MDDI 演讲稿 · 2026-07-21
Josephine Teo部长在IBM Think on Tour新加坡站的讲话
Josephine Teo部长在IBM Think on Tour新加坡站的讲话
要点
- • 新加坡更新的《国家AI战略》优先帮助企业采纳AI并将其融入业务流程以实现可衡量的商业价值和投资回报率,将重点从个人生产力转向企业级影响。
- • 新加坡启动了针对四个关键部门的《国家AI任务》——先进制造、医疗、金融和连接——这些部门合计占国家GDP的40%。
- • 新加坡开发了「AI双语」专业人才模式,培训过程工程师、律师和会计师等领域专家,使其将深度领域知识与AI素养相结合,以便与数据科学家有效协作。
- • 两个互补的计划支持中小企业AI采纳:《国家AI影响计划》与SaaS平台合作,而《企业计算倡议》为定制AI解决方案提供补贴计算资源。
- • 《数字领袖加速启动营》是多方合作计划,IBM是早期参与者,为业务领导者提供实践AI经验、风险意识和组织内可持续、可扩展的AI实施方法。
- • 新加坡开发并在东盟各成员国间通过小国论坛分享SEA-LION大语言模型——一个拥有170亿参数、针对东南亚语言和文化细微差别优化的模型。
- • 新加坡在WEF达沃斯论坛推出了世界上第一个代理AI治理框架,认可自主代理系统产生不同于传统人为失败的新型风险,需要新的治理方法。
完整译文(中文)
MDDI 英文原文译文 · 翻译日期: 2026-07-28
主持人Ana Paula Assis,IBM欧洲、中东、非洲及亚太地区高级副总裁兼主席:我经常回到这样一个想法,即「赢得」企业AI竞赛在不同位置看起来是不同的。随着新加坡更新的国家AI战略的推出,该战略引入了部门使命和由总理领导的新AI委员会,显然你们正在提升新加坡对AI的抱负。从你的角度来看,你能否定义你们所追求的成功版本,以及是什么促使了这里的方法转变?
部长Josephine Teo:我会将我们在更新的国家AI战略中所做的工作描述为「双击」而不是系统重启。当我们在2023年12月推出国家AI战略2.0时,我们已经有了一种感觉,即发展速度会非常快,以至于我们一推出文件,其中的一些部分就已经过时了,它总是需要更新。
但真正有趣的是,当我们实施这项战略时,我们意识到与以前的技术周期相比,某些事情已经反转了。对于之前引入的早期技术,我们作为个人的第一次接触通常是作为劳动力的成员。我们的组织采用了该技术,然后进行了大规模的培训轮次。我们先在工作中学会了如何使用该技术,然后才意识到该技术可能具有个人应用,并开始在家中使用它。
个人计算机就是这样。我们对计算机的第一次接触是在办公室。对许多人来说,与电子邮件的第一次互动也是在办公室。但AI是相当不同的。AI真正民主化了对能够对我们的生活产生深远影响的东西的访问。你和我几乎每天都使用AI。我相当确定,在你的智能手机和其他设备上,你已经在使用AI。今天,情况相反:我们可能比我们的组织更广泛地使用AI。
你们中的许多人可能已经尝试过vibe coding。你正在构建应用程序来跟踪你孩子的日程。你正在使用它来扫描互联网以查找有趣的文章并将其呈现给你。我有一个代理为我做这件事。
所以这就是差距所在:个人生产力改进的速度比企业生产力更快。然后你考虑更大的挑战。这项技术如何影响行业?它如何影响整个国家?这就是我们在更新国家AI战略时的思考。
我们说我们必须更加强调帮助企业采用这项技术并将其整合到现有流程中。对所有企业来说自然而然,也必须有投资回报率。在某个时刻,这必须转化为商业价值,转化为美元和美分,产生真实的、有形的好处。所以这就是我们选择强调的地方。
因此,推动并加快帮助企业,特别是在领导层,思考如何让这项技术发挥作用的努力,不仅仅是为了个别员工,而是在企业背景下。
例如,我们还与IBM进行合作,针对那些在其组织中负责数字化的领导者。我们希望他们从战略上思考如何在其运营中使用AI,以及他们如何可能重新思考其业务模式。
我们有一个国家AI影响项目,希望在更大规模上实现这一点。该项目补充了我们也希望通过国家AI使命实现的目标,这些使命更多关于部门的端到端转型。它们包括先进制造业、医疗保健、金融以及连接性,这些共同对我们的GDP贡献了40%。我们希望推进这些,以便好处不仅停留在个人水平,而是扩展到企业、行业、部门和国家水平。
主持人:继续下一个问题。你的一个观点真的引起了我的共鸣,那就是确保AI驱动包容性增长的承诺,而不仅仅是少数人的生产力。再次,我们深入思考AI如何可以增强人们的能力,而不是简单地替代任务。新加坡如何应对这个机遇,到目前为止你看到了什么早期进展和见解?
部长:当我们考虑包容性时,它也可以涵盖多个维度。
个人层面上存在包容性。我们关注劳动力中可能未充分接触AI如何改变其领域的部分。如果你在技术融合的环境中工作,你很可能会接触到AI工具。但在一些职业,在一些地区,采用可能滞后,可能需要一些时间。
因此,当我们实施劳动力能力发展项目时,一个领域值得更多关注。我们考虑了AI从业者、数据科学家、机器学习工程师。扩大新加坡此类从业者的范围是一项有意义的工作,我们开始着手进行。
我们还注意到还有其他专业人士,各自领域的专家,他们有AI从业者没有的东西。他们对他们在各自工作领域中面临的所有问题都有深入的了解,但不太了解AI如何能帮助解决这些问题。
所以我们开发了AI双语人才的概念——在各自领域的专家,他们掌握足够的AI知识,使他们与数据科学家和机器学习工程师的互动变得更加有意义,也更有可能转化为他们负责领域的真实好处。
我们讨论的是流程工程师这样的人,他们深刻了解生产线和生产流程。我们讨论的是律师、会计师和人力资源专业人士,他们有一些东西要贡献,他们可以帮助组织从AI采用中获益更多。
这是包容性的一种类型:我们如何包括那些其组织和职业不太可能自行成为AI早期采用者的人。
但还有另一种非常重要的包容性。我知道你会很熟悉这一点:技术扩散,通常是处于前沿的公司,如IBM,以各种想象中的方式使用该技术来改进他们的运作方式。但也会有许多中小型企业缺乏知识和资源,甚至不知道从哪里开始。如果我们真正具有包容性,我们也必须有接触中小型企业(SMEs)的项目。
还有一种我们认为包容性也很重要的方式,那就是在国家层面。新加坡很幸运,因为我们承办了像你们这样的伟大技术公司(IBM),因此通过你们,我们接触到了一些最先进的产品和服务。这在其他国家不一定如此,例如在我们的邻国中可以看到。
因此,通过我们参与小国论坛(拥有108个成员)并担任其召集人,我们制定了AI手册。在东盟内部,我们分享我们的开源模型——东南亚语言统一网络(SEA-LION),大型语言模型。它不是很大。我认为只有170亿个参数,与最大的模型相比很小。但它在我们的背景下有真正的用处,因为它捕捉了东南亚的语言和文化细微差别。
这些是我们希望能够推广包容性理念的不同方式。
主持人:我一直欣赏亚洲将所有人纳入AI采用的方式,我认为这真的可以作为世界其他地区的蓝图。部长,你提到了SMEs,对吧?这不仅仅是一项将为大公司带来好处的技术,这是一个非常难以平衡的问题:规模与增长。你如何确保这种规模的采用产生真实的影响,而不仅仅是打勾以确保你真的接触到了所有部分?
部长:这真的很有趣,因为当我与一些小企业互动时,我对他们尝试使用AI的创意程度印象深刻。
我去过一个小型食品和饮料店。当我与业主交谈时,他们告诉我他们已经在使用AI,我很好奇他们是如何使用的。嗯,有两个人,他们最初获得AI技能的方式是去参加培训。
我们有一个个人学习账户,称为SkillsFuture。政府在其中投入信用。你可以使用信用去参加培训,这两位企业家正好这样做了。他们去培训提供商处学习如何提示。他们进行业务的平台也创建了一个AI助手,他们学会了如何利用它来分析他们的销售数据。
他们在这个平台上的业务不是他们全部业务——它占他们收入的约20%。但这对他们来说足以理解他们的销售促进活动。因此,通过学习提示的技能,他们使用由平台提供的这个AI助手来找出他们的哪些促销活动正在产生更好的回报。他们还学会了使用AI工具来生成他们自己的营销材料。
所以虽然可能存在资源或知识差距,但一旦你填补这个差距,采用可以很快。我们建立的计划——国家AI影响项目——与已经为许多中小型企业提供软件即服务(SaaS)产品和服务的合作伙伴合作,我认为向产品中添加AI工具的想法是一种真正合理的方式让企业学习这项技术如何能为他们带来好处。
我们也非常热心于思考可能有更具定制需求的公司。换句话说,通过SaaS的标准产品可能不会满足他们的需求,所以我们有一个平行的项目——我们称之为企业计算倡议,通过与合作伙伴合作,我们提供计算资源,以尝试缓解SMEs的支出需求。这特别适用于当他们需要开发更加定制化的东西,是他们无法通过中介获得的东西时。
所以这些是我们试图给予SMEs优势的不同方式,并将AI是一种民主化技术的想法变为现实。
主持人:你们有一个很出色的项目叫「数字领袖加速训练营」(Digital Leaders Acceleration Bootcamp)。能否为我们进一步介绍一下这个项目如何助力民主化战略?
部长:好的,这源于我们与许多人就其组织内的经验进行的交流。一些人告诉我们「我在学习AI技能,但我的老板没有」。还有许多其他人可能仍然略微落后。所以人们告诉我们需要帮助业务领导者理解这项技术的实用性,我们不能仅仅依靠理论。我们需要给他们实际操作的经验,向他们介绍他们可以合作的潜在合作伙伴,以便在他们的组织中以可持续的方式实施AI。
毕竟,AI不是一种廉价技术。如果架构设计不当,你很容易就会用完代币。这些因素总是会影响业务所有者的计算:需要多少成本?使用这个工具需要花我多少钱?
数字领袖加速训练营(Digital Leaders Accelerator Bootcamp)就是为了这个目的而设计的。它旨在让业务领导者,特别是中小企业业务领导者,对AI的各个方面有更全面、更深入的了解,包括风险而不仅仅是好处,以及他们如何建立正确的系统和流程以有效使用AI。
我们决定这不是政府应该单独完成的事情。我们应该与合作伙伴合作,因为技术发展非常迅速,我们从他们在其他领域(可能在其他国家)的经验中受益。我们已经有这样一个项目,因为数字化之旅为我们推动更广泛的AI采纳提供了很好的基础。因此,扩展这个项目,注入更多AI元素,是一个非常自然的进展。
主持人:非常好,我们为能加入这个项目而感到非常自豪。我认为我们是第三个这样做的组织,我们采取的方式是整合我们在业务转型咨询方面的专业知识与我们的企业AI技术,帮助组织识别有意义的用例,快速构建最小可行产品(MVP),最重要的是,建立内部能力,以便在项目结束后很久继续他们的AI之旅。因此,知识转移,对于许多组织来说,挑战不是AI雄心的缺乏。而是知道从哪里开始以及如何负责任地扩展,这正是我们希望为项目做出贡献的地方。
部长,我想稍微改变一下话题,因为我们刚才讨论的关于抱负、包容性和规模的一切,只有在其下有信任的基础时才能成立。信任、治理和代理AI。我在我的演讲中强调的一点是,信任真的必须首先来,因为没有它,AI采纳根本无法扩展。当你从实验阶段转向在真实运营中嵌入AI时,治理对于维持信任变得至关重要。你在世界经济论坛达沃斯论坛上推出了世界上第一个代理AI框架,并且已经更新了它。当你将信任和治理的这些原则从框架转化为真实世界的实践时,你学到了什么?
部长:好的,如果我们回顾一下,即使在我们推出第一个国家AI战略之前,我们就已经制定了AI治理框架。所以,作为部长,我也对我的前任在我们推出一套战略之前就已经考虑到治理感到相当惊讶。我们继续强调创造一个受信任的AI实施环境。
事实上,AI创造的风险不同于我们习惯的风险。我们的风险管理框架,我们为各种系统安全、消防安全、飞行安全而设置的保障——所有这些都是为了应对人类在循环中时所创建的问题而设想和设计的。
但是,当你使用代理时,当代理被设计为代表人类做出决定时,产生的错误、风险和安全问题类型,老实说,还没有被完全理解。在我们完全理解代理被释放时可能产生的问题范围之前,需要相当长的时间。
我们知道我们人类会创建的问题类型,我们已经设计来防止这些问题变成灾难。我们不确切知道代理系统是否会产生相同范围的错误。因此,我们必须退一步问自己:那么我们需要做什么才能促进代理的采纳?
因此,对我们来说,理解我们为什么设计代理工作流程是非常重要的,我们真的需要花时间思考约束条件、原则以及如何在问题出现时对其进行缓解。
所以还处于早期阶段。我会说,在这方面,我们的意图是与那些帮助他们的客户和网络更有效地使用代理的合作伙伴合作。我认为通过从他们的实际经验中学习,我们有更好的机会改进我们的方法并在这些系统完全投入生产之前设计测试。
主持人:部长,我们的对话即将结束。现在让我们展望一下未来——让我们谈论量子。新加坡有自己的国家量子战略。你认为该国在量子领域最大的机遇在哪里,你今天是如何考虑为此做准备的,而不仅仅是五年后?
部长:事实上,大约20年前,我们就已经投资建立了量子技术中心,很长一段时间以来,我们有专家深入研究这个课题并将他们的能力提升到世界级水平。我真的很高兴他们能够做到这一点。如果你与国际科学界交流,他们会意识到新加坡内的能力。所以这是一个非常好的基础。
当我们开始思考提升我们的量子能力并为量子时代做准备时,有几个我们关注的领域。首先是,你是否有量子安全通信的选项?因为有了强大的量子计算机,今天解密的任何东西可能不再受保护。除了建立量子安全通信网络外,我们如何帮助人们迁移到量子安全密码学?所以这些是一直吸引我们的活动。
最近还有两个令人兴奋的发展。一个是我认为我们处于量子计算发展的阶段,对我们来说提出如何建立技能以开发量子算法并能够增长、构建将与我们的背景相关的应用以及什么将与新加坡的背景相关的应用是合理的。
每年我们要处理数百万个集装箱的移动,如果你去过集装箱堆场,你就会知道这些集装箱现在堆积得几乎十层高。所以,你从一艘船卸下的箱子是堆在第二层还是第八层是有区别的,因为当你需要将这个集装箱重新装到下一艘船上时,如果你把它堆在正确的位置,工作会少得多。
但这些是非常复杂的计算。古典计算机每次箱子无法装载或在不同时间装载时进行一次评估都需要花费数年。所以对我们来说有一个使用案例。当然,我们的金融部门也有量子计算的用途。我们认为对算法和应用已经有了需求的基础。这是我们正在努力的一个领域。
另一个领域同样令人兴奋。直到最近,我们不知道新加坡甚至可以有意义地参与某些类型的量子计算机组件的制造。事实证明,生产过程与我们的半导体制造能力有相关性,特别是在先进封装方面。
不久前在达沃斯,我坐在诺贝尔物理学奖得主约翰·马蒂尼斯旁边,解释新加坡对量子的兴趣,突然他举起手说「我要去新加坡!」。我很好奇,所以我问他「你去新加坡做什么?」。他说「因为你们有先进封装、半导体制造」。他的初创公司,一家名叫Qolab的公司,实际上正在与我们的联合铸造厂合作,设计和生产超导计算机的组件。所以这里有非常令人兴奋的发展。
主持人:太令人兴奋了。最后,部长,你希望房间里的人们从新加坡的未来方向中带走什么,这对我们所有人意味着什么?
部长:好的,用简单的一句话说,我们希望新加坡成为AI创新的家园,我们欢迎你成为我们充满活力的AI中心的一部分。
主持人:我们接受邀请,部长。非常感谢你抽出时间,感谢你为这次对话带来的愿景的清晰性。能够与新加坡和你合作是一个巨大的荣幸。
英文原文
MDDI 官网原始记录 · 抓取日期: 2026-07-28
Moderator Ana Paula Assis, Senior Vice President and Chair for IBM Europe, Middle East, Africa and Asia Pacific: I often come back to the idea that “winning” the enterprise AI race looks different depending on where you sit. With Singapore’s updated National AI Strategy, which introduced the sectoral missions and the new AI Council, led by the Prime Minister, it is clear that you are stepping up the ambition for AI in Singapore. From your perspective, could you please define the version of success that you're aiming for, and what prompted the shift in approach here?
Minister Josephine Teo: I would characterise what we're doing in the updated National AI Strategy as a “double click” rather than a system reboot. When we put out National AI Strategy 2.0 in December 2023, we kind of already had a sense that the developments were going to happen at such a fast clip, that as soon as we put the document out, parts of it would already be outdated, and it would always need a refresh.
But what was really interesting is that, as we implemented the strategy, we realised something had inverted compared to previous technology cycles. With earlier technologies that were being introduced, our first contact as individuals was usually as members of the workforce. Our organisations adopted the technology, then conducted massive rounds of training. We learned how to use the technology at work before we realised that this technology could have personal applications and started using it at home.
The personal computer was like that. Our first encounter with the computer was in the office. For many people, the first interaction with email was in the office too. But AI is quite different. AI is truly democratising access to something that can have a profound impact on our lives. You and I use AI almost daily. I am pretty sure that on your smartphone and other devices, you are already using AI. Today, the converse is true: we might be using AI to a larger extent than our organisations are.
Many of you have probably tried vibe coding. You are building apps to keep track of your children's schedule. You are using it to scan the internet for interesting articles and to surface them to you. I have an agent that does that for me.
So here's where the gap is: individual productivity is improving is at a faster clip than enterprise productivity. Then you think about the bigger challenge. How does this technology impact industries? How does it impact the entire nation? That was what we were thinking about when we refreshed our National AI Strategy.
We said we have to put more emphasis on helping enterprises adopt this technology and integrate it into their existing processes. As is natural for all businesses to expect, there also has to be an ROI. At some point, this has to translate into commercial value, into dollars and cents producing a real, tangible benefit. So that was where we chose to place the emphasis.
Hence, the push to accelerate and boost efforts in helping businesses, especially at the leadership level, think about how they can make this technology come alive, not just for individual employees, but in the enterprise context.
For example, we have also a collaboration with IBM targeting leaders who hold responsibility for digitalisation in their organisations. We want them to think strategically about how AI can be used in their operations and how they might rethink their business models.
We have a National AI Impact Programme that hopes to do this on a wider scale. This programme complements what we are also hoping to do through the National AI Missions, which are more about the end-to-end transformation of sectors. They are advanced manufacturing, healthcare, finance, as well as connectivity, which together contribute 40% to our GDP. We are hoping to push these, so that the benefits don't stay at the individual level, but expand to enterprise, industry, sectoral, and national levels.
Moderator: On to the next question. One point of yours that really resonates with me is this commitment to ensuring AI drives inclusive growth, not just productivity for the few. And again, we're thinking deeply about how AI can augment people and enhance their capabilities, not simply replacing tasks. How is Singapore approaching this opportunity, and what early progress and insights are you seeing so far?
Minister: When we think of inclusivity, it can also cover several dimensions.
There is inclusivity at the individual level. We're concerned about pockets of our workforce that may not have adequate exposure to how AI can transform their domains. If you work in a technology-infused environment, you are very likely to be exposed to AI tools. But in some professions, in some areas, adoption may lag, and it may take some time.
So, when we were implementing our workforce capability development programmes, one area deserved greater attention. We were thinking of AI practitioners, data scientists, machine learning engineers. Expanding the pool of such practitioners in Singapore was a meaningful exercise, and we set about doing it.
We also noticed there are other professionals, experts in their own domains, who had something the AI practitioners did not. They have intimate knowledge of all the problems that they faced in their respective areas of work, but not quite how AI could help solve them.
So we developed this idea of AI bilinguals – experts in their own field who pick up enough AI knowledge that their interactions with the data scientists and machine learning engineers become far more meaningful, and far more likely to translate into and real benefits in their areas of responsibility.
We are talking about people like process engineers, who know the manufacturing line and the production processes deeply. We are talking about lawyers, accountants and HR professionals, who have something to bring to the table, who can help organisations benefit more from AI adoption.
That was one type of inclusivity: how we include people whose organisations and professions were unlikely, on their own, to become early adopters of AI.
But there is also another very important type of inclusivity. I know you would be very familiar with this: technology diffusion, it is very often the companies at the frontier, like IBM, that use the technology in every way imaginable to improve how they function. But there will be many small and medium enterprises who lack the knowledge and resources, and who don't even know where to begin. If we are truly inclusive, we must also have programmes that reach the small and medium enterprises (SMEs).
There is one other way which we think inclusivity also matters, and that's at the country level. Singapore is very fortunate in the sense that we host great technology companies like yourselves (IBM), and so through you, we have exposure to some of the most advanced products and services available. This is not necessarily the case in other countries, as can be seen among our neighbours, for example.
So through our participation in, and as convener of the Forum of Small States, which has 108 members, we developed an AI playbook. Within ASEAN, we share our open-source model – the Southeast Asian Languages in One Network (SEA-LION), large language model. It is not very large. I think only 17 billion parameters, which is small compared to the biggest models. But it has real usefulness in our context because it captures the languages and the cultural nuances of Southeast Asia.
These are the different ways in which we hope to be able to promote the idea of inclusivity.
Moderator: I always admire the way that Asia is bringing all the people along in the adoption of AI, and I think that this could really serve as a blueprint for the rest of the world. Minister, you talked about SMEs, right? It is not just a technology that is going to drive benefits to the large corporations, and this is a very tough balance to strike: scale versus growth. How do you make sure adoption at that scale creates real impact, not just ticking the boxes to make sure that you really reached all the segments?
Minister: It is really quite interesting because when I interacted with some small businesses, I was quite struck by how creative they were in trying to use AI.
I've been to a small F&B outlet. When I was talking to the business owners, they told me that they were already using AI, and I was very curious how. Well, there are two people, and the way in which they first picked up AI skills was to go for training.
We have an individual learning account, called SkillsFuture. The Government puts credits in it. You can use the credits to go for training, and these two entrepreneurs did exactly that. They went to a training provider and learnt how to prompt. The platform they were doing business on had also created an AI assistant, which they learnt to tap to analyse their sales data.
Their business on this platform was not all of their business - it made up about 20% of their revenues. But that was enough data for them to make sense of their sales promotions. So, through learning the skill of prompting, they used this AI assistant that was provided by the platform to figure out which of their promotions were generating better returns. They also learned to use AI tools to generate their own marketing materials.
So while there may be a resource or knowledge gap, the adoption can be quick once you plug this gap. The programme that we put in place, the National AI Impact Programme, works with partners who perhaps already offer Software as a Service (SaaS) products and services to many small and medium enterprises, and the idea that you can add an AI tool to the offerings is, I think, a really reasonable way for the enterprises, to get to learn how this technology can benefit them.
We are also very keen to think about companies that may have more bespoke needs. In other words, a standard offering, through SaaS may not satisfy their needs, so we have a parallel programme – we call it the Enterprise Compute Initiative, where by working with partners, we make compute available, to try and moderate the expense requirement for SMEs. This is especially when they need to develop something that is more bespoke, something that they can't quite get through an intermediary.
So these are the different ways in which we are trying to give our SMEs a leg up, and bring to life the idea that AI is a democratising technology.
Moderator: You have this great initiative called the Digital Leaders Acceleration Bootcamp. Can you tell us a little bit more about how that helps in that democratisation strategy?
Minister: Well, it comes from talking to many individuals about their experiences in their organisations. Individuals were telling us that “I'm learning AI skills but my bosses aren't”. There are many others who are, perhaps, still slightly behind the curve. So people were telling us that we need to help business leaders understand the usefulness of this technology, and we cannot just rely on theories. We need to give them hands-on experience, introduce them to prospective partners that they can also work with, so as to implement AI in a sustainable way in their organisations.
After all, AI is not a cheap technology. You can easily use up tokens if you did not architect it right. These things will always feed into a business owner's calculations: How much does it take? How much does it cost me to use this tool?
The Digital Leaders Accelerator Bootcamp was designed with this purpose in mind. It was designed to give business leaders, particularly SME business leaders, a fuller and deeper understanding of all that comes with AI, including the risks, not just the benefits, and how they can put in place the right systems and processes in order to use AI effectively.
We decided that this was not something the Government should do on its own. We should work with partners because the technology moves very fast, and we benefit from their experiences in other domains, perhaps in other countries as well. We already have such a programme because the digitalisation journey serves as a very useful foundation for us to promote wider AI adoption. So expanding this programme, infusing more AI elements in it, is a very natural progression.
Moderator: That's very good, and we are very proud to join the programme. I think we're the third organisation to do that, and we are doing that as one idea – bringing together our consulting expertise in business transformation with our enterprise AI technology, to help organisations identify meaningful use cases, build Minimum Viable Products (MVPs) quickly, and most importantly, develop the internal capability to continue their AI journey long after the programme ends. So, transferring the knowledge, and for many organisations, the challenge isn't a lack of AI ambition. It's knowing where to start and how to scale responsibly, and that's exactly what we hope to contribute to the programme.
Minister, I want to shift gears slightly because everything we've just discussed in terms of ambition, inclusion, scale only holds up if there's trust underneath it. Trust, governance, and agentic AI. One thing that I emphasize in my talk is that trust really comes first, because without it, AI adoption simply doesn't scale. As you move from experimentation to embedding AI in real operations, governance becomes critical to sustain the trust. You launched the world's first framework for agentic AI at WEF Davos and you have already updated it. What are you learning as you translate these principles of trust and governance from framework to real world practice?
Minister: Well, if we take a step back, even before we put out the first National AI Strategy, we had articulated an AI governance framework. So, for me as a minister, I was also quite struck that my predecessors had already thought about governance even before we put out a set of strategies. We have continued this emphasis on creating a trusted environment for AI implementation.
The truth of it is that AI creates risks that are different than the risks we are used to. Our risk management frameworks, safeguards we put in place to all kinds of systems-building safety, fire safety, aircraft safety – all of these were conceived of and designed to tackle the kind of issues that humans create, when humans are in the loop.
But when you use agents, when agents are designed to make decisions on behalf of humans, the kinds of errors, risks, and safety issues that arise, are honestly not completely well understood. It will be quite a long time before we fully appreciate the range of problems that could be created when agents are unleashed.
We know the kinds of problems that we humans create, and we have designed to prevent those problems from becoming disasters. We don't exactly know whether agent systems will produce the same range of errors. Therefore, we have to take a step back and ask ourselves: What then do we do in order to be able to promote agent adoption?
So, it is very important for us to understand what we are designing the agent workflow for, and we really have to spend time thinking about the harnesses, the principles, and how to mitigate problems as they arise.
So it is still early days. I would say that in this regard, it is our intention to work with partners who are in the business of helping their clients and networks use agents in a more effective way. I think through learning from their actual experience, we have a much better chance of improving our methods and designing tests before these systems are fully put into production.
Moderator: Minister, we are starting to come to a close in our conversation. Let's now take a peek into the future – let's talk about quantum. Singapore has its own national quantum strategy. Where do you see the biggest opportunity for the country in quantum, and how are you thinking about preparing for it today, not just five years down the road?
Minister: As it turns out, from about 20 years ago, we already invested in starting up a centre for quantum technologies, and for the longest time, we had experts who were working to deeply research the topic and bring their capabilities up to world-class levels. I'm really glad that they've been able to do so. If you talk to the international scientific community, they are aware of the capabilities within Singapore. So that's a really good foundation.
When we started thinking about levelling up our quantum capabilities and preparing for the quantum age, there were a few areas that we were concerned about. The first was, do you have the option of quantum safe communications? Because with powerful quantum computers, whatever is decrypted today may no longer be protected. How do we also, apart from building up quantum-safe communications network, help people to migrate to quantum-safe cryptography? So those were the activities that have been engaging us.
Two more recent developments bring a lot of excitement. One is that I think we are at the stage of development in quantum computing that it is reasonable for us to ask how do we build up the skills in order to develop quantum algorithms and to be able to grow, build the applications that will be relevant in our context, and what would be relevant in Singapore's context.
Every year we are dealing with millions of container movements, and if you have been to a container yard, you will know that these containers are stacked by now almost ten levels high. So, it makes a difference whether the box that you are unloading from one vessel is stacked at level two or stacked at level eight, because when you need to reload this container to the next vessel, if you stacked it at the correct place, there's a lot less work.
But these are very complex computations. It would take a classical computer years to make one assessment each time the box could not be loaded or was loaded at a different time. So there is a use case for us. Certainly, our financial sector also has uses for quantum computing. We think that there is already a basis for demand for algorithms and applications. That's one area that we're putting effort into.
The other area is equally exciting. Until recently, we did not know that Singapore could participate meaningfully even in the manufacturing of components for certain types of quantum computers. It turns out the production process has adjacencies with our semiconductor manufacturing capability, particularly in advanced packaging.
Not long ago at Davos, I was sitting next to Nobel Physics Prize winner, John Martinis, explaining Singapore's interest in quantum, when he shot his hand up and said, "I'm going to Singapore!” I was very curious, so I asked him, "What are you going to Singapore for?” He said, "Because you have advanced packaging, semiconductor manufacturing”. His startup, a company by the name of Qolab, is in fact working with our federated foundry to design and produce components for superconducting computers. So there are very exciting developments here.
Moderator: Super exciting. To conclude, Minister, what is the one thing that you hope people in this room take away about Singapore's future direction and what could it mean for all of us?
Minister: Well, in a simple sentence, we would like Singapore to be the home of AI innovation, and we welcome you to be part of our vibrant AI hub.
Moderator: We accept the invitation, Minister. Thank you so much for your time, the clarity of the vision that you brought to this conversation, it's a big privilege to partner with Singapore and with you.