并不是想危言耸听，但如果不加制约，可能会出现一种数字农奴制——一个制度，其中工人像古时的农奴一样，不再受土地或封建领主束缚，而是受算法束缚。我们已经在实时看到这一未来的开端正在展开。平台工人已经在为黑箱算法工作，这些算法对他们的收入和工作时长拥有很大的控制权。随着人工智能的发展，许多认知工作和白领工作将越来越多地被自动化，并可能受到算法的控制。曾经被认为安全的职位可能不再安全。
因此，我们需要加强工人保护框架，涵盖留任福利以及工人对其在工作场所创建数据的权利等领域。由人工智能驱动的增长不能以损害工人利益为代价，也不能进一步加剧经济权力向资本所有者倾斜的现象。
主席先生，该动议的第三项要求议院为工人和企业提供配备和支持，以抓住新机遇，共同进步。尽管AI威胁要自动化和替代许多现有职位，但仍然存在许多难以使用AI自动化的劳动形式。
例如，水管工、电工、空调技术人员、采血员和其他熟练行业已被评估为不太可能被AI取代。这些工作是一个正常运作的社会的基本支柱。然而，长期以来，新加坡的我们低估了这些角色，在经济和社会方面都是如此。如果我们真正致力于确保增长保持包容性，我们必须纠正这种不平衡。在许多其他发达国家，水管工、垃圾收集员或空调技术人员的工作薪酬足够高，可以维持中产阶级的生活方式。新加坡的情况并非如此。
我们已经做出政策选择，用薪酬较低的外国工人填补这些职位，而我们的本地工人则被引导进入高薪白领工作。虽然这对我们来说已经运行良好数十年，但随着生成式AI威胁要减少高薪白领认知职位的数量，这可能不再可持续。
因此，我们必须提高蓝领部门的工资并改善职业发展道路，这些部门目前不太吸引人，但也不太容易被AI取代。我们必须通过政策、文化和教育来提升他们的地位，这样新加坡人就不再会把这样的工作视为不受欢迎的。
这可能需要困难的权衡。例如，我们应该重新调整某些部门的政策，以确保本地熟练行业的工资有意义地上升，并吸引更多新加坡人来填补这些职位吗？同时，我们必须更好地利用我们强大的职业教育机构。我们的工业培训学院和理工学院应该引导更多学生从事专业化的高价值行业。在一个由AI驱动的未来，工作的尊严不必仅仅取决于一份工作是否是白领或高科技。我们必须扩大新加坡人认为有吸引力和有意义的工作范围。
主席先生，AI无疑将决定我们经济、社会和生活的未来。但我们不应该让AI来定义我们作为人、作为公民和作为新加坡人的身份。我这样说是因为摆在我们面前的问题不仅仅是AI会创造还是摧毁工作。更深层的问题是：在一个由AI塑造的时代，我们会成为什么样的社会和什么样的人？因为主席先生，如果我们不小心，我们可能在经济上成功，但在更基本的方面削弱自己。
例如，AI创造了一个知识不再稀缺的世界。文本可以被总结，论文可以在几秒钟内写出，方程可以被解决。我之前谈过我作为本科生在难懂的文本中苦恼的经历。这是缓慢的、通常令人沮丧的工作，但正是通过这种奋斗，我学会了如何思考，如何质疑，以及如何理解世界。
然而，今天，完成任何认知活动所需的努力已经以远大于计算器取代算盘或打字机取代笔的程度而崩溃。在鼓励我们的学生利用AI时，我们如何能确保他们继续学习如何理解观念、如何阐述论点、如何解决问题，以及如何培养智力独立性？
主席先生，我重申我的警告——新加坡必须成为一个AI韧性社会，而不是AI依赖的社会。通过不断将我们的任务外包给AI，我们可能会削弱或破坏我们的创造力、想象力、判断力，甚至同情心的能力，或者让这些实践技能因缺乏使用而萎缩。
这里的危险是诱惑使用AI作为思考和解决问题的捷径。一方面，有些人把AI视为某种第二大脑——把记忆、决策，甚至判断的某些方面外包给ChatGPT或Claude。
诚然，AI工具可以提高我们的思维能力并充当智力辅助工具。然而，在我们和世界之间创造了一层人工中介的情况下，我担心AI会削弱我们理解世界的能力。我所说的理解世界，是指能够按照我们自己的条件，通过我们自己的认知努力来解释、理解和连贯地感知我们周围的世界的能力。随着时间的推移，这将涉及反思性的试错，平衡我们对世界的深思熟虑的解释和判断，与世界如何作用于我们。
解释和判断是必须通过不断定期使用来磨练的实践技能。我们通过行使、测试和挑战这些技能来开发它们。对世界和应该做什么做出判断是一项独特的人类任务，不应该轻易放弃。
我不反对第二大脑的想法。我的担忧更具体——对第二大脑的依赖，如果不加以检查，将削弱第一大脑的平衡性和反应力。
另一方面，我们看到人们与AI伴侣形成情感依附。这些是刺激同情心但不真正互惠的关系。这表明了人们可能失去对现实世界中人类关系的关注的真实风险。如果人们把这些AI伴侣视为与我们周围他人发展友谊的艰难工作相比的舒适捷径，我们可能会看到我们社交网络的进一步贫困。
在两种情况下，危险都是一样的。我们开始用人工近似替代真实的人类经验、意义制造和判断。当这种情况发生时，我们可能会逐渐失去按照我们自己的方式清晰地理解和驾驭世界的能力。主席先生，现在用马来语。
（用马来语）：【请参考方言演讲。】主席先生，最后一点。有一种传统的马来艺术形式是我心中所爱：潘图——一种有其特定规则的诗歌形式。潘图由四行组成，有特定的米数和韵律方案。其意象通常源于自然和日常生活场景，以传达重要的社会价值观和建议。
不遵循这些结构和约定的潘图通常不被视为好的潘图，如果可以称之为潘图的话。许多潘图仍然在马来人中被牢记，通过口头传承代代相传。简而言之，潘图体现了一种传统——连接今天的马来人与我们之前的祖先。
因此，我想问：如果我们教学生用AI生成潘图，而不是发现自己尝试这些行的乐趣，我们会失去什么有价值的东西吗？使用AI生成潘图的技能一定会转化为写一个好潘图的工艺，或者甚至欣赏这种艺术形式的美学敏感性吗？当一个文化主题被简化为AI输出时，对马来语言、文化和传统的长期影响是什么？
（用英文）：主席先生，最后一点。有一种传统的马来艺术形式是我心中所爱——潘图。这是一种有其特定规则的诗歌形式。由四行组成，潘图有特定的米数和韵律方案。意象通常源于自然和日常生活场景，以传达重要的社会价值观和建议。不遵循这些结构和约定的潘图通常不被视为好的潘图，如果可以称之为潘图的话。
许多潘图仍然在马来人中被牢记，通过口头传承代代相传。简而言之，潘图体现了一种传统，连接今天的马来人与我们之前的祖先。
因此，我想问：如果我们教学生用AI生成潘图，而不是自己尝试这些行的乐趣，我们会失去什么有价值的东西吗？更重要的是，使用AI生成潘图的技能一定会转化为写一个好潘图的工艺，甚至欣赏这种艺术形式的美学敏感性吗？当一个文化主题被简化为AI输出时，对马来语言、文化和传统的长期影响是什么？
主席先生，我不是在建议我们回到AI使用之前的时代。我们必须适应。但我们需要辨识力。我们必须清晰地看待AI能提供什么和不能提供什么，并始终问AI服务的目的是什么，以及它是否适合该目的。我们必须避免被困在一个以AI为中心的凝视中，这样我们就只能对现实有一个狭隘的、人工中介的理解，以及理解和关联世界及其周围人的能力贫困。主席先生，让我用潘图来结束我的演讲。
（用马来语）：【请参考方言演讲。】在议会中背诵潘图时；
最好不要使用AI；
马来人是有文化修养和礼貌的；
诗人的灵感将不会被放弃。
（用英文）：在议会中背诵潘图时，最好不要使用AI。马来人是有文化修养和礼貌的，诗人的灵感将不会被放弃。
下午3:51 主席先生：秩序，我们在议院已经待了接近五小时。我建议现在休息。我暂停会议，将在下午4:10重新主持。秩序，秩序。
会议相应暂停
从下午3:51至下午4:10。
下午4时10分继续会议。
[副议长（谢耀泉先生）主持]
人工智能（AI）转型无失业增长（议案）
[(程序文本) 辩论恢复。(程序文本)]
副议长先生：Kenneth Tiong先生。
下午4时10分 Kenneth Tiong Boon Kiat先生（阿裕尼）：副议长先生，我声明利益关系，我担任一家开发AI应用程序并提供AI咨询的公司的董事。
自ChatGPT发布以来的三年半里，我经历了两个令人敬畏和恐惧的时刻。第一个时刻是2022年11月。GPT-3.5可以迭代软件功能、生成想法、编写代码。五年前，普遍的观点是每个人都应该学会编码。如今，编码能力供应充足且廉价。计算机科学毕业生，甚至来自斯坦福大学等顶尖学校的毕业生，正在苦苦寻找工作。GPT-2是一个生成有趣打油诗的玩具。三年后，它的后继者消除了整个职业的稀缺性。我们在2023年和2024年曾讨论prompt engineering。这个话题也逐渐消退了。
第二个时刻是2025年11月，当时Anthropic发布了Claude Code，一个与前沿模型配对的可靠AI代理。我可以让计算机整夜运行，到最后会有工作完成。这与与聊天机器人聊天是一种不同的体验。聊天机器人与你来回互动，完善你的想法，满足你的各种改变想法，对你的演讲进行批判性测试。代理除非需要澄清，否则就会直接去做事情。它可能有一点偏差，但你提供输入后，再过五分钟或50分钟，它就会回来并解决问题。一个非常聪慧的初级同事。
现在我们有了AI代理、Claude Code、Codex工具，如果我可以借用网络术语的话，这让我成为了'Claude信徒'。我在自己的工作中使用Claude Code。我可以给它最模糊的规范，它就会返回最精妙的数据工作流或网站布局。对于一个无论如何都无法自己设计漂亮网站的人来说，这是一种解放。
使用这些工具的过程中蕴含一种游戏精神，这是每个新加坡人都应该体验的。这预示了一个令人疲惫的世界——软件工程师每周工作80小时，同时整夜运行多个AI代理，这样总有人或机器在时刻工作。求职者，尤其是白领工作的应届毕业生，申请数百个职位却没有收到一次面试。求职门户网站，如LinkedIn，已经成为简历的存放处，在那里，真实的体验就像向虚空中投射求职申请。
变化的速度让我们都感到谦卑。我对任何以'人工智能永远不会'开头的论断都持怀疑态度，因为这些预测的有效期往往只有几个月。让我关心的不是目标，而是谁会在过程中被落下，以及我们是否在建立制度来确保没有人被落下。
我有三项建议。首先，获取高端AI（尤其是AI代理）的权限应该是普遍的，而不是受限于课程注册或工会会员身份。其次，我们必须以对待国家双边关系相同的战略严肃性来对待少数几家开发前沿AI的公司，因为他们在定价、获取和部署方面的决定如今直接影响我们的生产率边界，程度与任何贸易协议相同。第三，我们必须通过升级应对AI速度人员替代的冗员处理制度，为工人争取缓冲时间。
主席先生，我认为获取高端AI（尤其是AI代理）是一项权利，而不是特权。智能能力（就其提升意义而言）不应该因财富而产生差异。我每月在这些工具上花费几百元钱，因为它们改变了游戏规则。但对于那些无法负担的人来说，不平等从一开始就被固定了。这是否从一开始就将他们排除在外？
政府部分采纳了我的同事Gerald Giam在2024年提出的建议，以提供通用高级AI模型访问权限。SkillsFuture Premium AI Access Scheme为注册选定课程的新加坡人提供六个月的免费工具，这是正确方向的一步。同样，NTUC的补贴涵盖21个AI工具。这些都是很好的开始，但它们不必要地受限于课程注册和工会会员身份。至关重要的是，它们可能不会涵盖AI代理——这是真实生产率差距将开放的层级。
为什么这很重要？运行AI代理成本高昂。我们可能希望代理访问的成本轨迹与互联网带宽或计算成本相同，但没有必然的理由认为它一定会这样。这是一个经验性的问题。
Anthropic的首席执行官在1月表示，其80%的收入来自企业客户，由按令牌付费模式的API调用产生。如果代理默认保持企业级别，那么个人公民——求职者、自由职业者、退休者——将被排除在真正的生产率收益发生的层级之外。
有三个可能的方向。
其一，谈判主权访问权——与前沿AI提供商达成大规模许可协议，为所有公民提供量大从优的AI代理访问权。
其二，如果代理访问在市场中由雇主提供，则应使其普遍化，要求一定规模以上的公司为所有员工提供代理级别的AI，就像我们对CPF的要求一样。
其三，如果前沿代理成本仍然过高，则确定最小的、可行的代理级别，并为其提供普遍资助。
政府是否会将高级AI访问权作为普遍权利，而不是将其限制在课程完成或工会会员身份之后？
主席先生，我最近才了解到，甚至顶尖的两三个前沿AI实验室的AI工程师也担心因为无法使用Claude Code而落后。我刚从中国回来，亲身了解到在那里根本无法使用Claude Code。Anthropic完全阻止来自中国大陆、香港和澳门的API调用。
如果甚至是开发前沿AI的工程师也渴望获得彼此的工具，如果整个国家都可能被锁定在外，那么访问权就不是一种便利。这是一种战略能力。而我们国家面临的问题是我们是否会确保这一点，还是永远只能是价格接受者。
世界上也许有三到五家公司，其在定价、获取和部署方面的决定将塑造每个经济体的AI发展轨迹。当Anthropic或OpenAI决定对代理级别访问的收费或其服务对象时，该决定对新加坡生产率边界的影响与任何贸易协议一样直接。
因此，我们应该以对待国家双边关系相同的战略认真性来对待这类公司——已经跨越系统重要性阈值的前沿AI公司。不是因为它们是主权实体——它们并非如此，它们缺乏国家的持久性和合法性，仍然受母国法律约束——而是因为它们的决定对我们的经济产生主权级别的后果，我们应该相应地与之互动。
这在实践中意味着什么？有四个方面。
首先，在主权层面谈判获取权。在前沿AI代理成本上升而非下降的可能未来中，新加坡应该寻求代理级别访问的批量许可协议，就像我们谈判能源供应一样。这意味着要接受前沿AI访问权可能成为国家支出中持续更高的项目，并有系统地采购，因为替代方案——公民因价格而无法获取定义生产率的工具——更加糟糕。
其次，我们根据我们拥有的东西进行贸易。Nvidia首席执行官Jensen Huang将AI堆栈描述为五层蛋糕：能源、芯片、基础设施、模型和应用。在我看来，我们在能源方面没有规模优势。我们没有前沿模型能力。在应用层，除了我们能自己建立的知识聚集地外，几乎没有竞争优势。我们将面临与全球最高成本地区的竞争。
但新加坡在数据中心建设方面很有优势。而且我们在水重复利用和综合水管理方面处于世界领先地位，这对水资源短缺的东南亚地区的数据中心扩张形成了制约。如果我们将自己定位为这一地区首选的基础设施伙伴，那就是真正的杠杆——这是我们可以用来交换访问权、定价权和存在的筹码。
因此，当Anthropic或OpenAI这样的公司与我们接触时，我们应该成为他们的首选区域双边伙伴，在区域内推出和扩大数据中心建设，以及提供这些数据中心运作所需的所有基础设施。
第三，我们需要吸引真实的技术存在。我们应该寻求前沿AI公司在这里建立开发办公室——而不是主要建立销售办公室，这是2010年代FAANG公司的经历。而且我更倾向于我们要有质量意识。大多数自称为'AI公司'的公司并非前沿AI公司。我们需要针对前沿AI公司制定有针对性的战略和合作。
第四，让新加坡人进入这些实验室。一旦你进入前沿人工智能生态系统，就能更容易地在这些公司之间流动。我欢迎政府进行一些事实调查——联系已经在这些公司和职位上的本地和海外新加坡人，了解他们或同事是如何被聘用的，并将这些信息传播给我们的学生和技术研究人员。目前，根据传闻，在美国，人工智能研究人员的薪酬在50万至100万美元之间（不计股权）相当普遍。因此，很明显，我们的利益所在就是想方设法让更多新加坡人进入这个紧张的劳动力市场。我真正希望看到的是建立一套针对前沿人工智能实验室研究人员的技能框架。
主席，我最后一点是关于转变的。让我从一个人开始。在杭州，一位名叫周的质量保证主管在2022年末加入一家科技公司，月薪为人民币25,000元，约新加坡元4,800元，负责审查人工智能模型输出的准确性和安全性。到了2025年，他的雇主决定可以由人工智能模型来做他的工作。他们提供了一份薪资约降低40%的新岗位。他拒绝了。他们解雇了他。周申请仲裁并胜诉。公司随后起诉并败诉。公司上诉，再度在杭州中级人民法院败诉。该判决书于今年4月28日发表，即国际劳动节前三天。
法院的理由值得我们关注。该公司主张，人工智能已使周的角色过时——这是'客观情况发生重大变化'，足以在中国《劳动合同法》下正当化解雇。法院不同意。法院认为，人工智能的采用是一种刻意的商业战略，而非不可预见的事件。选择自动化的公司不能单方面将该决定的全部成本转嫁给工人。该公司未能证明合同的履行实属不可能，而减薪百分之四十的岗位调配也不是合理的替代方案。法院进一步指出，公司应优先对工人进行再培训，并帮助他们向更高级别的职位过渡。
一项原则值得新加坡认真考虑,即故意的商业决策不应该将其全部成本转嫁给工人。
如果一名新加坡人周明天在现有框架下遭裁员,他会赢吗?我们现有的《管理过剩人力和负责任裁员三方咨询委员会(TAMEM)》是咨询性的,而非法定的。雇主可以合法地将一个职位自动化,并在不首先尝试对工人转岗或重新培训的情况下,终止该工人的雇用。而公共财政——通过SkillsFuture和新加坡劳动力部——将承担该工人转变的成本。没有人工智能特定的通知期。没有法定的转岗优先义务。工人没有诉权来对其解雇原因提出质疑。
数据表明我们正在进入这一问题开始产生影响的时期。人力部发布的2025年第四季度《劳动力市场报告》显示,2025年的裁员人数约为14,490人,较前一年的约13,000人增加。PMET裁员发生率达到每千名常住员工10.1人,高于2015至2019年期间的衰退前常态8.0。裁员集中在金融服务、信息通信和专业服务这三个最容易受人工智能影响的部门。在2025年,信息通信业就业出现了直接下滑。
政府在4月30日宣布了三方就业委员会。我当然欢迎其意图。但它没有创造新的权力,没有对雇主施加新的义务,也没有给失业工人新的权利。政府打算如何让这个委员会发挥作用?
工人所经历的往往不是关于AI驱动重组的坦诚对话，而是绩效改进计划。在许多情况下，这个过程有些'虚演'的成分，旨在掩盖一个预先确定的结果。我预见可能会给出这样的误导性理由，工人必须有权对此进行质疑。
我提议三个方向。首先，在AI驱动的职位消除前，强制规定90天过渡通知期。其次，优先重新部署的义务——在AI驱动的雇佣终止前进行重新培训或调任。这些条款将放缓AI颠覆的速度，而速度决定了是否可能进行调整。第三，工人如果认为终止雇佣的理由具有误导性，应能够对其进行实质性的质疑，以确保这些AI重组保护措施真正有效。
议长先生,最后。芬兰向人民提供了无条件现金收入。他们更幸福,压力也更小——而且绝大多数人仍然走进就业办公室申请工作。美国民调专家David Shor今年对美国人进行了民调:以三比一的比例,跨越各种政治立场,他们都选择创造就业而非直接转移支付。人们在被给予全民基本收入和就业之间选择时,总是选择就业。不是因为他们不理性,而是因为工作是你被需要的地方,而全民基本收入无法取代被需要的感觉。
所以,没有失业增长——对的。但不仅仅是这样:不能是收益被资本过度获取、调整负担落在劳动身上的增长。普遍获得,所以知识不被财富所限。战略性参与,所以我们在自己的未来中不是被动的价格接受者。以及一个裁员框架,其中决定自动化的公司先于工人承担这一决定的成本。
我不认为敬畏和恐惧会消散。但在一个为工人而建设的国家里，有更美好未来的希望。谢谢。
副议长先生：桑吉夫·蒂瓦瑞先生。
下午4时25分，桑吉夫·库玛·蒂瓦瑞先生（被提名议员）：副议长先生，在我开始之前，我向议厅两侧的各位工会同仁致以问候。感谢你们的支持。
副议长先生，作为工会人士，我们的角色不仅是支持变革，而是确保变革对我们的工人有利。从迄今为止的所有讨论来看，毫无疑问，人工智能带来了新的机遇、新的工具、新的工作方式以及更好工作的潜力。
对于劳工运动而言，无失业增长的人工智能转型必须意味着三件事。第一，人工智能增强工人的能力，而不是大规模替代他们。第二，人工智能带来的生产力收益被重新投资到人员培训、新产业、更好的工资和实际增长中。第三，没有任何工人被留下来独自应对这一转型。我将逐一论述这些问题。
确保生产力收益得到共享。副议长先生，如果我们不主动采取行动，人工智能带来的收益将不会自动得到共享。这些收益往往会集中在具有规模和能力来部署它的企业手中。转型的商业案例令人信服，我支持政府宣布的支持企业加快人工智能采用的努力，以便企业能够把握新的机遇。
然而，我呼吁寻求做大蛋糕的企业，要聚焦于工作重新设计和培训，以便与工人一起推进。在这里，我必须感谢许多支持这一呼吁的尊敬的议员。
全球有警告称，人工智能在未来几年可能会大幅减少初级白领职位。在本地，星展银行已宣布计划通过采用人工智能，在各个市场将其合同员工和临时员工共减少约4,000人。
虽然企业在优化员工队伍规模和技能结构，但我们必须保持清醒的认识，即并非所有这样的优化都能转化为经济增长，使我们的家庭兴旺、孩子茁壮、老年人安享晚年。
因此，工人正在密切关注。他们想知道是否存在让人工智能的收益惠及工人而不仅仅是管理层和股东的途径。许多工作场所才刚刚开始思考这样的途径需要什么样的形式，以及未能提供这样途径的隐患。
正如一些议员所提及的，最近中国法院一直在积极审查因人工智能相关重组而解雇员工的案件，并选择保护劳动权利，反对不公平的人工智能相关裁员。在一个案件中，仲裁庭明确指出人工智能替代不是解雇的合法理由。在另一个案件中，由于人工智能接管工作导致的大幅职务和薪酬降低未被视为合理的重新分配建议。
我希望新加坡不会看到此类诉讼案件。因此，企业必须遵守人道转型标准。当公司部署人工智能导致职位被淘汰时，企业应该拥有转型计划、再就业机会、资助的再培训和分阶段的时间安排。
这些措施必须通过CTC或三方框架与工会合作进行，以确保共同管理。我们应该将其作为基准，而不是例外。雇主和员工之间的社会契约必须随着技术而演进。
工会应该尽早参与公司的转型计划，以整合新技术、实施工作重新设计并协助工人适应新工作。在人工智能未替代的职位中，人工智能正在增加工作的速度、密度和复杂性，而非减少它。
但是，我要提醒大家，当人工智能推动人类工作边界而工作重新设计没有充分同步进行时，人们应该担心工作环境将变得不可持续，工作强度和压力非常高，可能导致疲惫、疲劳和较差的心理社会健康。我们已经在许多当今工作场所看到这一情况，特别是对于专业、管理和行政人员（PME）而言，工作越来越多地基于结果，工作和个人生活之间的界限更加模糊。人工智能存在进一步加速这一趋势的风险。
人工智能赋能的心理社会影响也值得进一步关注。我们基于时间的就业保护是为数字化程度较低的时代设计的，当时工作时间更固定，界限更明确。如今，这些新兴工作模式表明我们在如何支持工人方面还有进一步演进的空间。
这是新加坡工会发挥关键作用的地方。通过集体协议、公司级别的接触和多公司举措，例如NTUC的CTC倡议中的蜜蜂皇后伙伴关系，工会确保生产力收益被转化为更好的工作、更好的工资，最重要的是更好的工作条件，而不仅仅是更高的产出和股东回报。此外，当人工智能被用于支持招聘决策和绩效评估时，我们必须警惕无意中的偏见，并确保信息的机密性保障。
通过转型支持工人。即使收益得到共享，我们仍然面临一个更棘手的问题：那些工作被彻底替代的工人会怎样？
副议长先生，我们通常给出的标准回应是重新培训、适应、继续前行。这种建议假设工作者有时间、有财务缓冲和出错的余地来承担这样的风险。但并非所有工作者都有这种便利条件。我想要诚实相待，因为模糊的乐观主义对于失业者来说是一种承受不起的奢侈，我们必须确保系统关注这一点。
对我们的中期职业和年长的PME来说尤其如此。他们是有抵押贷款和账单要付的工作者，有子女仍在上学，通常还要照顾年迈的父母。他们不仅仅是在管理职业生涯。他们肩负着整个家庭的责任。
对他们来说，转变是高风险的。一次失败的转变不仅仅是暂时的挫折。它可能意味着长期失业、收入损失以及对其家人的长期影响。这一点我们已经在人力部提供的数据中看到了，与2019年衰退前的规范相比，PMET裁员人数有所增加，反映出他们在经历重组的行业中面临更大的风险。
这就是我们必须进一步支持养家者及其家庭的地方，确保重新培训导致真实的工作成果，转变得到支持，通往好工作的路径清晰，特别是对于那些进行中期职业转变的人。
我们不是依靠福利，而是依靠工作福利。不是最低工资，而是对我们劳动力关键部门的渐进工资模式。在人工智能时代，我们可以为我们的PME求职者寻求更好的支持。我们必须继续密切监测那些申请了求职者支持的人，并帮助他们尽快重新找到下一个更好的工作。
副议长先生，在人工智能采用中给予工作者真正的声音，其中分享收益和支持转变的前两个支柱离不开第三个支柱。在人工智能如何进入其工作场所的问题上给予工作者真正的声音同样重要。
在发达经济体中，一个原则变得越来越清晰，工作者的声音必须是技术如何重塑工作方式的一部分。在比利时等国家，工会和雇主已经在一起工作，围绕工作时间之外的沟通、工作量和人员配置制定规范。
在新加坡，我们在三方模式中拥有坚实的基础。但作为一名工会主义者，我想提出一个更广泛的观点。如果我们认真确保人工智能被公平地使用，以及人工智能驱动转变带来的收益能够到达工作者手中，那么我们必须欢迎工会代表在人工智能时代最脆弱的PME。
PME不是一个单一的群体——航空航天领域的工程师、银行业的金融分析师、科技阶段的项目经理——他们的工作环境非常不同，经历人工智能转变的影响也大不相同。工会能够从基层塑造工作场所规范，以承认多样性的有针对性方式来运作。因此，雇主应该考虑允许工会代表PME。
让工作者声音出现在桌子上的机制已经存在——它就是CTC。通过CTC，工会直接与管理层合作，制定转变路线图、重新设计工作和提升工作者技能，确保在公司转变时没有人被遗漏。
让我举一个例子。新巴士有限公司在全国运输工人工会和CTC补助金的支持下，使用人工智能全面改革了其公交车维护运营。该公司实施了人工智能驱动的诊断系统用于预测性维护，而不是裁员，而是为超过50名工作者创建了一个新的诊断专家职业计划。这样的例子必须被放大，更多的雇主应该这样做。
我们必须继续利用这一点来支持工作者和企业在人工智能转变中的发展。最近，NTUC与亚马逊网络服务（AWS）和华为等全球技术领导者合作，通过CTC生态系统为100,000名工作者和100家企业提供人工智能技能培训。
在个人层面，工会成员也可以获得工会支持，支付人工智能模型订阅费的一半。这是除了政府提供的六个月订阅之外的补充。我希望更多领先的跨国公司能够与我们的工会合作，提供更多培训，提升工作者的人工智能技能，为我们的集体未来做出贡献。
总之，副议长先生，我呼吁新加坡在这些领域向前发展。
首先，关于分享收益，我们必须确保当企业以人工智能进行转变时，收益通过公平工资、更好的工作条件和围绕工作强度的更清晰规范与工作者分享，包括对工作时间之外沟通和响应的期望。这些必须根据我们的新加坡背景进行校准，但意图明确。
其次，在支持转变方面，我们必须加强我们如何通过人工智能转变支持工作者，确保人工智能使企业能够释放新的增长，培训导致真实的工作机会，重新培训与工作重新设计结合在一起，工作者不会被单独留下来应对这些变化。
第三，在给予工作者声音方面，当人工智能被引入工作场所时，工作者及其工会必须尽早参与。不仅仅是在招聘和其他就业决定上，而是在人工智能如何改变工作范围、工作流程和性能期望上。这意味着欢迎工会代表PME的能力，并扩大CTC等机制的规模，以便工作者的声音嵌入在每个转变旅程中。
没有失业增长的人工智能转变不是一个口号。这是一个承诺。一个承诺，增长应该对每个人都有意义，而不仅仅是对经济金字塔顶端的人。而是对护士、教师、物流工人、小业主、第一次进入劳动力的年轻人。他们不是技术进步故事中的脚注。他们是进步之所以重要的原因。这些不是相互竞争的优先事项；它们齐头并进，我们正站在历史上罕见的拐点之一，我们今天做出的选择将为未来几代人回荡。
这就是三方合作伙伴必须履行、必须使其发生的地方，这也是我希望这个议院能帮助我们实现的。我强烈支持该议案。[掌声。]
副议长先生：沙拉艾尔·塔哈先生。
下午4点38分 沙拉艾尔·塔哈先生（巴西立-樟宜）：谢谢您，副议长先生。副议长先生，我声明我的利益，我从事航空航天和先进制造业工作，重点关注战略、数字转变和人工智能转变。
副议长先生，我今天站在这里怀着深深的感激之心。我在一个非常普通的新加坡家庭中长大，父母都是工薪阶层，但我获得了在世界各地建造和改装先进工厂的非凡机会。
从德国到英国，从北美到亚洲，我有幸从事工业4.0设施的建造和工作，配备了有史以来一些最精密机器的尖端工厂，这些机器生产的零件精度如此之高，只能在世界上为数不多的几个地方制造，以及组装了有史以来一些最先进的工程系统的设施。
副议长先生，经过这么多年，一个教训比所有其他教训都更突出。决定成功的不是机器，也不是技术。是人。我见过拥有金钱能买到的最好技术的工厂因为错位、因为不信任而陷入困境，因为工作者、工会、管理层和政府没有朝同一个方向发展。我也见过更谦虚的设施超额完成预期，因为每个人都与共同目标相一致。
这就是为什么这个辩论很重要，因为当我们谈论转变，特别是由人工智能驱动的转变时，我们不仅仅是在谈论技术。我们在谈论人、工作者、生计和尊严。
我想要承认我们的劳动运动、NTUC秘书长黄志明先生和杨晚龄女士以及议院成员李孟庭先生和沙克蒂亚迪·苏帕特先生提出这项议案。他们的立场不仅仅是正确的。也是及时的。
它是及时的，因为它补充了总理劳伦斯·黄先生在其预算演讲和五一劳动节集会上制定的方向，他在那里谈论了新加坡必须如何应对人工智能和全球不确定性的现实，同时坚定地与我们的工作者站在一起。而且即使技术改变了我们的经济，我们也不能把我们的人民落在身后。
我们的劳动运动以清晰和坚定的方式回应了这一点。这一转变必须推动新加坡的下一个增长阶段，但必须以所有人的公平和机会为基础。我们必须装备工作者和企业以抓住新的机会，使进步不仅仅是被创造，而是被分享。这是我们必须向下一代做出的承诺。
副议长先生，在不同国家工作过，我遇到了许多劳动运动，许多关注保护工作，保护今天存在的特定工作。通常为了保护今天的工作，他们不可避免地必须抵制变革，即使变革的浪潮是不可避免的。但我们在新加坡有什么是不同的。
从我的企业经验来看，NTUC、新加坡国家雇员联合会和政府之间的三方合作伙伴关系是独特的，独特到我的许多海外同事都真诚地感到困惑，为什么它能够如此良好地运作，为所有人带来真实的积极成果，因为我们的工会不仅仅保护工作，他们保护工作者。
我们的工会领导人,如电力和燃气员工工会的萨玛德兄弟、电子和电气工业联合工人会的法赫米兄弟、SATS工人工会的普博兰和戈维登兄弟、法定委员会员工联合工会的加布里埃尔兄弟以及这里的许多工会领导人,与工人站在一起,不仅是为了他们今天的处境,而是为了他们明天需要达到的位置。他们致力于保持工人的相关性、就业能力和准备好在经济发展时抓住更好的机会。
副议长先生,这是我们永远不应该掉以轻心的事情。请允许我围绕三个关键理念来阐述我对这项议案的立场:转变性力量、为所有人提供机会和无就业增长。
首先,关于人工智能的转变力量。人工智能的影响可以在三个层面上理解:个人、企业和产业。在每个层面上,成功都取决于工人、企业和政府的合作程度。在个人层面上,人工智能是一个力量倍增器。
它提高生产力、增强技能,使每个工人能够做得更多、更好、更快。我们许多人已经通过Open AI、ChatGPT、Microsoft Copilot、Claude、Gemini和Canva等工具体验到了这一点,但这种转变不是偶然发生的。工人必须准备好学习、适应和不断提升自己,企业必须投资培训、重新设计工作并赋能其劳动力有效使用这些工具。
政府必须提供支持结构、强大的技能框架、可获得的培训途径和广泛的技术访问权。这就是为什么我对政府提供的帮助新加坡人采用人工智能工具的支持感到鼓舞,这进一步由NTUC补贴其成员人工智能订阅的举措加强。这很重要,因为人工智能不能成为只有少数特权人士使用的工具。它必须对大众保持可获得,以便每个工人都有机会提高生产力、加强能力并有意义地参与新加坡的下一个增长阶段。
在企业层面上,人工智能可以实现更好的决策、更敏锐的运营和更高的效率。它将数据转变为洞察力,将洞察力转变为行动。但要实现这一点,公司需要正确的框架。工人需要适当的能力,政府必须提供正确的环境以负责任地扩大转变。
在产业层面上,人工智能创造了全新的价值。它重新塑造商业模式。它改变竞争并解锁新的增长。在新加坡这样的紧张劳动力市场中,这种企业和产业转变必须与深入的业务流程重新设计和有意义的工作重新设计齐头并进,正如这里的一些议员所提到的。
根据我在该行业的亲身经历,采用人工智能的决定并不仅仅是关于税收激励,正如议员Andre Low先生所指出的那样。真正的驱动力是我们如何提升和重新培训我们的工人,使他们能够承担需求不断增长的高附加值工作,以及不这样做的机会成本。
税收激励帮助公司投资必要的人工智能工具和基础设施。但同样重要的是支持工人度过这一转变的方案,无论是SkillsFuture劳动力发展补助金、NTUC CTC补助金、工会培训援助计划和新加坡劳动力部的职业转换计划等计划,这些举措支持工作重新设计、培训,甚至在工人进行提升和重新培训期间提供工资支持。
通常,采用人工智能并不是技术和工人之间的二元选择。这是关于重新设计业务流程,以便企业能够通过更有能力、更熟练和更高效的劳动力做更多事情来应对世界的挑战。
这些由人工智能解锁的价值必须被分享——分享以便工人得到提升、企业变得更强大、社会一起向前发展。但最终,这是我们必须继续维持的工人、企业和政府之间的社会契约——一个以公平性、包容性和共同进步为基础的契约。
综合考虑,人工智能不仅仅是任何其他技术工具。它是一个全系统的转变。这就是为什么三方合作在人工智能时代更加重要。我很高兴听到劳工运动的立场。
第二,关于为所有人提供机会。议长先生,这一转变将创造经济增长。但这也是一个充满真实不确定性的时期。我们必须承认这些挑战。我们的应届毕业生正在感受到这一点。许多人为了确保永久职位而苦恼。多个实习正在成为常态。我们在什么时候会询问这是否成为真正就业的替代品?
当人工智能重新塑造从开发者到律师的职业时,我们如何确保我们的年轻人仍有有意义的入口点?如果公司开始质疑入门级角色,那么我们也必须问,谁将培训我们下一代的劳动力?
我们的职业中期工人感受到这一点更为深刻。他们有家庭和责任,他们担心工作转变可能使他们的经验不那么相关。我们的蓝领工人——我们的技术人员、操作员和司机——对自动化和他们工作的未来提出了尖锐的问题。
这些恐惧是真实的。如果不解决,它们可能会分裂我们的社会。这就是为什么这种为所有人提供的机会不能仅仅留给市场力量,这也是议员Poh Li San提出的一点。它要求公司,特别是中层管理人员,给应届毕业生一个真正的机会。它要求企业重新设计工作并真诚地投资提升和重新培训。它要求我们所有人一起工作,以便每个新加坡人都能在这个新经济中找到自己的位置。只有这样,我们才能说这不仅仅是增长,而是为所有人提供的机会。
最后,关于无就业增长。在许多经济体中,无就业增长意味着没有就业的增长。但在新加坡,我们的情况不同。我们已经接近充分就业。所以,这不仅仅是关于创造更多的工作。这是关于确保我们的人民能够承担创造的工作。
因为增长将会到来,新的角色将会出现。但如果我们的工人还没有准备好,如果技能没有跟上步伐,我们就会冒一种不同的无就业增长的风险——不是缺乏工作,而是工作与我们劳动力拥有的技能之间的不匹配。避免这种情况意味着关注能力建设,而不仅仅是人员数量。
企业必须改变工作性质,而不是消除它们。工人必须继续学习。政府必须通过强大的系统和途径支持希望。
当我们做好这一点时,增长不会让人们掉队。它会提升他们。副议长先生,请用马来语。
(用马来语):【请参阅方言演讲。】议长先生,关于人工智能的讨论今天已经不再是离我们生活很遥远的事情。在新加坡和世界各地,一件事是明确的——人工智能带来了希望,但也带来了关切。
在我们的马来/穆斯林社群中,这些关切是真实的。年轻人担心就业的未来以及是否仍然存在机会。那些职业中期的人对自己的经验和技能是否仍然相关感到焦虑。蓝领工人——包括司机、技术人员和普通工人——想知道他们的工作是否会被自动化取代。
我们必须承认这些关切。但与此同时,我们不能仅把人工智能视为威胁。我们必须将其视为一个机会——一个一起进步的机会。
请允许我涉及人工智能转变中的三个重要点。
首先,关于建立技能以成为这一转变力量的一部分。人工智能只有在我们知道如何使用它时才会成为力量倍增器。这就是为什么我们必须准备好不断提升自己——重新培训和提升技能。
这里重要的是我们利用可用的支持——无论是通过新加坡劳动力(WSG)计划、NTUC还是社区举措,如M3+。例如,在M3+ Pasir Ris–Changi,我们运营各种计划来帮助社群提高他们的技能和就业机会。这些包括女性工作计划,帮助女性重返劳动力市场,以及在Pasir Ris举办的职业市场,以开放获取职业机会和就业网络。
这些努力没有停止在那里。通过Pasir Ris–Changi的HashTech计划,我们开始向我们的孩子介绍人工智能、机器人和自主系统——包括通过机器人大战等活动。这不仅仅是一个活动。这是一个从小开始建立信心、接触和未来就绪技能的努力。
关于技能,对人工智能的恐惧不应该阻止我们学习如何明智地使用它。人工智能可能削弱对马来语言和文化以及其他技能的深入理解的关切是可以理解的——如果在不理解基础知识和其局限性的情况下使用它。
像任何其他工具一样,重要的是我们如何使用它。掌握和欣赏马来语言在理解其美丽、价值和意义中仍然是关键。
但是,如果使用得当,人工智能也可以帮助保存我们的遗产。人工智能可以协助数字化旧Jawi手稿,生成受传统马来图案启发的蜡染设计,并促进马来语的学习和翻译。甚至经典的马来电影也可以为未来几代人保留。
技术不应侵蚀我们的身份认同。如果明智地使用，人工智能可以帮助保护语言、加强文化，并自信地将马来传统传承到未来。
请允许我也分享一首班顿诗。
金色香蕉送到海，
一个在箱顶成熟，
如果人工智能被非常明智地使用，
文化代代相传，深植心中。
(英文)：副议长先生，从根本上说，这不仅仅是一次经济转型。这是对我们社会契约的考验，这份契约必须在新时代重新确立，在这个新时代中，企业的承诺不仅仅是利润，更是人民；工人的承诺不仅仅是工作，更是终身成长；政府继续与两者并肩同行，确保没有人被落下。
如果我们能够做到这一点，如果我们能够以信任、目标和共同责任一起向前迈进，这项转型就不会分裂我们。它将使我们更加强大，因为当工人、企业和政府一起行动时，我们不仅仅是适应变化。我们塑造变化，我们从中受益，我们确保每一个新加坡人都一起向前迈进。副议长先生，我支持这项动议。[掌声。]
副议长先生：副教授 Terence Ho。
下午4时54分 副教授 Terence Ho（被提名议员）：副议长先生，我起身支持这项及时的动议。我首先想声明我的利益关系——我是新加坡社会科学大学成人学习学院的执行董事。
众所周知，人工智能是一种变革性技术。我们都认识到，它将深刻改变整个经济中的商业模式，进而改变工作的内容和性质。
作为一个小而开放、技术先进的国家，新加坡必须努力走在新技术的前沿，特别是像人工智能这样重要的技术。除了对我们的经济至关重要外，人工智能在应对新加坡人口和社会挑战方面也具有相当的潜力。但无论我们拥抱还是畏惧人工智能，都无法逃避它对我们公司和员工队伍的影响。
我将在演讲中提出四点。
首先，无就业增长不是新加坡的选择，因为优质就业对包容性增长以及实现公平、充满活力的社会至关重要。
新加坡的社会契约基于通过工作实现自给自足。这意味着通过就业和收入为自己和家人提供生活保障。多年前曾在本院表述过，'工作是最好的福利，充分就业是新加坡工人的最好保护。'
在这份社会契约中，政府的角色是培育有利于投资和创造就业的亲企业商业环境。任何愿意辛勤工作的新加坡人都将通过中央公积金储蓄有足够的资金来满足住房、医疗保健和退休需求。在实践中，政府以住房补助、中央公积金增值和医疗保健补贴的形式提供重大支持，以支持房屋所有权、退休充分性和医疗保健保障。
新加坡的社会经济模式随着时间推移而演变。我们现在通过社会保险实现更广泛的风险共担，补充个人储蓄以满足医疗保健和长期护理需求。存在更多结构性或永久性的社会支持，包括工作收入补充和银发支持。政府认识到经济和就业中断的更大风险，已通过SkillsFuture求职者支持为非自愿失业者引入收入救济，这已由议院议员讨论过。
但就业和收入仍然是新加坡社会经济模式和社会契约的核心。人工智能的最近进展对这一模式构成了挑战。全球享誉的人工智能先驱和行业领袖曾警告人工智能可能导致大规模失业的可能性。所谓"白领血洗"或"就业末日"的预测已激起公众恐惧，尽管其他评论人士声称这些恐惧过度了。
过去的变革性技术确实消除了某些工作，但它们也创造了新工作，因此我们不会都没有工作或过着无限闲暇的生活。
生成式人工智能引起了特别的关注，因为它可以接管与人类技能和创意相关的工作和任务，包括编码和数据分析等认知任务以及写作和设计等创意任务。这些任务需要通过多年教育和培训建立的技能，因此获得很好的报酬。它们支撑了许多新加坡人渴望的好工作。
虽然我们不应该低估人工智能的破坏，但仍有时间适应和应对。这是因为工作流失或失业的程度取决于技术扩散的速度，这在历史上遵循了S曲线。
我在3月提交了一份议会质询，询问人力部是否发现了任何人工智能促使新毕业生招聘放缓的迹象。确实，议院的许多议员都指出了这一关切。我当时收到的回应，昨天也得到了重申，是年轻学位持有者的就业率保持基本稳定。
这可能是因为人工智能的采用对许多本地公司仍处于早期阶段。许多公司需要时间从将人工智能视为仅仅的项目或生产力增强工具转变为围绕人工智能从根本上重新组织工作流程。然而，随着人工智能采用步伐加快，对公司生产力和利润的好处将增长，但对工作的影响也会增加。
许多议院议员也讨论过一个相关的关切，即在人工智能时代，利润将越来越多地流向科技公司和这些公司的股东，而工人获得的利润将减少，因为技能变得商品化。
虽然我们必须考虑对更多社会支持和新的再分配渠道的需要以保持我们社会的包容性，我们也必须继续为公民赋予通过良好工作和收入自给自足的能力。
我们中的一些人可能还记得Tharman总统在2015年圣加伦研讨会的一次采访中所解释的内容。他在描述新加坡的方法，我引用道："这是关于保持活力的文化，其中我为拥有自己的房子感到骄傲，通过我的工作赚取我自己的成功。我为抚养我的家人感到骄傲。保持这种文化的延续是使社会充满活力的原因。"
如果我们看世界各地经济如何发展，很明显成功的关键是由教育和创造就业机会推动的强大中产阶级的出现。许多拥有丰富自然资源的国家表现不佳，因为他们的重点一直是资源开采，使少数人受益，而不是教育和技能发展，这使很多人受益。也很明显，新加坡之所以成功，正是因为人民是我们唯一的资源。新加坡的经济发展是包容性增长的故事——这是我们必须坚持的道路。
这引导我进入第二点，我们必须支持工人发展深层领域知识、学习敏捷性和职业韧性。为使工人适应人工智能时代，人工智能工具培训当然很重要。对人工智能的熟悉和对不同人工智能工具的优势和局限性的理解来自频繁使用、调试和实验。但是，正如议院许多议员也意识到的那样，这只是部分答案。毕竟，人工智能工具应该随着时间的推移变得更直观和易于使用。
人们为工作带来的真正价值在于对领域或主题的深入理解，这意味着我们所有人仍然必须投入艰苦的努力来学习，并通过在学习过程中创造建设性摩擦来避免"认知卸载"，无论是在学校还是在工作场所。人工智能可以提供脚手架并可以帮助个性化学习，但它不能成为思考的替代品。
许多人确定的关键技能是学习如何学习，对变化具有适应性和韧性。这意味着走出我们的舒适区，不断挑战自己，适应不同的任务和工作环境，以及在多样化团队中工作。
这是每个人的责任：对自己的学习和职业发展负起责任，并在可用的情况下充分利用公共资金和资源。
雇主也负有责任。由人力部(MOM)开发的 Singapore Opportunity Index 突显了雇主如何为员工创造机会，例如通过招聘实践、职业发展路径和工作设计。通过识别具有支持职业成长良好记录的雇主，希望能够鼓励这些雇主投资于员工，帮助他们规划职业生涯。
第三点我想提出的是，我们不仅要为工作提升工人的技能，还要为工人改善工作。正如我在MOM拨款委员会辩论的演讲中所提到的，在医疗保健和技能行业等领域，对工人的需求将继续保持强劲，这是由老龄化人口以及这些职位相对抗AI取代的韧性所驱动的。
然而，这些工作很难吸引新加坡人，因为相比白领办公室工作，它们被认为声望较低或回报较少，或许不够舒适。但风险在于，当新加坡人努力寻找符合他们期望的工作之际，新加坡却日益依赖外国人来承担必要工作。
目前，本地劳动力中超过40%拥有大学学位。因此，传统上被认为不需要学位的工作和职业必须重新设计，以适应包括毕业生在内的各种劳动力。
薪酬只是问题的一部分。工作必须重新设计，以开发工人的"头脑、心灵和双手"技能，使其对工人更具吸引力，对人工智能颠覆具有更强的韧性。这可能涉及承担更大的专业责任、增加工作的认知、分析和创新内容，以及在工作中创造更多人际互动的机会。人工智能工具实际上可以通过增强人类专业知识来支持职业和半熟练工作的升级。通过使这整个范围的工作对新加坡人更具吸引力，我们可以避免结构性过度资格或就业不足。企业可以通过以技能而非资质为中心来进行工作设计。
我的第四点是，新加坡应该建立专业知识，成为技能优先和以人为中心工作重新设计的全球参考点。技能优先的方法意味着工人不会因其正式资格而被限制在特定的工作或职业。雇主认识到，无论工人的起点如何，他们都可以通过提升技能来满足工作要求。同样，工作和职业的范围可以扩展，以更充分地利用工人的技能。
人工智能已经在对工作进行分割——分解为多项任务，其中一些分配给人工智能，另一些分配给人类工作者。重要的是，工作重新设计应该以人为中心，这样人类工作者仍然可以做出有价值的贡献，由人工智能和技术增强，而不是让流程完全自动化，人类参与最少。
随着智能代理AI现已能够执行跨越多个工作角色的流程，仅重新设计特定工作内的任务已经不够了。相反，组织必须着眼于重新设计端到端的工作流程。这是一种必须嵌入组织内部的能力，因为AI不断重塑工作的本质。新加坡有机会在技能优先就业实践和以人为中心的工作重新设计方面引领步伐，这将同时造福我们的企业和劳动力，对我们的社会契约也至关重要。
成人学习学院的技能优先实践中心最近推出了一系列技能优先工作论文和配套的圆桌讨论。这些论文和讨论吸引了来自世界各地的专家、政策制定者和行业从业者的广泛国际关注。
人工智能对工作和学习的影响是所有国家和社会都在努力应对的一个问题，没有人拥有所有答案。这是一个富有前景的研究领域，因为企业和社会都在寻求适应和转变。我们处于一个复杂的运营环境中，没有久经考验的方案可以依靠。正如我最近与一位企业领导人交谈时所说的那样：我们在飞行中学习和适应。
在人工智能时代，学习和工作重设计都必须是迭代的、实验性的。我们需要新加坡和世界各地最聪慧的人才专注于此。正如新加坡在量子计算等新技术领域拥有世界领先的研究中心一样，我们应该在成人学习和以人为中心的工作重设计方面积累专业知识和经验。
当今，高等教育机构中遍布着卓越中心。例如，理工学院和ITE属于职场学习的全国卓越中心。新加坡管理大学已建立了韧性劳动力研究所，而新加坡科技学院推出了技能评估和验证倡议。在新加坡社会科学大学，成人学习研究所设有成人学习协作中心和技能优先实践中心。凭借从研究到转化的全方位专业知识，成人学习研究所可成为成人学习和就业能力的全国中心。
我们可以共同将新加坡建设为成人学习、职业健康、人机互补性和以技能为先的实践等领域的思想领导者和实验室。作为一个融入国际尖端研究和实践网络的全球创新者，新加坡可以帮助以促进经济增长和人类繁荣发展的方式塑造未来工作。
副议长先生，摆在我们面前的动议有力地表达了新加坡三方合作伙伴对包容性发展的承诺，这种发展造福工人和企业。这很重要，因为我们不能再理所当然地认为未来的经济增长必然伴随充分就业和收入上升。除了适应人工智能，我们的最终目标必须是使每位工人能够成长、做出贡献，并在工作中找到意义。
国家人工智能委员会和三方就业委员会的成立体现了这一承诺。这是一项举国上下的努力，每个人都有一份力量可以贡献。
最近，一位美国记者接触我，想了解新加坡如何应对人工智能及其对就业的影响。她指出，许多大型美国公司面临大幅削减员工的压力，以此来提高利润。确实，股东和投资者期望管理层用人工智能替代员工。当我向她分享新加坡的优先事项是培训员工与人工智能一起工作时，她用她的话把这种对比描述为「鲜明」和「鼓舞人心」。
借助我们独特的三方合作以及所有伙伴的承诺，我相信企业和员工能够以坚定的决心和信心迎接即将到来的人工智能转型。
副议长先生：杨亚历克斯先生。
下午5时09分 Alex Yeo先生（Potong Pasir）：副议长先生，人工智能可能令人害怕。我想起工作中第一次收到年轻同事的法律意见书初稿，其中某些内容是由人工智能生成的，当时我心中警钟大作。「这些内容可靠吗？我会因为提交这份文件而被法院问责吗？」尽管这些内容已经过核实，并与经过深思熟虑的「人类」生成的法律分析结合在一起，但我仍然感到焦虑和担忧。
这个事件让我回想起我初入法律界时的情景。我会在办公桌上收到来自某位高级合伙人的书面备忘录，其中包含关于某些事项的指示。有一次，我问他是否可以用电子邮件会更容易，但我被告知电子邮件不可靠，而有了书面备忘录，他才能确信我会收到信息。我们都知道不能和老板争论，但最终这些书面备忘录确实转变成了电子邮件，也许是因为意识到电子邮件指示即使在办公时间之外也能可靠地传达给我。
正如历史上每次工业和技术变革一样，无论是蒸汽机、电力、个人电脑带来的数字化、互联网带来的连接，还是现在的人工智能，变革和转变总是伴随着焦虑和对未知的恐惧。人类天生对我们无法控制的事物抱有不信任——也许这样甚至是对的。
在人工智能方面，我们在新加坡尤为深切地感受到这一点。议院的许多议员都谈到了这些顾虑，以及来自各行各业新加坡人的忧虑。俗语有云，「唯一不变的就是变化」。对未知的恐惧是一种自然反应，但我们应该将其作为一种激励力量来重新思考旧的方式、学习新的方式，进而抓住新的机遇并实现增长。
因此，这项动议是及时的。它承认，利用人工智能促进增长是一把双刃剑。一方面，人工智能可以成为新加坡经济发展下一阶段的驱动力；另一方面，如果其发展和部署不加约束，可能导致社会问题，如就业流失和不平等加剧。
正如总理在其预算演讲中指出的那样，人工智能只是一个"工具"。我们如何利用它以及如何管理其部署将塑造我们的经济、我们的工作、我们的生活。因此，正如动议所述，我们对AI驱动增长的方法必须以公平、韧性和全民机会为基础。这项动议引起共鸣，因为它关乎将人民置于新加坡AI驱动增长方法的中心。增长必须具有包容性，造福我们的人民。我们不能不惜一切代价追求无就业增长。
先生，人们对人工智能对工作场所和劳动力的破坏性影响的认识程度极高。我们各行业的工人和专业人士、经理及行政人员(PMEs)的忧虑和关切不是假设性的。这些都是真实存在的，甚至是可以量化的。新工会(NTUC)最近进行的一项调查发现，我们超过半数的PMEs感到迫切需要提升技能以保持相关性。近三分之一的人对被替代感到焦虑。其他研究表明，半数新加坡人担心他们的角色可能被自动化，许多人关切人工智能将更多地惠及公司利润而非普通工人。
我们初次进入劳动力市场的年轻毕业生面临着严峻的现实。随着人工智能对日常工作的自动化，雇主们提高了用人标准，从一开始就要求具备更高阶的批判性思维和人工智能协作能力。如果任其发展，人工智能的颠覆可能导致不公平的结果。那些能够抢占先机或成功过渡的组织和个人将获得指数级增长的收益，而那些未能做到的将被落在后面。
多年来，我们一直主动预判像这样的颠覆性变化。通过SkillsFuture等项目，我们向新加坡人投资并灌输终身学习的价值观，以及定期提升技能的必要性。这为我们现在大力推进AI采纳奠定了良好基础，如国家AI影响计划（National AI Impact Programme）旨在支持一万家企业，帮助十万名工作者提升AI能力。
然而，普通民众的AI能力和素养同样重要。
对此，我想提出两点。
首先，你们会想起我演讲开始时讲的个人逸事。无论是过去的计算机、智能手机，还是今天的人工智能，熟练使用任何工具都关乎建立信心。
林文兴先生是前NTUC秘书长，他与我分享了他在上世纪80年代参与政府计算机化工作的经历。这在当时是战略性决定，但工人们害怕计算机。因此，政府设计了计算机素养课程，由NTUC推出，使用早期苹果计算机。熟悉键盘的使用，以及对于那些记得的人来说，玩PacMan这样的游戏。工人们逐渐克服了恐惧，拥抱了熟悉感。重要的是，关键信息必须是，这是一个能帮助你更好、更快地完成工作的工具。现在，这个新工具是人工智能。
虽然提高我们工人的技能以利用与各自工作场所相关的人工智能工具至关重要，但人工智能素养应该是一项国家级的努力，应在我们的学校、社区俱乐部甚至积极老龄化中心提供。
这个想法是将人工智能素养融入生活的一部分，无论是使用人工智能工具创建一个简单的电子贺卡，该工具可以创建动画图形，或使用机器人建立一个十亿美元的公司。只有这样，我们才能设想整个人民在具有人工智能驱动增长的经济中共同进步。
如果拥抱人工智能是一项国家战略举措，那么我们应该为所有新加坡人推出一个国家人工智能识字和素养计划。
其次，支持工人成为人工智能流利使用者应该不仅仅是为他们提供人工智能工具和使用工具的方法。我们还必须为工人提供时间和能力，以学习如何在他们的工作场所应用人工智能工具。
让年轻毕业生找到工作，并确保年长工人和PME进入新的角色是迫切需要的，但如果人工智能要改变我们的经济，我们必须确保我们的劳动力通过更深层次的学习有效地学习，同时说服我们的企业和组织创建允许我们的工人测试他们的新技能、从错误中学习和改进的工作场所和系统。学习必须与建设能力相结合。
在最广泛和最普遍的工具使用中，人工智能可以在几秒钟内生成内容、总结和回答问题。我们需要一支不仅能够使用人工智能工具获得这些成果，而且能够与人工智能作为协作伙伴合作，同时应用判断力、理由、创造力和背景来推动高影响力价值的劳动力——人类元素。
何铭华教授在最近一篇倡导更深层次学习的《商业时报》文章中举了美光新加坡的例子，该公司的内部人工智能技能提升计划不仅停留在意识阶段，还让员工使用人工智能工具更快地提取见解、更好地分析风险、自动化日常任务、更有效地规划项目和改进决策制定。
我们如何说服更多的企业和组织投入时间和宝贵的资源与我们一起实现这些目标？提高我们的劳动力技能，确保他们拥有必要的凭证和知识，可能会让他们找到工作，但这不能保证企业和组织会以能够建立和优化他们的人工智能能力的方式雇用和培训工人。
本政府一直刻意地将我们的政策重点放在长期进步而不是短期收益上。因此，我相信由总理领导的人工智能国家委员会将以相同的基础制定计划和倡议。
事实上，在我们的制度中，我们已经具备了政府、工会和雇主密切合作的能力，以实现长期目标，确保我们的劳动力配备了知识、技能、深刻理解和实际应用成果。
我们的三方合作模式，其中所有三个合作伙伴经过几十年建立了信任、相互尊重和平等伙伴关系，在人工智能采用的这个新阶段携手合作，将帮助我们确保我们的工人、企业和经济能够抓住新机遇并共同进步。
在我结束之前，我想支持NTUC秘书长黄志明先生关于建立针对新加坡市场的市场情报和前瞻系统的提议。我们可以理解，从三方合作伙伴的信息、数据点、分析和研究中汲取见解，以感知早期信号、协调应对和在必要时提供主动早期干预，这将有多么有用。
话虽如此，虽然支持我们的工人重新培训并转向不同的角色以防止失业很重要，但我们也应该探索使用相同系统中的信息来确定政府如何激励人工智能初创企业为我们的劳动力创造新的就业机会的可能性。例如，据报道，中国的人工智能电影制作初创企业得到了激励和财政支持。据报道，他们开创了微剧或竖屏剧这种新的娱乐格式，在全球掀起了波澜。
先生，如果我们要以人工智能作为新加坡经济发展的下一个阶段，我们必须进行转型，不仅要改造我们的经济，还要改善每一位工作者和每一位新加坡人的生活。副议长先生，我支持本动议。
副议长：Patrick Tay先生。
下午5时20分 Patrick Tay Teck Guan先生（先锋区）：副议长先生，我起身支持本动议。我想感谢本议院中的NTUC兄弟姐妹为支持本动议而到场。
像PME（专业人员、经理和行政人员）这样的知识工作者极易受人工智能影响，不同于之前主要影响基层员工的自动化浪潮。我们许多中等收入的PME属于被夹在中间或保护不足的群体。他们被期望表现得像高管一样，但保护程度不如基层员工，同时还要面对来自外籍PME的激烈竞争。处于职业中期的PME被夹在年轻和年长的受赡养人之间，承受不起失业。然而，当他们因收入和年龄较高而被裁员时，往往需要花费更长时间才能找到新工作，通常还要付出降薪的代价。
我们认为PME具有特权地位和适应能力，他们拥有资源，能够主动承担责任以提升技能，也能够应对挫折。这一假设已不再成立。人工智能将在所有PME部门和各个级别中既增强又破坏工作任务。我们必须认识到人工智能是一种变革性技术，它有潜力创造新机遇和共同繁荣，但也有潜力通过将财富和权力集中在顶端来加剧不平等，特别是如果在采用人工智能的竞争中忽视了对广大中产阶层的保护措施。
为此，我主张新加坡对人工智能的政策必须以人为中心，而由人工智能推动的增长必须以工作者为中心。这意味着我们致力于我所称的'3E'。'3E'是公平增长、加强的保护和参与的劳动队伍。
第一个'E'，公平增长。当我们谈论人工智能驱动的无就业增长时，这并不必然意味着大规模失业。然而，这可能意味着人工智能带来的收益可能不会流向广大中产阶层。今年早些时候，经济发展局（EDB）宣布预期创造的就业岗位数下降至15,700，这是至少20年来最低的数字，尽管所吸引的投资比前一年更多。这表明虽然我们可能看不到无就业增长，但我们很可能会看到创造岗位较少的增长。求职者可能会为更少的空缺岗位进行竞争，就业不足可能会上升，工资可能会停滞。与以前相比，年轻毕业生可能会面临更大的挑战来获得全职就业。
在全球范围内，我们已经看到一批公司，特别是科技部门的公司，宣布了大规模的裁员，原因是人工智能。
公平增长意味着AI驱动的增长所得将与工人共享，形式包括更高的工资、福利和工作前景。作为开始，我们需要提高对何为公平和负责任裁员的标准，例如要求提前裁员通知、支持工会根据行业规范谈判裁员福利，以及设计AI补助激励措施，要求雇主证明他们为有意义地重新部署那些工作被AI接管的工人而做出的努力。
当新加坡努力吸引全球顶尖AI人才来到我们的国家时，我们也必须确保这建立并加强我们的新加坡核心。我要求政府通过诸如能力转移计划等项目鼓励互惠，以便知识和专业知识流向我们的本地中小企业。同时，政府也可以通过诸如海外市场沉浸计划等项目，将本地AI人才送往海外顶尖AI公司进行培训实习，从而投资于本地AI人才。引进全球专业知识与开发我们自己的全球人才管道是同一枚硬币的两个方面。两者都深化了我们本地劳动力的能力。
第二个"E"，增强保护。在向AI的过渡中，不可避免地，一些工人会受到影响。我们不能让他们自生自灭。他们需要职业指导、财务支持和机会来更强地反弹。我感谢政府推出求职者支持计划，让非自愿失业的工人受益于长达六个月的过渡性支持，同时他们接受培训或寻找下一份工作。
求职者支持计划的收入门槛目前设定为5000美元（不包括中央公积金），这只能覆盖少于20%的本地中小企业。我希望政府考虑将此门槛提高至本地中小企业的总中位数收入，目前为2025年的8400美元，或考虑一些其他合适的等效方案来满足受影响中小企业的需求。同样地，政府也可以考虑允许拥有HDB住房贷款的人延期还款长达六个月，特别是当他们无法支付抵押贷款时，以缓解他们的即时现金流需求。
新加坡采取了经过深思熟虑、框架化的人工智能治理方法。我们没有落后。我们在谨慎推进。通过信息媒体发展局的人工智能治理框架、网络安全局为保护代理人工智能系统的补充意见和自愿测试工具包，我们鼓励了创新和负责任的采用。
但随着人工智能从协助决策转变为制定决策，包括在招聘、晋升和重组中，我们必须跟上步伐。其他发达经济体已经率先采取行动，明确将与就业相关的人工智能列为'高风险'。
这对工作者意义重大。招聘AI是否会自动将残疾应聘者排名较低？如果人力资源部门在重组期间依赖AI工具来筛选谁留谁走，当结果看似不公平时，工作者有什么救济途径？在这种情况下谁应当承担责任——人力资源团队、采购该AI工具的雇主，还是开发该工具的开发者？
这些不是假设性的关切。新加坡科技设计大学（SUTD）与GovTech联合研究发现，大规模学习模型可以从爱好和志愿服务等其他数据点中可靠地推断出个人特征，如候选人的性别，即使简历已进行匿名处理。
我们很幸运通过了《工作场所公平法案》。其原则——即就业决定必须公平并基于劳绩，每位工作者都有权获得公平的好工作机会——无论这些决定是由人类还是算法做出，都应该适用。
但是，虽然这些原则是技术中立的，我们目前的反歧视措施还没有明确解决如何将它们应用于人工智能做出的决定。随着人工智能的应用加速，雇主需要明确什么是负责任的使用，工作者需要确保现有保护措施在进入人工智能支持的工作场所时仍然适用。我们应该缩小这一差距，不是通过扼杀创新的法规，而是通过清晰、实际的三方指南来确保公正和公平的过渡。新加坡的优势是我们的三方传统，我们应该加以利用。
为此，我请求政府考虑以下几点。首先，采用就业相关人工智能的雇主应该被指导进行与影响程度相适应的风险评估，并确保有意义的人类监督。其次，人力资源专业人士应得到培训和自我评估工具的支持，以负责任地使用人工智能并识别偏见。参与数据治理和网络安全的官员也可以在这个不断发展的领域更新他们的技能和知识，因为越来越多的公司采用与企业数据整合的人工智能。第三，应该给予工作者透明度。他们应该知道在影响他们的决定中人工智能在哪里被使用，什么防护措施已到位，以及现有的救济途径如何适用。第四，我们应该从源头着手，与人工智能供应商和开发者合作，以确保底层软件在到达我们的工作场所之前符合公平和透明的基本原则。国际劳动组织已经开始了这一旅程，新加坡凭借我们的三方传统，可以成为这个领域的先行者。
第三个也是最后一个"E"，即敬业的劳动力。工作者掌握人工智能并弄清楚如何将人工智能融入他们的工作流程，而不是反过来。最终，一个组织不能只靠人工智能运行，必须有工作者参与。简单地从上往下强制推行人工智能不会产生效果，甚至可能产生抵触和沉没成本。工作者是最终用户，也是他们自己工作流程中的专家。他们知道人工智能在哪里增加价值，在哪里不足。如果你想让人工智能发挥作用，你必须询问做这项工作的人。
我们已经有了一个经过验证的机制来做到这一点——我们全国工会大会（NTUC）的CTC。CTC在公司层面将管理部门、工会和工作者聚集在一起，共同设计转型计划，把技术采用与工作重新设计、技能升级和更高的薪酬相配套。
让我分享一个例子，总理在五一节集会上分享过。在淡港医院（TTSH），医疗服务员工工会（HSEU）与管理部门通过CTC合作推出了智能排班系统，可以处理多个班次模式，将排班时间从超过90分钟减少到不足15分钟，这样护理经理可以将更多时间花在其他核心工作上。
资深注册护士梁莉安（Lilian Teng），现年69岁，在淡港医院工作了19年，她简单地说：随着技术让工作对身体的要求降低，只要她保持健康，她就可以继续有效地工作。这就是敬业劳动力的样子。
但仅靠公司层面的努力是不够的。随着三方就业委员会的成立，政府、雇主和工会现在可以协调行业转型，以工人为中心，确保人工智能培训、职位重新设计和转型支持由基层塑造，而不仅仅是从上而下的决定。
至关重要的是，三方就业委员会可以升级CTC生态系统，将其范围从大型雇主扩展到可能没有资源独自应对转型的中小企业。CTC在公司层面与工人合作。三方就业委员会将在国家层面这样做。他们共同确保人工智能转型不是强加给我们的工人，而是与他们一起进行的。用中文，议长。
（用普通话）：[请参阅原文演讲。] 副议长先生，人工智能已经来临——而且来势迅猛。但我们必须问：当人工智能创造财富时，财富流入谁的口袋？我提出三点。
首先，公平分享蛋糕。人工智能创造财富，但这些财富不能仅流向雇主。工人帮助烤蛋糕，他们也应该得到一份。
其次，如果失去工作，我们不能让人们自生自灭。求职者支援的资格标准可以扩大，这样更多的PMEs可以受益并获得更大的保障。我们必须未雨绸缪——在暴风雨来临前做好准备。
第三，一起走这条路。人工智能转型不能仅由雇主决定。俗话说，三个臭皮匠顶个诸葛亮。三方伙伴、工会和雇主必须共同努力，这样我们才能走得远、走得稳、走得快。
公平分享蛋糕，一起向前走。这是属于每个新加坡人的人工智能未来——一个以人民为核心的未来。
(英文):综上所述，关于人工智能是双刃剑的言论已经很多。这个比喻虽然被过度使用，但这并非虚言。
人工智能对广大中层的影响意味着它既是一项'百年一遇的技术'，也可能是百年一遇的分化力量，将收益集中在控制人工智能的人手中，同时却导致那些帮助设计、实施和构建人工智能的工人被取代。
公平增长、强化保护和充分参与的劳动力。这三项原则必须指引我们前进，如果我们希望在公平、韧性和为全体创造机会的框架下，在我们的人工智能转型中，将人工智能确立为一个助力，因为每一位工人都很重要。副议长先生，我支持本动议。
副议长先生：政务部长Jasmin Lau
下午5时34分 数字发展与信息部政务部长（劳家蕙女士）：副议长先生，我今天认真倾听了议员们的意见。议院内普遍对人工智能对我们工作者的影响表示真诚关切。这些关切是真实的。政府与大家一样有这样的关切。
我们不能放慢人工智能的发展。但我们不会让其结果听天由命。我们将努力促成在这里繁荣发展的公司与为此付出努力的工作者之间达成不同的协议。
在新加坡运营和增长中获益的公司，我们期待工作者获得公平的协议。不仅仅停留在言辞上，而要体现在工作设计、人员培训以及收益分享的方式上。在公共资源和政策用于支持业务转型的地方，我们期待公司为工作者交付明确而有意义的成果。
在我与数字发展与信息部(MDDI)和教育部(MOE)的各种对话与合作，以及通过经济战略评审，相同的关切一次又一次地被提出。我的工作五年后还会存在吗？人工智能会加剧不平等，让弱势群体掉队吗？如果人工智能提高了公司的生产力，工作者能分享这些收益吗？
这些并非不合理的担忧。这些担忧来自于那些辛勤工作、多年积累技能和经验、如今却感受到脚下地面在变化的人们。我将逐一回答这些问题。
首先，关于今天的工作是否会继续存在。让我坦诚相待。有些职位将发生重大变化。那些主要建立在重复同样步骤基础上的职位最容易受到影响。这并不是对从事这类工作的人们价值的判断。这对我们政府和雇主发出的信号是，我们需要现在就采取行动，而不是等到破坏到来后才行动。我们将会采取行动。
但是，AI不仅仅是一种取代工作的技术进步。与此同时，它正在开创全新的工作方式和以前不存在的新型职位。
一些学者将AI描述为"发明发明方法的发明"。它扩大了可以解决的问题的范围、可以构建的产品以及我们可以创建的行业。新加坡的一支小型生物科技团队可以进行的实验，在几十年前需要国家级实验室才能进行。一位单独创始人可以发布的软件，在三年前需要一支百人规模的公司才能交付。
因此，竞争加剧，但前沿也向外扩展。这就是为什么由高级议会秘书Goh Hanyan和我共同主持的经济战略审议委员会专注于确定新的领域，让新加坡能够利用人工智能建立真正的竞争优势。总理的国家人工智能委员会将推进这项工作。
议员指出了人工智能对中小企业的影响，因为人工智能使日常和分析性任务自动化。经济战略审议团队认识到这一点，这就是为什么帮助企业和员工主动应对转变成为了由国务部长Goh Pei Ming和国务部长Desmond Choo主持的委员会的重点。
对于失业工人，委员会研究了政府、雇主和工会如何能够提供更及时的帮助。正如我们在中期更新中所提到的，经济战略审议正在研究鼓励更早发出裁员通知的方法，这是由Mr Ng Chee Meng提出的。
关于中小企业(PME)具体地，委员会认识到他们可能面临更大的就业不确定性，并将建议提供更有针对性的支持。这包括考虑加强《求职者支持计划》(Jobseeker Support Scheme)，正如 Patrick Tay 先生所建议的那样，以及汲取私营部门的专业知识来加强对该群体的安置支持。
对于面临失业风险的工作者，《经济战略审查》将建议实际的方式帮助他们转向更有弹性的、需求更强的职位。我们将确定劳动力需求持续且人工智能失业风险较低的行业，并与这些行业的工会和雇主合作，为过渡中的工作者创造明确的、得到支持的进入点。我们必须使这些路径可行，而不仅仅是可见的。
举例来说，从事日常行政工作的中期职业工作者，例如从事数据输入或客户服务的工作者，可能会担心人工智能取代他。在工作便利化和再培训支持的帮助下，该工作者应该能够转向具有建立在其现有技能基础上的职位的行业。例如，该工作者可以探索医疗保健管理中的相邻职位。由于人口增长和医疗保健需求的增加，我们在这里看到强劲的需求，医疗保健需要独特的人类技能，这些技能对中断的抵抗力更强。
这一切需要的不仅仅是课程。它需要雇主、工会、培训提供商和安置支持紧密合作，以便工作者在过渡期间不会掉队。
世界上没有哪个政府对这一转变有所有的答案，我对任何声称相反的政府都会保持谨慎。新加坡能够承诺的是：我们不会等待完美的解决方案后再采取行动。我们现在就开始，并将在进行过程中调整我们的努力。
其次，关于不平等。议员们的担心是对的。能够放大能力的技术也可能扩大那些快速适应者和那些努力跟上者之间的差距。正如 Mark Lee 先生所指出的，我们面临的一些风险是生产率提高更多地流向那些已经领先的人，而职业阶梯的底部可能面临侵蚀。
我们的回应是提高底线，扩大入口。这意味着更早开始：在我们的学校中建立人工智能素养，使所有学生都能对人工智能充满信心，而不仅仅是那些有机会获得资源的学生。
目前，每个工业和技术教育学院(ITE)和理工学院学生已经被教授人工智能素养作为他们课程的一部分，我们现在正在将人工智能素养和安全的人工智能工具带入小学和中学课堂。这意味着所有学生，无论其经济背景如何，都可以安全地学习关于人工智能的知识。他们还可以学习人工智能如何能够有利于他们的学习，例如帮助他们完善他们的想法，他们也学习何时不应该使用人工智能。
正如 Desmond 部长今天早些时候所指出的那样，我们致力于支持可能缺乏强有力的家庭或父母监督和支持的学生。虽然学校中的人工智能素养将为他们提供良好而坚实的基础，但我们必须继续与社区和自助团体发展伙伴关系，以确保学校外部的监督和支持继续。
学习必须在毕业后继续。从2026年下半年开始，我们所有的高等教育机构(IHL)将为其校友提供精选的人工智能相关课程，有重大折扣，期限为一年。
对于已在劳动力队伍中的工作者，完成精选人工智能培训课程的新加坡人将获得六个月的高级人工智能工具的免费访问。我们将跟踪采用和使用情况，以查看我们是否需要做更多。
每个新加坡人，无论其起点如何，都应该有机会尝试人工智能工具并建立熟练度。
第三个问题是最难的，也是最重要的。工作者是否会分享收益？我们应该说清楚：这不会自动发生。仅凭技术本身会导致非常不平衡的结果。这就是为什么这不仅仅是一个市场问题。这是我们如何塑造经济中的规范和期望的问题。所以，让我清楚地说明我们的期望。
从人工智能中受益的公司应该投资于他们的人员，而不仅仅是技术。这意味着尽可能地培训现有工作者，而不仅仅是雇用新工作者。这意味着促进员工使用前沿人工智能工具的途径，创建实践社区，激励学习和提升技能。
它还意味着在与工作者密切磋商的情况下重新设计工作，正如 Yeo Wan Ling 女士所建议的那样，使人们能够与人工智能一起工作，使用判断力、背景和经验，而不是简单地将工作者视为要减少的成本。当职位确实改变或消失时，它意味着在诉诸裁员之前，认真努力在组织内重新部署和重新培训工作者。
我们不仅仅是在要求我们的公司进行国家服务。我们要求他们做的是他们自己长期利益所在的事情。在人工智能时代，人类的直觉和直观性仍然是关键。我们都知道，当我们使用人工智能时，我们需要引导它。在我们反复完善输出时，提出正确的问题并运用判断力。
这不是一次性的。如果你不开发理解你的组织背景的人，并使用这种知识来加强你的人工智能系统，你将来会被遗留一个非常浅薄和空心的公司。如果这里的公司用人工智能完全取代人类，他们将来会发现自己没有竞争优势，因为人工智能对所有公司都是可用的。他们还会发现自己受到人工智能公司的摆布。所以，我们的目标是找到一种方法，使我们的公司在长期内最好地为可持续增长而定位。
Saktiandi Supaat 先生提出了需要平衡的监管方法，这些方法不会阻碍人工智能的采用。确实，我们不会试图通过立法来获得良好的结果。这从来都不是新加坡的主要方法。但我们同样清楚，"自愿"不能意味着"在实践中是可选的"。
在部署公共资源的地方，我们将要求工作者成果。我们将与公司合作以满足这些期望。如果存在持久的差距，我们将审查我们的支持如何适用。我们将与三方伙伴讨论如何公平有效地做到这一点，以鼓励公司投资于培训、工作重新设计、重新部署和安置。
如果我们做得好，我们将能够在人工智能时代创造和维持良好的工作。好工作不仅仅是存在的工作。它是允许工作者进步的工作。它应该公平支付，反映技术带来的生产率提高。它应该建立仍然相关的技能，包括作为常规在职培训的一部分，以便工作者不会被困在容易被自动化替换的任务中。它应该给工作者一种尊严和代理权感，而不是将他们的角色简化为遵循机器生成的指示。
我们已经看到，当有强有力的承诺时，这是可能的。在 PSA，人工智能和自动化帮助实现了创纪录的货物量。与此同时，该公司对2,000多名工作者进行了再培训并重新部署到高技能职位。他们继续雇用数千名更多员工，因为他们的增长速度快于竞争对手。
对 Andre Low 先生，我要说：自动化和增强并不相互排斥。保护一名工作者可能意味着有意自动化重复和体力上要求很高的任务，并升级同一工作者的技能，以便技术可以在他承担更高价值的角色时增强他的能力。
即使是较小的企业也在发挥他们的作用。以我们本地的当铺 Maxi-Cash 为例。过去，希望交换珠宝的客户会与销售顾问交互，销售顾问会将他们的案例转交给评估员以评估珠宝的真实性。Maxi-Cash 通过对25名销售顾问进行再培训以使用人工智能启用的认证系统来增强此过程，该系统可以在仅五秒内准确评估珠宝的成分。现在，这些销售顾问可以补充现有的评估员库，减轻他们的工作量并减少客户等待时间。这是我们希望在新加坡看到的作为常规而非例外的负责任转变。
副议长先生，我认真聆听了今天在议院中从两方议员分享的许多建议和观点。我们可能在具体政策思想或特定措施应如何设计、融资或排序上有所不同。这是民主辩论的性质，这是非常健康的。
但我相信这个议院中对一项基本原则有广泛共识：增长和进步的收益必须与所有新加坡人公平而广泛地分享。这不应该是政党或意识形态问题。这是我们作为新加坡人必须共同坚持的原则。
所以，让我明确地说这一点。如果新加坡在我们的人工智能雄心中成功 - 而我们应该永远不要假设成功是自动的，因为它将需要持续的努力、艰难的选择、调整，也许还需要一些好运。但如果我们成功，那么政府将确保收益被广泛分享。
收益不能仅仅流向那些已经拥有资本、优势或访问权限的人。它们必须转化为更好的工资、更好的机会和所有新加坡人的更大安全性。对工人的最好保护不仅仅是中断后的再分配。它是从一开始就塑造如何创建和分享收益，并确保新加坡工作者在人工智能经济中保留代理权。
这个政府在新加坡数十年的发展中能够取得这些成果。我们决心在应对这一人工智能转变时继续这样做。我们的政策从未是静态的。随着情况的变化，我们已经持续调整、刷新和加强了它们。这种纪律将继续。
最终，每个新加坡人都应该能够看看新加坡所建立的东西并说，"我在这一进步中有利益关系。我在这一增长中有份额。这个未来，也属于我和我的家人。"
这种共同的承诺也是使新加坡对这一转变的方法具有独特之处的原因。我们的力量不仅仅是技术。这是我们跨越政府、企业和工会合作的方式。
对于正在观看这场辩论的工人们，我想直接对你们说：政府站在你们这一边，我们正在抢在中断影响你们之前采取行动，而不是之后。你们不会独自面对这一切。我们今天在这个议院做出的承诺，就是对你们的承诺。
对我们的企业领导者：人工智能为你们提供了强大的新能力。但你们如何使用这些能力将决定你们公司的未来，以及你们与那些与你们共同建立公司的人之间的关系。在10年内领先的公司不是那些削减成本最快的公司，而是那些通过将人的判断与机器能力相结合来建立更强大团队的公司。
但我也想澄清另一件事。不是每个企业都需要采用人工智能，也不是每个追求都需要从人工智能转型的角度来看待。完全由人创造的东西有真实的价值，随着人工智能变得更加普遍，这种价值可能会增长，而不是减少。
当我们周围的一切都是自动生成、优化和扩展的，那些不是这样的东西就会脱颖而出。无法重复的现场表演和返场。承载人类手工痕迹的手工陶瓷碗。用心和工艺精心准备的食物，而不仅仅是一致性。与花了一生时间打磨艺术的书法大师的对话。
我认为我们将看到对这些东西的欣赏重新复兴。新加坡不仅应该认可这一点，我们应该拥抱它。我们的工匠、表演者、工艺师不是在逆潮流而行。在充满人工智能生成内容的世界中，他们可能会发现自己恰好在世界所注视的地方。
超越近期的过渡，有一个长期的问题我们必须回答。我们现在需要对教育系统做什么，为我们的学生准备未来世界？
我们必须接受人工智能将在机器擅长的任务中继续进步。因此，我们更需要专注于使我们独特人性的东西。提出没有人想到过的问题的好奇心。以训练数据无法预测的方式连接不同领域思想的创意。能够读懂氛围、赢得信任、知道什么时候最有效的解决方案可能不是正确解决方案的同理心。
我们经常称这些为软技能。在人工智能时代，它们将成为我们人民和新加坡竞争优势的硬核边缘。这就是为什么我们将审视我们的教育系统，以确保我们以与一直以来对学术卓越所应用的相同严谨性和意图来发展这些品质。
我们必须继续建立坚实的基础，确保我们的学生不会过度依赖人工智能的快捷方式。我们的人脑是需要锻炼的肌肉，真正的掌握——那种能在压力下坚持、人工智能无法简单替代的掌握——来自辛勤工作、实践和深入理解。因此，听到陈慧玲女士同意这一点很好，我们感谢她支持我们的方法。
但严谨和探索不是对立的。真正掌握某件事的学生正是有信心超越它的人。他会提出更难的问题，承担没有明显答案的问题，他会发展出真正属于自己的兴趣。我们正在努力建立的是一个既要求深入的学科纪律，又要求广泛自由的教育系统。不仅仅是因为我们的学生值得拥有两者，而是因为新加坡的未来取决于两者。
这并不意味着放弃我们的标准。这意味着扩展我们认为卓越的范围。提出意想不到问题的学生，出于真诚兴趣深入追求某事的学生，能够持有两个矛盾观点并逐一处理的学生——这样的学生并未落后。在我们正在建立的世界中，这样的学生可能走在我们所有人的前面。
我们致力于与我们的教育工作者、家长和年轻的新加坡人一起做这件事。因为如果我们把这件事做对，如果我们培养一代不仅懂人工智能而且深深具有人性的人，那么新加坡不仅会度过这一过渡期。我们将成为下一个人类进步时代围绕其构建的社会。
副议长先生，我们今天对这一过渡将要求什么——对政府、企业和工人——都是诚实的。并非每条路都会顺利。有些人将面临真正的中断，我们的责任是确保没有人独自面对它。我们将使人工智能为新加坡人服务。我们将确保随着经济增长，工人与之同步前进。
但我想以我相信我们的注意力最终必须停留的地方结束——我们正在建立的一代。如果我们培养出好奇、富有创意、深深具有人性的新加坡人，他们能提出机器无法提出的问题，赢得算法永远无法赢得的信任，那么我们不仅仅是管理这一过渡。我们将定义它之后的样子。我支持这项议案。[掌声。]
副议长先生：国务政务部长陈德勇。
下午6时 总理公署国务政务部长（陈德勇先生）：副议长先生，我首先声明我作为全国职工总会副秘书长的权益和新加坡工业及服务业雇员联合会(SISEU)执行秘书的权益，在这些职位上我密切参与支持我们的工人。今天，我想继续支持我们的资深工人，并反映他们在人工智能时代的关切。
让我先分享一个关于傅女士的故事，她是一位55岁的求职者，向全国职工总会的e2i寻求帮助。在离开她的上一份工作——超过20年的工作——后，她发现求职过程发生了相当大的变化。甚至简历写作也改变了。简历过去是为人写的，但她发现如今它们经常首先被机器筛选。工作申请也转移到了不那么直观的数字门户，不太容易让像她这样的人来导航。所以，她感到迷茫和不确定。
傅女士的经历在资深工人中并不罕见，反映了他们对工作流程变化的焦虑。对于一些人来说，人工智能提供了真正的机会。对于其他人来说，它造成了不确定性和焦虑。对于我们许多资深工人来说，他们的经历由三个关键差距塑造，我认为我们集体必须努力解决。
首先是接入差距。虽然新加坡在缩小资深人士的接入差距方面取得了进展，但他们中的智能手机所有权仍然落后于其他年龄组。此外，资深人士可能对人工智能工具的接入较少。
我在我的工会SISEU组织的一次人工智能研讨会中亲眼目睹了这一点，大约有90名工会领导人参加，他们的平均年龄约为53岁。虽然他们都使用智能手机，但许多人是第一次尝试人工智能工具。可以理解的是，最初有些犹豫。但通过简单、有指导的用例，他们很快上手了，并使用人工智能为工会的家庭日和会员制活动生成海报。有些人甚至为他们的家人做生日和周年纪念横幅。
当我们结束会议时，许多领导人主动与我分享他们享受了这次会议，现在他们意识到学习使用人工智能工具并不那么困难。他们唯一要求的是希望会议能更长，幻灯片上的字体对他们来说能更大。
这鼓励了我，因为它表明问题不在于缺乏意愿，而是缺乏接入机会，在某种程度上对于他们中的一些人来说，这是关于信心的问题，我们可以通过精心策划和定制人工智能工具的接入，为资深人士腾出时间学习和增加知识来克服这个问题。
其次，技能差距。我们看到培训参与中的差距，人力部2025年报告发现，50至64岁的居民的培训参与率最低，为44.5%，相比之下，40岁以下的人参与率约为60%。
告诉资深人士去提升技能、去参加课程和重新技能化很容易，但实际上，我们知道，面对承诺、账单要付、时间和精力有限的情况，迈出第一步有时并不容易。我们必须记住，他们中的许多人已经经历了多个变革和转型周期，可能感到疲劳、不确定，甚至质疑更多培训的相关性。
这些关切是真实的。我们必须以适当的速度通过实用和精简模块为他们提供更容易获得的培训，并使人工智能与他们的工作技能更加相关。
第三是机会差距。即使资深工人愿意学习，他们在实际工作中可能没有相同的机会从人工智能中受益。
经合组织2025年就业展望强调，在经合组织国家中，通过实践学习的机会随年龄下降，62%的25至29岁的成年人报告有此类机会，但在60岁及以上的人群中降至45%。此外，皮尤研究中心2025年报告发现，在工作中使用人工智能的工人中，73%的年龄在18至49岁之间，只有27%的年龄在50岁及以上。
这就是为什么我们需要与雇主合作，为我们的资深人士提供使用人工智能工具的机会，并在他们的工作中获得生产率收益。资深工人带来宝贵的经验，借助人工智能，这些优势可以更进一步。我在这个议院已经不少于两次谈过这个话题。
斯坦福数字经济实验室的研究支持这一观点。它强调，在人工智能的引入下，美国的资深就业一直保持韧性，甚至可能有所增长，因为他们看到资深人士带来的隐性经验、知识和软技能使他们能够通过人工智能提高生产率。
对我们的资深工人，我们理解你们的挑战，我们在这一过渡中与你们同在。与我们迈出第一步。开始参加课程，尝试工具，从你们周围的人那里学习，你们就能在人工智能经济中茁壮成长。
副议长先生，本院现审议的动议很重要。该动议强调经济增长必须以公平、韧性和全民机遇为基础，并决心帮助工人把握这些新机遇。这一点也必须同样适用于我们的资深工人。
NTUC认可，长期影响力最好通过伙伴合作模式来实现，并通过人工智能就绪新加坡倡议采取了积极步骤，该倡议重点关注三个关键领域。
首先，培训和提升工人技能，以填补技能差距和可及性差距。为了缩小技能差距，NTUC LearningHub开发了综合的人工智能学习路径，针对不同熟练程度的学习者提供三个不同级别：基础培训，用于建立人工智能素养和应用能力；中级培训，针对特定部门或职位量身定制；以及针对从事深度技术且希望深化人工智能专业化和能力的人员的高级培训。
我很高兴地注意到，迄今为止反响热烈。自2026年2月以来，超过4,000名工人已报名参加LearningHub的人工智能课程。我也非常高兴，其中39%的学员是资深工人。
Neo博士建议对能力进行认证。这是LearningHub已经在做的事情。例如，它与公司密切合作，设计与政府技能框架一致且符合公司需求的人工智能课程。我们也与AWS和Microsoft等行业领袖合作，根据行业需求对学员的能力进行认证。我们将继续把这一做法扩展到更多部门和行业。
同时，在人工智能就绪新加坡倡议下，我们也通过NTUC的工会培训援助计划（UTAP）为工会成员提供最高达50%的人工智能高级订阅工具补贴，以缩小可及性差距。我也很高兴向各位议员通报，在这首批人工智能工具订阅中，NTUC的高级补贴确实涵盖一系列工具，包括编码和基于代理的工具，如Claude Code、Codex、Manus等。我认为总共有20或21个工具。
我们之所以将其作为会员特权提供，仅仅是因为我们使用现有的专为我们会员培训设计的UTAP资金模式。但我们将继续审查这一点，取决于未来的采纳情况和兴趣程度。
我们也与新加坡民航局等部门机构合作，为我们的工会领导人开发部门级人工智能培训路径。
其次，我们通过NTUC的CTC支持企业进行业务转型和职位重新设计。迄今为止，NTUC已建立3,800个CTC，启动了900多个业务转型项目，惠及超过300,000名工人。
让我分享另一个例子。我知道在这次辩论中各位听过许多例子。这个例子来自常绿集团，一家本地办公用品和文具供应商。通过与新加坡手工及商业工人工会（SMMWU）的CTC补助金项目，它实施了一个由人工智能驱动的电子订购系统，以自动化订购流程并改进库存管理。有了这个新系统，订单处理等手工工作减少了约60%。工人可以专注于更高价值的任务，如管理客户关系和利用数据优化库存。
随着生产力的提高，该公司能够处理40%更多的订单，并为员工提供加薪。这就是我们所说的互利共赢的成果——企业生产力提高，我们的工人也随之进步。
第三，我们通过新产品和服务改进职位匹配，帮助工人获得好工作。让我回到我演讲开始时提到的Foo女士。在e2i职业教练的密切支持下，她对自己的技能和新的职业市场有了更深入的了解。她的教练还向她介绍了NTUC的人工智能职业教练和e2i的人工智能面试官。在支持和鼓励下，Foo女士能够自信地使用这些人工智能工具来完善简历，并在实际面试前进行面试练习。我很高兴分享，Foo女士已找到新的职位，并在此过程中增进了对人工智能的了解。
副议长先生，人工智能就绪新加坡倡议是我们如何实现本动议意图的一个例子。它支持工人建立人工智能技能，为他们提供运用这些技能的工具，并与企业合作以提高生产力和创造新机遇。
展望未来，我们欢迎公司和合作伙伴参与，随着我们扩大努力和扩大覆盖范围，最终为我们的企业和工人提供更好的支持。
副议长先生，这些努力很重要，我们已经看到令人鼓舞的成果。但人工智能带来的变化规模也很大，工人中存在很大的不确定性和焦虑。这就是为什么三角合作制——其建立在数十年开放沟通和信任基础上的良好记录——对应对这一挑战至关重要。
新加坡以前曾成功应对过重大变革。在1980年代，当计算机首次进入工作场所时，工人们担心这些机器可能会取代他们在数据录入和档案管理中的角色，而公司则担心成本、技能短缺以及日常运营中断。
但三方伙伴积极行动。政府投资基础设施和技能培养，包括国家电脑局，以推动全国采用信息技术。雇主主动进行业务转变，采用新技术和重新设计的工作流程。劳工运动推动大规模技能升级，组织研讨会和讲座，为工人们在心理和实践上做好应对变革的准备。
由于三方伙伴团结一致地行动，企业的生产力提高了，工人从事了薪资更高的更好工作，新加坡增强了竞争力。
副议长先生，三方就业理事会将是实现我们对AI时代的共同愿望的关键平台，正如本动议中所列明的。它将建立在政府、雇主和劳工运动各方的努力基础之上，使伙伴能够扩大外展范围、加快政策实施、调配资源，以便工人和企业能够从人工智能中抓住机遇。
三方就业理事会将采取务实和迭代的方法。我们一开始可能没有所有答案，但我们确信，在数十年的合作和共同目标基础上建立的深厚信任将使我们能够实现包容性经济增长的愿望。副议长先生，我现在将用普通话发言。
（以普通话发言）：【请参阅讲话原文。】副议长先生，新加坡需要利用人工智能来推动下一阶段的经济增长。但更重要的是，这种增长必须建立在对所有人都公平、包容和有韧性的基础之上。
新加坡的三方伙伴——工会、雇主和政府——多年来紧密合作，建立了深厚的信任，使我们能够团结一致、共同克服挑战，无论面临什么困难。我们将继续支持我们的工人在人工智能时代抓住机遇并增强他们的竞争力。
今年2月，全国职工总会推出了'AI就绪新加坡'倡议，积极鼓励工人学习和掌握人工智能工具。该倡议帮助他们弥补意识、技能和获取方面的差距，使他们为人工智能驱动的经济做好更充分的准备。正如谚语所说，'机遇偏爱有准备的人，成功属于最坚持的人。'人工智能时代已经来临。我希望每个人都与全国职工总会一起，积极提升技能、学习并应用人工智能。
(英文):副议长先生,人工智能是我们这一代人的决定性技术。但我们面临这一挑战时,拥有通过数十年三方合作建立的坚实基础。
对于我们的三方伙伴,让我们继续紧密合作,帮助我们的企业转型并保持竞争力,同时支持我们的员工保持生产力并充分利用机会。
对于我们的员工,我们将继续支持你们利用人工智能。
对于我们的资深员工,你们的经验很重要,我坚定相信这将是人工智能时代的优势。与我们一起迈出这一步,提升技能并不断学习,包括向你们年轻的同事学习,我们可以共同努力弥合接入差距、缩小技能差距,为所有人创造更多机会。因为在新加坡,我们一直相信进步必须具有包容性,当我们向前迈进时,我们一起迈进,因为每一位员工都很重要。副议长先生,我支持这项动议。[掌声。]
副议长:人力部长陈思伦。
下午6时16分 人力部长(陈思伦医生):副议长先生,尊敬的先生,让我首先承认许多新加坡人现在正在感受的——不确定性、焦虑、一种脚下地面在移动的感觉;世界变得不如过去那么可预测,贸易紧张局势、供应链脆弱性、中东地区的战争和油价的急剧上升。
在我们本地,本议院议员已经谈到困扰所有同胞心头的事情:人工智能可能削弱我们的技能、我们多年积累的经验,甚至可能夺去我们的工作的焦虑。这种焦虑因大型科技公司宣布因人工智能采用而裁员的新闻而进一步加剧。
这些是合理的关切，我们认真对待。这样规模的变化确实令人不安。但人工智能能够并将创造我们目前无法完全想象的机会。当然，与此同时，它也会带来我们无法完全预见的扰乱。
但与此同时，出现了一些早期迹象给我们理由保持谨慎乐观。最近的全球调查显示，三分之二进行过早期人工智能驱动裁员的公司已经开始重新招聘。为什么会这样？因为他们发现人工智能可以处理可预测的和常规性的工作，但客户仍然需要人类的判断力、同理心和真实的联系，这些是人工智能无法提供的。
让我举一个个人的小例子。在准备今天的演讲时，我的团队使用人工智能来帮助完善我的工作。它提供了有用的参考资料，包括我们人力部最近发布的研究，显示新加坡只有约6%的公司因采用人工智能而减少了员工数量。
但有一件事它无法理解——许多许多工人所感受到的影响和焦虑。它无法提供同情，无法同情人，无法理解细微差别，也无法生成能够捕捉工人真实经历本质的政策回应。这是任何算法都无法替代的。
[议长主持]
摆在我们面前的动议做出了四项承诺。政府和人力部认真对待每一项——都是作为继续建设和进一步发展的基础。
黄志明先生谈到了人工智能对我们劳动力的变革性影响。政府长期以来一直认识到人工智能的潜力。我们目前的努力建立在这一领域已经完成的工作的坚实基础上。我们在2019年制定了第一个National AI Strategy，远早于ChatGPT的推出，我们在教育、医疗、物流、安全和市政服务等领域启动了国家人工智能项目。
当大型语言模型在2022年末爆炸性出现，使人工智能变得易于获取和通用时，我们在2023年以National AI Strategy 2.0刷新了我们的战略，并制定了投资超过10亿美元用于人工智能计算能力、人才和产业发展的计划。这包括建立AI卓越中心和增加人工智能从业者的数量。
随着人工智能加快步伐并与我们外部环境的重大转变相互作用，我们去年召集了Economic Strategy Review来加强我们的应对。最近在今年的预算演讲中，我们成立了由总理主持的National AI Council，以推动使用人工智能对我们经济的实际转变。
在每一步，我们都与我们的三方伙伴积极合作，以在各个部门推动具体行动和转变。因此，虽然我们将走入不可预知的水域和不确定的未来，但我们可以充满信心地这样做，我们并非完全毫无准备。
各议员都对人工智能对就业流失的影响提出了关切，许多人也提出了有思想性的建议，说明我们如何可以更好地在这一过渡期间支持工人和企业。我们听到了你们的关切，我们欢迎来自议院两边议员提出的建议。
事实上，议院中对我们试图实现的目标存在广泛的共识，即在这一人工智能转变中实现全民包容性增长。我们可能不同的地方在于我们如何实现这一目标。我们的方式一直是投资于我们的人民，保持我们工人的经济价值，并塑造人工智能收益如何被创造和分享。我们不想停留在恐惧和忧虑上，我们想要能够激励和鼓舞我们的劳动力继续增长。
Mr Gerald Giam先生和Mr Andre Low先生强调了对包容性增长的结构性威胁。我赞赏他们在这个问题上认真的态度。我们认识到这些困境。问题是：在哪里以及如何进行干预？
Giam先生提议建立National AI Equity Fund，用从受益于人工智能的公司的资金向每个新加坡公民支付500美元。罗先生同样提议通过冗余保险对那些失业的人进行赔偿。我认识到需要加强我们的系统，以确保在这一过渡期间没有人会掉队。我同意生产率收益的广泛分享不会自动发生，因为市场单独无法保证良好的社会成果。
让我明确说明。政府一直知道这一点，一直在为此采取行动。Giam先生和罗先生的提议都基于一个更悲观的前提，即新加坡人在人工智能转变中本质上是被动的乘客，没有能力抓住机会，只能依靠支持来应对他们无法掌控的旅程。
我不能接受，也不会接受这样的前提。你们的提议都不是赋权。对我来说，这是妥协。认命于大规模失业是不可避免的这一事实，我们能做的最好的事就是缓解打击。我们应该更加相信我们新加坡同胞的韧性和适应能力。
如果工人被排除在经济之外，仅靠再分配是不够的。新加坡的传统一直是投资于人而不是为他们补偿困难；这是我们真正的政策传统，而不是罗议员所描述的那样。
更好地使用人工智能采用产生的任何盈余的方式是资助可获得和有效的技能提升，以增强新加坡人的价值。为此，政府在过去五年中在本地劳动力倡议上花费了超过$10 billion。
摆在我们面前的选择，议院议员们，是在两个非常不同的愿景之间进行选择。一个说你得到救济，然后，用那个，得到机器生产的馅饼的一小份。另一方面，我们认为你应该与机器一起做大馅饼，通过好工作和好工资分享我们的经济繁荣。
第一个愿景初看起来可能很慷慨，但最终，会限制和削弱你更广泛的目标。第二个愿景对政府、雇主和工人都提出了更高的要求，但它将我们所有的新加坡同胞视为有能力的成年人，他们的未来值得投资，而不是一个需要通过转移支付来管理的人口。
议院议员们，我相信第二个愿景是可能的，因为当人工智能改变我们的工作方式时，有些工作会演变。有些工作可能会消失，但如果我们能让每个人都在同一艘船上一起移动，我相信我们会成功。正如Mark Lee先生和Yeo Wan Ling女士所说，它也为企业和工人创造了新的机会。我们的责任和重点是帮助我们所有的工人和企业抓住这些机会。
因此，我们在这场辩论中永远不应该基于焦虑和忧虑来建立论点。我们的方法不是害怕未来，而是让我们自己塑造未来，因为这是真正的新加坡精神。
我们已经用这种精神度过了每一波技术和经济重组，但我们并不自满。人力部正在密切监测人工智能对我们劳动力的影响。我们首次对企业的调查显示，人工智能目前在新加坡增强而不是替代劳动力。目前约十分之三的公司已经采用人工智能，而在已经采用人工智能的公司中，只有少数，约6%，报告了员工数量减少。
更常见的是，企业正在重新设计工作，他们正在创建新的人工智能相关角色，表明人工智能正在改变工作方式、工作如何被重新组织，而不是减少工作。十分之七的使用人工智能的企业已经看到了生产率的提高。
然而，正如我所说，我们永远不应该自满。我们必须为人工智能采用步伐加快、势头增强、规模扩大时，对工作的影响会更大做好准备。这就是为什么我们不断地为自己做准备。
我们的目标是帮助更多企业成功。同时，让他们的员工利用人工智能做得更好，而不是被人工智能取代。让他们的工作变得更有成就感、更有意义，而不是相反。以及人工智能的好处在企业本身和劳动力之间分享。
对于可以以更灵活节奏工作的工人，人工智能可以实现新形式的灵活工作和由小团队甚至"solopreneurs"完成的兼职工作。除了灵活性外，人工智能还可以重塑谁参与我们的劳动力，包括老年人，正如Poh Li San女士所谈到的。我们将通过三方老年就业工作组探索如何扩展灵活工作模式。
Hamid Razak博士谈到了他从基层听到的犹豫和焦虑，特别是来自年长的PMEs，他们想知道他们的技能是否仍然有一席之地。Yip Hon Weng先生也要求为企业提供更好的支持。让我分享政府在做什么来为个人和企业为这一转变做准备。
首先，我们正在改革我们的劳动力和技能支持系统，以提供更及时和有效的支持。正如我在昨天关于《技能和劳动力发展局法案》二读五小时辩论后分享的那样，这个SWDA的成立将把SkillsFuture Singapore和Workforce Singapore的技能和就业便利能力集中在一个屋檐下，使个人和雇主获得适当支持变得更加无缝、更加综合。
我们同意黄志明先生的观点，即从SWDA中获取的所有数据所产生的情报必须继续建立在信任的基础之上，我们期待与三方伙伴密切合作，确保我们对劳动力市场的评估继续是有根据且最新的。这将是我们如何走在破坏之前并支持由人工智能变化驱动的工人的重要组成部分。
这包括面临自主驾驶车辆部署的平台工人，正如杨玉玲女士所强调的那样。人力部和新加坡劳动力发展局已经与运输部和三方伙伴紧密合作，为这些司机加强转型过渡路径，以应对即将到来的自主驾驶车辆部署。我想补充的是，实际上作为代理机构，是新加坡劳动力发展局。但实际上，目前与运输部紧密合作的是SkillsFuture新加坡公司和新加坡劳动力发展局。
第二，我们将采取更多措施提高新加坡人的人工智能素养。目前，MySkillsFuture网站上有超过1600门与人工智能相关的课程。我们将推出诊断工具，供个人评估其当前的人工智能准备程度，并找到适合其需求的课程，提供与雇主需求相一致且经验证的培训成果。
从今年下半年开始，注册参加选定SkillsFuture人工智能课程的新加坡人将获得六个月的高级人工智能工具免费使用权。这将帮助他们将课堂学习应用到日常生活和工作中。邓庆康先生建议不设条件地使所有人都能获得此访问权限。这是政府仔细考虑过的事项。但并非所有新加坡人都需要前沿的智能体级工具。对许多人来说，免费版本已足够，而且应用广泛。
通过将补贴与培训挂钩，我们能够更好地针对那些更认真地寻求提升人工智能使用水平的人，并帮助他们以最优和负责任的方式使用这些强大工具。正如何锦贤副教授和杨瑜先生之前所分享的那样，我们希望新加坡人利用可用资源，在学习之旅中积极主动。
正如刘美娟政务部长所分享的，新加坡资讯通信媒体发展局也将扩展TechSkills加速器项目，开发人工智能双语工作者，首先从会计、法律和人力资源专业人士开始。[请参阅《人力部长的澄清》，官方报告，2026年5月6日，第96卷，第30期，书面声明更正部分。]更多细节将在适当时候公布。
第三，为了支持企业，我一再强调我们已为企业劳动力转型计划拨出超过4亿美元。我不想过多赘述，因为我相信我在昨天的二读演讲中已经涵盖了大部分内容。但叶先生问这些补助金是否可以与劳动力成果条件挂钩。今天，利用劳动力发展补助金(职位重新设计+)的企业需要在其转型计划中支持劳动力成果，如工资增长和员工留任。今年晚些时候，符合条件的企业还将在重新设计的SkillsFuture企业信用下获得1万美元，这可用于抵消符合条件的劳动力转型项目的自付费用，包括企业劳动力转型计划下的项目。
我们同意李明先生的观点，认为行业协会和企业劳动力转型计划可以解决这些问题，同时确保劳动力在此过程中被纳入其中。商会在将企业与正确的专业知识和资源相连接方面发挥特别重要的作用。这就是为什么我们任命新加坡商业联合会和SNEF作为企业劳动力转型计划的锚点项目伙伴，以便将综合劳动力转型支持直接带给企业，并帮助我们加快各行业的人工智能采纳。
我们也在支持劳动运动在企业和工人转型中的努力。政府在2025年向新加坡全国工会联合会合作转型中心赠款增拨约2亿美元，并将赠款延长至2028年。最近，我们与新加坡全国工会联合会合作扩展赠款，以更好地支持蜂王企业推动集群级转型。
尽管我曾短暂离开去接听电话，但听到黄志明先生分享合作转型中心如何帮助许多企业实现转型，同时改善工人生活的情况时，我感到欣慰。我特别注意到他的敦促以及他进一步扩展合作转型中心倡议的建议，以及他将合作转型中心提升到三方水平的雄心。我们期待与三方伙伴合作，共同探索实现这一目标的途径。
有人呼吁我们超越项目层面的干预措施，做出更具结构性的转变，改变企业投资工人的财政激励。结构性机制，如洛和民先生所呼吁的那样，已经存在。像SkillsFuture企业信用这样的补助金为企业投资其员工能力创造了直接的财政激励。我们将继续审查和加强此类支持，作为新加坡劳动力发展局工作的一部分。
我认为我们所有人都应该认识到支持企业转型的重要性，不是笼统的、大规模的战略，而是差异化的、精准的、按行业和按企业分别进行的企业转型支持。尽管这更加繁琐，但我相信从长远来看，这也更具可持续性。
最后，我们加强了对失业工人的转型支持，使他们能够更强劲地反弹。政府无法保护每一份工作，但我们肯定会尽最大努力支持和保护每一位工人，因为每一位工人都很重要。
因此，随着人工智能转型，工作流程将重新组织和改变，工作也将改变，某些工作可能会被替代。经历转型可能很具挑战性。但我向所有工人保证，你们不会孤单。
我们已经认识到，随着变化步伐加快，我们必须加强支持机制。这就是为什么我们去年推出了SkillsFuture求职者支持计划。这是我们在《前进新加坡》下刷新的社会契约的一部分。该计划向非自愿失业人员提供临时财政救济和求职支持。它对许多新加坡人产生了影响，帮助他们重新站稳脚跟，以信心重返工作岗位。
洛和民先生可能对该计划有些误解。它不是冗余保险，因为它不仅仅是为失业提供现金赔付。它是对再就业的支持。该计划在工人的再就业之旅中提供支持。它为低收入和中等收入群体提供一定程度的财政支持，正是为了他们不会急忙接受第一份可能不适合的可用工作。
新加坡劳动力发展局用实际的全面支持补充求职者支持计划，以提高其求职的质量。我们意识到长期失业会损害工人的长期职业前景，这就是为什么财政支持有时间限制。它逐步下降，因为我们相信工人非自愿失业的前两到三个月是影响最大的时期。因此，我们在初期提高支持水平以鼓励工人，提供支持提升，当逐步下降时，我们希望工人能够找到适合他们的工作。
但我们听到一些呼声。黄志明先生和泰先生提议提高JS计划收入门槛，以更好地支持高收入人群。我们将研究该计划如何改进，并将仔细研究这一点。
我们也听到黄志明先生关于要求政府提前通知遣散的呼吁，即在员工最后工作日之前，以及李明先生对企业在这方面的顾虑的反思。我们希望取得正确的平衡。三方伙伴已经在正在进行的《就业法》审查中讨论缩短遣散通知期限。我们希望看到向政府的通知尽可能在受影响工人最后工作日的前后发生，因为这样还能使及时的就业促进支持工人成为可能。
关于邓庆康先生加强对失业工人保护的建议，《就业法》已经通过建立程序保障（如通知期和争议解决途径）提供了基于广泛基础的保护。这适用于所有类型的失业，不仅仅是由于人工智能造成的。
我们的人工智能驱动增长必须以公平、复原力和共享机会为基础，这不会自然发生。维克拉姆·内尔先生问我们有什么保障措施确保工人在人工智能采纳增加时得到公平对待。政府已制定了框架，如《智能体人工智能模型治理框架》和AI Verify，以为人工智能供应链中的各方建立明确的责任，为人工智能开发人员和用户提供负责任实践的清晰指导，包括人力资源技术解决方案提供商。萨克蒂安迪·苏帕特先生恰当地指出，人工智能采纳在各行业、工人群体和不同规模的企业中以不同速度进行。如果不付出刻意的努力，人工智能带来的收益可能会流向某些人，而其他人被抛在后面。在中国，法院已经裁定纯粹为了降低成本而用人工智能替代员工是违法的。
国务部长陈振声和三捷夫·库马尔·蒂瓦里先生谈论了新加坡全国工会联合会近年来在为工人配备人工智能相关技能和支持劳动力转型方面所做的工作。这正是我们应该利用的那种能力，以确保更多工人和企业了解可用的支持，以及人工智能采纳可以在整个经济中加快。这就是为什么我们全力支持新加坡全国工会联合会成立三方就业委员会的提议。三方就业委员会将采取协调的三方方法，动员企业和工人在人工智能时代实现公平和复原力增长。
正如何锦贤副教授所指出的，人工智能应该增强工人，而不是替代他们。我们将利用新加坡国家雇主联合会的商业顾问和新加坡全国工会联合会的合作转型中心帮助企业以驱动增长和增强工作角色的方式采纳人工智能，优先选择增强人类能力而不是替代他们的技术。我们将利用三方伙伴与工人、工会和雇主的强大联系，推动跨行业和职业阶段的广泛人工智能培训，以确保在人工智能重塑我们旅程时没有工人被抛在后面。
在那些必须进行重组的技术或企业中，我们将与企业合作，帮助工人进行转向、提升技能和重新技能培训。
我们也将特别关注对人工智能对初级工作的影响感到担忧的学生和年轻工人。高等学府继续增强其课程以跟上人工智能的进步。所有高等学府从今年下半年开始，将为其校友提供选定的人工智能相关课程，并提供重大折扣，期限为一年。
进入劳动力市场的毕业生也可以利用教育部的SkillsFuture带薪实习计划，该计划将课堂培训与企业的在职培训相结合，以建立雇主重视的技能和经验。
林瑞生副教授呼吁扩展青年学徒制路径。我们同意。结构化学习必须辅以真实的工作场所经验。我们将继续与货币管理局和新加坡资讯通信媒体发展局等行业领袖合作，支持高增长行业的学徒制，从我们的GRIT等项目经验中学习，我们已准备好在必要时改进和扩展这些项目。
议长先生，让我总结一下。新加坡曾经经历过深刻的破坏，从亚洲金融危机到非典，再到新冠肺炎。每一次，每一场危机我们之所以能度过，不是因为政府有所有答案，而是因为工人、企业和政府肩并肩站在一起。这就是三方制的力量。
在许多国家，人工智能成为一场拉锯战。一方是工人，另一方是企业。进展受到质疑，信任受损。新加坡不必走上这条路。我们共同努力，把整个经济蛋糕做大，并确保利益广泛共享。
对于想知道自己立场的工人，我们总会有你们的一席之地。你们的经验、你们的判断，比以往任何时候都更加重要，对于你们对国家的承诺、多年来、几十年来的支持，我们深表感谢。非常感谢。[掌声。]
对所有年轻的毕业生，你们的想法、你们的动力，比以往任何时候都更加重要。你们的热情、你们的求知欲、那种联系、那种政务部长贾丝敏·劳刚才谈到的求知欲，比以往任何时候都更加重要，我们支持你们。
对于我们所有的企业，如果你感到不确定，不知道从何开始，你不必独自解决这个问题。我们将与你并肩同行。我们将帮助你转型，帮助你竞争，这样你就能为你的企业和员工创造更好的机会。
我们不会把工作的未来、我们工作者的生计、我们新加坡人的命运交由偶然决定。我们将塑造一个包容的、前瞻的、以实际行动为基础的转型。
新加坡人永远不会是人工智能驱动未来中的无助乘客，而是我们人工智能之旅起航时的共同副驾驶。我们将以新加坡的方式向前迈进，政府、雇主和工会携手合作，确保我们的人工智能转型创造良好的就业机会，为每一位新加坡工作者开辟通往更美好未来的清晰道路，因为每位工作者都很重要。基于此，我对这项议案表示支持。[掌声。]
下午6时50分 议长先生：在议会中，我们也在采纳和拥抱人工智能，同时我们在这一旅程中为我们的工作人员做好准备。Low先生有澄清意见吗？议长先生，请先动议豁免。
英文原文
SPRS Hansard 原始记录 · 抓取日期：2026-06-09
[(proc text) Resumption of Debate on Question [5 May 2026], (proc text)]
[(proc text) That this House – (proc text)]
[(proc text) 1. Recognises the transformative power of new technologies, especially Artificial Intelligence (AI), to drive Singapore’s next phase of economic development; (proc text)]
[(proc text) 2. Emphasises that Singapore’s approach to AI-enabled growth must be anchored in fairness, resilience, and opportunity for all; (proc text)]
[(proc text) 3. Resolves to equip and support workers and enterprises to seize new opportunities and advance together; and (proc text)]
[(proc text) 4. Affirms that economic progress must remain inclusive, and that Singapore must not have jobless growth, because every worker matters. (proc text)]
[(proc text) Question again proposed. (proc text)]
12.32 pm Mr Speaker : Mr Mark Lee.
Mr Mark Lee (Nominated Member) : Mr Speaker, building on the earlier speech by my colleague National Trades Union Congress (NTUC) Secretary-General Ng made last night, I would like to focus on how this Motion is made real at the enterprise level.
Sir, no jobless growth cannot be achieved through worker support alone. It must also be designed into the way enterprises transform, the way jobs are redesigned and the way our system supports firms to move with confidence.
History shows that in periods of technological change, the winners are not those who try to protect existing business models but those who understand their underlying strengths well enough to redeploy them into new arenas. Fujifilm is one example. It did not survive the collapse of film by trying to sell more film. It built on capabilities in materials, optics and imaging to move into skincare, diagnostics and healthcare technology.
In sectors where Singapore is already strong – advanced manufacturing, logistics and connectivity, finance and healthcare – AI is not replacing the industry itself but changing how value is created within the industry. That is the mindset Singapore needs now. Our task is not to preserve every job exactly as it is. Our task is to help our enterprises and our workforce recognise their strengths, adapt them and move into the next phase of growth together.
I will divide my remarks into three parts: first, what AI is actually doing for businesses; second, its impact on jobs and workers; and third, how we can build a clearer enterprise front door and a wider bridge forward so that businesses and workers can cross the transition together.
Mr Speaker, businesses adopt AI where it delivers measurable outcomes. The evidence is already emerging. In customer service, generative AI improves productivity by around 15%, with larger gains among less experienced workers. Firms are also seeing double-digit gains in software engineering while in operations and supply chains, AI is improving forecasting, reducing waste and optimising inventory and logistics.
Second, AI does not simply improve jobs. It reconfigures work. Global evidence shows how AI adoption is increasingly concentrated among higher-skilled workers, with firms re-organising work around smaller, more experienced teams supported by AI. This creates a double risk: first, productivity gains may accrue more to those already ahead, widening inequality; second, it risks eroding the bottom of the career ladder.
If entry-level roles are reduced too quickly, the traditional pathway where workers build judgement through experience is disrupted. Firms may still require mid-level capability but fewer workers will have had the opportunity to develop it. That is a structural issue.
At the same time, new roles are emerging, integrating AI into workflows, validating outputs, redesigning jobs and translating domain knowledge into solutions. Companies like DBS and Mastercard are using AI to handle routine queries and personalise responses at scale, freeing up human agents for higher-value work. We are seeing the same among small and medium enterprises (SMEs). MTM Labo, a skincare company, for example, uses an AI tool called Hana that supports customer enquiries in multiple languages, allowing its team to focus on more complex, high-touch interactions.
This is an important point. AI, when deployed thoughtfully, does not just replace jobs. It changes the nature of jobs and can raise the value of human work.
But adoption is not plug-and-play. It requires integration into workflows, redesign of processes and alignment with business strategy. This is where many firms, especially SMEs, face challenges in translating AI into implementation. If we do not address this, capability will concentrate among larger firms and among more skilled workers. The gap will widen. That outcome would run directly against the spirit of this Motion.
However, we must also be careful about how we respond to these changes.
I understand Mr Ng's good intent behind the call for earlier notification of retrenchment to better support workers. But if firms are not yet ready to redesign jobs or absorb workers differently, earlier notification alone will not solve the problem.
If AI is re-organising work, perhaps a better solution that matters more is not whether we intervene earlier after displacement occurs but intervening early enough before displacement becomes necessary. We should shift the focus from managing retrenchment to enabling all firms to redesign jobs and retrain workers so that they transform and the workforce adjustment happens alongside transformation, not after it.
This brings me to my third point – how do we we build a bridge forward? A bridge that is wide enough for many to cross, not just a select few.
The recently introduced Enterprise Workforce Transformation Package is a step in the right direction. With the Singapore Business Federation (SBF) and the Singapore National Employers Federation (SNEF) as programme partners, companies can access advisory support to redesign processes and job roles and tap on the SkillsFuture Workforce Development Grant for consultancy, workforce technology adoption and capability building. This is a meaningful shift.
However, today, firms are still navigating multiple schemes, multiple agencies and multiple claims processes, slowing adoption at the point where speed matters most. But I am heartened to hear from Minister Tan last night that the merger of SkillsFuture Singapore and Workforce Singapore into Skills and Workforce Development Agency aims to solve this issue.
But can we do more to help businesses?
This brings to my first dimension of practicality. One way forward is also for AI grants and schemes to have a more integrated approach where businesses can access this support through a single interface rather than navigating multiple agencies and deploy it flexibly, whether for basic implementation, subscriptions or experimentation, without repeated layers of claims, just like the SkillsFuture Enterprise Credit wallet.
For larger or more complex customised projects, there may also be a case for more upfront support so that firms are not constrained by cashflow when making longer-term investments.
At the same time, we must recognise that AI adoption involves experimentation. Not every project will succeed. If firms are penalised despite genuine effort, we risk discouraging innovation. A reasonable tolerance for failure will be necessary if we want companies to move decisively.
The second dimension is capability at scale. The pool of experienced AI professionals remains small and highly competitive. If we are too restrictive on bringing in foreign AI talents, we will slow down capability building across our economy. So, our efforts to build a wide bridge must also mean keeping our talent pipelines open. Not just to bring in talent, but to allow that talent to cross-pollinate skills across firms and sectors.
For SMEs, one area we can consider is to give targeted flexibility to bring in specialised AI expertise beyond existing manpower constraints. This can be time limited and on an application basis, with some checks in place to prevent abuse.
The third dimension is through our institutes of higher learning (IHLs). IHLs can be positioned more deliberately as execution platforms for applied AI, especially through Centres of Excellence anchored around postgraduate programmes. Many postgraduate students, including foreign talent, bring prior industry experience and technical depth. When paired with local undergraduates, this creates a practical model for capability transfer. If anchored around real SME and sectoral problem statements, these teams can go beyond proof-of-concept work to develop deployable solutions.
This achieves several outcomes. It lowers the cost of experimentation for SMEs while enabling cross-pollination between international and local talent, and it creates a pipeline for startups to emerge, anchored in Singapore and focused on solving real industry demands.
This model also helps address to the broken career ladder. As entry-level pathways narrow, embedding students in real problem-solving builds capability earlier. At the same time, it strengthens our students' critical thinking, preparing them to question and validate AI and not just rely on it.
The fourth dimension is industry enablement. Today, many firms are attempting to solve similar AI problems in isolation. This leads to duplication of effort, higher experimentation costs and slower adoption.
Trade associations and chambers are structurally positioned to address this gap. They operate at the interface between government policy and firm-level behaviour and can translate national AI strategies into sector-specific implementation. They can function as coordinating platforms, identifying common industry problem statements, aggregating demand and working with solution providers and IHLs to develop integrated, deployable solutions aligned to actual workflows and job roles.
Let me illustrate. SBF is developing an AI tool to help businesses understand the rules of origin of free trade agreements and how to apply preferential tariff treatment when goods are exported overseas. This is one example of how an industry‑led approach can reduce duplication and improve efficiency.
For many SMEs, the challenge is also on applied capability. Firms want to know which problems to prioritise, who can help and how to proceed without excessive cost or risk.
The Singapore Chinese Chamber of Commerce and Industry (SCCCI) AI Experience Programme, launched together with the Infocomm Media Development Authority (IMDA) in support of the Digital Enterprise Blueprint shows this clearly. It has been heavily oversubscribed because SMEs are looking for guided entry points.
Similarly, SCCCI's AI Enablement Programme allows SMEs to define real problems and work with students from Nanyang Polytechnic, Singapore Polytechnic, Temasek Polytechnic and the Singapore University of Technology and Design (SUTD) to develop solutions. SMEs gain workable solutions. Students gain relevant experience. And knowledge spreads across the system. With the right support and funding, trade association and chambers can become platforms that accelerate AI adoption across sectors.
Finally, Mr Speaker, the fifth and most important dimension is human capital. The success of AI-enabled growth will not be determined by how many tools we deploy, but also by how many workers we carry through that change.
I agree with Mr Ng that workers who are displaced, whether due to AI or industry consolidation, need stronger support during transition. But we should also consider how that support is structured.
Today, much of it follows a "train and place" approach, where workers are first retrained and then supported to find a job. In practice, this can be uncertain. No worker wants to be retrenched, spend months in training and still face uncertainty about the next job. We should, therefore, move more deliberately towards a "place and train" model. If another company is prepared to take in a displaced worker, even if the fit is not immediate, we should support that transition directly. This can be done by targeting temporary wage support to the receiving employer, similar to the spirit of Jobs Support Scheme (JSS) but anchored under an industry transition fund so that companies are incentivised to hire first and retrain on the job.
This shortens the period of uncertainty for workers, while giving the firms the confidence to take in and develop new talent. This is also where trade associations and chambers, and unions can also play a coordinating role – identifying firms with demand and matching them with workers at risk.
Finally, Mr Speaker, the open bridge must be a moral and social contract, and at the heart of that contract is trust. Workers must see AI as enabling, not threatening. If AI is seen as a tool to remove jobs or close off pathways, adoption will slow not because the firms lack technology but because trust is lacking.
And if that trust is broken, we may inadvertently create a lose-lose outcome where governments step in with more restricted workforce regulations around AI adoption, raising longer-term costs and reducing flexibility for businesses. Trust must, therefore, be built deliberately through how AI is deployed, how jobs are redesigned and how workers are supported through change.
Sir, I am a businessman and I join the call to support my union brother Mr Ng in this Motion because I believe this embodies the true spirit of tripartism that has served Singapore well.
We cannot say every worker matters and then leave workers to navigate this transition alone. Businesses must lead in redesigning jobs and investing in their people. Workers must step forward and adapt. And Government must ensure the system enables both. Only then can workers and businesses advance together.
Mr Speaker, this motion reflects Singapore's determination to get this right. Let us take the proactive path to work together, to build trust early and ensure that AI expands opportunity rather than narrows it. Sir, I strongly support the Motion. [ Applause. ]
Mr Speaker : Mr Saktiandi Supaat.
12.49 pm Mr Saktiandi Supaat (Bishan-Toa Payoh) : Mr Speaker, before I begin, I would like to declare that I am working in a bank, a financial institution in Singapore. I am also an advisor to the Union of Power and Gas Employees (UPAGE) and the Logistics and Supply Chain Union (SCEU).
Mr Speaker, I would like to thank, foremost, the Secretary-General of NTUC and Member, Mr Ng Chee Meng, for moving this important Motion and for setting out the need for a new compact for AI-enabled growth, one that keeps workers at the centre of our transformation, anchored in fairness, resilience and opportunity for all.
I will focus on how we can build a more inclusive AI economy, where growth is not only strong, but broadly shared.
AI is no longer emerging; it is already reshaping how we work and live. Beyond well-known AI tools, I saw this first-hand during engagements with the UPAGE, SCEU and, recently, Manpower Government Parliamentary Committee's learning journeys to SMRT, NTUC Finest at Punggol and Chye Thiam Maintenance Pte Ltd.
In different sectors, power and gas, supply chain, transport, retail, food and beverage (F&B), cleaning and facilities management, all of them embedding AI, autonomous vehicles (AVs) and robotics into workflows, raising productivity, creating new jobs and redesigning roles for existing workers.
There is now a global race in AI innovation and adoption. And there is a growing belief that those economies and companies that move early and decisively will capture the greatest value.
But Mr Speaker, Sir, as this House has consistently emphasised, economic success must be inclusive. Economic success is not just growth, but how widely its benefits are shared. Uneven growth is not a model Singapore should follow. Besides the redistribution measures that we have implemented through tax measures and targeted assistance, we must cultivate a sustained mindset to ensure AI-enabled growth is inclusive.
Usage of AI has raised concerns for many workers. For example, will AI take away my job? Will it lead to jobless growth?
Based on the NTUC's survey on economic sentiments in Singapore, which it conducts yearly, the fear that AI would replace their job or current role is more pronounced for professionals, managers and technicians (PMETs) and entry-level jobseekers. For non-PMEs and lower-wage workers, the lower level of concern could be because they do not use AI tools as extensively and are unaware of how AI would impact their job opportunities and not because there is no AI-disruption risk.
These concerns are reinforced by news of job restructuring globally, as well as uneven adoption of AI across sectors and occupations.
Mr Speaker, Sir, let me illustrate this unevenness with a concrete example from our own financial sector, of which I am working in. In banking here, AI is no longer emerging, it is already deeply embedded and a core driver of productivity. Across the sector, our local banks are deploying automation in operations and customer servicing, particularly in labour-intensive and repeatable processes. These are not experimental use cases; they are transforming how work is done across the value chain.
AI is now used in operations, such as processing, settlements and compliance, and in credit evaluation through machine learning models that support faster and more consistent underwriting. It is even beginning — well, I would not say beginning; it is already playing a bigger role in hiring, particularly in initial screening.
But the impact is not uniform. Routine clerical and processing roles are most exposed, while hiring is shifting towards higher-skilled roles in data, AI, cybersecurity and governance. At the same time, regulation is sustaining demand for oversight roles in risk, compliance and audit.
But crucially, more complex work still requires human judgement. Handling nuanced customer issues, managing relationships and making judgement calls cannot be easily automated. As a result, many roles are not disappearing but evolving. For example, credit officers are moving towards interpreting and oversight while contact centre roles are shifting towards experiential, escalation and trust-building. So, what we are seeing is not wholesale job replacement, but a reconfiguration of tasks within jobs.
Mr Speaker, Sir, while much of the AI discussion focuses on PMETs, we must not overlook skilled tradespersons and our blue-collared workers. Our electricians, technicians and maintenance workers are essential. AI cannot repair lifts or maintain MRT systems on its own. As our economy becomes more digital, these roles will become more sophisticated, not less. They are, in fact, high-mastery professions.
If AI raises the premium on skills, we must also raise how we recognise mastery. But beyond recognition, we must also rethink how mastery is built. As AI reshapes how work is performed, we must also rethink how skills are transmitted.
Today, many of our industry transformation maps (ITMs) guide sectoral growth and workforce development. But they were largely designed for a pre-AI world. There may be merit in updating these frameworks to explicitly account for how AI is changing apprenticeship and on-the-job training pathways. This issue has been raised in this House before and it deserves renewed attention.
In particular, we should consider whether we need Industry Training Continuity Maps alongside our ITMs, to ensure that even as AI takes over more routine tasks, we continue to sustain a strong pipeline of deeply skilled human workers especially in roles where mastery, judgement and hands-on expertise cannot be replaced.
Today, this is less visible in skilled trades. This is why I have also proposed a National Master Trades Accreditation framework during the last Committee of Supply, to recognise progression, reward deep skills and integrate AI competencies.
If we get this right, AI will not hollow out middle-skilled jobs, it will elevate them. This will also help elevate further the skilled graduates from our Institutes of Technical Education (ITEs) and polytechnics.
Mr Speaker, Sir, given the immense opportunities and risks, AI as a growth engine requires sound policies that benefit workers and citizens. Countries, such as the United Arab Emirates and Finland, have adopted coordinated national AI strategies combining government leadership, enterprise adoption and workforce development.
Here in Singapore, we have taken important steps. Budget 2026 announced the establishment of a National AI Council led by Prime Minister Lawrence Wong, alongside incentives for businesses through the Enterprise Innovation Scheme and support for workers via SkillsFuture and the TechSkills Accelerator.
I would like to offer some suggestions to equip workers and enterprises more effectively, so that no worker is left behind.
First, we must normalise AI as a way of life. We must go beyond training pathways and time-limited access to AI tools. While I welcome the provision of temporary access through Government and NTUC initiatives, we must think ahead about what happens after this initial phase of subscriptions.
Many of the more capable AI tools require ongoing subscriptions. Over time, this may create a divide between those who can afford to use these tools regularly and those who cannot. If left unaddressed, we risk creating a new form of inequality between AI "haves" and "have-nots".
Because access to AI tools directly affects productivity, learning and income potential, unequal access will translate into unequal outcomes. We should therefore consider how to ensure sustained and affordable access, especially for lower-income workers, freelancers, tradespersons and small businesses.
Possible approaches include a baseline level of subsidised access, similar to digital connectivity, tiered or group-based pricing with industry partners, shared access through community centres, libraries and training hubs, and ensuring employers receiving AI support also extend access to workers.
Mr Speaker, Sir, if AI is to be a force for inclusive growth, access cannot be a privilege, it must be broadly shared. And in the digital age, access to AI may become as fundamental as access to the Internet. We must ensure no Singaporean is priced out of that future.
One way to drive adoption is for the Government to be the "first customer" of useful AI tools and to mitigate AI transition-related concerns. AI-enabled systems can provide faster and more practical responses to citizens navigating Government services. As AI systems consistently deliver useful outcomes and quick advice to Singaporeans, confidence in AI and AI adoption will grow.
Against this backdrop, I would also like to acknowledge the Government's efforts to support workers through an AI-shaped economy, with employment remaining the central outcome and address job anxieties.
As such, it is important to recognise, for example, that employment outcomes for the Malay/Muslim community under M³ and Focus Area 4 (FA4) have been delivered at both scale and through targeted support. Between 2022 and 2025, Workforce Singapore and NTUC's Employment and Employability Institute (e2i) assisted over 29,000 Malay/Muslim jobseekers, with more than 19,000 placed into jobs.
At the same time, through community-based pathways under M³ and FA4, over 6,000 jobseekers were engaged, with more than 500 securing employment, including those requiring more sustained support. This reflects both the breadth of our national employment system and the depth of our community-anchored interventions. Building on this, FA4 workstreams will sharpen their focus on supporting workers through an AI-shaped economy, with employment remaining the central outcome.
I am glad that NTUC will work closely with MENDAKI through NTUC's e2i to strengthen job transitions, particularly for young adults transiting from campus to career, who may be entering the workforce amid heightened uncertainty about job relevance and AI-driven displacement. This includes strengthening early career pathways by partnering IHLs and integrating engagements with e2i's career services, job matching and employer networks, so that fresh graduates are better prepared for a changing labour market.
For underserved Malay/Muslim workers, as an early step, MENDAKI and NTUC's e2i jointly piloted Langkah Digital AI workshops in community settings, with plans to scale further this year; and I plan to attend some of these workshops. Taken together, these deliberate employment-linked interventions will help to ensure that productivity gains from AI do not result in jobless growth, but instead, equip Singaporeans, across life stages, to adapt, remain employable and progress with confidence, supported by NTUC, its partners and the wider Labour Movement. So, I encourage our community to take advantage of these initiatives to upskill.
Second, we must focus on the infrastructure that enables AI. Singapore has invested in strong digital rails. Systems, such as Singpass, already allow secure transactions, including legally binding processes, such as the Lasting Power of Attorney. The next step is to enhance interoperability through application programming interfaces (APIs), so more services can be integrated seamlessly.
When services are integrated, AI can significantly enhance efficiency and user experience. At the same time, we must calibrate data-sharing frameworks and safe harbours, so that data can be used responsibly without stifling innovation.
Third, we must ensure employers redesign workflows to embed AI meaningfully. Member Mark Lee has mentioned that. Training alone is not sufficient. While the Enterprise Workforce Transformation Package provides useful support, it tends to reach large firms that are already inclined to transform. We need to go further.
One possibility is to launch an "AI Bilingual" accreditation, for employers and not just for workers and jobseekers. While it can be on a voluntary "opt in" basis, like BCA's Green Mark Certification Scheme or TAFEP's Fair Employment Badge, the accreditation can be tied to certain other benefits or quotas to incentivise companies to come forward. Like existing voluntary schemes, this could be linked to incentives to encourage broader participation.
Fourth, we must support those with traditional employers, tradesmen, lower-wage workers and platform workers. AI can act as a personal assistant, enhancing productivity and income. For example, tradesmen can use AI tools to generate quotations, invoices and customer responses; lower-wage workers can use AI for scheduling and financial planning; and platform workers can optimise routes and jobs across platforms, increasing autonomy. Is there scope for the Government to invest in such tools and provide time-limited access, so these workers can experience their practical benefits?
Finally, we must recognise that not all workers have equal capacity to adapt to AI. Time constraints, caregiving responsibilities and life-stage challenges affect participation in training. We should move forward towards flexible learning; integrate training into work; and strengthen cross-sector mobility. This ensures our workforce remains agile, mobile and inclusive. Mr Speaker, Sir, allow me to now to speak in Malay, please.
( In Malay ) : [ Please refer to Vernacular Speech .] We want every worker to receive the support they need to upskill and not be left behind as AI continues to progress. Through my interactions with Malay/Muslim workers, many see AI as an opportunity, but also worry that they cannot keep pace with this rapid technological advancement.
This concern is valid. AI is transforming the way we work. PMETs in particular are beginning to ask: are my skills still relevant? Can I adapt to these changes? The fundamental question is: Does this AI economy have a place for me, or will I be left behind?
As co-chair of the Economic Resilience Committee alongside Dr Wan Rizal, our focus is clear – to build and strengthen the economic resilience of our community by embracing the AI transition with openness and readiness. We want growth that creates opportunities and empowers workers, not replaces them.
We will assess the implications of the economic shifts that the Economic Strategy Review Committee will outline, identify new sectors and growth opportunities and understand how we can encourage broader participation from the Malay/Muslim community in these areas. At the same time, we are developing targeted strategies to strengthen community involvement in economic transformation initiatives, so that participation can be deepened across all segments – from youth to professionals and entrepreneurs.
Within the Malay/Muslim community, this work has already begun and must be strengthened through the M³, now known as M³+. Allow me to share some examples of efforts being undertaken by Malay/Muslim institutions to raise AI literacy among our community.
We are seeing encouraging initiatives. At Majlis Ugama Islam Singapura (MUIS) (or Islamic Religious Council of Singapore) and the mosques, AI literacy programmes help the community understand the responsible use of technology. The IftaSG initiative uses AI for Fatwa research. Programmes encouraging thoughtful AI integration have also been made available to asatizah, to enable richer and more meaningful Islamic learning experiences.
At Persatuan Ulama dan Guru-Guru Agama Islam Singapura (PERGAS), AI training equips asatizah with digital skills through programmes such as Diversity-driven Upskilling for Asatizah, the AI Accelerator Challenge, and AI for Asatizah Entrepreneurs.
At the Association of Muslim Professionals, for working professionals, the "Learning Circles: All About GenAI" programme will be held this month. It will explore how generative AI is reshaping the way we work and how professionals can begin applying it meaningfully in their daily roles.
At MENDAKI, the MENDAKI Achievement Programme, or MAP, now uses AI tools such as Khanmigo and KiteSense Luminee to enhance the learning outcomes of students from less privileged backgrounds. This reflects a commitment to ensuring that technological progress serves as a catalyst for social mobility and inclusive growth within our community.
Mr Abdul Kadir bin Abdul Rahman, a veteran educator in science and mathematics, is a fine example of how three decades of deep experience can be combined with present-day innovation. Now a trainer in the MAP programme, he is a strong advocate for using AI technology to improve learning quality. He has noted that one significant change is students' increased willingness to ask questions – fostering a more interactive and supportive learning environment.
In addition, MENDAKI's Langkah Digital initiative provides AI-Ready workshops, hands-on training and upskilling programmes to help individuals understand and apply AI in their lives and work. MENDAKI has partnered with institutions, such as SUTD, opening up opportunities in AI, design and application-based learning – so that our community is not merely a consumer of technology, but capable of mastering it.
This shows that AI can be a catalyst for social mobility – if we ensure that access and opportunity are widely shared. But not everyone starts from the same point. Some have access, a supportive environment and the time to learn. Others face constraints – whether in terms of time, family responsibilities, or self-confidence. That is why our approach must be inclusive. Training must be accessible, relevant and practical, so that every individual has the opportunity to adapt and progress alongside these changes. Ultimately, success in the AI economy is not measured by technology alone, but by how well we ensure that every citizen can move forward with confidence and hope.
( In English ): Mr Speaker, Sir, AI will bring both disruption and opportunity. If managed well, it can raise productivity and expand opportunities for all. But if left unmanaged, it can widen inequality.
We must ensure that AI drives not just growth, but inclusive growth. If we get this right, AI will not divide our workforce, it will strengthen it.
And in doing so, we will renew this compact for AI-enabled growth. One where every Singaporean, whether working with code or with their hands, has a place and a role and a future in our economy. I wholeheartedly support this Motion, Mr Speaker.
Mr Speaker : Ms Yeo Wan Ling.
1.09 pm Ms Yeo Wan Ling (Punggol) : Mr Speaker, not long ago, I was at a stop light in Punggol when an autonomous shuttle glided past. I was not the only one watching. Around me, drivers and pedestrians looked up – a mix of curiosity and something quieter. A low, humming anxiety, fringed with a dash of awe. And behind their eyes, a very human question: what does this mean for me?
That image has stayed with me. AI and autonomous technology are transforming the way we work, live and play, faster than any technology humankind has seen. So, the question this House must answer today is not how these technologies work, but what we are doing – concretely, deliberately – to make sure our workers' lives and livelihoods are not left behind.
Mr Speaker, that is what this Motion is really about. And I want to speak to it not with mere assurances, but with a plan. A plan for our workers, a plan for our union members, a plan for our brothers and sisters sitting up in the gallery supporting us in this Motion.
The transformation is already happening, quietly, all around us. At Changi Airport, autonomous baggage tractors ferry luggage between terminals. At Marina Barrage Service Road, autonomous sweepers clear leaves and litter. At Pasir Panjang Terminal, driverless automated guided vehicles move containers between yards. And our first revenue-generating autonomous bus services are set to run on two routes in the second half of this year.
Upskilling has rightly been at the forefront. But job redesign is equally critical to re-engineer existing jobs for new realities, to create new job types and to support workers through transitions as AI reshapes job longevity. And for job redesign to truly move the needle, it must be a genuine, ground-up effort with workers and their real workflows at the centre. Let me elaborate.
First, consult workers deliberately, to really understand their work. As Executive Secretary of the National Transport Workers' Union (NTWU), I have seen first-hand what it looks like when tripartism works. Our management partners, SBS Transit, SMRT and others, have been preparing our bus captains and technicians for the advent of AI, electric vehicles (EVs) and AVs. Employers provide upskilling and training. Government supports companies and workers through that process. And unions, we do what we do best at: listening carefully on the ground to what workers truly need.
It is exactly that ground listening that surfaced something we would have otherwise missed. Even as we move towards 50% of our bus fleet becoming electric by 2030, our bus captains flagged that EV training had important gaps. Unlike conventional buses that use mirrors, EVs use digital monitors and our captains told us about the time delay, the glare, the eye strain and in more severe cases, nausea. They asked for longer training and preparatory times. The union pushed for it with our tripartite partners and it was addressed.
Mr Speaker, that is feedback no consultant's report would have surfaced. But it directly shapes bus design, driver safety and passenger experience. Workers know their jobs better than anyone. That is a resource we must keep on tapping.
In anticipation of our first AV bus services, NTWU, last year, surveyed around 500 bus captains and technicians. One in three expressed concern that AVs would affect their jobs – job security was the top worry, followed by fears of pay cuts. Unsurprising. These are sentiments shared by transport workers worldwide. Yet one in three of our Singaporeans, also remained confident that drivers would continue to play an important role.
So, we dug deeper. We sat with bus captains and asked them to walk us through a day's work, not what their job description said, but what they actually did.
What they told us turned our assumptions upside down. On paper, we assumed driving was the core of a bus captain's job, perhaps, 80% of their tasks. Our captains told us it is closer to 20%. The other 80%, helping elderly passengers board safely, managing crowding, de-escalating difficult situations, giving directions, being a calm and reassuring presence on board and even telling passengers they can only have a singing performance when seated – these are deeply human responsibilities that no AV can replace.
This has profound implications. If we had acted on our paper assumptions about the bus captain role, we would have misjudged job sizes, skill requirements and salary structures – creating inequitable outcomes for workers and human resource (HR) planning disasters for organisations alike. Getting the job description right is not a bureaucratic exercise. It is the foundation on which all of job redesign rests.
Mr Speaker, the unions and the Tripartite Jobs Council will continue to walk the ground. But we cannot do this alone, not if we are serious about job redesign at scale. I call on the Government to resource this properly: to fund systematic study and mapping of actual job roles and workflows, so that job redesign is built on ground truths and not just assumptions.
Mr Speaker, my second point is this: for AI transformation to succeed, workers and customers must be at the centre of the reimagination process of what AI can bring to workers and businesses. Not consulted after the fact. Not informed of decisions already made. At the centre, right from the start.
AI will transform work as we know it. But where exactly it will land – which tasks, which roles, which industries – nobody can fully predict that. That is precisely why the reimagination process matters so much. We cannot wait until the dust settles. We have to build, prepare and yes, dare to dream of what an AI-powered workplace can look like together with our workers. The most important lesson I have taken from visiting companies in transformation is this: when you involve workers early and genuinely, they do not resist change. They drive it.
Mr Speaker, let me tell you about Trusted Hub. A Singapore SME, 25 years in business, in the business of data processing, which, at its heart, actually is what AI is. Rewind to 2001, Trusted Hub was handling Government submissions from members of the public; stacks and stacks of paper; photocopiers, faxes, prints. Fast forward to 2026, same business, more or less the same clients, but a completely different way of working. AI now processes much of the data, taking the load off their staff.
What impressed me when I visited was not the technology. It was the people. Because Trusted Hub brought their workers into the reimagination process as stakeholders – not passengers – the majority of their staff have upskilled themselves to programme AI Agents, creating both enterprise and innovation value for the company. And the oldest AI Agent programmer in the company? A gentleman in his 60s. Self-taught. And this is what happens when you do not underestimate your workers.
I have spoken in this House before about FairPrice's Store of Tomorrow at Punggol Coast Mall, featured at international trade shows as a model for the supermarket of the future and a living showcase of how technology can make work better, easier and safer for our workers. It displaces fear not with words but with evidence people can walk into and see for themselves.
But what made it work was not the AI. It was the process. Workers and unions shaped and designed the system, not inherited it. And because of that, staff did not just accept the change, they owned it.
And what I want is more of this. Stores of tomorrow, bus interchanges of tomorrow, restaurants of tomorrow, clinics of tomorrow. Living testbeds that allow reimagination to happen, not just within companies but across clusters and our communities, so that conversations about AI in the workplace can take place openly, candidly and with imagination, rather than dread.
Very much like my Punggol residents watching our autonomous shuttles glide by, a low hum of anxiety, yes, but definitely fringed with a dash of awe.
While the shape of tomorrow's workplace is still forming, one thing is clear. Putting workers and work processes at the centre of transformation is not optional, it is the method. What does it look like in practice?
It is Chye Thiam Maintenance offering $200 training allowance to workers who volunteer to be trained on their robo-sweepers, making transformation something workers choose and not something done to them.
It is Grab working with unions to assess whether an AV Shuttle safety driver can sustain a full eight-hour shift on continuous alert because worker welfare is part of the design and not an afterthought.
And it is a British entrepreneur who has started calling his AI bots, AI employees, to remind himself and his team that AI is not about replacing people but about changing roles.
These are not grand gestures. They are small, deliberate, but very significant acts that normalise AI in the workplace and make it something workers can see themselves thriving in rather than being displaced by. This involves responsible employers, progressive employees and indeed, a supportive and nurturing Government. It is the tripartite way and it is why the Tripartite Jobs Council matters so much to organise, to set the tone right from the start, on how AI is embedded and rewarded in everyday company life.
Mr Speaker, this is the real answer to unfounded fears about AI displacement – not reassurances, but evidence. Evidence that when workers are treated as co-creators, transformation is faster, adoption is stronger and outcomes are better for everyone.
The Tripartite Jobs Council is well-placed to drive this reimagination work at every level, through Company Training Committees (CTCs), CTC Queen Bees at cluster level , sectoral AI uplift plans across industries. Our Queen Bees can bring their contractor ecosystems along, as what FairPrice did with their Store of Tomorrow. Unions will do what we do best: walk with workers and management through what the road ahead looks like, and what new roles are emerging along the way.
But Mr Speaker, this really requires investment and intentionality. I call on the Government to resource sectoral AI uplift plans for industries – retail, logistics, healthcare – with the same deliberateness that has started to guide our AV roadmap for public transport. Workers deserve to know not just that AI is coming, but where the next testbeds will be, what the new jobs will look like and how to get there. Clarity is not a luxury. For workers standing at that crossroads, it is everything.
Mr Speaker, my third point is this: even the best-run AI transition will see jobs disappearing and some occupations finding the tasks they do taken over by AI. That is the honest truth. And we should not paper over it with optimism. Hence, transition support must be real, it must be timely and it must reach those who need it most.
We owe our workers a system that catches them before they fall too far and gets them back to a good job as quickly as possible. That system must start with job redesign. Not as an afterthought but as the first line of defence. If we redesign jobs well and early, we reduce the number of workers who need to be caught in the first place. The best transition support is one that makes the cliff shorter to begin with.
That is why the signal we send to enterprises matters so much. AI grants must be tied to mandatory job redesign requirements and productivity gains linked to worker outcomes. If these enterprises are unable to retain our workers, these companies should be required to notify the Government early on personnel whom they are unable to retain, so that these displaced workers can be assisted by e2i and our newly-formed Tripartite Jobs Council. This will be the assurance to workers that Singapore's AI transition will not result in jobless growth and that we keep the transition time to a new good job as short as possible.
Mr Speaker, I am heartened by our Prime Minister's assurance during Budget 2026 that the AV transition will be managed carefully, with close engagement with Platform Worker Associations and our drivers. As Advisor to the National Taxi Association and the National Private Hire Vehicles Association, I want to speak directly to that. In Mandarin, please, Speaker.
( In Mandarin ) : [ Please refer to Vernacular Speech .] Our taxi and private-hire drivers are already navigating a fiercely competitive environment with high fuel costs. Seeing AVs operating in Punggol and hearing news of autonomous bus pilots, they cannot help but harbour a quiet, unspoken worry. They are not asking us to halt technological progress – but what they need is not just reassurance. They need a clear sense of direction.
How will the geofencing of autonomous vehicles be progressively expanded? What is the timeline? New roles such as remote operators and safety supervisors are beginning to emerge. I hope that drivers who are willing will be supported and given access to training, so that they can transition into these new positions. For those who are not yet able to make that transition, I also hope that the newly established Skills and Workforce Development Agency will take the time to understand their needs more carefully – because they are not a homogeneous group and cannot be treated as one.
This is not just a matter that concerns platform drivers. Our technicians and tradesmen keep Singapore running with their hands, yet in conversations about AI, they are often invisible. Their contributions have long gone without sufficient recognition.
I am glad that the Ministry of Manpower (MOM) has begun driving efforts in this area, starting with the electrical trade. We must press on to build career pathways for tradesmen that are more promising and more respected, while harnessing AI to enhance their capabilities – not to replace their judgement.
( In English ): Mr Speaker, the workers most exposed to AI disruption are often the ones with the least buffer – least savings, least flexibility, least time to wait for a system to catch up with them. That is why our response must be tripartite in the fullest sense. Employers and platform partners must lean in as their business models evolve and not step back. This means staying involved in transition support, co-sharing training cost, covering opportunity cost and supporting workers through employment and post-employment pathways.
Unions will do what we have always done, walk the ground, listen and shape livelihood opportunities alongside our workers and we will continue to "jaga rumah" – by keeping watch on what other jurisdictions are doing, from China's Internet court ruling that AI replacement alone is not grounds for dismissals to California's requirement for human safety operators on AVs. These are signals of a world working out where the boundaries are. Singapore must learn from them, and when necessary, get ahead of them. Government must design transition support around the people who need it and not around what is administratively convenient. This is a standard we must hold ourselves to.
Mr Speaker, I will conclude with three calls to the Government.
Give time. Job redesign cannot be rushed. It requires sitting with workers, understanding what their work really is, not just what the job description says, and going back to the ground when the first answer turns out to be incomplete, as ours was with bus captains. Companies need to be supported through this and not just pushed into it.
Give help on the reimagination piece. Most companies, especially our SMEs, cannot do this alone. I look to the Government to provide practical facilitation, frameworks and funding that makes job redesign achievable. And I look to our leading companies, our Queen Bees, to step forward, share what has been worked on, and bring their sectors along with them. Transformation that stays within one company is transformation that is only half done.
Make NTUC the linkway. Our unions, our e2i, our Tripartite Jobs Council – we are already on the ground, in the companies, with our CTCs, sitting across the table from workers and employers every day. We have trust that took many, many years to build. Our Labour Movement is ready to be the connective tissue of this transition, matching displaced workers to redesigned roles, advocating for fair treatment and holding everyone, including ourselves, to account. The SWDA and our agencies must build on this.
Mr Speaker, I think back to that autonomous shuttle gliding through Punggol. Our workers watching it are not asking us to stop it. They are asking us to make sure that as it moves forward, they move forward too. That is the answer we owe them. Not just a promise; a plan.
I believe that an AI transition with no jobless growth is possible. Not because the technology will take care of it, but because we will. If we consult workers properly, involve them in the reimagination of their work and back that up with transition support that actually reaches the people who need it most. I support the Motion.
Mr Speaker : Mr Gerald Giam.
1.28 pm Mr Gerald Giam Yean Song (Aljunied) : I declare my interest as the owner and director of a company that provides software to training providers.
Mr Speaker, we face a structural threat to our workforce. For decades, Singapore's economic model has been built on the premise that a highly educated and skilled workforce would hold the keys to a prosperous future and be a buffer against economic storms. However, we are now in the midst of a paradigm shift where AI is not only augmenting human capability, but in many ways replacing it. Unlike past economic cycles, where such turbulence could be written off as an episode of creative destruction, AI promises to be a harbinger of a fundamental shift in our economic and social relationships. Taking this concept further, it would even impact the roles that the Government plays in mediating between the individual and society.
Today, we must recognise that the very nature of labour's economic power is changing. Failure to address this issue, even as productivity soars, will lead to an entrenched lower and middle class with the loss of economic agency. This concern is articulated by Jasmine Sun in an opinion piece for the New York Times, where she identifies the San Francisco consensus, a growing recognition that the hiring of young workers in highly AI exposed occupations is already in decline. She reminds us of the risk of a resulting permanent underclass, where the gains of technology are concentrated in the hands of a very few.
Not all the evidence points towards catastrophe. A 2025 US National Bureau of Economic Research working paper found that tasks with higher AI exposure do experience reduced labour demand. However, overall employment effects have so far been modest as productivity gains offsets some displacement. Similarly, a study published in the Quarterly Journal of Economics by the Massachusetts Institute of Technology's Danielle Li and Stanford's Erik Brynjolfsson found that generated AI tools boosted worker productivity by nearly 15%, with the greatest gains among the less experienced workers, thus suggesting AI can be a ladder, not just a trapdoor.
It should be noted that these studies examined early and controlled deployments. As agentic AI scales across entire industries simultaneously, the distributional consequences may be more severe and swifter than early productivity research would suggest.
We cannot be certain which trajectory Singapore is on. The asymmetry of risk demands that we prepare for the harder scenario, not the easier one.
This concern is shared by the very architects of the AI revolution. In 2021, OpenAI's CEO Sam Altman predicted in his blog post "Moore's Law for Everything" that AI would shift power from labour to capital, positing that if public policy does not adapt accordingly, most people will end up worse off than they are today. Crucially, Altman was not fatalistic. He argued that the proactive redistribution of AI-driven wealth, including giving citizens equity stakes in the economy, could make this a broadly prosperous transition.
Similarly, Dario Amodei, the CEO of Anthropic, has observed that the health of a democracy is premised on the average person having leveraged through creating economic value, a view he expressed in his 2024 essay, "Machines of Loving Grace".
The erosion of that leverage is a deeply concerning prospect that requires a bold and structural policy response. Singapore is uniquely positioned to lead this response and to capture the genuine economic opportunities AI presents for our people. As a small, open economy with a highly educated workforce, strong institutions and well-capitalised sovereign wealth funds, we have the tools to act swiftly and structurally, compared to many large nations.
But that window of opportunity will not remain open indefinitely. While cost arbitrage makes offshoring attractive, AI could erode that advantage – not by bringing those jobs back but by enabling small teams of skilled Singaporeans to do the work that once required hundreds of offshore workers. The opportunity is not in reshoring in a traditional sense but the concentration of higher-value orchestration and oversight roles here at home, where trust, institutional quality and proximity to decision-makers matter.
AI's equalising potential extends beyond white-collar work. A blue-collar worker who struggles with English could dictate in their mother tongue and have AI render as professional documentation in real time, freeing them to focus on their craft rather than their grammar. AI should be an equaliser that elevates the technical master, not a wedge that stratifies our workforce. AI tools can also power a new breed of local startups by enabling small hyper-efficient teams to create immense value and scale, achieving global reach with minimal manpower.
Singapore must therefore be at the forefront of this shift while ensuring that benefits accrue to all citizens. This will require workers and entrepreneurs who are trained, skilled and adept at harnessing AI tools and innovations and empowering their employees to do the same.
Our current efforts to reskill Singaporeans are often hampered by the trap of low-utility external training programmes which produce certifications that lack real-world currency in an AI-driven economy. These programmes enrich training providers while leaving workers with skills that have little economic value. This misalignment risks creating a two-speed economy where capital owners and tech-integrated firms leave behind those stuck in the slow lane of traditional employment, leading to a fundamental erosion of social cohesion and increasing the risk of long-term structural unemployment.
To address this, I propose the establishment of a National AI Equity Fund. This fund is a necessary safeguard to maintain the integrity of our social contract. It is a strategic surplus transfer from enterprises which benefit immensely from AI back to Singaporeans to facilitate our collective stability.
I will elaborate on the precise funding mechanisms shortly after I explain the uses of the fund. I propose the fund be organised in two distinct pillars.
The first is a social dividend where revenue is distributed as a direct payout to every adult Singapore citizen. I propose an initial citizen dividend of $500 per adult citizen, scaling upward as fund contributions grow. This is modest by design. It is not meant to replace income, but to provide a tangible signal that every Singaporean has ownership in our shared future.
Based on our current citizen population, this would cost approximately $1.5 billion annually – or less than 10% of last year's Budget surplus – and provide a meaningful return to every Singaporean household. This would serve as a social floor, ensuring that the gains from national digital prosperity provide tangible peace of mind and dignity for all.
This dividend will provide an additional cushion for families as the nature of work evolves. It also allows Singapore to reap the full productivity benefits of AI without overly exacerbating social inequality.
An argument could be made that the Community Development Council (CDC) vouchers already do this, but those are entirely discretionary. The social dividend I propose is a structural entitlement – a function of receipts rather than what the fiscal mood of the moment happens to be. That distinction matters enormously for a family planning its future.
The other portion of the fund will be dedicated to a mastery fund, which will be an employer-led, on-the-job training (OJT) model that moves training out of the classroom and into every enterprise.
I propose that the mastery fund provides a mastery apprentice wage covering 50% of the gross salary, capped at a median wage for six months, for any Singapore citizen entering or transitioning into an AI-augmented role. This rewards the worker's effort in adapting while lowering the barrier for firms to hire, train and retain talent in this volatile market.
Recognising that many SMEs lack the capacity to design structured OJT programmes, I propose that the fund also finance a pool of expert OJT consultants. These consultants experienced in OJT design will rotate between firms to structure OJT blueprints tailored to each firm's specific needs. This will help SMEs fill their talent gap while also addressing the need to create new steps in the ladder of training and apprenticeships for new entrants into the marketplace.
Furthermore, I suggest a mentorship credit be provided to employers to compensate senior staff for the time they spend on structured mentorship, turning our workplaces into true academies of mastery and ensuring that skills remain relevant to the actual needs of the economy.
The mastery fund should be made available to all business entities and societies that are founded and based in Singapore, including micro enterprises. The use of funds should be closely monitored to ensure that it genuinely contributes to AI mastery within each firm. I estimate the annual cost of the mastery fund to be approximately $1.42 billion.
Let me set out the financing details.
The first source is a marginal increase of two percentage points of the corporate income tax rate for firms with annual profits exceeding $100 million. By focusing on these companies, we capture the automation surplus from those best positioned to drive growth through AI rather than headcount. Whether global tech firms or traditional giants, these enterprises are at the forefront of decoupling revenue from labour. This tax increase will generate an estimated $1.5 billion annually, ensuring that gains from record-breaking efficiency are recycled back into the National AI Equity Fund for the benefit of all Singaporeans.
The second source is a targeted increase in the utilisation of our investment returns. I propose raising the maximum net investment returns taken into the Budget from 50% to 52.5%, with this additional 2.5% flowing directly into the fund. Based on current estimates, this would raise approximately $1.45 billion annually.
Our sovereign wealth entities, GIC and Temasek, have been early movers into the AI space, investing in foundational firms like Anthropic and committing billions to the AI infrastructure partnership alongside Microsoft, BlackRock and Nvidia. As these global Investments profit from the automation of labour worldwide, it is only right that we recycle a modest portion of those gains back into our own workforce.
Relocating 2.5% is not a radical request. It ensures our reserves provide more than just financial stability, but also the long-term economic agency of every Singaporean.
As we look toward the future, we cannot simply assume that displaced workers will transition smoothly into new roles as they have in previous technological revolutions. The steam engine did not replace human judgement, but AI may do just that. That is precisely why passive reskilling is insufficient and why the financial security of a social dividend is needed. Workers shifting towards less automatable roles in entrepreneurship, care work, the skilled trades, sports and the arts do not just need training, but time and security to make that leap.
Certainly, new jobs will emerge that we cannot yet imagine, but we must build a system robust enough to support our people even if that emergence is slower or more unevenly distributed than we would otherwise hope. The National AI Equity Fund provides a financial buffer for Singaporeans to make these transitions with confidence.
During this year's Committee of Supply Debate, I proposed a Youth Wage Credit Scheme – a targeted wage subsidy for employers who hire younger Singaporean workers. The National AI Equity Fund extends that logic into a broader longer-term framework for all Singaporeans navigating the AI transition and other technological disruptions.
Mr Speaker, the National AI Equity Fund is a renewal of our social contract for the digital age. We cannot allow AI to become a wedge that fractures our society. Instead, we must use it to become the greatest equaliser our nation has ever known. By establishing the social dividend and the mastery fund, we give every Singaporean a direct stake in our digital prosperity and the resources to stay ahead of the curve.
Let us make it our goal to ensure that as machines grow more capable, our people grow more secure. By acting now, we can ensure that technological progress serves the dignity and economic agency of every Singaporean. Sir, I support the Motion.
Mr Speaker : Ms Poh Li San.
1.43 pm Ms Poh Li San (Sembawang West) : Mr Speaker, in this Sitting and indeed, in the past few Sittings, few speeches have been made without mentioning the age of AI. Much has also been said by the Government about how the global disruption will impact our play, our work and our lives.
In policy-making, there is always the binary choice: ride this AI wave or be submerged and be left behind. This is Hobson’s choice and the answer is obvious. But we cannot ask a question of a strawman. Singapore is a small, open and digitally connected economy. AI will be a fact of economic life.
The Government has said that it will grow our economy, support our businesses and take care of our workers. But there is a difference between policy-making in the Ministries and implementation on the ground.
At street level, the AI transition looks intimidating, expensive, and for many middle-aged workers, a place of anxiety and confusion. This is the first wave of change and may be the hardest. The Government, businesses, unions and workers must struggle together to ride out this wave.
During the transition, some jobs will disappear, but new jobs will also emerge. Left to the market, there will only be growth where the strongest, fittest and most able benefit. In a city where the law of the economic jungle operates unfettered, let us be honest, the AI transition will benefit some, but not all. This growth will not lead to better and more prosperous lives for all.
But that is not the job for the market. That is our job; all of us here in this House must bend the market to our will: to create more high-value jobs for Singaporeans and retrain displaced workers but to do so in a way that also meets the business imperative for profits, so that our economy can continue to grow in the long run. We have built Singapore on solutions that met both interests in the past, and we must do so again in the future.
Let me talk concretely about two ways that AI can benefit our workers.
We used to say that people are Singapore’s only resource. We are now a superaged society with a total fertility rate of 0.87. Our resource pool is shrinking. Human resource is now the key bottleneck and cost driver for most businesses, especially SMEs which are hiring 70% of local workforce. If businesses close down, more workers will lose their jobs, even those not threatened by AI.
Our businesses have faced worsening labour shortages over the past decade. The 2025 ManpowerGroup's latest Talent Shortage Survey reveals that nearly four in five employers in the Asia Pacific region are struggling to find skilled talent, with 77% reporting difficulties. In particular, many jobs that Singaporeans cannot or will not do are done by non-Singaporeans.
But there is a limit to our dependence on foreign workers, including political and social constraints. We need AI-powered robots to replace foreign workers in roles that no Singaporeans would want to do or can do. For instance, heavy duty roles in construction, maritime and aviation sectors, that are exposed to the harsh elements of a warming climate. This will be a game changer for us.
The next frontier is in physical generative AI or embodied AI. In more recent times, generative AI technologies have been integrated with physical systems, enabling machines to interact with and adapt to the real world. It enables robots to learn complex tasks, such as manipulation and navigation, via simulation and transferring intelligence from digital models to real world hardware. Put simply, robots and humanoids capable of thinking and even perceiving, can be deployed in unstructured and dynamic environments, to assist or even replace human workers.
In recent months, companies such as Dexterity AI, Figure AI and Unitree Robotics have demonstrated their capabilities in AI-powered robots and humanoids in specialised roles.
Unlike generative AI tools like ChatGPT that trawl the Internet to train its models, physical generative AI tools need to be trained in contextualised environments for the roles and tasks they are set out to do. Over time, these physical AI capabilities will mature and become accessible to businesses facing manpower shortage. These AI-powered robots can help our businesses overcome manpower constraints, lower costs and increase profitability.
Physical AI robots are good at repetitive tasks but cannot replace every single role. Jobs and process redesigned into man-machine hybrid teams will be the new norm. Seniors and women can join the transformed workforce – with repetitive, heavy-duty roles done by robots and complex supervisory roles performed by humans. It will be a new model of freedom and empowerment, unimaginable today but a reality in the very near future.
Singaporeans can be upskilled as supervisors of robots. New high-value job roles such as design, build and maintenance of these AI robots will be created for young engineers and technicians.
More Singaporeans can retire at a later age if they wish to, since their roles will become less physically demanding. Seniors and women can join industries previously dominated by those with stronger physical abilities. And robots also do not carry any social baggage.
Mr Speaker, the transition to AI-powered robots is my area of work, and this is the vision we are working towards – to solve real problems for businesses and elevate the quality of life for workers. I feel strongly that our AI transition should be focused on customising physical generative AI solutions for our industries, so as to help every Singaporean on this journey of empowerment.
Prime Minister Lawrence Wong outlined four key pillars for our National AI Strategy. In particular, in the Advanced Manufacturing and Transport Connectivity sectors, AI-powered robots will indeed be the force-multiplier.
Are we ready for this transition? Not yet. We are well-positioned for it, but we must move fast. And I would suggest the following six steps.
One, unions should forecast which are the types of jobs and sectors at risk, as well as numbers of workers that may be displaced.
Two, MOM should fund retraining for affected workers, to prepare them for other roles or other industries.
Three, workers should also step up, learn new skills and be open to new job opportunities.
Four, the Ministry of Education (MOE) and IHLs should redesign academic programmes to shift students away from fields already taken over by AI. All IHL students should learn AI tools relevant for their disciplines.
Five, the Ministry of Trade and Industry should attract more world-class physical generative AI companies to set up headquarters in Singapore and attract talents for research and development (R&D).
Six, businesses should be open to work with AI companies to automate and redesign work processes, revamp job roles and create man and machine hybrid teams. Mr Speaker, I would like to share a few points in Malay.
( In Malay ) : [ Please refer to Vernacular Speech .] Mr Speaker, Singapore's AI transition must be managed jointly by Government, businesses, unions and workers to avoid uneven gains. Physical AI can ease labour shortages and reshape work into human machine teams. With job redesign, upskilling and education reform, workers can move into higher value roles, while businesses can grow with higher productivity.
To support this transition, Government support and regulation are crucial to fund retraining of workers, create higher value jobs, attract leading AI firms and ensure that AI is used ethically for broad societal benefit.
( In English ): In the near future, a new AI ecosystem will emerge. Technology companies create AI solutions, businesses own them and workers leverage them.
But the Government must set the rules. AI must be used as a force for good and not for criminal and harmful exploits. Establishing the ethics around AI use will make the difference between our society benefiting from the use of AI or becoming enslaved by it.
But there is also a deeper moral question relating to AI. AI is artificial; it has no intrinsic good, no value in and of itself. We, in this House, have a duty to bend the market in the use of AI, not just to forbid what is criminal but to enable what is fair, good and just. We must ensure that the AI transition does not merely create growth but creates jobs, benefits workers, strengthens businesses and elevates communities. Mr Speaker, I would also like to conclude my points in Mandarin.
( In Mandarin ) : [ Please refer to Vernacular Speech .] Mr Speaker, Singapore's AI shift needs a coordinated effort by Government, businesses, unions and workers to ensure that both businesses and employees stand to benefit, and to support and assist those who are affected. This includes providing retraining and expanding the scope of education, creating higher-value jobs so that more Singaporeans can adapt to these changes as quickly as possible.
Physical AI – robots combined with generative AI – can ease labour shortages by taking on tough and risky work in sectors, such as construction, aviation and maritime, while reshaping roles into human-machine teams.
I would like to propose several key steps to support the AI transformation:
First, companies should automate and redesign jobs; second, unions should flag at-risk roles; third, workers should keep learning; and fourth, Government should set clear AI rules. A national transformation should not merely be pursued for the sake of higher economic growth, but should ensure that all segments of society can benefit.
( In English ): Mr Speaker, the Motion on which I rise to speak today asks for us to affirm that AI transition "must not lead to jobless growth". And this "must" is not an empirical prediction, nor is it empty rhetoric. It is political resolve.
AI in this free market may or may not be the new model of freedom and empowerment for our people. It is our resolve that makes it so. Mr Speaker, I support the Motion. [ Applause. ]
Mr Speaker : Mr Andre Low.
1.57 pm Mr Low Wu Yang Andre (Non-Constituency Member) : Mr Speaker, the Motion before this House calls for an AI transition that does not leave Singapore's workers behind. The Prime Minister, the Labour Chief, the Government as a whole, have all said the same in the past months; that this is what they intend. What I want to examine this afternoon is whether the policy architecture we have is equal to the commitment we are being asked to affirm.
Mr Speaker, every AI deployment a firm makes is at its heart a choice. The firm can use AI to make its existing workers more capable, more productive, more valuable than they were before or it can use AI to do without those workers entirely. The economist's shorthand for this is augmentation as opposed to automation: augmentation where AI works alongside the worker, and automation where AI replaces them.
Stanford economist, Eric Brynjolfsson, one of the leading academic voices on AI and labour markets, has made a convincing case that in an unaided market without deliberate policies steering in the other direction, incentives systematically favour automation. Firms find it easier and cheaper to deploy AI to replace workers than to retrain them. The tax code, the labour market institutions, the cost structures of capital all tilt the playing field. Even though augmentation creates more total value over time, more good jobs, broader prosperity and a fairer distribution of the gains, the default trajectory of an unguided system is automation.
The Government's chosen and declared direction is augmentation. The Motion before us today assumes augmentation. The Labour Chief in this Chamber yesterday put the same commitment in his own words – not AI instead of workers but AI working for workers.
The philosophical direction is settled across the aisle. The substantive question is whether our policy architecture matches it.
There are three places where architecture is currently miscalibrated. Three places where, today, the system is permitting automation despite promises to the contrary.
The Labour Chief yesterday said that AI is also reshaping professional, manager and executive (PME) jobs in higher-end professions, like doctors, lawyers and accountants. The Prime Minister has said much the same – AI will affect Singapore's professionals, managers and technicians (PMETs) who have spent years building specialist careers and who are now being told that the ground below them is moving.
At his May Day rally last week, Prime Minister Lawrence Wong said, "We may not be able to protect every job, but we will protect every worker." The question is whether the instrument the Government has chosen, the SkillsFuture Job Seeker Support scheme, delivers on that promise. The Prime Minister has termed the Job Seeker Support scheme the "Singapore way", a more pragmatic, more Singaporean alternative to the redundancy insurance that is the Workers' Party's (WP's) preferred solution. That reads the Singapore tradition backwards.
Mr Speaker, the Labour Chief said in the Chamber yesterday that financial support during the transition is not welfare, it is an investment in worker outcomes. By that test, the tradition has long been built on investments of exactly that kind. The Central Provident Fund (CPF), MediShield Life, MediSave, these are all universal contributary schemes paid out when life's major contingencies hit. Each catches every worker because the contingency it insures against can hit every worker. That is the Singapore way.
The Jobseeker Support scheme is not built in that tradition. It is a tax-funded grant gated on pre-redundancy income, closer in design to a means-tested assistance than to insurance against contingency. As currently configured, it pays up to $6,000 over six months in tapering monthly instalments, starting at $1,500 and ending at $750 over the last three months and it is only available to workers who earn $5,000 a month or less before they were made redundant.
The Labour Chief acknowledged in this Chamber yesterday that the ceiling excludes PMEs who face the same displacement risk in the AI era and has proposed raising the qualifying ceiling to closer to the PME median gross income level.
If this proposal is adopted, it is movement in the direction that the WP has long argued for. But Mr Ng's proposal moves the line, ours would remove it. Raising the ceiling lets more workers into the scheme but it does not change what the scheme does for them. For those who do qualify under the ceiling, the taper carries its own message: a payment that starts high and slowly reduces is not a flaw. It is a countdown. And a countdown pushes a worker to take the first offer, not the right one.
MOM's own data tells us why this matters. Of retrenched residents in the final quarter of last year, 43.6% of PMETs had not found new employment within six months. That is the cohort that the Jobseeker Support scheme runs out on. And of those who do find work within six months, roughly four in 10 return at lower wages than before. So, they took what was available and not what their experience was worth. Most of us have experienced how the higher up the career ladder you climb, the longer it takes for you to find your next role.
Mr Speaker, a PMET who is pushed by a six-month countdown into a lower paid job that they did not want has experienced exactly the automation outcome that the Government's framework was supposed to prevent, with a small cushion attached for the fall. Raising the ceiling only widens the cohort, but it does not shorten the countdown.
Mr Speaker, the WP's proposal for redundancy insurance scheme is built in the actual Singapore tradition. We pay out 40% of last drawn salary with no income ceiling and no tapering mechanism. It is funded by employer-employee contributions in the same model as the CPF and it covers every worker who pays in, including the professionals the Labour Chief has identified as the most exposed because the contingency it insures against does not stop at $5,000, $7,600 or any other ceiling Parliament may set.
The Prime Minister said we must protect every worker. The instrument the Government has selected does not. The WP's does.
Mr Speaker, when a firm is contemplating a major AI deployment, it stands at a fork in the road: down one path it retains the existing workers and retrains them to operate alongside the AI; down the other, it retrenches, runs leaner, brings in a smaller AI-fluent workforce. The first is augmentation. The second is automation.
But what does our tax code say to the firm at that decision point? The current architecture rewards activity. It rewards capital expenditure on AI. It rewards expenditure on training. These are good things to reward, but what the architecture does not currently do is reward the choice itself.
A firm that retrenches its existing workers and trains a smaller set of new hires receive the same fiscal treatment as a firm that retain and retrains its existing workforce. A firm that buys AI to replace workers receives the same fiscal treatment as a firm that buys AI to augment them.
The tax code is silent at the fork.
And as Bronson previously observed, silence at the fork is not neutrality in consequence. When the tax code does not actively reward retention, the underlying economics tilts firms toward retrenchment. Labour is, after all, the most expensive line on the balance sheet and labour costs are permanent in a way that one-off training costs are not. An unaided market would choose retrenchment.
Yesterday, Mr Ng defended the CTC framework in this Chamber as the mechanism that ties enterprise transformation to worker progression and proposed expanding it through the new Tripartite Jobs Council.
CTC operates at the project level for firms that engage with it, with grant funding attached, expanding its reach scales the grant model, but does not change the broader fiscal architecture that every firm operates within, whether or not it is within the CTC scheme. And it is this broader fiscal architecture that shapes chief financial officers' financial decision-making at the decision point.
In February, in this House, I propose a retraining tax credit, a deduction available only to firms that can demonstrate that they have retained an existing worker into an AI-augmented role, rather than retrenching them. It is this missing conditional piece that will give firms a fiscal signal precisely at the point where they have to make a decision. This retraining tax credit would reward a proactive choice instead of simply investing in AI.
The fourth limb of this Motion affirms that economic progress must remain inclusive. That is a commitment about distribution, not just growth. My colleague Gerald Giam has proposed a National AI Equity Fund to deliver on that commitment structurally. The instrument I am proposing today is the diagnostic tool that any redistributive mechanism, including Mr Giam's, needs to operate on. Because the third condition for an augmentation strategy, to be real, is verification.
Mr Speaker, augmentation is, in the end, a testable claim. It makes a prediction that wages in the sectors where AI is being deployed alongside workers, will track the productivity gains that these workers helped to create. If that prediction holds, the framework that the Government has adopted is being delivered as advertised. If productivity rises in these sectors, but wages do not move alongside it, then what is being delivered is something other than augmentation, whatever language we use to describe it.
Right now, we have very few mechanisms and very few systematic ways of telling which is occurring.
The Government is investing serious public money at scale in four national AI mission sectors, advanced manufacturing connectivity, finance and healthcare. Public funds are flowing into these sectors and more through the CTC grants, the newly formed Tripartite Jobs Council, the Skills and Workforce Development Agency and various enterprise transformation programmes. These are appropriate investments, but public investment creates a corresponding public accountability obligation. where public money goes in, the public has a right to know what is coming out and to whom.
So, what I am asking for is a targeted transparency mechanism, an annual AI gains audit scoped specifically to the four national AI missions to start, reporting to Parliament on how productivity gains from state-backed AI investments are being distributed between wages and returns to capital. Over time, its scope and coverage can be expanded.
In February, in my Budget speech, I framed this as a distribution question. Today, with this Motion before the House asking us to affirm that economic progress must remain inclusive, I propose it again as something more fundamental. The AI gains audit is the most direct instrument available to Parliament to test whether the Government's chosen direction of augmentation is actually being delivered. If the gains are being shared with workers, the audit will say so and the framework will have evidence to back its claim. If they are not, we will know before the gap becomes a chasm and before this Motion becomes a statement of hope rather than of policy.
Mr Speaker, the choice between augmentation and automation is not made in one day. It is made every day by the architecture of the schemes we run, the tax code we maintain and the data we choose to collect. Whatever the House says today, that architecture will keep making the choice on our behalf.
Right now, my position is that the architecture pushes workers towards the first available job rather than the right one. Our tax code says nothing to affirm at the fork between retraining workers and retaining them and we have built no mechanism to tell whether the gains from public AI investment are reaching the people whose name that investment has been made. And that is why I support this Motion. I urge the Government to give it the architecture it requires so that we can make sure that no worker is left behind. Thank you, Mr Speaker.
Mr Speaker : Dr Hamid Razak.
2.10 pm Dr Hamid Razak (West Coast-Jurong West) : Mr Speaker, Sir, I declare that I am a business owner for a private orthopaedic practice, which is unionised, and also an advisor to the Health Services Employers Union (HSEU).
I rise in support of the Motion, an AI Transition with No Jobless Growth. AI is already here. It is not a pilot; it is already becoming a platform.
Sir, our question is not whether we adopt AI. We will. The broader question is whether we grow without leaving our workers behind. In the next decade, Singapore should be judged not by how fast we deploy AI, by how well we translate adoption into better jobs, better wages and stronger trust at the workplace.
I speak in three roles today as a professional, as a parent and as a Member of Parliament listening to my residents.
First, the professional anxiety. Many PMETs, they are not afraid of technology, they are uneasy about the uncertainty because AI rarely replaces the whole job. It unbundles tasks, it compresses teams, it changes what employers hire for. And when you cannot see how your role evolves, anxiety rises.
Second, the parental anxiety. Parents today ask very simple questions: will my child have a fair start? What will entry-level work look like? And if entry-level work shrinks, who will then train the next generation?
Third, the resident anxiety and this is the most practical one. Mid-career workers worry about displacement. Caregivers worry about time. Many people cannot just stop their work to train or retrain. They are not asking for guarantees. They are asking simply for a fair chance and a system that they can navigate.
Mr Speaker, Sir, we should be candid about AI. AI is smart, but it is not wise. It can hallucinate, it can sound confident and yet still be wrong. So, the future should not be about humans competing with AI. It should be about humans working with AI, with judgement, with verification and with accountability.
This Motion is just not about technology. It is about trust, job redesign and the worker journey in whole. Trust will determine if this adoption would succeed. If AI is experienced by workers as surveillance, the trust will thin and eventually break. And when trust breaks, adoption will slow and gains will not be sustainable.
Prime Minister Wong spoke about protecting every worker and scaling practical tripartite tools, like the CTCs for the AI transition. This is the direction we should double down on and I offer four practical moves on this front.
First, skills must be a pathway and not a menu. SkillsFuture is a major national asset. But on the ground, many workers tell me this. It is useful, but it is also overwhelming. Too many courses, too many badges, too little signal.
So, the problem now is not just access. It is navigation. A worker should not need to scroll for hours to guess what really matters to him or his next job. So, I suggest that we curate clearer AI-relevant pathways by sector, by job role, with a clear front door and clear employer recognition. And we can consider additional incentives for those who choose priority courses that support AI-enabled growth, especially when there is clear employer demand. This could mean higher subsidy tiers or outcome-linked support, such as completion plus interview, attachment or redeployment pathways subject to design and feasibility.
Second, tie AI adoption to job redesign. Many Members have spoken about this. If we fund adoption, we should ask, how will tasks change, how will workers be redeployed and how will the performance measurements continue to remain fair? Productivity must show up as better work and, ultimately, better wages for our workers and not only a shrinking headcount.
This is not meant to be punitive. It is meant to be practical. This is where our tripartite partners can help with playbooks, with templates and advisory support so that SMEs are not left alone to figure it out.
Third, bring AI readiness to the professional sectors, like clinics, law firms, accounting firms. Many are small, PMET-heavy and time poor. They want to adopt AI but they worry about safety, confidentiality, liability and trust.
One practical model already shared in this House is already emerging in healthcare. In April this year, HSEU and GP+ Co-operative signed an agreement to train primary care clinic staff in AI awareness, and to help primary care clinics adopt technology and redesign their workflows, supported by the CTC approach and the CTC Grants. I observed this partnership up close. The value is in making adoption practical, responsible and anchored on job redesign, and not just a tool roll-out.
I hope that we can extend this cluster-based, CTC-style approach to other professional sectors too, including law and accountancy, so smaller practices can move from uncertainty to readiness, with clear governance standards and worker protection.
For our workers, support should begin when need is recognised. That means faster job matching, modular training that fits real-life schedules and practical guidance for responsible transitions. In practice, structured coaching and a clear next step reduces anxiety, because it shifts a worker from waiting to acting. Mr Speaker, Sir, I will now speak in Tamil.
( In Tamil ) : [ Please refer to Vernacular Speech .] Hon Speaker, many feel concerned when talking about AI. They worry that jobs may disappear, that the value of skills may diminish and what may happen to the future of children. These concerns are real. The questions are also difficult, but our response is not to fear.
AI is advancing quickly, but human mercy, trust, sense of justice, creativity, language, culture – all these cannot be fully replaced by any machine. AI can compute; but the human connection, human judgement and the human responsibility will always remain with us. So, we must move ourselves from the path of fear to the path of opportunity. The rise of AI does not mean that humans are no longer needed. Rather, it makes it clearer on what truly are the important tasks that humans must do.
In this regard, the humanities are important; language skills are important; cultural nuances are important; social understanding is important. Healthcare, caregiving, education, social services, counselling and work that involves direct contact with people – these are fields that AI cannot replace.
The Tamil language and Tamil culture are a support in this endeavour; our literature nurtures the human feeling. Our culture strengthens social responsibility. That is our strength. So, this is what we must tell our young people: embrace AI but also grow the human capability.
Learning is not merely a certification. It is a path, a belief, a plan for the future. When growth comes, employment opportunities must come with it. Support for change must also come with it. So, do not fear. Let us have faith.
( In English ): Mr Speaker, Sir, no jobless growth must mean one thing. Growth that workers can feel, in wages, in dignity, in a clear next step.
So, I offer one governing standard. The test is not how many schemes we have. The test is whether a worker can quickly see the right course, for the right job, at the right time. Whether a parent can feel confident about their child's runway and future, and whether the citizen's journey feels seamless.
If we keep this direction and refine delivery with tripartite resolve, Singapore can deploy AI effectively, responsibly and at speed, while strengthening trust and protecting dignity. With these observations, Mr Speaker, I support the Motion.
Mr Speaker : Ms He Ting Ru.
2.19 pm Ms He Ting Ru (Sengkang) : Mr Speaker, Singapore's approach to AI is often cited by international institutions and consultancies like BCG, and prominent figures, such as International Monetary Fund (IMF) Managing Director, Kristalina Georgieva.
Our technological infrastructure and initiatives to upskill our workers are key parts of how we plan to confront the disruptions and opportunities presented to us by this new and rapidly developing technology.
However, we must also recognise and act on an additional uncomfortable reality. Singapore is one of the most vulnerable economies to AI disruption. International estimates suggest that around 60% of workers in advanced economies are in jobs that are highly exposed to AI. For Singapore, that share seems significantly higher. Because we are a high-skill services-oriented hub, estimates from the IMF indicate that approximately 77% of our local workforce is highly exposed to AI disruption, and our transition is likely to be sharper and more acute than in many other economies.
How is AI fundamentally reconfiguring our labour market? This can be understood through three distinct shifts.
First, many existing jobs will be transformed from within. AI is taking, or has already taken, over routine information processing tasks – drafting, summarising, extracting data and standardising analysis. Managers, health professionals and legal professionals are already using AI tools to handle these types of tasks, freeing up time for judgement, complex problem-solving and human interaction.
Second, some jobs will be displaced. In what economists call high exposure, low complementarity roles, AI can perform most of the core tasks on its own and there are fewer reasons to keep humans in the loop. Clerical support workers and many business and administrative associate professionals, whose work is built around routine documentation, basic processing and standardised customer queries, face the highest risk that their roles will shrink or even disappear. Advances in agentic AI technology and models have only sharpened this impact. In the UK, some financial institutions, like investment banks, have relooked their hiring of fresh graduates for certain roles because of AI's automation capabilities.
Third, AI will also create new jobs and new demands. We are already seeing rising demand for AI engineers, data scientists and AI-product specialists, but also for data-savvy professionals across finance, healthcare, logistics and education. These new roles tend to offer higher wages, but only for workers who can supply the right mix of technical and complementary human skills.
Yes, indeed, the AI job transformation is already here and we are in the midst of a major disruption. Yet, the impact will not be uniform across all professions, nor is it, and will it, affect our society and economy evenly. For now, AI disruption is strongest amongst white-collared workers, especially entry-level roles. Unlike previous technological disruptions that have historically affected blue-collared jobs, AI today will most affect cognitive, white-collared roles – a call centre agent, an admin officer or a junior business support executive, whose workday is built around standard processes, routine reports and scripted responses, is in a role where AI can perform almost all core tasks.
In such high exposure, low complementarity white-collar roles, employers can consolidate positions, slow hiring or redesign jobs to ensure that fewer people are expected to do more with AI as a simple justification. If we do not address this, the benefits of AI will end up with only a small group of workers.
Research suggests that productivity and wealth gains could disproportionately accrue to those best positioned to leverage AI capabilities. One documented economic effect of high-skill job creation is increased local service demand. Studies from major tech hubs, including San Francisco, indicate that each high-end job is associated with the creation of approximately four jobs in local service sectors, such as retail and food services.
Even if such spillover effects generate more jobs, the quality and availability of these jobs for vulnerable workers is less certain to me. In Singapore, lower wage and routine-intensive roles are more likely to be held by vulnerable worker groups who may also face greater displacement risk from automation.
International institutions, including the IMF and World Bank, have noted that AI could exacerbate income inequality in the absence of policy intervention. The extent to which spillover effects from AI-driven growth would benefit lower-income workers remains uncertain. We need Singapore-specific research, modelling these distributional impacts and to make this data publicly available, to inform more targeted policy responses.
We must also remember that Singaporeans are already feeling the strain of rising property prices and higher cost for essential services. These pressures are real. They have been building for some time as we are a small, open economy, significantly dependent on capital inflows. Would AI's effects drive further unequal wealth accumulation? It is, therefore, a fair and pressing question to ask: could AI-driven economic activity inadvertently add to daily cost pressures?
Beyond broad economic pressures, we must turn toward the human face of this transition. As jobs continue to be reshaped and workers continue to be upskilled, we cannot leave behind those who face systemic barriers as our nation progresses towards an AI-ready future. Amongst them are persons with disabilities, women, lower-income Singaporeans, as well as young graduates.
AI can introduce new forms of discrimination against persons with disabilities. As AI algorithms are often trained via pattern recognition, they arrive at determinations based on common patterns within datasets. Thus, if skilled historical data is being used to train AI for, for example, recruitment processes, AI might reinforce this bias for job applications from persons with disabilities and any other group which historically, is not well represented in this space.
Female workers, too, face a heightened risk of marginalisation from AI. A 2024 IMF report on Singapore's labour market found that women are under-represented in AI-intensive science, technology, engineering and mathematics (STEM) roles, and among workers with AI engineering skills. Women in STEM held 29% of entry-level positions, 24.4% of managerial positions but only 12.12% of C-suite roles. Altogether, this means that they are less represented in what is regarded as the safe side of AI. They would thus be less well positioned to benefit where AI compliments high-skill work. Additionally, International Labour Organization data, released in March 2026, found that occupations dominated by women are nearly twice as likely to be exposed to GenAI risks compared with male-dominated ones, with even stronger differences presenting when looking at high automation risk.
Taken together, this creates a double disadvantage. Female workers are less likely to gain from AI's benefits, while remaining more vulnerable to displacement. In short, women face higher risk and have fewer opportunities.
For our young graduates, new uncertainty has been introduced by the way AI has been reshaping jobs. The erosion of entry-level jobs has presented a catch-22 dilemma for Generation Zs. While companies are still looking to hire professionals for experienced roles, young graduates have fewer opportunities to gain such experiences as jobs are absorbed by AI.
With more than 20% of graduates unable to secure full-time permanent roles in 2025, a nearly 5% increase from 2023, and over 60% of graduates claiming that the job search has become difficult, it is only natural that young graduates have become more anxious about landing full-time employment.
Adding to this is recent research, which has shown that simply being aware of AI's potential to augment or threaten one's job can increase burn-out, mainly by heightening job insecurity and emotional exhaustion amongst workers.
While AI is often associated with disruption to white-collar work, vulnerable workers and families face significant risks too.
Unequal access to AI tools and training could entrench existing disadvantages. Those without the resources of home or home environments conducive to learning new skills may find themselves falling further behind. If left unaddressed, then this risks hardening inequality across generations.
Measuring impact on Singapore beyond economic output, what does this all mean for Singapore? Just this past week, we have seen the launch of the Marriage and Parenthood Reset Work Group. What is the effect of AI advances on our birth rate? Economic insecurity has already been cited by young Singaporeans as a reason for delaying or foregoing parenthood, but the barriers go beyond finances. Job uncertainty erodes a sense of stability and confidence in the future, the feeling that one has a firm enough footing to build a family and put down roots. If AI-driven disruption deepens this broader sense of insecurity, we can reasonably expect further downward pressure on our already tragically low total fertility rate.
The Government has to be even more targeted in ensuring that all workers, regardless of their gender, age, occupation, income and accessibility needs, are fully prepared for the disruption caused by AI, to ease financial pressures on vulnerable workers who are made redundant. This will minimise the uncertainty and toll of unemployment on both workers and their families as AI displacement becomes more commonplace.
To ensure our policies are working, we need more public data for us to measure AI-driven disruptions on our labour market. For example, how we measure the success of our AI programmes.
Following up in response to my Parliamentary Question on 24 February this year, I noted that the AI apprenticeship programme is currently assessed through three primary indicators: one, the total number of practitioners trained; two, the percentage of AI Apprenticeship Programme graduates who took up AI engineering related roles, and; three, the completion and supervision of project quality. It is a good start, but they do not tell us the effects of AI programmes and disruptions on different groups of society. These measures focus on throughput rather than equity. We need data on wage trajectories, job quality and retention in AI roles two to three years after the programme is completed. We need more data.
First, the participant data profile should have more details made public. This can include previous occupations, income band before training, age, gender, education and disability status. This allows us to see where participants come from. High exposure, low complementarity roles, or already high complementarity roles. This will inform if vulnerable groups are even putting their feet through the door.
Next, more accurately measuring AI disruption in the wider labour market can come in the form of exposure complementarity mapping, thus understanding whether jobs are high exposure and low complementarity, and to establish a tuned framework to track displacement, wage changes and job quality across demographic groups. Such data gives the Government a clearer picture of how AI is affecting different communities, so that support can be directed where it is most needed.
I will now turn to some thoughts on how our youths can address the challenges of AI.
If AI displaces a significant share of entry level roles, young workers may find fewer opportunities to build the foundational experience traditionally needed to progress into senior positions. One of our nation's solutions could be to better encourage and support entrepreneurship amongst youths. This will allow them to also gain valuable skills independently, rather than wait to be picked up to be employed by an established firm.
This approach builds on an already open door. AI has greatly reduced barriers to starting a business by being deployed to build websites, analyse data, run marketing and even automate back-office tasks. We have many schemes for startups, such as grants and boot camps, but do these initiatives adequately provide sustained long-term support across the full lifecycle of a burgeoning firm?
Moreover, our grant architecture remains milestone heavy and programme bound, encouraging compliance over competition. We need a culture and framework that recognise the value of a failed startup, or that support founder-led networks over time. Drawing on lessons from other entrepreneurial hubs, what are the areas that have inhibited Singapore's ability to establish a more sustainable ecosystem conducive for entrepreneurs?
First, we must continue to build sustained informal networks that made an entrepreneurship culture self-sustaining. Our current networks are often programme based and time limited, skewed towards short-term coaching. Yet research shows that informal mentorships arising from mutual choice and affinity are far more effective than administrative matching. If mentorship is only linked to short-term grants, our youths may miss out on the benefits that accrue from the trust-based guidance that can be seen in, for example, Silicon Valley. In leading entrepreneurial hubs like Silicon Valley and Shenzhen, informal founder networks have been a critical but often overlooked driver of success. They enable knowledge sharing, supply chain connections and a spin-off of new ventures from anchor firms.
Singapore can gain much from this. While we have anchors like Grab and Block 71, the Asian Development Bank has noted that our ecosystem trails others because our collaboration remains policy-driven rather than organically clustered. How can we reduce administrative burden on founders to ensure that they do not become overly occupied with meeting grant milestones instead of establishing the market competitiveness they need to survive AI-driven disruption.
One possibility is to limit formal reporting to end of grant rather than more regularly to strike a balance. Singapore must also better leverage our anchor firms. Companies like Grab, Sea and Singtel hold deep reservoirs of technical expertise and industry networks that largely remain locked within the firm.
Could we use targeted tax credits or co-investment matching for peer development programmes to encourage anchor firms to run structured mentorship and spin-out programmes for early-stage founders? This will allow organic networks to form around existing reservoirs of excellence, rather than hope that Government grant cycles will do so.
The private sector must lead, and the Government's role should shift from convener and gatekeeper to catalyst. This is how we can start to grow our entrepreneurial system from within industry.
We must also learn to value failure. Singapore's culture of economic emphasis and social conformity makes us sometimes afraid to fail. A 2018 piece of study by the Organisation of Economic Cooperation and Development (OECD) found that Singapore students expressed a greater fear of failure than their peers compared with any other participating country. Yet entrepreneurship means being tolerant of failure. Founders have to make decisions with incomplete information and meaningful innovation has to be backed up by some freedom to fail. We have to treat failure as a stepping stone rather than a stigma, or we end up stifling the very ecosystem we are trying to build and leave our youths ill-equipped to flourish in an age of disruption.
We can do so by beginning our own transition towards a better space for entrepreneurship, encourage experimentation and normalise entrepreneurial failure as growth and experience.
Failure should be a stepping stone, not a dead end. And we began this transition within schools where we have to move away from perfect scores, where we have entrepreneurial projects in schools which expose students to the inner workings of a startup. We should also showcase failed projects for their bonus.
Singapore's current bankruptcy framework can also be re-examined to better support entrepreneurs. Currently, founders who fail face the same restrictions as any other bankrupt, with travel bans, director disqualification and no automatic discharge, regardless of whether their failure was the result of genuine risk-taking or financial misconduct. Could we explore a dedicated pathway for bona fide startup failure, one that allows founders to be discharged sooner, resume directorship more quickly and have their experience recognised as something valuable rather than a liability. It is not to make failure consequence free, but to ensure that the cost of an honest bet gone wrong does not permanently deter our most enterprising young Singaporeans from trying again.
Finally, it is also my hope that we use our experiences navigating the AI transition to play a regional and global role as other economies too attempt to navigate the disruption.
Singapore comes from a place of strength and we are already intentionally deciding to lead the way when it comes to setting the agenda in global AI governance. Our stewardship role must extend beyond frameworks, and we have to play our part in addressing global imbalances in AI development and use reflected in recent data. World Bank 2025 data show that high income countries account for 87% of notable AI models, 86% of AI startups and 91% of venture fund capital funding, despite representing just 17% of the global population. There is justifiable concern about how vulnerable groups and the global South are woefully underrepresented in the AI space. As responsible world citizens, we can do our part to address this.
Recently, we have already begun developing AI tools tailored to Southeast Asian languages through Project Sea Lion, recognising that much of the developing world risks being left behind by AI systems built on Western data. We should build on this by championing equitable AI access across the Association of Southeast Asian Nations (ASEAN), exporting our governance expertise to nations that lack the capacity to develop their own frameworks and ensuring that the rules governing AI reflect not just the interests of the powerful, but the needs of the many.
This is not merely an abstract foreign policy and ambition. It has direct consequences for jobs here at home. Singapore's standing in the global AI ecosystem, gives us leverage to shape how AI tools are built, deployed and adopted across the region. We should use that leverage intentionally. When our researchers —
Mr Speaker : Ms He, you have a minute left.
Ms He Ting Ru : When our researchers develop AI system that work across Southeast Asian languages, we create tools that can be deployed in our own service sectors, our hospitals, our schools. When our companies lead in AI adoption, we generate demand for new skills, new roles and new industries that our workers can be trained into.
We must ensure Singaporeans are in the room where these technologies are being built and not merely be on the receiving end of decisions made elsewhere. Our global AI leadership is ultimately an investment in ensuring that the answer is the former. This approach also ultimately has the added benefit of creating more jobs and opportunities for Singapore in what would be a true trickle-down effect. I support the Motion.
Mr Speaker : Mr Yip Hon Weng.
2.39 pm Mr Yip Hon Weng (Yio Chu Kang) : Mr Speaker, Sir, I declare I work in a global investment firm working on ecosystem workforce strategies.
In recent weeks, a plane has been circling San Francisco with a banner that reads, "Stop Hiring Humans." The same message appears on billboards and bus shelters across the city, alongside slogans such as "The Era of AI Employees Is Here." The campaign is the work of Artisan, an AI startup. This is not just a marketing stunt. It reflects a fear that the future of work may exclude people rather than empower them.
I rise in support of this Motion because that must not be Singapore’s approach. AI must not be a signal to workers that they are dispensable. In my work in Temasek, I have seen how technology disrupts industries, and I want to lay out my key thesis upfront. To achieve growth without casualties, enterprise AI adoption cannot just be about buying technology. It must follow a deliberate thread: we must first build AI fluency; use that fluency to drive workflow and job redesign; and ensure that this redesign leads to tangible, shared outcomes for our workers.
Let me begin with an important observation. In the Temasek ecosystem, many companies are already investing in AI. Tools are being deployed and pilots are multiplying. But the real constraint we are seeing is not technology, compute, or capital. It is workforce readiness. We are not short of technology. We are short of transformation.
In our AI Fluency workshops with over 20 Temasek portfolio companies, we see clearly that fragmented AI literacy remains a primary bottleneck. We are working closely with Chief Human Resource Officers and Chief Technology Officers to bridge the gap between adoption and actual value creation. Fundamentally, this is a skills-matching problem. Where skill supply lags, opportunity does not disappear. It simply moves elsewhere.
The AI transition we are debating is structural, global and accelerating. Tasks that took weeks now take hours, and soon minutes or seconds. Change no longer moves in a linear way, it moves exponentially. In this context, adoption is no longer optional. In Singapore, while large firms wrestle with legacy systems and heavy compliance, and SMEs face severe constraints in capital and bandwidth, the implication is the same for both: enterprises that do not adopt AI will struggle to remain competitive.
But if AI adoption is necessary, disruption is inevitable. We must be clear about the risks to workers if this transition is not managed carefully. On one hand, as AI lowers the cost of many tasks, demand for those tasks can expand rather than contract. Economists refer to this as the "Jevons employment effect", where efficiency leads not to less work, but to more work in new forms. We have seen this before. ATMs reduced routine tasks but expanded banking. Word processors increased output and shifted work to higher-value roles. AI will likely follow the same pattern.
But the practical reality often produces a K-shaped outcome. Experienced, AI-enabled workers capture disproportionate gains, while those without such capabilities, especially entry-level workers, risk falling behind. So, the question is not whether AI creates growth. It is who that growth accrues to. The real risk is not that AI replaces jobs. It is that it replaces opportunity at scale. A worker may remain employed but face slower progression and a quiet erosion of experience. Our task is not to deny disruption. Our task is to govern it.
Mr Speaker, Sir, if we are to govern this disruption effectively, the debate must shift. It is not enough to observe whether firms adopt AI. We must demand accountability for what happens after adoption. The question is simple. Are workers better off after transformation than before it? We must ask: are jobs and workflows being redesigned? Are gains being shared? If AI raises output but weakens livelihoods, that is not transformation. It is exclusion. We must ensure public funds do not subsidise this.
Hence, I ask the Government: can we establish clear conditionalities for our support schemes? If public grants are funding a company’s pivot, should it not be explicitly tied to a national, human-centric scorecard? A scorecard that tracks the number of net new roles created, the scale of workflow redesign, wage improvements, staff retention and upskilling. If we are serious about no jobless growth, our adoption metrics must move beyond counting jobs to measuring careers.
From our work in AI fluency in Temasek, we know companies are urgently asking for guidance in leadership capability, job redesign, measurement of outcomes, trust and governance. Companies cannot navigate this alone.
This is where our Labour Movement, NTUC, e2i and the unions come into play. We must empower them to provide this guidance, ensuring that union leaders and management sit at the same table, mapping out the enterprises' technology roadmap and the workers' retraining schedules simultaneously. If companies need guidance on job redesign and shared outcomes, our tripartite partners must be right there on the ground with them.
The recently announced Tripartite Jobs Council is a timely step, but it must actively bridge the gap between firm-level transformation and worker-level outcomes. Because the real challenge is not introducing AI into firms, it is integrating workers into that transformation.
This brings us to the central challenge of this transition: AI is not just a technology multiplier; it is a leadership multiplier.
Leaders must have real conviction in the transformational potential of AI and lead by example in using it, guiding its application and bringing their workforce along. AI can write, design and optimise. But it cannot exercise judgement, build trust or carry people through uncertainty. That responsibility remains human.
Mr Speaker, Sir, employers have a critical responsibility, but without the right leadership, the easiest way to adopt AI is to simply cut headcount. We are already seeing this tension play out globally. We have seen Amazon announcing 16,000 job cuts in early 2026 while leaning further into AI for corporate efficiency.
When AI is introduced mainly as a headcount strategy, it breeds fear. When introduced as a capability strategy, it builds trust. Stories of this fear have long played out in our workplace, even among AI-enabled workers.
When generative AI first started trending, some workers proactively explored AI on their own to improve their efficiency at work, but kept it a secret. They worry that if they reveal the source of their newfound productivity, they will eventually be made redundant or be loaded with more work without extra compensation. When trust is absent and gains are not shared, workers hide their capabilities rather than sharing them.
True transformation requires leaders to adopt a long-term perspective. Firms must expect short-term productivity lags as workers transition to new ways of working and they must create space for experimentation. However, we must acknowledge that many businesses struggling with high operating costs in this challenging economy do not have the luxury of time.
I ask the Ministry: how can we better support companies to absorb these short-term lags, ensuring that the cost of time required to retrain workers does not become an excuse for lay-offs?
Mr Speaker, Sir, as employers lead this transition, there is one structural shift we must recognise clearly – before job redesign can happen, we must have workflow redesign.
We ask workers to change, but we leave the system unchanged. AI cuts across functions and domains, reimagining how processes connect and how value is created. That reshaping of the entire process must come before individual roles themselves are redesigned.
However, here lies a significant gap in our current policy approach. Today, much of our national support is heavily focused on individual job redesign. We ask workers to adapt to new job scopes, but legacy company processes are left unchanged.
As a result, AI is often layered onto outdated workflows with silos and fragmented data. Productivity stalls and frustration rises. Workers resist change not because they are stubborn but because it is deeply frustrating to use advanced AI tools within broken workflows.
So, I ask the Government and our tripartite partners: can we expand our support schemes to explicitly look into workflow redesign? How can we provide enterprises with the expertise and funding to reimagine their cross-functional processes first? If we fix the workflow, workers will naturally see the value of the technology, turning inertia into eagerness to adapt.
Mr Speaker, Sir, even with the best workflows, disruption will occur. Some workers will be displaced and some roles will change faster than expected. We often point to existing measures like SkillsFuture and career conversion programmes. But here is a hard truth – if these measures are sufficient, why are our workers still so deeply anxious?
The answer is that AI disruption moves at an unprecedented speed and workers worry our safety nets cannot catch them fast enough.
I ask the Government: how are we rigorously tracking the speed and effectiveness of our existing measures, particularly the financial runway for displaced workers, to guarantee that they remain truly responsive?
For the workers who remain, basic AI capability will no longer be a distinct advantage. It will be the price of staying in the game. The task is to help workers transition from being mere AI users to becoming AI conductors, workers who know how to curate, steer and verify AI outputs.
This brings me to a critical concern regarding our workforce pipeline. If AI automates drafting, summarising and first-pass analysis, what happens to our entry-level jobs? If young graduates cannot get a real first job and the mentorship they need, they will never gain the foundational experience earlier cohorts relied on to grow and we risk losing our future workforce.
I ask the Government: how are we working with employers and industry leaders to protect and redesign entry-level pathways so that our youth can develop the professional judgment required to become the AI conductors of tomorrow?
In conclusion, Mr Speaker, Sir, let me return to where I began. In the Temasek ecosystem, we see companies investing in AI, piloting new tools and pushing forward with transformation. But the decisive constraint is not the technology. It is whether the workforce is ready.
I shared this story with chief technology officers across our Temasek companies. A factory invested heavily in new machines. They were faster, smarter and more efficient. But productivity fell, not because the technology failed, but because the people were left behind.
On another line, the company did something different. Instead of replacing workers, they retrained them. Machine operators became data readers. Technicians became problem solvers. What changed was not the equipment. It was the capability and confidence of the people using it. Soon, breakdowns fell. Ideas came from the shop floor. Workers who once feared change began to lead it. The same machines. The same factory. But a very different future.
That is the lesson. Technology may set the pace. But people determine the direction. And in an AI transition, fluency, not just adoption, determines whether that direction is inclusive.
That brings us to the Motion before us. An AI transition with no jobless growth is not just about creating jobs. It is about ensuring that workers advance with technology, not fall behind it. It is about translating productivity into progression. It is about turning innovation into shared outcomes.
If adoption builds capability, then fluency must build advantage. If work is redesigned, then skills must be deepened. If growth is created, then it must be broadly shared.
But this will not happen on its own. It requires coordination. It requires leadership. It requires trust. And this is where Singapore has a unique advantage. Our model of tripartism, where Government, employers and workers move together, gives us the ability not just to react to change, but to shape it. This is our secret weapon.
When firms invest, workers must be equipped. When jobs are redesigned, workers must be involved. When disruption occurs, support must be credible. Because this is not just a technology transition, it is a workforce transition. The establishment of the Tripartite Jobs Council is an important step in ensuring that this alignment happens in practice.
Technology will move. Markets will adapt. But we must be clear about the future we are building. It cannot be one that says, "Stop having humans". It must be one that says, "Invest in people". Whether our workers advance is a choice we must make together, deliberately and decisively. Thank you, and I support the Motion. [ Applause. ]
Mr Speaker : Assoc Prof Jamus Lim.
2.54 pm Assoc Prof Jamus Jerome Lim (Sengkang) : Mr Speaker, my contribution in today's debate is straightforward. I argue that if our objective is to protect our workforce from job losses that could result from an economy-wide embrace of AI, then our efforts today should mainly be directed towards policies that promote new hiring rather than those that focus either on reducing displacement or pushing for retraining.
The explanation is simple. The evidence shows that to date, job displacement of current workers due to AI has been modest and localised whereas the hiring slowdown of new workers is already evident and even likely to accelerate.
In principle, the consequences of AI could bite on two ends of the labour market. It could reduce the incentives for firms to hire, thereby lowering the number of total new job openings, or it could raise the frequency of hiring by companies or induce workers to quit.
Hiring slowdown results when AI tools allow a company to cheaply and effectively replace job functions that they previously needed to hire a human worker for. This is especially the case for entry level since the lack of experience among new graduates and the relatively straightforward grunt work new hires are generally tasked to do make this group somewhat less valuable and more replaceable by a machine.
But as many observers, including Members of this House, have already pointed out, this is a chicken and egg problem. If we do not absorb new workers into our corporations, we surely cannot expect them to gain the necessary experience and job-specific skills that make them valuable as mid-career professionals.
Job displacement occurs, in contrast, when AI tools reveal that certain roles are no longer needed as they can be well replicated by AI. Tasks that used to be done by a human are replaced and if there is nowhere else in the firm for this person to be reassigned to or if the individual turns out to be too costly, then they are let go.
On the positive side, AI could open up new opportunities for displaced workers to pursue a career elsewhere, either because they gain AI-related skills that make them more valuable in the marketplace or because perhaps they could go into business for themselves.
For now, however, the message from studies worldwide is clear. While there has been little evidence of displacement thus far, there are more ample signs that there has been a decline in hiring. This has been the case for AI-exposed sectors following the advent of generative AI such as ChatGPT and is likely to accelerate as agentic AI matures. Prospects are especially perilous for early-career, entry-level workers. And even when hired, such workers tend to receive lower salaries.
The reasons for this are intuitive. AI mainly substitutes for mechanical, repeatable and well-defined tasks, which are mostly performed by junior employees. Firms still value the maturity and experience of senior employees and, by and large, would rather skimp on hiring and re-allocate their otherwise loyal staff rather than giving them the boot.
Sir, these trends are also visible in our local labour markets. Thus far, AI is yet to contribute much to job displacement here. MOM's latest labour market report reveals that since 2023, overall retrenchments have remained stable and the unemployment rate of about 2% has not budged much since 2022.
In response to questions about the PMET sector, Senior Parliamentary Secretary for Manpower Shawn Huang also pointed out that retrenchments among PMETs in AI-exposed sectors such as finance and infocomm remain low, numbering only 960 in the final quarter of last year. Moreover, Senior Parliamentary Secretary Huang also pointed to the large number of vacancies – around 10 times higher – in these sectors over the same period. This could be interpreted as a healthy robust labour market for new hires, but I will caution against it. This is because as any jobseeker will tell you – an opening does not a job make. These jobs have to be filled, ideally by Singaporeans who are themselves looking for jobs.
Here is where the picture is less encouraging. The latest graduate employment survey shows a drop in the share of graduates that managed to land a job in almost every single field of study, with around one in every four graduates unable to secure full-time employment.
In response to a Parliamentary Question filed, Minister Desmond Lee pointed to how the decline was due to a post-pandemic hiring surge and that what we are seeing is simply a mean reversion to the early trend.
I am less sanguine. Based on my calculations, what is true that pre-pandemic and permanent employment among graduates averaged around 70% in 2020, it was closer to 85% as recently as a decade ago, which is significantly better.
The youth unemployment rate which is lower in the 2020s then it was in the prior two decades has admittedly, elsewhere in the world, also steadily inched up since 2022, by around a percentage point. And unlike earlier instances when uptakes followed an economic cycle, Singapore's economy is actually currently in expansion.
On the demand side there has also been reports that some employers have been tentative and reluctant to onboard workers, albeit these thankfully appear to be a minority for now. Moreover, this pessimistic picture also mass more troubling pathologies. Many Singaporean workers may have had to contend themselves with opportunities that do not fully employ their skills and talent. Such mismatches are not well captured by the aggregate data.
Think of the graduate with an advanced degree from a local university but nevertheless still felt compelled to work in food delivery, or the student who spent years at a top university abroad but has been repeatedly rejected by employers since coming home. Or the experienced mid-career professional with bills and a young family to support, who floundered unsuccessfully in the job market month after month despite upskilling as advised. I believe others in this House will have seen cases similar to these in our weekly Meet-the-People Sessions. And indeed, two recent studies published by NTUC and MOM, corroborate these examples.
Overqualification is the greatest for those who are early in their careers and the gap between the involuntary and voluntarily underemployed is greatest for those under 30. Coupled with the global climate of economic policy uncertainty, we may be heading toward an era of the so-called "great hesitation" in hiring in our local labour markets, similar to what has been observed elsewhere in the world.
If our goal is, as the title of the Motion suggests, to avoid jobless growth, then it follows that we should prioritise policies that target the hiring of the labour market. Let me offer a few.
First, we can improve the incentives for companies to hire fresh graduates. As I have shared in the long cut for this year's Committee of Supply, this would call for expanding the existing GRaduate Industry Traineeships (GRIT) programme to a national level, cross-sectoral national internship initiative. Young workers will be free to apply their SkillsFuture credits toward paid apprenticeship and internship programmes with companies willing to take them on.
Corporations, especially SMEs, should also be able to submit credible proposals for in-house, on-the-job training to MOM, which will then offset the cost of taking on these trainees, drawing on the SkillsFuture enterprise credit and other subsidy schemes already earmarked for businesses. My hon friend, Gerald Giam, has also proposed an AI mastery fund for this purpose, which is complementary to what I am suggesting here.
Second, such short term, by which I mean six months to a year, apprenticeships and internships should also embed a clear employment pathway, conditional on reasonable performance on the part of the employee, unless a waiver is granted to employers due to changed economic circumstances.
These trainees should be treated as employees under the Employment Act and receive the same legal protections and entitlements, including a minimum period of annual leave, which GRIT trainees currently do not receive.
Third, we can ramp up the delivery of social skills training in communication, empathy, judgement, networking and vision in the final year of their tertiary education prior to workforce entry. Research has shown that AI is the most complementary to workers when the job demands require the fulfilment of not only cognitive tasks, but also in iterative collaboration between humans and AI. But our graduates often load their school time with the pursuit of academic competencies, leaving them woefully under prepared for such interfacing functions.
Fourth, if indeed we stand by our belief that we want our graduates to focus on acquiring competencies rather than certifications, as MOE has made clear in its support for stackable, micro-credentials pathways in our autonomous universities and as corroborated by recent research, then we should put our money where our mouth is and end hiring requirements that insist on a diploma or degree in the public sector if the competency can be demonstrated, otherwise. This can occur with proof of skills via a series of micro credentials, or when candidates pass a live demonstration during the interview stage.
Sir, AI is a general-purpose technology. Like all general-purpose technologies before it, AI will destroy perhaps as many jobs as it creates, but as we confront the bleeding edge of this transition, we must set the stage for those who are most affected by the roll-out, which, for now, at least are clearly our young entry level workers. We need targeted policies that will help sidestep the great hesitation in hiring them. This is how we best ensure that the growth promises of AI are not overshadowed by fears of millions of missing jobs.
Mr Speaker : Dr Neo Kok Beng.
3.06 pm Dr Neo Kok Beng (Nominated Member) : Mr Speaker, Sir, I used to be a visiting professor of innovation policy at Harvard Kennedy School for 10 years and currently I am still a visiting professor of innovation management at Fudan University.
AI is what we really call disruptive technologies, of which I spent my doctorate on. It is paradigm shift and when you say paradigm shift means it is shifting from one, or completely one industry to other areas that actually will destroy the old ways of working.
Let me just give you an example. Last week, I visited at AI startup in the Science Park, so we were talking about collaborations on a couple of projects in media, and I only saw two persons in the room with a capacity of 20 persons. So, I asked the chief executive officer, "Where are all the staff?" They say, well, they never come to the office, but they are working. And I say, "When do you see them?" They say, "Well, I saw them last week when the network went down and there were no communications. As the broadband was down, they came back to check on their agents to see are they really working?" So, I asked, "How would you know they are really working?" The answer, "Well, actually, they produce the code at any time, all the way, 24/7." So, he has got agents, they are working 24/7. So, I said, "How do you measure the productivity?" And I asked one question, "How many tasks or jobs have you replaced since, or how many jobs have you done, the capabilities of people doing the engineers or the coding jobs, since last year, one year ago?" And the answer that came back is five. So, compared with last year and this year, this guy has agents working for him and he performed the task of five persons.
We can look at it from two angles: one is this company is supremely productive; the other thing to look at is, we have five jobs less.
Which one would you choose? Well, if you are the CEO, you know what to choose. If you are the NTUC Secretary-General, I am not so sure.
So, I asked the next questions. He happened to be interviewing potential staff for his expansion, and so I ask him, "How do you find this guy who is doing his Masters in computing? Is he up to par?" And the answer that came back is, "Well, based on what I discussed with him and his answer shows he is two years behind the current technology".
Two years behind and I was like, wow, so when this guy graduates, maybe next year, what is going to happen to him? Technology is always two years in front of him.
And therefore, that means, do we put this guy into the real environment, which is basically internship, on-the-job attachments, or this person when he graduates, he really needs to speed up on the current competencies where the AI technologies are moving so fast. So, really, this is a tsunami.
Personally, I get myself involved in the small little non-governmental organisations. We are working on one pet project, which is to monitor the senior citizens who are staying alone, so that if anything happens to them, we know. And we actually are using AI, because most of these senior citizens speak dialect dialects, so we are using robot companions, small ones, with the ability to understand dialects; and to monitor them. It is very good, because it is very difficult to get caregivers to go around monitoring and visiting these people.
So that is one thing that the AI is really, really useful for. The robotics AIs are really useful so that we can cover things that Singaporeans do not want or are probably not so suitable to do the job.
The other projects that I am working on is imaging, using AI for magnetic resonance imaging. We will talk about it in some other time.
The issue is that the workplace experience is now changing quite a bit. So, do we, or our staff, or our existing people, or PMEs, or workers have the skills for them to carry on in the job. I am glad actually that the Labour Movement has introduced the CTCs. It is a very good mechanism to bring AI into the workplace or working with the enterprise. And I am glad that there are such grants for it.
But the question then is how do we define competencies? Some Members talked about the workflow redesign, process redesign – but how do we know that at the end they are competent? Where are the competencies level at the workplace? So, I think the new agency, SWDA, should be able to work together with the Labour Movement to define the competencies.
But what else can we do with these competencies? Is it fixed to workplaces; so, one workplace, one company? Or is it portable?
So, maybe we can consider involving the professional institutions, so that for each level or each competency level, whether it is stackable, micro-credentials, they are all certified and recognised by the industry. And therefore, it is portable for this person throughout his careers.
AI is here to stay. Like most workers, initially, I was, I would not say sceptical, but unwilling to change my style. But now, I think I have got no choice. So, for the past one year, I have been working on it. Even my wife has to use AI to generate videos and pictures, although she is an artist, she likes to draw – but it has become part of her life.
It is a tsunami of change and I support the Motion. As I have previously done in my previous voluntary life as a council member of Institutions of Engineer, Singapore, I am the one who actually proposed working with the Labour Movement to set up the Young Engineers Leadership Programme, including the advanced and the global. I believe that the engineering institutions and the professional institutions could work with the labour unions to certify all such programmes for career pathways for the workers.
Mr Speaker : Ms Eileen Chong.
3.15 pm Ms Eileen Chong Pei Shan (Non-Constituency Member) : Thank you, Mr Speaker. In Mandarin, please.
( In Mandarin ) : [ Please refer to Vernacular Speech .] Mr Speaker, I agree with many of the points raised in the Motion, including the commitment to ensure that no worker is left behind during the AI transition.
However, to realise this vision, we also need to share the gains from adopting AI and ensure that future workers can continue to remain competitive and stay ahead of the curve. At present, when technology is adopted to improve productivity, it is often the employer who benefits. I propose upgrading the Flexible Work Arrangement Guidelines so they are given legislative force, which ensures that employees too, can enjoy AI productivity gains.
When AI improves productivity and work efficiency, we should encourage workers to use the time freed up to be with their families, to rest, to participate in activities and to build relationships with others.
Additionally, the workers of tomorrow – who are the children in our schools today – are also already beginning to encounter AI in the classrooms. Some parents have raised concerns about whether introducing AI to children at Primary 4 might be too early. Neuroscientists have also pointed out that premature or excessive use of AI and technology may make learning too easy, thereby depriving children of the opportunity to develop deep learning capabilities.
Children in their formative years should be learning how to think, ask questions and making judgements. I therefore call on the Government to track and regularly report on the impact that AI adoption in our schools has on the cognitive development of students across different age groups.
In the AI era, independent thinking and judgement are the very skills that AI cannot replace. These are what we should be imparting to the next generation so that they remain competitive and resilient, no matter how the world changes.
( In English ): Mr Speaker, I share the values outlined in the Motion: that growth must be inclusive, that every worker matters and that no one should be left behind in the AI transition. Ensuring that no one is left behind involves more than just ensuring job full growth. It requires a commitment to sharing the rewards of AI driven productivity. It also requires that we ensure that future generations of workers can thrive in an era defined by AI and possibly other technologies have that have not yet been invented.
Mr Speaker, much of the discourse about AI-driven economic transition has been focused on the need for workers to upskill and remain relevant. While these efforts are essential, they do not answer another equally important question: how do we ensure that the equitable distribution of the AI productivity dividend?
Presently, employers are the default beneficiaries. They benefit from either more output from the same headcount or the same output from a lower headcount. Such productivity gains do not automatically become employee gains. Without deliberate policy design, they tend to remain exclusively employer gains.
One way to share the AI productivity dividend with workers could be through time. During the MOM Committee of Supply debate in March, I made a case for flexible work arrangements to be given legislative force. The right to request flexible work is not the same as the right to have it. We should not rely on guidelines that place the burden of action on the employee who can least afford to do so.
I would like to reiterate the call for flexible work legislation today. It has become more salient as we discuss how the AI transition can benefit Singaporeans. As AI generates real productivity gains, the question of whether Singaporean workers will share in these gains as time regained, not just as higher output, is one which the market will not answer on its own. It must be designed for.
What does more time mean in practice? It means the parents who can be present and do more than just paying for tuition classes. It means fewer caregivers having to choose between a job and a family member who needs them. It also means rest, real rest, in a country where 61% of employees feel exhausted and 39% of workers dread going to work. These are not soft outcomes. There are conditions under which human capabilities are replenished and sustained.
Will the Government and tripartite movement commit to prioritising worker well-being alongside employer gains and economic growth as it shapes AI era policy? If so, I urge the Government to begin by giving legislative teeth to flexible work arrangements.
As AI makes company more productive, workers should have a meaningful and enforceable claim on the time that AI frees up. Time to rest and to pursue the kind of human connection that AI cannot replicate, and that our fertility rate is telling us we are running short of.
Mr Speaker, I now want to turn to a group of Singaporeans who matter most to our long-term success. If we say that every worker matters, then we must look at the workers who are not yet in the workforce. And I am talking about our children who are in today's classrooms and some of them in the galleries above.
Right now, our 10-year-olds in Primary 4 are being introduced to AI tools. While there is, of course, teacher supervision and guardrails in place, we should also be asking a more fundamental question. Is this early exposure building their capability and ability to thrive in an AI world, or is it building an early dependence on AI-powered tools? Some parents are already asking. Is Primary 4 too early? What are the real gains? And more importantly, what are the trade-offs?
These are not just parental anxieties. There are also serious questions being asked by neuroscientists. In his book, "The Digital Delusion", neuroscientist Dr Jared Horvath makes a point that should give us pause. When technology makes thinking too easy, the depth of learning disappears. AI is the ultimate offloading tool. It reads, writes and calculates with minimal user input. But our children are not yet experts looking to offload and increase productivity. They are learners and learning requires struggle. It requires the cognitive friction that AI is designed to remove.
If our children start to offload their thinking at age 10, they do not develop the mental muscles needed to spot errors, ask meaningful questions, or form independent views. What we call AI-enabled personalised learning, then risks becoming customised comfort. It feels like progress because it is frictionless, but it may be short circuiting the cognitive development we are trying to support.
This brings me to a concern that I raised earlier today: the equity paradox in AI use. I appreciate Minister Desmond Lee's point about how MOE actively engages parents through Parents Gateway and share guidance on how they can better support their children at home. But not every child in Singapore has a parent at home who is digitally engaged, has the time to act on that guidance and is equipped to scaffold their children's learning beyond what happens in a classroom. Children from less privileged backgrounds with less access to parental guidance and fewer non-screen enrichment activities may end up leaning on AI more heavily, and not less.
For a child who comes home to an overstretched household where there is no one to redirect, question or supervise, AI will always produce an answer, always reduce the friction and always make the thinking easier. That is not empowerment. If AI dependency erodes cognitive development that it is meant to supplement, then the children most at risk are the ones that we are trying our hardest to support.
Mr Speaker, my colleague Assoc Prof Jamus Lim noted during the recent Budget debate that the gap between stronger and weaker university students is no longer about what they submit in written assignment, but about their willingness to question and think beyond the script. These abilities are built or not built over years. If we displace that effort at age 10, our children cannot simply download it at university. And if the children who are doing the most unsupervised AI offloading are those who already have less of these abilities, then we are not closing the gap. We are widening it – earlier.
A global study published this January by the Brookings Institution found that the biggest risk of AI in education is the displacement of effortful thinking during crucial development years. Interestingly, 65% of the students surveyed in this study cited the undermining of cognitive development as the top risk of the use of AI. The children themselves can feel the difference.
Mr Speaker, I am not suggesting that we do not use AI tools in school. I am suggesting that we follow the evidence, not the hype. Generative AI has been public for barely four years. We do not yet have long-term data on how it affects a child's brain. We should not let the speed of a technology cycle outpace the care that our children deserve.
I also appreciate the Minister's update this morning that the Singapore Longitudinal Early Development Study (SG LEADS) by A*STAR will expand to collect data that will help us understand Singapore children's AI usage patterns and how AI usage affects their learning and well-being outcomes. I hope this will also include the impact of using AI tools in education on our children's cognitive development, including their effect on their executive function and skills like critical thinking, reading comprehension and capacity for sustained independent effort. We must ensure that we are preparing our children for a world we cannot predict by giving them the one tool that will always be relevant: a strong and independent mind.
This Motion rightly calls for Singapore's approach to AI enabled growth to be anchored in fairness, resilience and opportunity for all. I agree. And this is why I spoke today about two critical things that the AI transition is challenging us to protect: time and mind.
For the workers of today, we should legislate the right to flexible work so that productivity gains are reclaimed as time for rest, care and connection. And for our children, the workers of the future, we must protect the cognitive friction necessary for learning, ensuring that we are cultivating independent minds that can solve a hard problem without reaching for a digital crutch. The AI transition is not just an economic event. It is perhaps the most significant opportunity in a generation for us to ask what kind of society we will build with the time and capability that technology returns to us. Mr Speaker, I support the Motion.
Mr Speaker : Mr Vikram Nair.
3.26 pm Mr Vikram Nair (Sembawang) : Mr Speaker, I support this Motion. AI is already reshaping our economy. It is improving productivity, enabling new business models and strengthening our global competitiveness. For Singapore, this is an important opportunity. But alongside these benefits, there is also a real concern – how do we ensure our workers are not displaced faster than they can adapt?
Over the course of human history, economic growth has been corelated with the creation of new jobs. When countries moved through industrialisation for example, as industries opened, new jobs were created for people all around. Of course, economic growth can also come not just from increases in labour, but also increases in productivity. And this is also to be welcome because it creates higher paying jobs for those who are working. Singapore has benefited from both of these trends.
Against this backdrop, the conceptual concern with AI is a simple one: will it increase productivity so much that significantly fewer jobs will be needed? The implication for this is that the fewer people who have jobs or alternatively, those that control capital, will get all the benefits from the higher productivity while a large group of people will lose jobs. Essentially, the winners will take a lot more and there will be a larger number of losers.
If we look at developments in other countries, we see that governments are beginning to respond. They do so not by stopping technological change, but by introducing measured safeguards to ensure that workers are treated fairly as the adoption of AI increases.
One area I wish to discuss is the use of AI in the job selection process itself. For instance, in the European Union, the recently adopted Artificial Intelligence Act recognises that AI systems used in employment, such as those involved in hiring, evaluation and performance monitoring, can significantly affect workers' livelihoods. These systems are therefore classified as "high risk" and are subject to requirements such as bias testing, transparency disclosures and human oversight.
This complements Article 22 of the General Data Protection Regulation, under which individuals have the right not to be subject to decisions based solely on automated processing where such decisions produce legal effects concerning him or her or significantly affect him or her. In an employment context, this means that important decisions, such as hiring or dismissal, cannot be made purely by algorithms without meaningful human involvement.
In New York City, the Automated Employment Decision Tools Law requires that AI systems used in hiring or promotion undergo regular bias audits and that applicants are informed when such tools are being used.
While these are not laws which directly prevent job loss, they do ensure that decisions affecting employment are not made with reliance on AI in an opaque or unaccountable manner. They also promote fairness and help guard against unintended discrimination in automated decision-making.
Meanwhile, in countries such as Germany and France, labour laws require employers to follow structured processes before lay-offs, including consulting employee representatives, providing advance notice, and making efforts to retrain or redeploy workers. Our NTUC is engaged in similar activities with our employers here. These requirements may not be specific to AI, but they help ensure that transitions are managed in a structured and responsible manner.
Mr Speaker, these examples suggest that instead of blocking technological change, governments recognise that legislation can provide guardrails and ensure that as companies adopt AI, they do so in a way which takes into account the impact on workers. This is particularly important in maintaining trust between employers and workers. If workers feel that decisions are being made transparently and with safeguards in place, they are more likely to support rather than resist the adoption of new technologies.
For Singapore, we can consider whether there should be clearer expectations around human oversight in employment decisions involving AI. While many employers already adopt such practices, formalising this principle can help ensure consistency across sectors. We can also explore whether workers should have a clearer right to transparency, including the right to know when AI systems are being used to assess their performance or influence decisions about their employment.
In addition, it is worth considering whether we should strengthen expectations around responsible workforce transitions. When major technological changes significantly affect jobs, employers can be encouraged to provide structured support such as retraining opportunities or redeployment pathways.
Ultimately, it is important to recognise that legislation alone is insufficient and must be complemented by strong institutions, proactive employers and workers who are willing to adapt and learn. Our goal should be to maintain a system where businesses remain innovative and competitive, workers feel secure and supported, and opportunities continuing to expand over time.
This leads me to my second point – what we can do for jobs which are most likely to be affected by AI. AI is particularly effective at performing routine and rules-based tasks. As a result, roles in areas such as administrative work and those involving entry-level analysis are more exposed to displacement.
However, the issue is not simply that these jobs may disappear. More importantly, these roles often serve as entry points into the workforce, providing workers with the experience and skills needed to progress. If such opportunities are reduced, workers may find it harder to build careers over time.
In this sense, the risk is not only displacement, but also the gradual erosion of career pathways. Over time, this could lead to a situation where it becomes increasingly difficult for individuals to move from entry-level positions into more skilled and higher-paying roles.
Therefore, beyond retraining in a general sense, our focus should also be on facilitating practical transitions. Workers should be supported in moving into adjacent roles where their existing skills can still be applied and built upon. This makes transitions more feasible, particularly for mid-career workers.
At the same time, companies can be encouraged to redesign jobs so that AI complements rather than replaces human workers. For example, while routine tasks can be automated, human roles requiring judgement, communication and problem-solving can and should be retained and enhanced. This way, AI becomes a tool which increases productivity rather than a substitute for labour.
In practical terms, employers adopting AI can be encouraged to identify adjacent roles for affected workers early on and to provide structured pathways for redeployment into these roles. This may include short, focused training modules or job redesign which allow workers to gradually build new competencies.
Such measures help ensure that workers are not abruptly displaced, but are instead guided through a managed transition where their skills and roles within their organisations are preserved. The unions, the Government and employers can work together on a framework for this.
In relation to the creative industries, including music, writing and acting, we should consider if legislation or further protection is needed in relation to copyrighted material being used to train AI and whether remedies for this should be purely private or whether there is scope for the Government to provide a framework for such materials to be protected. This may include the right to one's image and voice. If left purely to private law, only the well resourced would be able to take up the matter, whereas if there is a framework for this, individual artistes, writers and others might be able to benefit from such protection.
Singapore has navigated many economic transitions successfully over the years. Each time, we have combined openness to change with a commitment to social mobility and shared progress.
The transition to an AI-driven economy will be another such test. It will require us to strike a careful balance between innovation and protection. If we approach this thoughtfully, we can ensure that AI becomes a source of opportunity and that growth remains inclusive. I support this Motion.
Mr Speaker : Mr Fadli Fawzi.
3.35 pm Mr Fadli Fawzi (Aljunied) : Mr Speaker, today's Motion rightly recognises the transformative power of AI and affirms that AI-enabled economic growth must remain inclusive.
My speech consists of three broad points. First, we must protect the economic positions of workers and prevent the economic fruits of AI from accruing solely to those who own the AI models or produce the hardware powering AI. Second, we must ensure that AI-resilient employment pathways remain viable for Singaporeans. Third and most importantly, we must hold firm to the idea that technology should serve humanity and not the other way around, because ultimately, the goal is not just growth without joblessness. It is growth without losing who we are as humans and as Singaporeans.
Sir, the second limb of the Motion statement calls upon the House to emphasise that Singapore's approach to AI-enabled growth must be anchored in fairness, resilience and opportunity for all, while the fourth limb asks the House to affirm that economic progress must remain inclusive and that Singapore must not have jobless growth.
These are extremely important goals, because if the rise of AI is not managed properly, it could represent not just technological disruption but a recalibration of power between labour and capital. For example, last month, Meta announced that the keystrokes and workflows of every one of its employees in the US will be recorded. Screenshots will be taken occasionally throughout the workday. All this data will form datasets used to train AI systems that could one day replace these employees. Other companies could follow suit soon.
While this is being done in the US, we in Singapore should ask whether companies such as Meta should be allowed to harvest employee data in this way without any clear safeguards. Should there not be stronger protections about how such data is collected and used? Should workers not have a stake in the value that is created in their own data?
If we fail to address these questions, we risk sleepwalking into a future where wealth and power are concentrated in the hands of a few technology giants who increasingly use AI to take over work previously done by their human employees. These firms will continue to be the engine of economic growth, investing in larger and larger data centres and more powerful semiconductor chips that continue to generate gross domestic product growth.
As a country, Singapore may benefit through our shareholdings in and partnerships with these tech companies. However, we must ensure that these benefits, which primarily accrue to the capital owners, do not come at the expense of the labour force. These developments pose a real risk that workers who are replaced may see their economic power steadily eroded, with a larger number of workers having to chase after a smaller pool of lower-paying jobs.
I do not mean to be alarmist in suggesting that if unchecked, what could emerge is a form of digital serfdom, a system where workers like serfs of old are not bound by land or feudal lords but by algorithms. We are already seeing the beginnings of this future play out in real time. Already, platform workers work in service to black box algorithms that have a great deal of control over their earnings and how many hours they work. As AI advances, many cognitive and white-collar jobs will become increasingly automated and possibly, under the control of algorithms. Roles once considered secure may no longer be so.
As such, we need to strengthen frameworks for worker protection in areas such as retention benefits and the rights of workers over data they create at the workplace. AI-enabled growth must not come at the cost of workers and a further tilting of the balance of economic power towards capital owners.
Sir, the third limb of the Motion asks the House to equip and support workers and enterprises to seize new opportunities and advance together. Even as AI threatens to automate and replacement many existing roles, there remain many forms of labour that are difficult to automate using AI.
For example, plumbers, electricians, air-conditioning technicians, phlebotomists and other skilled trades have been assessed to be much less likely to be replaced by AI. These jobs are essential pillars of a functioning society. Yet for too long, we in Singapore have undervalued these roles, both economically and socially. If we are serious about ensuring that growth remains inclusive, we must correct this imbalance. In many other first world societies, the job of a plumber, garbage collector or an air-conditioning technician pay high enough to allow a middle-class lifestyle. This is not the case in Singapore.
We have made a policy choice to fill these roles with lower-paid foreign workers while our local workers are channelled into high-paying white-collar jobs. While this has worked well for us for decades, this may no longer be sustainable as generative AI threatens to reduce the number of well-paying white-collar cognitive roles.
We must therefore raise wages and improve career pathways in blue-collar sectors that are currently less attractive and yet also less vulnerable to displacement by AI. We must elevate their status not just through policy, but through culture and education so that Singaporeans will no longer see such jobs as undesirable.
This may require difficult trade-offs. For example, should we recalibrate our policies in certain sectors to ensure that wages for local skilled trades rise meaningfully and attract more Singaporeans to fill these roles? At the same time, we must make better use of our strong vocational institutions. Our ITEs and polytechnics should guide more students towards specialised high-value trades. In an AI-driven future, the dignity of work must not be tied solely to whether a job is white-collar or high tech. We must expand the range of jobs that Singaporeans considered attractive and meaningful.
Mr Speaker, AI will undeniably determine the future of our economy, our society and our lives. But we should not allow AI to come to define us as humans, as citizens and as Singaporeans. I say this because the question before us is not merely whether AI will create or destroy jobs. The deeper question is this: what kind of society and what kind of human beings will we become in an age shaped by AI? Because Sir, if we are not careful, we may succeed economically, yet diminish ourselves in more fundamental ways.
For example, AI has created a world where knowledge is no longer scarce. Texts can be summarised, essays can be written and equations can be solved in seconds. I spoke before about my own experience as an undergraduate struggling through dense text. It was slow, often frustrating work, but it was through that struggle that I learned how to think, how to question and how to make sense of the world.
Today, however, the effort required to complete any cognitive activity has collapsed to an extent far greater than when the calculator replaced the abacus or the typewriter replaced the pen. In encouraging our students to leverage AI, how can we ensure that they can continue to learn how to grapple with ideas, how to formulate arguments, how to problem solve and how to cultivate intellectual independence?
Sir, I reiterate my caution – that Singapore must become an AI-resilient society and not an AI-reliant one. By constantly outsourcing our tasks to AI, we may erode or undermine our capacity for creativity, imagination, judgement and even empathy, or let these practical skills atrophy from lack of use.
The danger here is the temptation to use AI as a shortcut for thinking through and solving problems. On the one end, there are those who regard AI as a kind of second brain – outsourcing memory, decision-making and even aspects of judgement to ChatGPT or Claude.
It is true that AI tools can sharpen our thinking and serve as intellectual aids. However, in creating a layer of artificial mediation between us and the world, I am concerned that AI would dull our capacity to make sense of the world. By making sense of the world, I mean the ability to interpret, comprehend and coherently perceive the world around us on our own terms, through our own cognitive efforts. And over time, this would involve reflective trial and error, balancing our considered interpretations and judgements of the world with how the world comes to bear upon us.
Interpretation and judgement are practical skills that must be honed through constant and regular use. And we develop these skills by exercising, testing and challenging them. Making judgements about the world and what should be done is a distinctively human task that should not be easily surrendered.
I am not against the idea of a second brain. My worry is more specific – that the reliance on a second brain, if left unchecked, will weaken the equity and reflexes of the first brain.
On the other end, we see people forming emotional attachments with AI companions. These are relationships that stimulate empathy but do not truly reciprocate it. It demonstrates the real risk that people can lose sight of human relations in the real world. If people see these AI companions as a comforting shortcut to finding companionship in contrast to the hard work of developing friendships with others around us, we may see a further impoverishment of our social networks.
In both cases, the danger is the same. We begin to substitute authentic human experience, sense-making and judgement with artificial approximations. And when that happens, we may gradually lose our ability to navigate the world with clarity on our own terms. Mr Speaker, in Malay.
( In Malay ) : [ Please refer to Vernacular Speech .] Sir, a final point. There is a traditional Malay art form that is close to my heart: the pantun – a poetic form with its own specific rules. Made up of four lines, the pantun has a specific metre and rhyme scheme. Its imagery is typically drawn from nature and scenes of everyday life, to communicate important social values and advice.
A pantun that does not follow these structures and conventions is usually not regarded as a good pantun, if it may be called one at all. Many pantuns are still known among Malays by heart, passed down orally through generations. In short, the pantun embodies a tradition – connecting the Malays today to our forefathers before.
Hence, I want to ask: do we lose something valuable if we teach students to use AI to generate pantuns, rather than discovering the fun of experimenting with the lines themselves? Does the skill of using AI to generate pantuns necessarily translate into the craft of writing a good pantun, or even the aesthetic sensibility to appreciate the art form? And what is the long-term impact to the Malay language, culture and tradition when a cultural motif is reduced to an AI output?
( In English ): Sir, a final point. There is a traditional Malay art form that is close to my heart – the pantun. This is a poetic form with its own specific rules. Made up of four lines, a pantun has a specific meter and rhyme scheme. Imagery is usually drawn from nature and scenes of everyday life, to communicate important social values and advice. A pantun that does not follow these structures and conventions is usually not regarded as a good pantun, if it may be called one at all.
Many pantuns are still known among Malays by heart, passed down orally through generations. In short, the pantun embodies a tradition, connecting the Malays today to our forefathers before.
Hence, I want to ask: do we lose something valuable if we teach students to use AI to generate pantuns rather than the fun of experimenting with the lines themselves? More importantly, does the skill of using AI to generate pantuns necessarily translate into the craft of writing a good pantun or even the aesthetic sensibility to appreciate the art form? And what is the long-term impact to the Malay language, culture and tradition when a cultural motif is reduced to an AI output?
Sir, I am not suggesting that we return to a time before AI use. We have to adapt. But we need discernment. We must be clear-sighted about what AI can and cannot offer and always ask what is the purpose AI is serving and whether it is fit for that purpose? We must avoid being boxed in into an AI-centric gaze in which we are left with a narrow and artificially mediated understanding of reality and an impoverished capacity to make sense of and relate to the world and those around us. Sir, let me close my speech with a pantun.
( In Malay ) : [ Please refer to Vernacular Speech .] When delivering a pantun in Parliament;
It is best not to use AI;
The Malays are cultured and courteous;
The poet's inspiration will not be abandoned.
( In English ): When delivering a pantun in Parliament, it is best not to use AI. The Malays are cultured and courteous, the poets' inspiration will not be abandoned.
3.51 pm Mr Speaker : Order, we have been in the Chambers for close to five hours. I propose to take a break now. I suspend the Sitting and will take the Chair at 4.10 pm. Order, order.
Sitting accordingly suspended
at 3.51 pm until 4.10 pm.
Sitting resumed at 4.10 pm.
[Deputy Speaker (Mr Xie Yao Quan) in the Chair]
An Artificial Intelligence (AI) Transition with No Jobless Growth (Motion)
[(proc text) Debate resumed. (proc text)]
Mr Deputy Speaker : Mr Kenneth Tiong.
4.10 pm Mr Kenneth Tiong Boon Kiat (Aljunied) : Deputy Speaker, I declare my interest as a director of a company that makes AI-enabled applications and consults on the same.
In the three and a half years since ChatGPT's release, I have had two moments of awe and dread. The first was in November 2022. GPT-3.5 could iterate on software features, generate ideas, write code. Five years ago, it was received wisdom that everyone should learn to code. Today, coding ability is cheap and abundant. Computer science graduates, even from top schools, like Stanford, are finding it difficult to find jobs. GPT-2 was a toy that generated amusing limericks. Three years later, its successors have made an entire profession's scarcity disappear. We used to talk about prompt engineering in 2023 and 2024. That talk has died down too.
The second was in November 2025, when Anthropic released Claude Code, a reliable AI agent paired with a frontier model. I could leave the computer running overnight and there would be work done at the end. It is a different experience from chatting with a chatbot. The chatbot engages you in back and forth, refining your ideas, indulging your whims, red teaming your speeches. The agent, unless it needs clarifications, just goes and does things. It may be off by a bit, but you give your input and it takes another five or 50 minutes before it comes back with the problem solved. A very smart junior colleague.
Now we have AI agents, Claude Code, Codex tools, that have made me, if I may borrow Internet lingo, Claude-pilled. I use Claude Code for my own work. I can give it the most wishy-washy specifications, and it returns the most wonderful data workflow or website layout. For someone who could never build a pretty website to save his life, it is liberating.
There is a spirit of play in working with these tools that every Singaporean deserves to experience. It is an exhausting world it heralds – software engineers pulling 80-hour weeks while running multiple AI agents overnight so that someone, human or machine, is always on the clock. Jobseekers, especially recent graduates in white-collar work, applying to hundreds of jobs without a single interview. Job portals, like LinkedIn, have become memory holds for resumes, where the lived experience is like shooting an application into the void.
The pace of change humbles us all. I am suspicious of any assertion that starts with "AI will never", because the shelf life of those predictions tend to be measured in months. What concerns me is not the destination, but who gets left behind on the way there and whether we are building the institutions to ensure no one does.
I have three propositions. First, that access to premium AI, especially AI agents, must be universal, not gated by course enrolment or union membership. Second, that we must treat the handful of companies building frontier AI with the same strategic seriousness we bring to bilateral relations with countries, because their decisions on pricing, access and deployment now shape our productivity frontier as directly as any trade agreement. Third, that we must buy time for workers by upgrading our retrenchment framework for AI-speed displacement.
Sir, I believe access to premium AI, especially AI agents, is a right, not a privilege. Intelligence, in the sense of uplift, should not stratify according to wealth. I spend a couple of hundred dollars a month on these tools because they are game changing. But for those who cannot afford to, it bakes in inequality from the start. Does it simply disqualify them from the off?
The Government has partially adopted the 2024 suggestions of my colleague Gerald Giam to provide universal premium AI model access. The SkillsFuture Premium AI Access Scheme, six months of free tools for Singaporeans who enrol in selected courses, is a step in the right direction. Likewise, NTUC's subsidies covering 21 AI tools. These are good starts, but they are unnecessarily gated behind course enrolment and union membership. And critically, they likely will not cover AI agents – the tier where the real productivity gap will open.
Why does this matter? AI agents are expensive to run. We may hope agent access follows the cost curve of Internet bandwidth or compute, but there is no necessary reason it should. It is an empirical question.
Anthropic's CEO said in January that 80% of its revenue comes from enterprise customers, driven by API calls on a pay-per-token model. If agents remain enterprise-grade by default, then individual citizens – jobseekers, freelancers, retirees – are locked out of the tier where the real productivity gains are being made.
Three possible directions.
One, negotiate sovereign access – a bulk licensing agreement with frontier AI providers for volume-discounted AI agent access for all citizens.
Two, if agent access is employer-provisioned in the market, make it universally so, require companies above a certain size to provide agent-grade AI to all employees, the same way we require CPF.
Three, if frontier agents remain too costly, identify a minimal, viable agentic tier and fund that universally.
Will the Government make premium AI access a universal entitlement, rather than gate it behind course completion or union membership?
Sir, I learnt recently that even AI engineers at the top two or three frontier AI labs are worried about falling behind because they cannot use Claude Code. And having just returned from China, I learned first-hand that one cannot use Claude Code there at all. Anthropic blocks API calls from mainland China, Hong Kong and Macau entirely.
If even engineers building frontier AI are desperate for access to one another's tools and if entire countries can be locked out, then access is not a convenience. It is a strategic capability. And the question for our country is whether we will secure it or whether we will be price-takers forever.
There are, perhaps, three to five companies in the world whose decisions on pricing, access and deployment will shape every economy's AI trajectory. When Anthropic or OpenAI decides what to charge for agent-tier access or whom to serve, that decision shapes Singapore's productivity frontier as directly as any trade agreement.
We should therefore treat this class of companies – frontier AI firms that have crossed a threshold of systemic importance – with the same strategic seriousness that we bring to bilateral relations with countries. Not because they are sovereign, they lack the durability and legitimacy of states and remain subject to home-state law, but because their decisions carry sovereign-grade consequences for our economy and we should engage them accordingly.
What does that mean in practice? Four things.
First, negotiate access at the sovereign level. In the possible future where frontier AI agent costs go up, not down, Singapore should seek bulk licensing agreements for agent-tier access the same way we negotiate energy supply. This means accepting that frontier AI access may be a permanently higher line item in the national expenditure and procuring it systematically, because the alternative – citizens priced out of the tools that define productivity – is worse.
Second, we trade based on what we have. Nvidia CEO Jensen Huang has described the AI stack as a five-layer cake: energy, chips, infrastructure, models and applications. In my view, we do not have energy at scale. We do not have frontier model capability. At the application layer, there is little moat outside of the knowledge agglomerations we can build for ourselves. We would be competing with some of the highest cost bases in the world.
But Singapore Inc builds good data centres. And we are among the world's leaders in water reuse and integrated water management, which is a binding constraint on data centre expansion across water-scarce regions in Southeast Asia. If we position ourselves as the infrastructure partner of choice for this region, that is real leverage – something we can bring to the table in exchange for access, for pricing and for presence.
So, when a company like Anthropic or OpenAI approaches us, we should be their preferred regional bilateral partner in rolling out and scaling their data centre build-up regionally, as well as all the infrastructure needed to make these data centres work.
Third, we need to attract real technological presence. We should seek frontier AI companies establishing development offices here – not predominantly sales offices, which was the experience with the FAANG companies in the 2010s. And I would prefer that we be quality-conscious. Most companies that call themselves "AI companies" are not frontier AI companies. We need targeted strategy and engagement with frontier AI companies specifically.
Fourth, get Singaporeans inside these labs. Once you are in the frontier AI ecosystem, it becomes much easier to circulate within that group of companies. I would welcome the Government doing some fact-finding – engaging our local and overseas Singaporeans already in these companies and roles, understanding how they or their colleagues got hired and disseminating that to our students and technical researchers. Right now, anecdotally, half a million to million-US-dollar salaries, excluding equity, in the US for AI researchers are fairly common. So, it is clearly in our interest to figure out how to get more Singaporeans into this tight labour market. What I would really like to see is a Skills Framework for frontier AI lab researcher.
Sir, my last point is about the transition. Let me start with a person. In Hangzhou, a quality assurance supervisor named Zhou joined a tech company in late 2022 at RMB25,000 a month, about S$4,800, reviewing AI model outputs for accuracy and safety. In 2025, his employer decided an AI model could do his job. They offered him a reassignment at roughly 40% less pay. He refused. They terminated him. Zhou went to arbitration and won. The company sued and lost. The company appealed and lost again, at the Hangzhou Intermediate People's Court. The ruling was published on 28 April this year, three days before International Workers' Day.
The court's reasoning is worth our attention. The company argued that AI had made Zhou's role obsolete – a "major change in objective circumstances", justifying dismissal under China's Labor Contract Law. The court disagreed. AI adoption, it held, is a deliberate business strategy, not an unforeseeable event. A company that chooses to automate cannot unilaterally shift the full cost of that decision onto the worker. The company had not shown the contract was impossible to perform and the reassignment at 40% less pay was not a reasonable alternative. The court added that companies should prioritise retraining workers and helping them transition to higher-level roles.
The principle, that a deliberate business decision should not externalise its full cost onto the worker, deserves serious consideration in Singapore.
If a Singaporean Zhou were retrenched tomorrow under our existing framework, would he win? Our existing Tripartite Advisory on Managing Excess Manpower and Responsible Retrenchment (TAMEM) is advisory, not statutory. An employer can lawfully automate a role and terminate the worker without first attempting to redeploy or reskill them. And the public purse, through SkillsFuture and Workforce Singapore, would pick up the cost of that worker's transition. There is no AI-specific notice period. There is no statutory redeployment-first obligation. There is no individual cause of action for the worker to challenge the reason for his or her termination.
The data suggests we are entering the zone where this matters. MOM's own fourth quarter of 2025 Labour Market Report reported about 14,490 retrenchments in 2025, up from about 13,000 the year before. PMET retrenchment incidence reached 10.1 per 1,000 resident employees, above the pre-recessionary norm of 8.0 set during 2015 to 2019. Retrenchments were concentrated in Financial Services, Information and Communications, and Professional Services – the most AI-exposed sectors. Information and Communications employment declined outright in 2025.
The Government announced the Tripartite Jobs Council on 30 April. I, of course, welcome its intent. But it creates no new powers, no new obligations on employers and no new rights for displaced workers. How does the Government intend for this Council to work?
Too often, what workers experience is not a frank conversation about AI-driven restructuring but a Performance Improvement Plan, a process that, in many cases, is a bit of "wayang", designed to paper over a predetermined outcome. I foresee that such potential misleading reasons may be given and workers must have the power to be able to challenge this.
I propose three directions. First, a 90-day mandatory transition notice before AI-driven role elimination. Second, a re-deployment-first obligation, retraining or reassignment before AI-driven termination. These provisions will slow the velocity of AI disruption; and velocity is what determines whether adjustment is possible. Third, for workers to be able to substantively challenge the reasons for their termination if they feel they are misleading, so that these AI restructuring protections will be real.
Sir, in closing. Finland gave people unconditional cash as income. They were happier, less stressed – and the great majority still walked into the employment office and asked for work. The American pollster David Shor polled Americans this year: three to one, across every political persuasion, they chose job creation over direct transfers. People, when offered the choice between a universal basic income and employment, invariably choose employment. Not because they are irrational, but because a job is where you are needed, and being needed is not something a universal basic income can replace.
So, no jobless growth – yes. But more than that: no growth where the gains are captured disproportionately by capital and the burden of adjustment falls on labour. Universal access, so intelligence is not rationed by wealth. Strategic engagement, so we are not price-takers in our own future. And a retrenchment framework where the company that decides to automate bears the cost of that decision before the worker does.
I do not think the awe and dread goes away. But in a country that builds for its workers, there is hope for a brighter future. Thank you.
Mr Deputy Speaker : Mr Sanjeev Tiwari.
4.25 pm Mr Sanjeev Kumar Tiwari (Nominated Member) : Mr Deputy Speaker, before I start, my greetings to my fellow unionists on both sides of the viewing Chamber. Thank you for the support.
Mr Deputy Speaker, as unionists, our role is not just to support change, but to ensure that the change works for our workers. With all the discussions so far, there is no doubt that AI brings about new opportunities, new tools, new ways of working and the potential for better jobs.
For the Labour Movement, an AI transition with no jobless growth must means three things. First, AI augments workers, it does not replace them wholesale. Two, the productivity gains from AI are reinvested into people, into training, into new industries, into better wages and real growth. Three, no worker is left to navigate this transition alone. I will speak to each of these in turn.
Ensuring productivity gains are shared. Mr Deputy Speaker, if we are not deliberate, the gains from AI will not automatically be shared. They will tend to concentrate in firms with the scale and capability to deploy it. The business case for transformation is compelling and I support the Government's announced efforts to support enterprises on this to accelerate their AI adoption, so that they can seize new opportunities.
However, I call on businesses seeking to grow their pie, to be laser-focused on job redesign and training to bring their workers along with them. Here, I must appreciate the many hon Members who have supported this call.
Globally, there are warnings that AI could significantly reduce entry-level white-collar roles in the coming years. Closer to home, DBS Bank has announced plans to reduce its contract and temporary staff by around 4,000 across various markets, with AI adoption.
While firms rationalise their workforce sizes and skills mix, we must be clear-minded that not all of such rationalisation may translate into economic growth that enables our families to thrive, children to flourish and seniors to enjoy their golden years.
Workers are therefore paying attention. They want to know that there are pathways for the gains from AI to benefit workers, and not just management and shareholders. Many workplaces are only at the beginning of figuring out what such pathways need to look like and the pitfalls of failing to provide such pathways.
As mentioned by some Members, recently, courts in China have been active in reviewing cases regarding the dismissal of employees due to AI-related restructuring and choosing to protect labour rights against unfair AI-related lay-offs. In one case, the arbitration panel clarified that AI replacement was not valid grounds for dismissal. In another case, a massive role and salary reduction due to AI taking over the work was not considered a reasonable re-assignment proposal.
I would like to believe that we will not see such court cases in Singapore. Hence, companies must be held to a human transition standard. When a company deploys AI that eliminates roles, it should be required to have a transition plan, re-deployment offers, funded retraining, phased timelines.
It must work with the unions through the CTCs or the tripartite frameworks, to ensure this is managed together. We should make this a baseline, and not the exception. The social contract between employer and employee must evolve alongside technology.
Unions should be involved early in the company's transition plans to integrate new technology, implement job redesign and transition workers to handle new work. In roles that AI is not displacing, AI is increasing the speed, density and complexity of work rather than reducing it.
However, I caution that when AI has pushed human boundaries and job redesign is not done adequately in tandem, there is concern that the working environment will be unsustainable, with very high intensity and pressures that can lead to burn-out, fatigue and poorer psychosocial health. We already see this in many of today's workplaces, especially for PMEs, where work is increasingly outcome-based and the boundaries between work and personal life are more blurred. AI risks accelerating this trend even further.
The psychosocial implications of AI enablement deserve further attention too. Our time-based employment protections were designed for a less digitally connected era with more fixed working hours and clearer boundaries. Today, these new emerging work patterns suggest there is room to further evolve how we can support workers.
This is where our unions in Singapore play a critical role. Through collective agreements, company-level engagements and multi-company initiatives, such as the Queen Bee partnerships for the NTUC's CTC initiative, unions ensure that productivity gains are translated into better jobs, better wages and most importantly better working conditions, not just higher output and shareholder returns. In addition, when AI is deployed to support hiring decisions and performance reviews, we must watch for unintended biases and ensure safeguards for the confidentiality of information.
Supporting workers through transitions. Even when gains are shared, there is a harder question we must confront: what happens to workers whose jobs are displaced altogether?
Mr Deputy Speaker, the standard response we often give is to reskill, adapt, move on. That advice assumes that workers have time, the financial buffer and margin for error to take such risks. However, not all workers have this luxury. I want to be honest, because vague optimism is a luxury that the displaced cannot afford and we must make sure the system watches for this.
This is especially so for our mid-career and older PMEs. They are workers with mortgages and bills to pay, with children still in school and often, elderly parents to take care of. They are not just managing careers. They are carrying entire households.
For them, transitions are high stakes. A failed transition is not just a momentary setback. It can mean prolonged unemployment, income loss and long-term repercussions for their loved ones. And this we are already seeing in the data that is provided by MOM, where there has been a rise in PMET retrenchments compared to the pre-recession norms in 2019, reflecting their greater exposure to sectors undergoing restructuring.
This is where we must go further to support our breadwinners and their families, ensuring that reskilling leads to real job outcomes, that transitions are supported and that pathways to good jobs are clear, especially for those making mid-career shifts.
Instead of welfare, we have workfare. And instead of minimum wages, progressive wage models for key segments of our workforce. For the AI era, we can seek better support for our PME jobseekers. We must continue close monitoring of those who applied for jobseeker support and help them bounce back as soon as possible for the next better job.
Mr Deputy Speaker, giving workers a genuine voice in AI adoption, where the first two pillars of sharing gains and supporting transitions cannot happen without the third. Giving workers a genuine voice in how AI enters their workforces is equally important.
Across advanced economies, one principle is becoming clear, worker voice must be part of how technology reshapes work. In countries, like Belgium, unions and employers are already working together to establish norms around after-hours communication, workload and staffing.
In Singapore, we have a strong foundation in our tripartite model. But as a unionist, I want to make a broader point. If we are serious about ensuring AI is used fairly and that the gains from AI-driven transformation reach workers, then we must welcome unions to represent PMEs who are most vulnerable in the AI era.
PMEs are not a monolithic group – an engineer in aerospace, a financial analyst in banking, a project manager in the tech phase – very different work environments and go through very different impacts of AI transformations. Unions are able to shape workplace norms from ground up, in a targeted manner that recognises diversity. Hence, employers should consider allowing unions to represent PMEs.
The mechanism for having the workers voice at the table is already here – it is the CTC. Through the CTC, unions work directly with management to chart out transformation roadmaps, redesign jobs and upskill workers so that no one is left behind when a company transforms.
Let me just give one example. SBS Transit, with support from the National Transport Workers Union and the CTC Grant, overhauled its bus maintenance operations using AI. The company implemented AI-powered diagnostic systems for predictive maintenance and instead of cutting jobs, it created a new diagnostic expert career scheme for over 50 workers. Such examples must be amplified and more employers should do such things.
We must continue to leverage this to support workers and enterprises in the AI transition. More recently, NTUC is partnering global technology leaders, like Amazon Web Services (AWS) and Huawei, to equip 100,000 workers and 100 enterprises with AI skills through the CTC ecosystem.
At the individual level, union members can also tap on union support for up to half of the subscription fees for AI models. This is in addition to the six-month subscription provided through the Government. I hope more leading multinational corporations can work with our unions to provide more training and uplift the AI skills of workers for our collective future.
In conclusion, Mr Deputy Speaker, I call for Singapore to move forward in these areas.
First, on sharing gains, we must ensure that as enterprises transform with AI, the gains are shared with workers through fair wages, better working conditions and clearer norms around work intensity, including expectations on after working hours communication and responsiveness. They must be calibrated to our Singapore context but clear in intent.
Second, in supporting transitions, we must strengthen how we support workers through the AI transition by ensuring that AI enables enterprises to unlock new growth, that training leads to real job opportunities, that reskilling is twinned with job redesign and that workers are not left to navigate these changes on their own.
Third, in giving workers voice, workers and their unions must be engaged early when AI is introduced into workplaces. Not just on hiring and other employment decisions, but on how AI changes job scopes, workflows and performance expectations. This means welcoming unions' ability to represent PMEs, and scaling mechanisms, like the CTC, so that worker voice is embedded in every transformation journey.
An AI transition with no jobless growth is not a slogan. It is a commitment. A commitment that growth should mean something to everyone, not just those at the top of the economic pyramid. But to the nurse, the teacher, the logistics worker, the small business owner, the young person entering the workforce for the very first time. They are not footnotes in the story of technological progress. They are the reason progress should matter at all. These are not competing priorities; they go hand-in-hand and we are standing at one of those rare inflection points in history where choices we make today will echo for the next generations.
That is where the tripartite partners must deliver, must make this happen and that is also what I hope this House will help us deliver. I strongly support the Motion. [ Applause. ]
Mr Deputy Speaker : Mr Sharael Taha.
4.38 pm Mr Sharael Taha (Pasir Ris-Changi) : Thank you, Mr Deputy Speaker. Mr Deputy Speaker, Sir, I declare my interest as someone working in the aerospace and advanced manufacturing industry, focusing on strategy, digital transformation and AI transformation.
Mr Deputy Speaker, I stand here today with a deep sense of gratitude. I grew up in a very ordinary Singaporean home with working class parents, but was given an extraordinary opportunity to build and retrofit advanced factories across the world.
From Germany to the United Kingdom, from North America to Asia, I have had the privilege of building and working on industry 4.0 facilities, cutting edge factories equipped with some of the most sophisticated machines ever created, machines that produce components of such precision that they can only be manufactured in a handful of places in the world and facilities that assembled some of the most advanced engineering systems ever built.
Mr Deputy Speaker, Sir, after all these years, one lesson stands above all else. It is not the machine, nor the technology that determines success. It is the people. I have seen factories with the best technology money can buy struggle because of misalignment, because of distrust, because workers, unions, management and government were not moving in the same direction. And I have seen more modest facilities outperform expectations because everyone was aligned to a common purpose.
That is why this debate matters, because when we talk about transformation, especially one driven by AI, we are not just talking about technology. We are talking about people, about workers, about livelihoods, about dignity.
And I want to acknowledge our Labour Movement, NTUC Secretary-General, Mr Ng Chee Meng, and Ms Yeo Wan Ling and Members of this House, Mr Mark Lee and Mr Saktiandi Supaat, for putting forth this Motion. Their position is not just right. It is also timely.
It is timely because it complements the direction set out by Prime Minister Mr Lawrence Wong in his Budget speech and the May Day Rally, where he spoke about how Singapore must confront the realities of AI and global uncertainty while standing firmly with our workers. And even as technology reshapes our economy, we must not leave our people behind.
Our Labour Movement has echoed this with clarity and conviction. That this transition must drive Singapore's next phase of growth, but it must be anchored in fairness and opportunity for all. We must equip both workers and enterprises to seize new opportunities so that progress is not just created but shared. This is the promise we must make to our next generation.
Mr Deputy Speaker, having worked across different countries, I have encountered many labour movements, many focus on protecting jobs, protecting specific jobs that exist today. And often to protect the jobs of today, they invariably have to resist change, even when the tide of change is inevitable. But what we have in Singapore is different.
From my enterprise experience, our tripartite partnership between the NTUC, Singapore National Employees Federation and the Government is unique, so unique that many of my overseas colleagues are genuinely puzzled by how well it works with real positive outcomes for all, because our unions do not just protect jobs, they protect workers.
And our union leaders, like brother Samad from the Union of Power and Gas Employees, brother Fahmi from United Workers of Electronics and Electrical Industries, brother Poobalan and Goviden from SATS Workers' Union, brother Gabriel from the Amalgamated Union of Statutory Board Employees and many of our union leaders here, stand with the workers, not just for where they are today, but for where they need to be tomorrow. They focus on keeping workers relevant, employable and ready to take on better opportunities as the economy evolves.
And that, Mr Deputy Speaker, is something that we should never take for granted. Allow me to frame my position on the motion around three key ideas: transformative power, opportunity for all and jobless growth.
First, on the transformative power of AI. The impact of AI can be understood at three levels, the individual, the enterprise and the industry. And at every level, success depends on how well workers, businesses and Government work together. At the level of the individual, AI is a force multiplier.
It enhances productivity, augment skills and allows each worker to do more, do better and do faster. Many of us are already experiencing this today through tools, like Open AI, ChatGPT, Microsoft Copilot, Claude, Gemini and Canva, but this transformation does not happen by chance. Workers must be prepared to learn, adapt and continuously upgrade themselves, and businesses must invest in training, redesign jobs and empower their workforce to use these tools effectively.
And the Government must provide the support structure, strong skills framework, accessible training pathways and broad-based access to technology. That is why I am encouraged by the support the Government is providing to help Singaporeans adopt AI tools, further strengthened by NTUC's initiative to subsidise AI subscription to its members. This is important because AI cannot become a tool only for the privileged few. It must remain accessible to the masses so that every worker has the opportunity to improve productivity, strengthen capabilities and participate meaningfully in Singapore's next phase of growth.
At the level of the enterprise, AI enables better decision, sharper operations and greater efficiency. It turns data into insights and insights into action. But to realise this, companies need the right framework. Workers need the right capabilities and the Government must provide the right environment to scale transformation responsibly.
At the level of the industry, AI creates entirely new value. It reshapes business model. It transforms competition and unlocks new growth. In a tight labour market, like Singapore, this enterprise and industry transformation must go hand in hand with deep business process re-engineering and meaningful job redesign, as mentioned by a few of the Members here.
And speaking from my own experience in the industry, the decision to adopt AI is really just about tax incentives, as characterised by Member Mr Andre Low. The real driver is how we upskill and reskill our workers so that they can take on higher value-added jobs that are increasing in demand and the opportunity cost of not doing so.
The tax incentives help companies invest in the necessary AI tools and infrastructure. But equally important are the schemes that support workers through this transition, whether it is programmes such as the SkillsFuture Workforce Development Grant, NTUC CTC Grant, the Union Training Assistance Programme, and Workforce Singapore's Career Conversion Programmes, these initiatives support job redesign, training and even provide wage support while workers undergo upskilling and reskilling.
Very often, AI adoption is not a binary choice between technology and workers. It is about re-engineering business processes so that enterprises can do more with a more capable, more skilled and more productive workforce to take on the challenges of the world.
These values, unlocked by AI, must be shared – shared so that workers are uplifted, businesses grow stronger and society moves forward together. But ultimately, this is a social compact we must continue to uphold between workers, businesses and government – one anchored on fairness, inclusion and shared progress.
Taken together, AI is not just any other technology tool. It is a system-wide transformation. That is why tripartism matters even more in the age of AI. And I am heartened to hear the position of the Labour Movement.
Second, on opportunity for all. Mr Speaker, this transition will create economic growth. But it is also a period of real uncertainty. We must acknowledge these challenges. Our fresh graduates are feeling it. Many struggle to secure permanent roles. Multiple internships are becoming the norm. At what point do we ask whether this becomes a substitute for proper employment?
As AI reshapes professions from developers to lawyers, how do we ensure there are still meaningful entry points for our young people? If companies begin to question entry-level roles, then we must also ask, who will train the next generation of our workforce?
Our mid-career workers feel this even more deeply. With families and responsibilities, they worry that job transformation may render their experience less relevant. Our blue-collar workers – our technicians, our operators and drivers – are asking hard questions about automation and the future of their jobs.
These fears are real. If left unaddressed, they can divide our society. That is why this opportunity for all cannot be left to market forces alone, a point also raised by Member Poh Li San. It requires companies and especially middle managers to give fresh graduates a real chance. It requires businesses to redesign jobs and invest honestly in upskilling and reskilling. It requires all of us to work together so that every Singaporean can find their place in this new economy. Only then can we say that this is not just growth, but opportunity for all.
Finally, on jobless growth. In many economies, jobless growth means growth without jobs. But in Singapore, our context is different. We are already near full employment. So, this is not just about creating more jobs. It is about ensuring our people can take on the jobs that are created.
Because growth will come and new roles will emerge. But if our workers are not ready, if skills are not kept in pace, we risk a different kind of jobless growth – not a lack of jobs, but a mismatch between jobs and the skills our workforce has. Avoiding this means focusing on capability, not just capacity.
Businesses must transform jobs, not eliminate them. Workers must continue learning. The Government must support hope with strong systems and pathways.
When we do this well, growth will not leave people behind. It will lift them. My Deputy Speaker, in Malay, please.
( In Malay ) : [ Please refer to Vernacular Speech .] Mr Speaker, the discussion about AI today is no longer something distant from our lives. In Singapore and around the world, one thing is clear – AI brings hope, but also concern.
Within our Malay/Muslim community, these concerns are real. Young people worry about the future of employment and whether opportunities still exist for them. Those in mid-career are anxious about whether their experience and skills remain relevant. And blue-collar workers – including drivers, technicians and general workers – wonder whether their jobs will be replaced by automation.
We must acknowledge these concerns. But at the same time, we cannot view AI only as a threat. We must see it as an opportunity – an opportunity to progress together.
Allow me to touch on three important points in the AI transformation.
First, on building skills to be part of this transformative force. AI will only become a force multiplier if we know how to use it. That is why we must be prepared to continuously upgrade ourselves – to reskill and upskill.
This is where it is important for us to make use of the support available – whether through Workforce Singapore (WSG) programmes, NTUC, or community initiatives, such as M 3 +. At M 3 + Pasir Ris–Changi, for example, we run various programmes to help the community enhance their skills and employment opportunities. These include Women-at-Work to help women return to the workforce, as well as the Career Marketplace held in Pasir Ris to open access to career opportunities and employment networks.
And these efforts do not stop there. Through the HashTech programme in Pasir Ris–Changi, we are beginning to introduce our children to AI, robotics and autonomous systems – including through activities such as Robot Wars. This is not merely an activity. It is an effort to build confidence, exposure and future-ready skills from a young age.
Regarding skills, the fear of AI should not prevent us from learning how to use it wisely. The concern that AI could diminish any deep understanding of the Malay language and culture, as well as other skills, is understandable – if it is used without understanding the basics and its limitations.
Like any other tool, what matters is how we use it. Mastery of and appreciation for the Malay language remains key in understanding its beauty, values, and meaning.
However, if used appropriately, AI can also help preserve our heritage. AI can assist in digitalising old Jawi manuscripts, producing batik designs inspired by traditional Malay motifs and facilitating the learning and translation of the Malay language. Even classic Malay films can be preserved for future generations.
Technology should not erode our identity. If used wisely, AI can help preserve the language, strengthen culture and carry Malay heritage into the future with confidence.
Allow me also to share a pantun.
Golden bananas brought to sea,
One ripens atop a chest,
If AI is used very wisely,
Culture is inherited, in the heart it rests.
(In English) : Mr Deputy Speaker, Sir, at its heart, this is not just an economic transition. This is a test of our social compact, a compact that must now be renewed for a new era where businesses commit to not just profits but to people, where workers commit to not just jobs, but to lifelong growth, and where the Government continues to stand with both, ensuring that no one is left behind.
If we can do this, if we can move forward together with trust, purpose and shared responsibility, this transformation will not divide us. It will make us stronger because when workers, businesses and the Government move together, we do not just adapt to change. We shape it, we benefit from it and we ensure that every Singaporean moves forward together. Mr Deputy Speaker, I support the Motion. [ Applause. ]
Mr Deputy Speaker : Assoc Prof Terence Ho.
4.54 pm Assoc Prof Terence Ho (Nominated Member) : Mr Deputy Speaker, I rise in support of this timely Motion. I would like to first declare my interest as the executive director of the Institute for Adult Learning at the Singapore University of Social Sciences.
AI, as we know, is a transformative technology. All of us recognise that it will profoundly transform business models across the economy and with it, the content and nature of work.
As a small, open and technologically advanced nation, Singapore must strive to be at the forefront of new technologies, especially one as significant as AI. In addition to being critical for our economy, AI also has considerable potential to help address Singapore's demographic and societal challenges. But whether we embrace AI or fear it, there is no escaping the impact it will have on our companies and workforce.
I will make four points in my speech.
First, jobless growth is not an option for Singapore as good jobs are integral to inclusive growth and to a fair and vibrant society.
Singapore's social compact is based on self-reliance through work. This means providing for oneself and one's family through employment and income. It has been said before in this House many years ago that "a job is the best welfare, and full employment is the best protection for the workers of Singapore."
In this social contract, the Government's role is to nurture a pro-enterprise business environment conducive to investment and job creation. Any Singaporean who is willing to work hard will have enough to meet his or her housing, healthcare and retirement needs through CPF savings. In practice, significant Government support is given in the form of housing grants, CPF top-ups and healthcare subsidies to support home ownership, retirement adequacy and healthcare assurance.
Singapore's socioeconomic model has evolved over time. We now have more extensive risk pooling through social insurance, complementing individual savings in meeting healthcare and long-term care needs. There is more structural or permanent social support in the form of the Workfare Income Supplement and Silver Support. And the Government, recognising the greater risk of economic and job disruption, has introduced income relief for the involuntarily unemployed through SkillsFuture Jobseeker Support, which has been discussed by Members of this House.
Yet employment and income remain central to Singapore's socioeconomic model and social compact. Recent advances in AI pose a challenge to this model. Globally renowned AI pioneers and industry leaders have warned of the possibility of mass job displacements arising from AI. Predictions of a so-called "white collar bloodbath" or a "jobs apocalypse" have stoked public fear even as other commentators have asserted that these fears are overwrought.
Transformative technologies in the past have indeed eliminated certain jobs, but they have created new jobs as well so that we are not all without jobs or leading lives of unlimited leisure.
Generative AI has raised particular concern because it can take over jobs and tasks associated with human skill and creativity, including cognitive tasks such as coding and data analysis and creative tasks such as writing and design. These tasks require skills built through years of education and training and are consequently well remunerated. They underpin many of the good jobs that Singaporeans aspire to.
While we should not underestimate the disruption from AI, there is still time to adapt and respond. That is because the extent of job disintermediation or displacement depends on the speed of technology diffusion, which has historically followed an S-curve.
I filed a Parliamentary Question in March asking whether MOM has detected any signs of AI prompting a slowdown in the hiring of fresh graduates. Indeed, many Members of this House have pointed to this concern. The response I received then, which was reaffirmed yesterday as well, was that employment rates for young degree holders has remained broadly stable.
This may be because the adoption of AI is still in its early stages for many companies here. It takes time for more firms to move from viewing AI as a mere project or productivity enhancement tool to fundamentally re-organising work processes around it. As the pace of AI adoption picks up, however, the benefits to firm productivity and profits will grow, but so too will the impact on jobs.
A related concern that many in this House have also discussed is that in the AI age, profits will increasingly accrue to technology companies and those who own shares in these companies, and less to workers as skills become commoditised.
While we must consider the need for greater social support and new channels of redistribution to keep our society inclusive, we must also continue to equip citizens to provide for themselves through good jobs and incomes.
Some of us may remember what President Tharman explained in an interview in 2015 at the St Gallen Symposium. He was describing Singapore’s approach, and I quote: "It is about keeping alive a culture where I feel proud that I own my home and I earn my own success through my job. I feel proud that I’m raising my family. And keeping that culture going is what keeps a society vibrant."
If we look around the world at how economies have developed, it is clear that the key to success is the emergence of a strong middle class enabled by education and job creation. Many countries with large natural resource endowments have not done well, because their focus has been on resource extraction, benefiting the few, rather than education and skills development, which benefit the many. It is also evident that Singapore succeeded precisely because people are our only resource. Singapore's economic development has been a story of inclusive growth – and that is the path we must stay on.
This brings me to my second point, which is that we must support workers to develop deep domain knowledge, learning agility and career resilience. To equip workers for the AI age, training in AI tools is certainly important. Familiarity with AI and understanding of the strengths and limitations of different AI tools comes with frequent use, tinkering and experimentation. But that, as many in this House have also realised, is only part of the answer. After all, AI tools are supposed to become more intuitive and easier to use over time.
The real value that people bring to jobs lies in deep understanding of domains or subject matter, which means all of us still have to put in the hard yards to learn and avoid "cognitive offloading" by creating productive friction in the learning process, whether in schools or at the workplace. AI can provide the scaffolding and can help personalise learning, but it must not become a substitute for thinking.
The key skill that many have identified is learning how to learn, being adaptable and resilient to changes. This means getting out of our comfort zones, continuously challenging ourselves, getting used to different tasks and work environments, and working in diverse teams.
This is everybody's responsibility: to take ownership of our own learning and career development, leveraging public funding and resources where available.
Employers too have a responsibility. The Singapore Opportunity Index developed by MOM highlights how employers can create opportunities for their workers such as through recruitment practices, career development pathways and job design. By identifying employers with a good track record of supporting career growth, employers will hopefully be encouraged to invest in their workers and help them chart their careers.
The third point I would like to bring up is that we must not only upskill workers for jobs, but also upgrade jobs for workers. As I mentioned in my speech at MOM’s Committee of Supply debate, there will continue to be strong demand for workers in areas such as healthcare and skilled trades, driven by an ageing population and the relative resilience of these roles to AI displacement.
However, such jobs have difficulty attracting Singaporeans as they are perceived to be less prestigious or rewarding, or perhaps less comfortable compared with white-collar office jobs. But the risk is that Singapore will become increasingly dependent on foreigners to take on essential work even as Singaporeans struggle to find jobs that meet their aspirations.
Today, over 40% of the resident workforce have university degrees. Jobs and occupations that have traditionally been regarded as non-degree jobs therefore have to be redesigned to be suitable for a broad range of workers, including graduates.
Pay is only part of the issue. The jobs have to be redesigned to tap on workers' "head, heart and hand" skills, so that they are more engaging for workers and more resilient to AI disruption. This may involve taking on greater professional responsibility, increasing the cognitive, analytical and innovation content of jobs, and creating more opportunities for interpersonal engagement in the jobs. AI tools can in fact support the upgrading of vocational and semi-skilled jobs by augmenting human expertise. By making the whole range of these jobs attractive to Singaporeans, we can avoid structural overqualification or underemployment. Enterprises can do so by centring job design on skills rather than credentials.
My fourth point is that Singapore should build up expertise as a global reference point for skills-first and human-centric job redesign. A skills-first approach means that workers are not pigeonholed by formal qualifications into certain jobs or occupations. Employers recognise that workers, regardless of their starting point, can upskill to meet job requirements. Likewise, the scope of jobs and occupations can expand to make fuller use of workers' skills.
AI is already fractionalising jobs – breaking them down into tasks, some of which are assigned to AI and others to human workers. It is important for job redesign to be human centric so that human workers can still make a valuable contribution, augmented by AI and technology, rather than have processes entirely automated with minimal human involvement.
With agentic AI now able to execute processes that span multiple job roles, it is no longer enough to redesign tasks within a particular job. Instead, organisations must look at redesigning end-to-end work processes. This is a capability that must be embedded within organisations as AI continually reshapes the nature of work. Singapore has the opportunity to set the pace in skills-first employment practices and human-centric job redesign, which will benefit both our firms and workers and is critical for our social compact.
The Institute for Adult Learning’s Centre for Skills-First Practices recently launched a series of skills-first working papers and accompanying roundtable discussions. They attracted much international attention, with participation from experts, policy-makers and industry practitioners around the world.
The impact of AI on work and learning is an issue that all countries and societies are grappling with, and no one has all the answers. It is a fertile area of research as firms and societies seek to adapt and transform. We are in a complex operating environment with no tried-and-tested playbook to fall back on. As one corporate leader I spoke with recently put it: we are learning and adapting mid-flight.
Both learning and job redesign in the age of AI must be iterative and experimental. We need the best minds in Singapore and around the world focused on this. Just as Singapore has world-leading research centres in new technologies like quantum computing, we should build up expertise and experience in adult learning and human-centric job redesign.
Today, there are nodes of excellence across the institutes of higher learning. For instance, the polytechnics and ITE are among the national centres of excellence for workplace learning. The Singapore Management University has set up a Resilient Workforces Institute, while the Singapore Institute of Technology has launched a Skills Assessment and Validation initiative. At the Singapore University of Social Sciences, the Institute for Adult Learning has an Adult Learning Collaboratory and a Centre for Skills-First Practices. With end-to-end expertise from research to translation, the Institute for Adult Learning can serve as a national focal point for adult learning and employability.
Together, we can build up Singapore as a thought leader and living laboratory in the areas of adult learning, career health, human-AI complementarity and skills-first practices. As a global innovator plugged into international networks of cutting-edge research and practice, Singapore can help to shape the future of work in a way that supports both economic growth as well as human flourishing.
Mr Deputy Speaker, the Motion before us powerfully expresses the commitment of Singapore’s tripartite partners to inclusive development that benefits both workers and firms. This is important because it can no longer be taken for granted that economic growth in the future will be accompanied by full employment and rising incomes. Beyond adapting to AI, our end goal must be to enable every worker to grow, to contribute and to find meaning in work.
The formation of the National AI Council and the Tripartite Jobs Council underscores this commitment. It is a whole-of-nation effort where everyone has a part to play.
Recently, an American journalist approached me to find out how Singapore is addressing AI and its impact on jobs. She noted that many major US corporations are under pressure to slash headcounts to boost profits. Indeed, there are expectations from shareholders and investors that management will replace workers with AI. When I shared with her that Singapore’s priority is equipping workers to work with and alongside AI, she described the contrast, in her words, as "stark" and "inspiring".
With our unique tripartite collaboration and the commitment of all partners, I believe that companies and workers can approach the coming AI transition with resolve and confidence.
Mr Deputy Speaker : Mr Alex Yeo.
5.09 pm Mr Alex Yeo (Potong Pasir) : Mr Deputy Speaker, AI can be scary. I recall the first time at work when I received a draft legal submission from my younger colleague who had some content generated by AI, the alarm bells went off in my mind. "Is the content reliable? Am I going to be taken to task by the Court for submitting this?" I was anxious and worried even though the content had been verified and put together with considered "human"-generated legal analysis.
This incident made me recollect what happened when I first joined the legal profession. I would find written memos on my desk with instructions on matters from a particular Senior Partner. When I asked once, whether an email might be easier, I was told that an email was not reliable and that with a written memo, he was assured that I would receive the message. We all know better than to argue with our bosses but eventually, the written memos did move onto become emails, perhaps with the realisation that the email instructions would reliably reach me, even after office hours.
As with each industrial and technological transformation in history, be it the steam engine, electricity, digitalisation with personal computers, connectivity with the Internet and now AI, change and transition always bring with them anxiety and the fear of the unknown. Humans are wired to be untrusting of that which we cannot control – and maybe even rightly so.
With AI, we feel this acutely in Singapore. Many Members in the House have spoken about these concerns and the anxieties felt by Singaporeans from all walks of life. As the adage goes, "change is the only constant". Fear of the unknown is a natural reaction, but we should use it as a galvanising force to re-think old ways, learn new ones and as a result, seize new opportunities and grow.
This Motion is therefore a timely one. It recognises that harnessing AI to grow, is a double-edged sword. On the one hand, while AI can be a driver for the next phase of Singapore’s economic development; on the other, if its development and deployment is left unfettered, it can lead to societal ills such as job displacement and widening inequality.
As the Prime Minister pointed out during his Budget Statement, AI is but a "tool". How we harness it and manage its deployment will shape our economy, our jobs, our lives. Our approach to AI-enabled growth, as the Motion states, therefore, must be anchored in fairness, resilience and opportunities for all. The Motion resonates because it is about putting people at the centre of Singapore's approach to AI-enabled growth. Growth must be inclusive and benefit our people. We cannot have jobless growth at all costs.
Sir, awareness of AI's disruptive nature to the workplace and to our workforce is extremely high. The anxieties and concerns of our workers and PMEs across industries are not hypothetical. They are real, even quantifiable. A recent NTUC survey found that more than half of our PMEs feel an urgent need to upskill just to stay relevant. Nearly a third are actively anxious about being replaced. Other studies have shown that half of Singaporeans fear that their roles could be automated, and many are concerned that AI will benefit the bottom-lines of corporations more than it benefits the everyday worker.
Our young graduates entering the workforce for the first time face a daunting reality. As AI automates routine execution, employers are raising the bar, demanding higher-order critical thinking and AI collaboration skills from the outset. Left on its own, the AI disruption could very well lead to unfair outcomes. Organisations and individuals who manage a head-start or transition well, will benefit exponentially, while those who do not, will be left behind.
For years, we have proactively anticipated a disruption like this, by investing and imbuing in Singaporeans the value of lifelong learning and the need to regularly upskill through programmes, such as SkillsFuture. This has put us in a good starting position as we push hard on AI adoption, like the National AI Impact Programme that aims to support 10,000 enterprises and help 100,000 workers become more AI fluent.
However, AI fluency and literacy among the general population is also equally important.
On this I would like to raise two points.
First, you will recollect my personal anecdote at the start of my speech. Fluency with any tool, be it computers or smart phones in the past or AI today, is about building confidence.
Mr Lim Boon Heng, a former NTUC Secretary-General shared with me, his experience with the Government's computerisation efforts in the 1980s. It was a strategic decision at the time, but workers were afraid of computers. So, the Government designed computer appreciation courses that were rolled out by the NTUC, using early Apple computers. Familiarisation with the use of the keyboard and for those who remember, playing games like PacMan. Workers slowly got past the fear and embraced the familiarity. Importantly, the key message must be, this is a tool that can help you do a job, better, faster. Now, that new tool is AI.
While it is vital that we upskill our workers to leverage on the AI tools that are relevant for their respective workplaces, AI fluency and literacy should be a national endeavour that is available in our schools, our Community Clubs and even our Active Ageing Centres.
The idea is to embed AI fluency and literacy as a part of life, be it in creating a simple e-greeting card with an AI tool that creates moving graphics or building a billion-dollar company using bots. Only then can we envision an entire people advancing collectively together in an economy with AI-enabled growth.
If embracing AI is a national strategic move, then we should roll out a national AI literacy and fluency programme for all Singaporeans.
Second, supporting workers to become AI fluent should be more than just providing them with the AI tools and the know-how on using them. We must also equip and afford workers the time and ability to learn how to apply the AI tools in their workplaces.
Getting young graduates past the door, and securing older workers and PMEs in new roles are imperative, but if AI is to transform our economy, we must ensure that our workforce learns effectively through deeper learning while persuading our businesses and organisations to create workplaces and systems that allow our workers to test their new skills, learn from mistakes and improve. Learning must be coupled with building capability.
At its broadest and most pervasive use as a tool, AI can generate content, summarise and answer in seconds. We need a workforce that not only can use the AI tool to obtain these outcomes, but to work with AI as a collaborative partner while applying judgment, reason, creativity and context to drive high-impact value – the human elements.
Prof Er Meng Hwa, in a recent Business Times article advocating for deeper learning, gave the example of Micron Singapore, whose in-house AI upskilling initiative did not stop at awareness but allowed employees to use AI tools to extract insights faster, analyse risks better, automate route tasks, plan projects more effectively and improve decision-making.
How do we persuade more businesses and organisations to devote the time and precious resources to obtain these objectives together with us? Upskilling our workforce to ensure that they have the necessary credentials and knowledge may get them past the door, but it is no guarantee that businesses and organisations will employ and train workers in the way that will build on and optimise their AI capabilities.
This Government has been deliberate in focusing our policies on long-term advancement rather than on short-term gains. I am therefore confident that the AI National Council, led by the Prime Minister, will lay out plans and initiatives on the same basis.
In fact, we already have, within our system, the ability for the Government, unions and employers to collaborate closely to achieve the long-term objective of ensuring that our workforce is effectively equipped with the knowledge, skills, deep understanding and practical application outcomes.
Our tripartite model, where all three partners, having built trust, mutual respect and equal partnership over decades, working hand in hand through this new phase of AI adoption, will help us to ensure that our workers, our businesses and our economy can seize new opportunities and advance together.
Before I conclude, I wish to support the proposal by NTUC Secretary-General, Mr Ng Chee Meng, for the setting up of a market intelligence and foresight system contextualised to the Singapore market. We can appreciate how useful it would be to draw insights from information, data points, analysis and the research of tripartite partners to sense-make for early signals, coordinate responses and provide proactive early intervention, where necessary.
That said, while supporting our workers to retrain and move on to different roles to prevent displacement is important, we should also explore the possibility of using information from the same system to identify how the Government can incentivise AI startups to create new jobs and opportunities for our workforce. For example, it has been reported that AI movie production startups in China are supported with incentives and financial support. They are reported to have pioneered micro-dramas or vertical dramas that is a new entertainment format making waves globally.
Sir, if we are to leverage on AI as the next phase of Singapore’s economic development, we must transform, not only our economy but also the lives of every worker, every Singaporean. Mr Deputy Speaker, I support the Motion.
Mr Deputy Speaker : Mr Patrick Tay.
5.20 pm Mr Patrick Tay Teck Guan (Pioneer) : Mr Deputy Speaker, Sir, I rise in support of the Motion. I would like to thank my NTUC sisters and brothers in this House for coming to support this Motion.
Knowledge workers like PMEs are highly exposed to AI, unlike earlier waves of automation that mostly impacted the rank and file. Many of our middle-income PMEs belong to a sandwiched or under-served group. They are expected to perform like the top but are less protected than the bottom and they face increased competition from foreign PMEs. Mid-career PMEs are sandwiched between younger and older dependents, and cannot afford to lose their jobs. Yet they can take a longer time to find new jobs when displaced due to their higher income and age, often at the expense of a pay cut.
We perceive PMEs as privileged and adaptable, who have resources and can take individual responsibility to upskill and also to cope with setbacks. This assumption no longer holds true. AI is set to both augment and disrupt job tasks across all PME sectors at all levels. We must recognise AI as a transformative technology that has the potential to create new opportunities and shared prosperity but also the potential to widen inequality by concentrating wealth and power at the top, especially if guardrails are disregarded for the broad middle in the race to adopt AI.
To this end, I submit that Singapore's approach to AI must be human-centred while AI-enabled growth must be worker-centred. This means that we commit to what I call the "3 Es”. The "3 Es" are equitable growth, enhanced protections and engaged workforce.
First "E", equitable growth. When we talk about AI-driven jobless growth, this does not necessarily mean mass unemployment. However, it may mean that the gains from AI may not trickle down to the broad middle. Earlier this year, the Economic Development Board (EDB) announced that the expected number of jobs to be created fell to 15,700, the lowest in at least 20 years, despite having attracted more investments than the year before. This indicates that while we may not see jobless growth, we may well see growth with less jobs. Jobseekers could be competing for fewer vacancies, underemployment could rise and wages could stagnate. Young graduates may find more challenges securing full-time employment compared to before.
Globally, we have already seen a wave of companies, especially those in the tech sector, announce wide-ranging job cuts citing AI as a cause.
Equitable growth means that gains from AI-enabled growth will be shared with workers, in the form of better wages, welfare and work prospects. As a start, we need to raise our standards for what constitutes fair and responsible retrenchment, such as by requiring early retrenchment notifications, supporting unions to negotiate for retrenchment benefits according to industry norms and designing AI grant incentives with conditions requiring employers to demonstrate efforts to meaningfully re-deploy workers whose roles and tasks are taken over by AI.
As Singapore aims to attract the world's top AI talent to our shores, we must also ensure this builds up and strengthens our Singaporean Core. I ask that the Government encourage reciprocity through programmes, like the Capability Transfer Programme, so that knowledge and expertise flow to our local PMEs. At the same time, the Government can also invest in homegrown AI talent by sending them on training stints to top AI companies overseas through programmes like the Overseas Market Immersion Programme. Bringing in global expertise and developing our own global talent pipeline are two sides of the same coin. Both deepen the capabilities of our local workforce.
Second "E", enhanced protections. Inevitably, some workers will be impacted in the transition to AI. We cannot leave them to sink or survive on their own. They will need career guidance, financial support and grace to bounce back stronger. I thank the Government for launching the Jobseeker Support Scheme for the involuntarily unemployed workers to benefit from transitional support for up to six months while they train or search for their next job.
The income threshold for Jobseeker Support Scheme is currently set at $5,000 excluding CPF, which would only cover less than 20% of resident PMEs. I hope that the Government will consider raising this threshold to the gross median resident PME income, currently at $8,400 as of 2025, or consider some other suitable schemes of equivalence to address the needs of impacted PMEs. By the same token, the Government can also consider allowing those with HDB housing loans a temporary deferment for up to six months, especially if they are unable to meet the mortgage payments to ease immediate cashflow needs.
Singapore has taken a considered, framework-based approach to AI governance. We are not behind. We are being deliberate. Through IMDA's Model AI Governance Framework, the Cyber Security Agency’s addendum to secure agentic AI systems and voluntary testing toolkits, we have encouraged innovation and responsible adoption.
But as AI moves from assisting decisions to making them, including in hiring, promotion and restructuring, we must keep pace. Other advanced economies have already taken the lead to explicitly classify employment-related AI as "high risk".
This matters greatly to workers. Will recruitment AI automatically rank candidates with disabilities lower? If HR relies on an AI tool to shortlist who stays and who goes during restructuring, what recourse does a worker have if the outcome feels unfair? Who is accountable in this case – the HR team, the employer who procured the AI tool or the developer who built it?
These are not hypothetical concerns. A joint Singapore University of Technology and Design (SUTD)-GovTech study found that large learning models can reliably guess personal characteristics, like gender of candidate from other data points like hobbies and volunteering, even when resumes are anonymised.
We are fortunate to have passed the Workplace Fairness Act. Its principles – that employment decisions must be fair and merit-based and that every worker deserves fair access to good jobs – should apply regardless of whether those decisions are made by a human or by an algorithm.
But while these principles are technology-agnostic, our current anti-discrimination levers have yet to explicitly address how they interact with AI-mediated decisions. As AI adoption accelerates, employers need clarity on what responsible use looks like, and workers need assurance that existing protections travel with them into an AI-enabled workplace. We should close this gap, not with regulations that stifles innovation but with clear, practical tripartite guidelines to ensure the just and fair transition. Singapore's strength is our tripartite approach and we should leverage it.
To that end, I ask that the Government consider the following. First, that employers who adopt employment-related AI be guided to conduct risk assessments proportionate to the level of impact and ensure meaningful human oversight. Second, that HR professionals be supported with training and self-assessment tools to use AI responsibly and identify biasness. Officers involved in data governance and cybersecurity can also update their skills and knowledge in this evolving area as more companies adopt AI that is integrated with enterprise data. And third, that workers be given transparency. They should know where AI is being used in decisions that affect them, what guardrails are in place and how existing avenues of redress apply. And fourth, that we explore going upstream, working with AI vendors and developers to ensure that the underlying software meets some baseline principles of fairness and transparency before it reaches our workplaces. The International Labour Organization has started this journey and Singapore, with our tripartite DNA, can be a frontrunner in this space.
Third and final "E", engaged workforce. Workers master AI and figure out how to embed AI into their workflows, not the other way round. Ultimately, an organisation cannot be run by no workers and AI alone. Simply imposing AI from the top will not produce results and can even create resistance and sunk cost. Workers are end-users and experts in their own workflows. They know where AI adds value and where it falls short. If you want AI to work, you have to ask the people who do the work.
We already have a proven mechanism for doing exactly this – our NTUC's CTCs. CTCs bring management, unions and workers together at the company level to co-design transformation plans, pairing technology adoption with job redesign, skills upgrading and better wages.
Let me share one example which the Prime Minister shared during the May Day rally. At Tan Tock Seng Hospital (TTSH), where our Healthcare Services Employees' Union (HSEU) worked with management through the CTC to roll out a Smart Scheduler that could handle multiple shift patterns and cut rostering time from more than 90 minutes to under 15, so that nurse managers could spend more time on other core work instead.
Senior Enrolled Nurse Lilian Teng, 69 years old, who has worked at TTSH for the past 19 years, put it simply: with technology making work less physically demanding, she can continue working effectively for as long as she remains healthy. That is what an engaged workforce looks like.
But company-level efforts alone will not be enough. With the formation of the Tripartite Jobs Council, the Government, employers and unions can now coordinate sectoral transformation with workers at the centre, ensuring that AI training, job redesign and transition support are shaped by those on the ground, not just decided from the top.
Critically, the Tripartite Jobs Council can level up the CTC ecosystem to extend its reach beyond large employers to SMEs that may not have the resources to navigate their transformation alone. CTCs engage workers at the company level. The Tripartite Jobs Council will do it at the national level. Together, they ensure that AI transition is not something done to our workers, but with them. In Chinese, Sir.
( In Mandarin ) : [ Please refer to Vernacular Speech .] Mr Deputy Speaker, AI is here – and it has arrived fast and with force. But we must ask: when AI generates wealth, whose pockets does it go into? I raise three points.
First, share the cake fairly. AI creates wealth, but that wealth cannot flow only to employers. Workers help bake the cake and they deserve a slice of it too.
Second, if jobs are lost, we cannot leave people to fend for themselves. The eligibility criteria for Jobseeker Support assistance can be broadened, so that more PMEs can benefit and have greater security. We must put up the umbrella before the rain comes – prepare for the storm before it arrives.
Third, walk this road together. The AI transition cannot be decided by employers alone. As the saying goes, three cobblers together are better than a Zhuge Liang. The tripartite partners, unions and employers must work together, only then can we go far, steady and fast.
Share the cake fairly and walk forward together. That is the AI future that belongs to every Singaporean – one that puts people at its heart.
( In English ): To conclude, there has been much said about AI as a double-edged sword. This metaphor has been used ad nauseam, but this is not untrue.
AI's impact on the broad middle means that it is a "once-in-a-generation technology" but could also be a once-in-a-generation divider that concentrates gains to those who control AI while displacing the very same workers who helped to design, implement and build it.
Equitable growth, enhanced protections and engaged workforce. These are three principles that must guide us in the way forward if we hope to anchor AI as an enabler in our AI transition in fairness, resilience and opportunities for all, because every worker matters. Mr Deputy Speaker, Sir, I support the Motion.
Mr Deputy Speaker : Minister of State Jasmin Lau.
5.34 pm The Minister of State for Digital Development and Information (Ms Jasmin Lau) : Mr Deputy Speaker, I have listened carefully to Members today. There is genuine concern across the House about what AI will mean for our workers. These concerns are real. The Government shares them.
We cannot slow down the development of AI. But we will not leave its outcomes to chance. We will work hard to secure a different deal between the companies that prosper here and the workers whose effort makes that prosperity possible.
Where companies benefit from operating and growing in Singapore, we will expect a fair deal for workers. Not just in words, but in how jobs are designed, how people are trained and how gains are shared. Where public resources and policies are used in support of business transformation, we expect companies to deliver clear and meaningful outcomes for workers.
In my conversations and engagements across the Ministry of Digital Development and Information (MDDI) and MOE work and through the Economic Strategy Review, the same concerns come up again and again. Will my job exist in five years' time? Will AI widen inequality and leave the vulnerable behind? If AI makes companies more productive, will workers share in the gains?
These are not unreasonable fears. They come from people who have worked hard, built up skills and experience over time, and now sense that the ground is shifting beneath them. I will take each of these questions in turn.
First, on whether today's jobs will continue to exist. Let me be honest. Some roles will change substantially. Roles built primarily around repeating the same steps are the most exposed. This is not a verdict on the value of the people who do that work. It is a signal to us in government and to employers that we need to act now and not after the disruption arrives. And act, we will.
But AI is more than just a technological advancement that replaces jobs. At the same time, it is opening up entirely new ways of working and new kinds of roles that did not exist before.
Some academics have described AI as an "invention of a method of invention". It expands the space of problems that can be solved, the products that can be built and industries that we can create. A small biotech team in Singapore can run experiments that would have required a national lab decades ago. A solo founder can ship software that took a hundred-man firm to deliver three years ago.
So, competition sharpens, but the frontier also moves outward. That is why the Economic Strategy Review Committee that Senior Parliamentary Secretary Goh Hanyan and I co-chaired, focused on identifying new areas where Singapore can use AI to build a real competitive edge. And the Prime Minister's National AI Council will take this forward.
Members have pointed out the impact of AI on PMEs, as AI automates routine and analytical tasks. The Economic Strategy Review team recognised this, which is why helping businesses and workers proactively navigate the transition was the focus of the committee chaired by Minister of State Goh Pei Ming and Minister of State Desmond Choo.
For displaced workers, the committee studied how the Government, employers and unions could offer more timely help. As mentioned in our mid-term update, the Economic Strategy Review is studying ways to encourage earlier retrenchment notifications as raised by Mr Ng Chee Meng.
On PMEs specifically, the committee recognises that they may face greater job uncertainties and will recommend more targeted support. This includes considering enhancements to the Jobseeker Support Scheme, as Mr Patrick Tay suggested, and tapping on private sector expertise to strengthen placement support for this group.
For workers at risk of displacement, the Economic Strategy Review will recommend practical ways to help them move into more resilient roles with stronger demand. We will identify sectors with sustained labour demand and lower AI displacement risk, and we will work with unions and employers in those sectors to create clear, supported entry points for workers making the transition. We must make these pathways walkable and not just visible.
To illustrate, a mid-career worker in a routine administrative role, for example in data entry or customer service, could be worried about AI displacing him. With job facilitation and reskilling support, the worker should be able to move into a sector where there are roles that build on his existing skillsets. For example, the worker could explore adjacent roles in healthcare administration. This is where we are seeing robust demand given the growth of our population healthcare needs, and healthcare requires uniquely human skills that are more resilient to disruption.
All this requires more than courses. It requires employers, unions, training providers and placement support working closely together, so that workers do not fall through the cracks during transition.
No government in the world has all the answers to this transition and I would be wary of any that claims otherwise. What we in Singapore can commit to is this: we will not wait for perfect solutions before acting. We are starting now and we will adjust our efforts along the way.
Second, on inequality. Members are right to worry. Technologies that amplify capability can also amplify gaps between those who adapt quickly and those who struggle to keep up. As Mr Mark Lee points out, some risks we face are that productivity gains accrue more to those already ahead, while the bottom of the career ladder may face erosion.
Our response is to raise the floor and widen the door. This means starting earlier: building AI literacy into our schools, so that all students develop confidence with AI and not just those who have access to resources.
Currently, every ITE and polytechnic student is already taught AI literacy as part of their course, and we are now bringing AI literacy and safe AI tools into primary and secondary school classrooms. This means that all students, regardless of economic background can learn about AI safely. They can also learn how AI can benefit their learning, such as to help them refine their ideas, and they also learn when they should not use AI.
As Minister Desmond also pointed out earlier today, we are committed to supporting students who may not have strong family or parental supervision and support. While AI literacy in school will give them a good and strong foundation, we must continue to develop partnerships with the community and the self-help groups to make sure the supervision and support continue outside of school.
Learning must continue beyond graduation. From the second half of 2026, all of our IHLs will offer selected AI-related courses at significant discounts for their alumni, for a period of one year.
For workers already in the workforce, Singaporeans who complete selected AI training courses will receive six months of complimentary access to premium AI tools. We will track take-up and usage to see if we need to do more.
Every Singaporean, regardless of starting point, should have the chance to experiment with AI tools and to build fluency.
The third question is the hardest and the most important. Will workers share in the gains? We should be clear: this does not happen automatically. Left on its own, technology can lead to very uneven outcomes. That is why this is not just a market question. It is a question of how we shape norms and expectations in our economy. So, let me set out clearly what we expect.
Companies that benefit from AI should invest in their people, not just in technology. That means training as many existing workers as possible and not just hiring new ones. It means facilitating their employees' access to frontier AI tools, creating communities of practice and incentivising learning and upskilling.
It also means redesigning jobs in close consultation with workers, as suggested by Ms Yeo Wan Ling, so that people can work alongside AI, using judgement, context and experience, rather than treating workers simply as a cost to be reduced. And where roles do change or disappear, it means making a serious effort to redeploy and reskill workers within the organisations before turning to retrenchment.
We are not just asking our companies to do national service. We are asking them to do what is in their own long-term interest. In an AI age, human instinct and intuition will remain key. We all know that when we work with AI, we need to steer it. Ask the right questions and apply judgement as we refine the output iteratively.
It is not one shot. If you do not develop people who understand the context of your organisation and use this knowledge to reinforce your AI systems, you will be left with a very shallow and hollow company in future. If companies here replace humans completely with AI, they will find themselves, in future, to have no competitive edge, when AI is available to all companies. They will also find themselves at the mercies of AI companies. So, what we are working towards, is an approach that best positions our companies for sustainable growth in the long term.
Mr Saktiandi Supaat brought up the need for balanced regulatory approaches that do not disincentivise AI adoption. Indeed, we will not seek to legislate our way to good outcomes. That has never been Singapore's primary approach. But we are equally clear that "voluntary" cannot mean "optional in practice".
Where public resources are deployed, we will ask for worker outcomes. We will work with companies to meet these expectations. Where there are persistent gaps, we will review how our support is applied. We will discuss with our tripartite partners on how this can be done fairly and effectively, in a way that incentivises companies to invest in training, job redesign, redeployment and placement.
If we do this well, we will be able to create and sustain good jobs in the AI age. A good job is not just a job that exists. It is one that allows a worker to progress. It should pay fairly and reflect the productivity gains that technology brings. It should build skills that remain relevant, including as part of routine on-the-job training, so that workers are not stuck doing tasks that are easily replaced by automation. And it should give workers a sense of dignity and agency, not reduce their role to simply following instructions generated by machines.
We have seen that when there is strong commitment, this is possible. At PSA, AI and automation have helped deliver record cargo volumes. At the same time, the company reskilled and redeployed more than 2,000 workers into higher-skilled roles. And they continue to hire thousands more, because they are growing faster than the competition.
To Mr Andre Low, I would say: automation and augmentation are not mutually exclusive. Protecting a worker can mean being intentional about automating tasks that are repetitive and physically demanding and upgrading the skills of the same worker so that technology can augment his capabilities as he takes on a higher value role.
Even smaller businesses are playing their part. Take for instance our local pawnbroker Maxi-Cash. In the past, a customer wishing to trade in jewellery would interface with a sales advisor, who would pass on their case to a valuer to assess the authenticity of the jewellery. Maxi-Cash enhanced this process by reskilling 25 of their sales advisors to use an AI-enabled authentication system, which can accurately assess the composition of jewellery in just five seconds. Now, these sales advisors can complement the existing pool of valuers, relieving their workload and reducing the customer wait times. This is the kind of responsible transformation we want to see in Singapore as the norm, not as the exception.
Mr Deputy Speaker, I have listened carefully to the many suggestions and perspectives shared in this House today, from Members on both sides. We may differ on specific policy ideas or on how particular measures should be designed, funded or sequenced. That is the nature of democratic debate, and it is very healthy.
But I believe there is broad agreement across this House on a fundamental principle: that the gains from growth and progress must be shared fairly and broadly with all Singaporeans. This should not be a matter of party or ideology. It is a principle that we must uphold together as Singaporeans.
So, let me say this plainly. If Singapore succeeds with our AI ambitions – and we should never assume success is automatic, because it will require sustained effort, difficult choices, adaptation and perhaps, some good fortune too. But if we succeed, then the Government will ensure that the benefits are widely shared.
The gains must not accrue only to those who already have capital, advantages or access. They must translate into better wages, better opportunities and greater security for all Singaporeans. The best protection for workers is not only redistribution after disruption. It is shaping how gains are created and shared from the outset and ensuring that Singaporean workers retain agency within an AI economy.
This Government has been able to deliver these outcomes over decades of Singapore's development. And we are determined to continue doing so, as we navigate this AI transition. Our policies have never been static. We have continuously adapted, refreshed and strengthened them as circumstances changed. And that discipline will continue.
Ultimately, every Singaporean should be able to look at what Singapore has built and say, "I have a stake in this progress. I have a share in this growth. This future, belongs to me and my family too."
This shared commitment is also what makes Singapore's approach to this transition distinctive. Our strength is not just technology. It is the way we work together, across Government, businesses and unions.
To workers watching this debate, I want to say this directly to you: the Government is on your side, and we are acting before the disruption reaches you, not after. You will not be doing this alone. Our commitment made in this House today is our commitment to you.
To our business leaders: AI gives you powerful new capabilities. But how you use them will define your company's future, and your relationship with the people who built it alongside you. The companies that will lead in 10 years are not those that stripped costs the fastest, but those that built stronger teams by combining human judgement with machine capability.
But I want to be clear about something else as well. Not every business needs to adopt AI, and not every pursuit needs to be seen through the lens of AI transformation. There is real value in things that are fully human created, and that value may grow, not shrink, as AI becomes more prevalent.
When everything around us is auto-generated, optimised and scaled, the things that are not will stand out. The live performance and encore that cannot be repeated. The hand-thrown ceramic bowl that carries the mark of a human hand. The meal prepared with care and craft, not just consistency. The conversation with the calligraphy master who has spent a lifetime honing his art.
I think we will see a revival of appreciation for these things. And Singapore should not just acknowledge this, we should embrace it. Our artisans, our performers, our craftsmen are not swimming against the tide of AI. In a world saturated with AI-generated content, they may find themselves exactly where the world is looking.
Beyond the near-term transition, there is a longer-term question we must answer. What do we need to do now with our education system, to prepare our students for the future world?
We must accept that AI will continue to get better at the tasks which machines do well. All the more, we need to focus on what makes us distinctly human. The curiosity that asks a question nobody has thought to ask. The creativity that connects ideas across domains in ways no training data predicts. The empathy that reads a room, earns trust and knows when the most efficient solution may not be the right solution.
We often call these soft skills. In an AI age, they will become the hard edge of competitive advantage for our people and for Singapore. That is why we will review our education system, to make sure we develop these qualities with the same rigour and intentionality we have always applied to academic excellence.
We must continue to build strong foundations and make sure our students do not become overly reliant on AI shortcuts. Our human brains are muscles that require exercise, and genuine mastery – the kind that holds up under pressure and that AI cannot simply replace – comes from hard work, from practice and from deep understanding. So, it was good to hear Ms Eileen Chong agree with this and we thank her for supporting our approach.
But rigour and exploration are not opposites. The student who has truly mastered something is precisely the one with the confidence to venture beyond it. He will ask harder questions, take on problems without the obvious answers and he will develop interests that are genuinely his own. What we are building towards is an education system that demands both the discipline to go deep and the freedom to go wide. Not just because our students deserve both, but because Singapore's future depends on both.
This will not mean abandoning our standards. It will mean expanding what we count as excellence. A student who asks the unexpected questions, who pursues something deeply out of genuine interest, who can hold two contradictory ideas and work through them – that student is not behind. In the world that we are building, that student may be ahead of all of us.
We are committed to doing this, together with our educators, our parents and young Singaporeans themselves. Because if we get this right, if we develop a generation that is not just AI-literate but deeply human, then Singapore will not just survive this transition. We will be the kind of society that the next era of human progress is built around.
Mr Deputy Speaker, we have been honest today about what this transition will demand – of the Government, businesses and workers. Not every path will be smooth. Some will face real disruption and our responsibility is to ensure no one faces it alone. We will make AI work for Singaporeans. And we will ensure that as our economy grows, our workers move forward with it.
But I want to end where I believe our attention must ultimately rest – on the generation we are building. If we develop Singaporeans who are curious, creative and deeply human, people who can ask the questions that machines cannot and earn the trust that algorithms never will, then we will not merely manage this transition. We will define what comes after it. I support this Motion. [ Applause. ]
Mr Deputy Speaker : Senior Minister of State Desmond Tan.
6.00 pm The Senior Minister of State, Prime Minister's Office (Mr Desmond Tan) : Mr Deputy Speaker, Sir, I begin by declaring my interest as the Deputy Secretary-General of NTUC and the executive secretary of the Singapore Industrial and Services Employees' Union (SISEU), where I am closely involved in supporting our workers. Today, I want to continue to support our senior workers and reflect their concerns in the age of AI.
Let me start by sharing about Mdm Foo, a 55-year-old jobseeker who approached NTUC's e2i for assistance. After leaving her previous job of more than 20 years, she found that the job search process had changed quite dramatically. Even resume writing has changed. Resumes used to be written for people, but she found out that today, they are often screened by machines first. Job applications also moved to digital portals that are not so intuitive for people like her to navigate. So, she felt lost and uncertain.
Mdm Foo's experience is not uncommon among senior workers and reflects their anxieties about changing work processes. For some, AI presents true opportunities. For others, it creates uncertainty and anxiety. And for many of our senior workers, their experiences are shaped by three key gaps that I think we collectively must try to address.
The first is the access gap. While Singapore has made progress in closing the access gap for seniors, smartphone ownership among them still lags behind other age groups. In addition, seniors may have less access to AI tools.
I saw this first-hand at one of the AI workshops organised by my union SISEU for about 90 union leaders whose median age was about 53. While all of them used smartphones, many were trying AI tools for the first time. Understandably, there was some initial hesitation. But with simple, guided use cases, they quickly picked it up and were using AI to generate posters for the union's Family Day and membership campaign. Some even went to the extent to do banners for their families for birthdays and anniversaries.
As we ended the session, many leaders came forward to share with me that they enjoyed the session and now, they realise that it is not so difficult to learn to use AI tools. The only thing they asked for is that they wished the session could be longer and the font on the slides can be bigger for them.
This encouraged me because it shows that the issue is not a lack of willingness, but rather a lack of access and, to some extent, to some of them, it is about confidence, which we can overcome by curating and customising access to AI tools and making time for our seniors to learn and to increase their knowledge.
Second, skills gap. We see a gap in training participation, where MOM's 2025 report found that residents aged 50 to 64 had the lowest training participation rate at 44.5%, compared with about 60% for those who are below 40 years old.
It is easy to tell seniors to go and upskill, to go and take a course and reskill, but in reality, we know that with commitments, with bills to pay, with limited time and energy, taking the first step sometimes is not easy. Many of them, we must remember, have lived through repeated cycles of change and transformation, and may feel fatigued, uncertain or even question the relevance of more training.
These concerns are real. We must make training more accessible for them at a suitable pace, through practical and bite-sized modules, and make AI more relevant to their job skills.
The third is the opportunity gap. Even when senior workers are willing to learn, they may not have the same opportunities to benefit from AI in their actual jobs.
OECD's Employment Outlook 2025 highlights that across OECD countries, opportunities to learn by doing fall with age, where 62% of adults aged 25 to 29 reported such opportunities, but this falls to 45% among those who are 60 and above. In addition, a 2025 Pew Research Centre report found that 73% of workers who used AI at work were aged 18 to 49, while only 27% were aged 50 and above.
This is why we need to work with employers to give our seniors the opportunity to use AI tools and to reap productivity gains in their job. Senior workers bring valuable experience and with AI, these strengths can go even further. I have spoken about this no less than two times in this Chamber.
Research from the Stanford Digital Economy Lab supports this. It highlighted that senior employment in the US has remained resilient and may even have grown with the introduction of AI because they see that seniors bring tacit experience, knowledge and soft skills that enable them to increase productivity with AI.
To our senior workers, we understand your challenges and we are with you in this transition. Take the first step with us. Start a course, try a tool, learn from those around you and you can thrive in the AI economy.
Mr Deputy Speaker, the Motion before the House is important. It emphasises that growth must be anchored in fairness, resilience and opportunity for all and resolves to equip workers to seize these new opportunities. That must also apply to our senior workers.
NTUC recognises that long-lasting impact is best achieved through a partnership approach and has taken proactive steps through an AI-Ready SG initiative, which focuses on three key areas.
First, training and upskilling workers to address skills and access gaps. To close the skills gap, NTUC LearningHub has developed a comprehensive AI learning pathway, with three different levels for learners with different proficiencies: foundational training to build AI literacy and fluency, intermediate training tailored to sectors or job roles, and advanced training for those in deep tech and who want to develop deeper AI specialisation and capabilities.
I am glad to note that to date, there has been strong interest. Since February 2026, more than 4,000 workers have enrolled in LearningHub's AI courses. I am also very happy that 39% of them are seniors.
Dr Neo has suggested certification of competencies. This is something that the LearningHub has already been doing. For example, it works closely with companies to design AI courses aligned with the Government's skill frameworks and that are tailored to companies' needs. We also partner with industry leaders such as AWS and Microsoft to certify learners' competencies based on industry demands. We will continue to expand this to more sectors and more industries.
At the same time, under AI-Ready SG, we are also closing the access gap by providing union members with subsidies of up to 50% for AI premium subscription tools through NTUC's Union Training Assistance Programme (UTAP). I am happy to also let Members know that in the first of these AI tool subscriptions, NTUC's premium subsidy does cover a range of tools, including coding and agent-based tools such as Claude Code, Codex, Manus and others. I think there are a total of 20 or 21 tools.
We are offering this as part of membership privileges only because we are using the existing UTAP funding model catered for our members' training. But we will continue to review this, depending on the take-up and the interest over time.
We are also partnering sector agencies like the Civil Aviation Authority of Singapore to develop sector AI training pathways for our union leaders.
Second, we are supporting firms in business transformation and job redesign through NTUC's CTCs. To date, NTUC has formed 3,800 CTCs, embarked on over 900 business transformation projects, benefiting over 300,000 workers.
Let me share another example. I know you have heard many examples over the course of this debate. It is from the Evergreen Group, a local office and stationary supplier. Through a CTC Grant project with the Singapore Manual and Mercantile Workers' Union (SMMWU), it implemented an AI-powered e-ordering system to automate the ordering process and improve inventory management. With this new system, manual work such as order processing was reduced by about 60%. Workers could focus on higher-value tasks such as managing customer relationships and using data to optimise inventory.
As they became more productive, the company could handle 40% more orders and provide wage increments for its employees. This is what we mean by win-win outcomes – where businesses become more productive and our workers progress with them.
Third, we are improving job matching with new products and services to help workers access good jobs. Let me go back to Mdm Foo from the start of my speech. Through close support from her e2i career coach, she gained a deeper understanding of her skills and the new job market. Her coach also introduced her to NTUC's AI Career Coach and e2i's AI Interviewer. With support and encouragement, Mdm Foo could confidently use these AI tools to sharpen her resume and also practise her interviews before the actual session. I am glad to share that Mdm Foo has found a new role and has gained familiarity with AI in the process.
Mr Deputy Speaker, AI-Ready SG is one example of how we can realise the intent of this Motion. It supports workers to build AI skills, gives them access to tools to apply these skills and works with businesses to improve productivity and create new opportunities.
Looking ahead, we welcome companies and partners to come onboard as we scale our efforts and increase our reach to ultimately deliver better support for our businesses and for our workers.
Mr Deputy Speaker, these efforts are important and we are already seeing encouraging outcomes. But the scale of change brought about by AI is also significant, with great uncertainty and anxiety among workers. This is why tripartism, with its proven track record built over many decades of open communication and trust, is critical to this challenge.
Singapore has navigated major transitions before. In the 1980s, when computers first entered the workplace, workers were concerned that these machines could replace their roles in data entry and filing and companies were anxious about costs, skills shortage and disruptions to their daily operations.
But tripartite partners leaned forward. The Government invested in infrastructure and skills, including the National Computer Board, to drive nationwide adoption of IT. Employers stepped forward to transform their businesses with new technologies and redesigned workflows. The Labour Movement drove skills upgrading en-masse, organised workshops and seminars, preparing workers mentally and practically for change.
Because tripartite partners moved together in solidarity, firms became more productive, workers took on better jobs with better pay and Singapore strengthened its competitiveness.
Mr Deputy Speaker, the Tripartite Jobs Council will be a key platform to realise our shared aspirations for the AI era as laid out in the Motion. It will build on efforts across the Government, employers and the Labour Movement and enable partners to scale outreach, accelerate policy implementation and direct resources so that workers and enterprises can seize opportunities from AI.
The Tripartite Jobs Council will take on a practical and iterative approach. We may not have all the answers upfront, but we are clear that our deep trust built over decades of cooperation and shared goals will allow us to achieve our aspiration of inclusive economic progress. Mr Deputy Speaker, I will now speak in Mandarin, please.
( In Mandarin ) : [ Please refer to Vernacular Speech .] Mr Deputy Speaker, Singapore needs to harness AI to drive the next phase of economic growth. But more importantly, this growth must be built on a foundation of fairness, inclusivity and resilience for all.
Singapore's tripartite partners – unions, employers, and the Government – have worked closely together over many years, building deep trust that has allowed us to unite and overcome challenges together, no matter what difficulties we face. We will continue to support our workers in seizing opportunities and strengthening their competitiveness in the age of AI.
In February this year, the NTUC launched the AI-Ready SG initiative, actively encouraging workers to learn and master AI tools. This initiative helps them bridge the gaps in awareness, skills and access, so that they are better prepared for the AI-driven economy. As the saying goes, "Opportunity favours the prepared and success belongs to the most persistent." The age of AI is already upon us. I hope that everyone will join NTUC in actively upskilling, learning and applying AI.
( In English ): Mr Deputy Speaker, AI is the defining technology of our generation. But we face this challenge with strong foundations built over decades of tripartite cooperation.
To our tripartite partners, let us continue working closely together to help our firms transform and stay competitive, while supporting our workers to remain productive and to maximise opportunities.
To our workers, we will continue to support you to leverage AI.
And to our senior workers, your experience matters and it is my firm belief that it will be an advantage in the AI era. Take that step with us, upskill and learn, including from your younger colleagues and together, we can close the access gap, narrow the skills gap and expand opportunities for all. Because in Singapore, we have always believed that progress must be inclusive, that as we move forward, we move forward together, because every worker matters. Mr Deputy Speaker, I support the Motion. [ Applause. ]
Mr Deputy Speaker : Minister Tan See Leng.
6.16 pm The Minister for Manpower (Dr Tan See Leng) : Mr Deputy Speaker, Sir, let me begin by acknowledging what many Singaporeans are feeling right now – uncertainties, anxieties, a sense that the ground is shifting beneath their feet; the world feeling less predictable than what it used to be, with trade tensions, fragility in supply chains, wars in the Middle East and the sharp rise in oil prices.
Closer to home, Members of this House have spoken about something that weighs on the minds of all of our fellow Singaporeans: the anxiety that AI may erode our skills, our experience built up over years or even take over our jobs. This anxiety has been sharpened by news of large tech firms announcing lay-offs attributed to AI adoption.
These are legitimate concerns and we take it seriously. And a change of this magnitude is indeed unsettling. But AI can and will create opportunities that we cannot yet fully imagine. Of course, it will, at the same time, also bring about disruptions that we cannot fully foresee.
But there are, at the same time, early signs that gives us reason for cautious optimism. Recent global surveys show that two in three companies that made earlier AI-driven cuts are already rehiring. Why is that so? Because they found that AI could handle the predictable and the routine, but customers still wanted human judgement, empathy and the genuine connection that AI could not provide.
Let me offer a small illustration of my own. In the preparation for my speech today, my team used AI to help refine the work to me. It surfaced useful references, including our MOM's newly released study showing only about 6% of firms in Singapore have reduced headcount due to AI adoption.
But one thing it could not appreciate was the impact and the anxiety that many, many workers feel. It could not offer empathy, it could not empathise, it could not understand nuance, nor could it generate policy responses that capture the essence of what workers are really experiencing. And this is what no algorithm can replace.
[Mr Speaker in the Chair]
The Motion before us makes four commitments. The Government and MOM take each one seriously – all of them as foundations to build on and to go beyond.
Mr Ng Chee Meng spoke about the transformative impact of AI on our workforce. The Government has long recognised AI's potential. Our current efforts build on a strong foundation of work already done in this space. We formed our first National AI Strategy in 2019, well before the introduction of ChatGPT and we embarked on national AI projects in areas such as education, healthcare, logistics, security and municipal services.
When large language models exploded onto the scene in late 2022, making AI accessible and general-purpose, we refreshed our strategies with the National AI Strategy 2.0 in 2023 and developed plans to invest over $1 billion in AI compute capabilities, talent and industry development. And this included establishing AI Centres of Excellence and growing the number of AI practitioners.
As AI picked up speed and interacted with major shifts in our external environment, we convened the Economic Strategy Review last year to sharpen our response. And more recently at Budget this year, we formed the National AI Council chaired by our Prime Minister to drive the practical transformation of our economy using AI.
At every step, we have acted proactively with our tripartite partners to drive concrete action and transformation across the sectors. As a result, while we will walk into uncharted waters into an uncertain future, we can do so with some confidence and we are not totally unprepared.
Various Members have raised concerns over the impact of AI on job displacement and many have also put forward thoughtful suggestions on how we can better support workers and businesses through this transition. We hear your concerns and we welcome the suggestions raised by Members on both sides of the House.
There is, in fact, broad agreement across this House on what we are trying to achieve, which is inclusive growth for all in this AI transition. Where we may differ, is in how we get there. Our approach has always been to invest in our people, keep our workers economically valuable and shape how the gains from AI are created and shared. Rather than dwell on fears, on apprehension, we want to be able to inspire and motivate our workforce to continue to grow.
Mr Gerald Giam and Mr Andre Low highlighted structural threats to inclusive growth. I appreciate the seriousness with which they have engaged on this issue. We recognise the conundrums. The question is: where and how to intervene?
Mr Giam proposed a National AI Equity Fund to pay every Singapore Citizen $500 funded by the companies that benefit from AI. Mr Low similarly proposed a payout for those displaced through redundancy insurance. I recognise the need to strengthen our systems to ensure that no one falls through the gap in this transition. And I agree that the broad sharing of productivity gains does not happen automatically, because markets alone will not guarantee good social outcomes.
Let me be clear. The Government has always known this and has always been acting on it. Both Mr Giam and Mr Low's proposals rest on a more pessimistic premise, that Singaporeans are essentially passive passengers in the AI transition, without agency to seize the opportunities and can only rely on support for a journey they cannot steer.
I cannot hold on and I will not hold on to such a premise. Both your proposals are not empowerment. To me, it is a settlement. Resigned to the fact that mass displacement is inevitable and that the best we can do is soften the blow. We should have more confidence in the tenacity and the adaptability of our fellow Singaporeans.
Redistribution alone is insufficient if workers are excluded from the economy. Singapore's tradition has been to invest in people rather than to compensate them for the circumstances; and that is our true policy tradition, rather than what the Member, Mr Low, had described.
The better use of any surplus generated by AI adoption is to fund accessible and effective upskilling that amplifies Singaporeans' value. And to that end, the Government has spent over $10 billion over the last five years on local workforce initiatives.
The choice before us, Members of the House, is between two very different visions. One says you get a handout and then, with that, a small share of the pie that the machines produce. Whereas, on the other hand, we feel that you deserve to grow the pie with the machines and share in our economic prosperity through good jobs and good wages.
The first vision initially may seem generous, but ultimately, caps and diminishes your broader end objectives. The second demands more from the Government, more from employers and also more from workers, but it treats all of our fellow Singaporeans as capable adults, with futures worth investing in, not as a population to be managed through transfers.
And Members of the House, I believe the second vision is possible, because as AI transforms how we work, some jobs will evolve. Some jobs may disappear, but if we are able to get everyone on the same ship moving together, I believe we will prevail. And as Mr Mark Lee and Ms Yeo Wan Ling said, it also creates new opportunities for businesses and workers. Our duty and our focus will be to help all of our workers and our businesses to seize them.
So, we should never build the case in this debate on angst and on apprehension. Our approach is not to fear the future, but let us forge the future ourselves, because that is the true Singapore spirit.
We have seen through each wave of technology and economic restructuring with this very spirit, but we are not complacent. MOM is closely monitoring AI's impact on our workforce. Our inaugural survey of the firms shows that AI is currently augmenting, rather than replacing labour in Singapore. Only about three in 10 firms have adopted AI currently, and amongst the firms that have adopted AI, only a small minority, about 6%, reported reduced headcount.
More commonly, firms are redesigning jobs, they are creating new AI-related roles, indicating that AI is changing how work is done, how they are being re-organised, rather than reducing jobs. And seven in 10 firms using AI are already seeing productivity gains.
However, as I have said, we should never be complacent. We must be prepared that as AI adoption gains pace, momentum and scale, the impact on jobs would be greater. And that is why we constantly prepare ourselves.
We have the goal to enable more businesses to succeed. At the same time, where their workers use AI to do better jobs, rather than be replaced by AI. Where their work becomes more fulfilling, more meaningful, not less. And where the benefits of AI are shared between the businesses themselves and the workforce.
For workers seeing a more flexible pace of work, AI can enable new forms of flexible work and fractional work done by small teams or even "solopreneurs". Beyond flexibility, AI can also reshape who participates in our workforce, including seniors, as Ms Poh Li San spoke about. And we will explore how to scale flexible work models through the Tripartite Workgroup on Senior Employment.
Dr Hamid Razak spoke about the hesitation and anxieties he heard from the ground, especially among older PMEs who wonder if their skills still have a place. And Mr Yip Hon Weng also asked for businesses to be better supported. Let me share what Government is doing to prepare individuals and businesses for this transition.
First, we are reforming our workforce and skills support system to deliver more timely and effective support. As I shared after a five-hour debate yesterday on the Second Reading of the Skills and Workforce Development Agency Bill, this formation of SWDA will bring the skills and employment facilitation capabilities of SkillsFuture Singapore and Workforce Singapore under one roof, making it more seamless, more integrated for individuals and employers to obtain the appropriate support.
We agree with Mr Ng Chee Meng that the intelligence that we have in gleaning and harvesting all the data in the SWDA, this intelligence must continue to be built on a foundation of trust, and we look forward to working closely with our tripartite partners to ensure that our assessment of the labour market continues to be grounded and also current. This will be an important part of how we stay ahead of disruption and support workers driven by AI changes.
This includes platform workers facing the deployment of AVs, as Ms Yeo Wan Ling highlighted. MOM and SWDA, they are already working closely with the Ministry of Transport (MOT) and tripartite partners to strengthen transition pathways for these drivers, ahead of actual AV deployment. I want to add that actually, as a proxy, it is SWDA. But actually, it is SkillsFuture Singapore and Workforce Singapore working closely with MOT currently.
Second, we will do more to improve Singaporeans' AI literacy. Today, there are over 1,600 AI-related courses on the MySkillsFuture website. We will introduce diagnostic tools for individuals to assess their current level of AI readiness and find courses which suit their needs, deliver proven training outcomes that are aligned with employer demand.
From the second half of this year, Singaporeans who enrol in the selected SkillsFuture AI courses will receive six months of free access to premium AI tools. This will help them to apply classroom learning to their daily lives and work. Mr Kenneth Tiong suggested to make this access universal, without condition. That was something that the Government considered carefully. But not all Singaporeans require frontier agent-grade tools. For many, free versions are good enough and widely available.
By tying subsidies to training, we are better able to target those who are more serious about levelling up the use of AI and we help them to make optimal and responsible use of such powerful tools. As Assoc Prof Terence Ho and Mr Alex Yeo shared about earlier on, we hope Singaporeans will tap on the resources available and be proactive in their learning journey.
As Minister of State Jasmin Lau shared, IMDA will also be expanding the TechSkills Accelerator programme to develop AI-bilingual workers, starting with accountancy, legal and HR professionals. [ Please refer to " Clarification by Minister for Manpower ", Official Report, 6 May 2026, Vol 96, Issue 30, Correction By Written Statement section. ] More details will be shared in due course.
Third, to support businesses, I have also emphasised time and again that we have set aside over $400 million for the Enterprise Workforce Transformation Package. I do not want to go too much into it because I believe I have already covered in most of my Second Reading speech yesterday. But Mr Yip asked whether the grants could be tied to worker outcomes conditions. Today, businesses tapping on the Workforce Development Grant (Job Redesign+) , are required to support workforce outcomes, such as wage growth and retention as part of their transformation plan. Later this year, eligible businesses will also receive $10,000 under the redesigned SkillsFuture Enterprise Credit and this can be used to offset out-of-pocket costs for eligible workforce transformation programmes, including those under the Enterprise Workforce Transformation Package.
We agree with Mr Mark Lee that trade associations and Enterprise Workforce Transformation Package addresses these issues while ensuring that the workforce is brought along on the journey. Chambers play a particularly important role in connecting firms with the right expertise and resources. That is why we have appointed the Singapore Business Federation and SNEF as anchor programme partners for the Enterprise Workforce Transformation Package so that integrated workforce transformation support can be brought directly to firms, and we can help to accelerate AI adoption across sectors.
We are also supporting the Labour Movement's efforts to transform businesses and workers. The Government topped up the NTUC CTC Grant by around $200 million in 2025 and extended the grant to 2028. More recently, we worked with NTUC to expand the grant to better support Queen Bee companies to drive cluster-level transformation.
Notwithstanding the fact that I stepped out for a short while to answer a call, I am heartened to hear Mr Ng Chee Meng's sharing of how CTC has helped many businesses transform, while improving the lives of workers. I particularly note his exhortation and his suggestion to further expand the CTC initiative and share his ambition to elevate the CTCs to a tripartite level. We look forward to working with tripartite partners to jointly explore ways to make this a reality.
There are calls for us to go beyond project level interventions, to make a more structural shift in financial incentives for companies to invest in workers. Structural mechanisms, the likes of what Mr Andre Low called for, already exists. Grants, like the SkillsFuture Enterprise Credit, create direct financial incentives for companies to invest in the capabilities of their workers. We will continue to review and enhance such support as part of the work of the SWDA.
I think all of us should appreciate the importance of supporting enterprise transformation, not as a blanket, boiling the ocean strategy, but differentiated, precise and targeted sector-by-sector, company-by-company supporting their enterprise transformation. Even though it is more tedious, I believe it is also in the long run, more sustainable.
Lastly, we have strengthened transition support for workers who are displaced, so that they can bounce back stronger. The Government cannot protect every job but we will certainly do our best to support and protect every worker because every worker matters.
So, with AI transition, work processes will reorganise and change, jobs will also change and some jobs may get replaced. Going through transitions can be challenging. But I assure all of our workers that you will not walk alone.
We have recognised for some time that we must strengthen our support mechanisms as the pace of change accelerates. This is why we launched the SkillsFuture Jobseeker Support scheme (JSS) last year. This is as part of our refreshed social compact under Forward Singapore. The JSS provides temporary financial relief and job search support to involuntarily unemployed individuals. It has made a difference for many Singaporeans, helping them to regain their footing and to return to work with confidence.
Perhaps Mr Andre Low may have some misperception about the scheme. It is not a redundancy insurance because it does not just merely provide a cash payout for displacement. It is a support for re-employment. The JSS supports workers in their re-employment journey. It provides a degree of financial support for the lower- and middle-income precisely so that they do not rush into the first available job that may not be a good fit.
Workforce Singapore compliments the Jobseeker Support Scheme with hands on wraparound support to improve the quality of their job search. And we are cognisant of the fact that prolonged unemployment can harm a worker's longer-term career prospects and that is why the financial support is time bound. It tapers downwards because we believe that the first two to three months when the worker is involuntarily unemployed is when the impact is most felt. So, what we do is we try to raise the level in the initial part to encourage workers, to provide that lift and when it tapers downward, we hope that the workers will be able to find the right jobs for them.
But we hear calls. Mr Ng Chee Meng and Mr Patrick Tay proposed to raise the JS scheme income threshold to better support higher-income individuals. We will look at how the scheme can be improved and we will study this carefully.
We also hear Mr Ng Chee Meng's call for earlier notification of retrenchments to the Government, before employees' last working day, and Mr Mark Lee's reflection of businesses' concerns on this. We want to strike the right balance. Tripartite partners are already discussing shortening the retrenchment notification duration under the ongoing Employment Act review. We, on our part, would like to see notification to the Government happening before or by the last day of work of the affected workers as far as possible, because then this would also enable a timelier employment facilitation support to workers.
To Mr Kenneth Tiong's suggestion on strengthening protections for displaced workers, the Employment Act already provides broad-based protections by establishing procedural safeguards, like notice periods and dispute resolution avenues. This applies to all types of displacements, not just due to AI.
Our AI-enabled growth must be anchored in fairness, resilience and shared opportunity and this is not something that would happen naturally. Mr Vikram Nair asked what safeguards we have to ensure that workers are treated fairly as AI adoption increases. The Government has developed frameworks, such as Model AI Governance Framework for Agentic AI and AI Verify to establish clear responsibilities for actors across the AI supply chain, giving clarity to AI developers and users on responsible practices, including HR technology solution providers. And Mr Saktiandi Supaat rightly pointed out that AI adoption is uneven at varying speeds across sectors, worker segments and businesses of different sizes. Without deliberate effort, the gains from AI could flow to some while others are left behind. In China, the courts have ruled that it is illegal to replace employees with AI purely to cut costs.
Senior Minister of State Desmond Tan and Mr Sanjeev Kumar Tiwari spoke about the work NTUC has done in recent years to equip workers with AI-related skills and supporting workforce transformation. These are exactly the kind of capabilities we should draw on to ensure that more workers and businesses know what support is available and that AI adoption can accelerate across the economy. And this is why we supported wholeheartedly NTUC's proposal to form the Tripartite Jobs Council. The Tripartite Jobs Council will take a coordinated tripartite approach to mobilise enterprises and workers towards fair and resilient growth in an AI era.
As Assoc Prof Terence Ho noted, AI must augment workers, not replace them. We will leverage SNEF’s business advisors and NTUC's CTCs to help businesses adopt AI in ways that drive growth and enhance job roles, prioritising technologies that augment human capabilities and not replace them. We will harness our tripartite partners' strong links with workers, unions and employers to drive broad-based AI training across sectors and career stages, so that no worker is left behind as AI reshapes our journey.
In those technologies or businesses that have to undergo restructuring, we will work with the businesses to help pivot, upskill and reskill the workers.
We will also pay special attention to students and younger workers who are anxious about AI's impact on entry-level jobs. The IHLs continue to enhance their curriculum to keep pace with AI advancements. All IHLs will offer selected AI-related courses for their alumni at a significant discount for a year, starting in the second half of this year.
Graduates entering the workforce can also tap on MOE's SkillsFuture Work-Study Programmes, which combine classroom training with on-the-job training at companies to build both the skills and experience that employers value.
Assoc Prof Jamus Lim called for the expansion of youth apprenticeship pathways. We agree. Structured learning must be complemented with real workplace experience. We will continue to work with sector leads, like the Monetary Authority of Singapore and IMDA to support apprenticeships in high growth sectors, learning from our experience from programmes, like GRIT, we stand ready to refine and to expand these programmes, if necessary.
Mr Speaker, Sir, let me conclude. Singapore has weathered deep disruptions before, from the Asia Financial Crisis to SARS, to COVID-19. Each time, each crisis we came through not because the Government had all the answers, but because workers, businesses and Government stood shoulder-to-shoulder. That is the strength of tripartism.
In many countries, AI becomes a tug-of-war. Workers on one end, business on the other. Progress contested, trust strained. Singapore does not have to go down that road. We work together to make our entire economic pie bigger and make sure that the benefits are widely shared.
To our workers wondering where you stand, there will always be a place for you. Your experience, your judgement, matters more than ever and your commitment to our country, your support through the years, through the decades, we are deeply appreciative. Thank you very much. [ Applause. ]
To all of our young graduates, your ideas, your drive, matters more than ever. Your enthusiasm, your curiosity, that connect, that curiosity that Minister of State Jasmin Lau talked about just now, matters more than ever and we are behind you.
For all of our businesses, if you are unsure, you are uncertain as to where to start, you do not have to figure it out alone. We will walk alongside with you. We will help you to transform, will help you to compete so that together you can create better opportunities both for your businesses and for your workers.
We will not leave the future of work, the livelihoods of our workers, our Singaporeans, to chance. We will shape a transformation that is inclusive, forward thinking, anchored in real action.
Singaporeans will never be helpless passengers to an AI-driven future, but Singaporeans will be our fellow co-pilots as our AI journey takes flight. And we will move forward in the Singapore way with Government, employers and the unions working together to ensure that our AI transformation creates good jobs, clear pathways for every Singaporean worker towards a better future because every worker matters. With this, I rise in support of the Motion. [ Applause. ]
6.50 pm Mr Speaker : In Parliament, we are also adopting and embracing AI as we equip our staff on this journey. Mr Andre Low has a clarification? Leader, please move the exemption first.