MDDI 演讲稿 · 2026-05-25
MOS Jasmin Lau 在 KPMG 新加坡「可信赖人工智能卓越中心」启动活动中的演讲
MOS Jasmin Lau 在 KPMG 新加坡「可信赖人工智能卓越中心」启动活动中的演讲
要点
- • 信任是新加坡AI战略的核心使能因素:没有信任,AI采用停滞的原因不在技术,而在人还没准备好。
- • ESR委员会已确定覆盖关键行业的AI任务,承诺AI收益广泛共享,覆盖中小企业与全体劳动者而非少数先行企业。
- • 影响贷款、招聘、医疗转诊等决策的AI系统必须公平、可解释、可问责,当事人有权知情并申诉。
- • AI审计必须由AI驱动并做持续监测:模型以周为单位演化,以月为周期的传统审计使保证永远滞后。
- • 新加坡推动 AI Verify 在东盟范围采用并认证第三方AI测试机构,目标是成为区域可信AI标准的制定、测试与输出地。
完整译文(中文)
MDDI 英文原文译文 · 翻译日期: 2026-06-09
新闻室 MOS Jasmin Lau在毕马威(KPMG)新加坡「可信AI卓越中心」启动仪式上的演讲 演讲 MOS Jasmin Lau在毕马威新加坡「可信AI卓越中心」启动仪式上的演讲 2026年5月25日
毕马威管理合伙人 Lee Sze Yeng 女士
毕马威合伙人兼AI卓越中心负责人 Lyon Poh 先生
各位业界伙伴与同仁,
感谢今天的邀请。
祝贺毕马威在新加坡迎来第85个年头。
85年不只是一个里程碑。它证明了由人长期一点一滴赢得的信任,是一种持久的竞争优势。今天启动的可信AI卓越中心(CoE),正是把这种精神带入一个新时代。
我想向在座各位致意。是毕马威的合伙人、员工和客户在几十年间建起了这家事务所。任何机构的85年,其实都是85年里无数次「即使不做更容易、也选择做对的事」的个人决定。信誉就是这样积累起来的。而这恰恰也是新加坡驾驭AI所需要的品格。
我们正处在一场大变革之中,所有人都知道。劳动者、公民,以及每一位企业领导者都明白这一点。
今天你去问任何一位劳动者——在银行、在诊所、在制造业车间——许多人会告诉你,他们不确定AI对自己意味着什么。
如果你问政务次长 Jasmin Lau 本人,我也会告诉你,我同样不确定AI对我自己、对新加坡意味着什么。在这个领域,没有人能预测接下来会发生什么。
而我们并不孤单。世界各地对AI的不安正在加剧。我们刷社交媒体了解动态,看到在各地大学毕业典礼上,领导人一谈AI就被喝倒彩。许多国家和民众对这项技术的焦虑,我们感同身受。
一部分焦虑源于真实的伤害,但更多是更根本的:人们担心被甩在后面。他们看到技术飞速进步,听到生产力和利润的巨大增长,然后会想——那也有我的份吗?
新加坡承受不起对此视而不见。我们也不会。我们许多人已在国会谈过这个问题,我们完全有意让AI的收益在全体人口中广泛共享。
今年早些时候,经济战略检讨(ESR)委员会列出了我们的AI雄心。我们确定了覆盖关键行业的AI任务(AI Missions)。我们致力于广基的AI采用——不只在领先企业,也覆盖中小企业和整个劳动队伍。
我们的目标是一个AI赋能的经济:让众多企业及其员工都受益,而不只是先行的少数。
但我与高级政务次长 Goh Hanyan 共同主持的ESR科技与创新委员会也明确指出:信任是核心使能因素。没有信任,采用就会停滞。不是因为技术没准备好,而是因为我们的人还没准备好。
因此,新加坡的AI战略要成功,就必须让我们的人——劳动者和公民——感到自己是其中的一分子,而不只是被动承受者。
对雇员,我们要通过再培训计划、职场治理标准、对哪些环节会发生变化的坦诚对话,让他们看到这场转型在规划时已把他们放在心上。企业在这里要承担非常大的责任。
对公民而言,这还意味着影响他们生活的AI系统——在公共服务、医疗、金融决策中——都必须公平、可解释、可问责。当一个AI系统影响你能否获得贷款、进入面试名单或得到转诊,当事人有权知道为什么,出了问题也有权提出质疑。
这不只是伦理问题。这关乎政府、机构与人民之间最基本的契约。我希望下次 Lee Sze Yeng 女士再问「你信任谁会守护你」时,更多人会说:即便政府在公共服务中全面铺开AI系统,我们依然相信政府会守护我们。
这就引出在座许多人已经在面对的问题:如果治理需要保证(assurance),保证需要审计,那么我们如何审计AI?
我们知道,传统审计靠查验记录、抽样交易、测试控制,这些都是成熟方法。但AI系统截然不同:复杂、对许多人而言不透明、而且持续演化。六个月前表现良好的模型,今天可能因为数据漂移、运行环境变化或模型重训而行为不同。
如果模型不是你自己拥有和设计的,你甚至可能不知道它已经变了。所以,如果你的审计周期以月计,而AI系统以周甚至天为单位更新,那么你的保证永远是滞后的。
要可信且规模化地审计AI,审计职能本身就必须由AI驱动,做持续监测和前瞻性风险管理,而不是周期性复核或事后调查。当AI越来越自主、在更少人工监督下做决策时,这一点尤其重要。
弥合这个鸿沟,需要既懂技术重要性、又有保证业务纪律的机构。这种组合很罕见,但毕马威多年来正是这样做的。
这正是毕马威可信AI卓越中心的设计初衷。毕马威把AI应用于自身的审计、税务和咨询职能,以自己为「零号客户」,作为AI驱动保证的试验场。他们自己先做难的部分,找出方法哪里有效、哪里需要打磨。在这个基础上,卓越中心再与企业合作负责任地部署AI——打造从一开始就内建治理与信任的可扩展AI解决方案。
对新加坡这个国家而言,我们在构建AI治理能力上一直相当有意识——同样,不是作为AI战略的事后补丁,而是从一开始就是战略核心的一部分。
跨境经营的企业面对日益碎片化的标准拼图。新加坡正积极塑造并协调这些标准——推动 AI Verify 等工具在东盟范围内采用,并启动第三方AI测试机构认证计划,让企业知道可以信任谁。目标是让新加坡和立足新加坡的企业成为区域可信AI的标杆——标准在这里制定、测试并输出。
随着更多企业跨境部署AI,对可信、独立保证的需求只会上升。这是新加坡可以引领的领域,我很高兴毕马威也将深耕这一领域。
让我回到开头,回到正注视着这一切如何展开的劳动者和公民。
他们没有要求我们放慢脚步。多数人要求的是被纳入其中。他们想知道AI的收益会被共享、风险会被管控、出了问题会有人负责。
满足这一期待是共同的责任——政府有责任,毕马威等业界领袖和在座各位也有责任。
新加坡正在为此创造条件:治理框架、监管清晰度、人才管道。毕马威决定把可信AI卓越中心落户于此,说明我们走在正确的轨道上。
但仅有框架还不够。真正的考验是新加坡人——为新岗位再培训的劳动者、与AI驱动服务打交道的公民——能否感到AI转型是「与他们一起发生」,而不是「发生在他们身上」。我们也要确保中小企业主能自如地使用陌生的新工具;我们在生态建设上投入越多,中小企业及其员工对这场转型就越安心。
这是我们所有人都应坚持的标准。在这样一个汇聚了毕马威及其伙伴的专业与担当的场合,我相信我们能够达到它。
非常感谢。
英文原文
MDDI 官网原始记录 · 抓取日期: 2026-06-09
Newsroom MOS Jasmin Lau’s Speech at KPMG Singapore’s Launch of Trusted AI Centre of Excellence Speeches MOS Jasmin Lau’s Speech at KPMG Singapore’s Launch of Trusted AI Centre of Excellence 25 May 2026
Ms Lee Sze Yeng, Managing Partner, KPMG
Mr Lyon Poh, Partner and AI CoE Lead, KPMG
Industry partners and colleagues,
Thank you for having me today.
Congratulations to KPMG on your 85th year in Singapore.
Now, 85 years is not just a milestone. It is proof that trust, which is earned by humans consistently over time, is a durable and competitive advantage. Today's launch of the Trusted AI Centre of Excellence (CoE) carries that same spirit into a new era.
I want to acknowledge the people in this room. The KPMG partners, the staff, the clients who have built this firm over many decades. 85 years of any institution is really 85 years of individual decisions to do the right thing even when sometimes it was easier not to. That is what credibility is made of. And it is also exactly the disposition Singapore needs as we navigate AI.
We are in the middle of something big, and everybody knows it. The workers, the citizens, and every company leader understands it.
If you ask any worker today - in a bank, in a clinic, on a manufacturing factory floor, many will tell you they are uncertain about what AI means for them.
If you ask the Minister of State Jasmin Lau, I would also tell you that I am not sure what AI would mean for myself as well as for Singapore. It is not a space where any of us can predict what is going to happen next.
And all of us are not alone. Around the world, we are seeing a growing unease about AI. We follow social media to see what is going on, we watch as across university graduation ceremonies, leaders are getting booed when they talk about AI. We are acutely aware of the anxiety that many countries and populations have about the technology.
Some of the anxiety stems from real harms, but a lot of it is more fundamental: people are worried about being left behind. They see the technology advancing fast, they hear about enormous gains in productivity and profit, and then they wonder - is that also for me?
Now, Singapore cannot afford to ignore this. And we will not. Many of us have spoken in Parliament about this issue, and we fully intend for the gains of AI to be shared broadly across the population.
Earlier this year, the Economic Strategy Review (ESR) committee set out our AI ambitions. We identified AI Missions across key sectors. We arecommitted to broad-based AI adoption — not just among leading firms, but also across our SMEs and our workforce.
The goal that we have is an AI-empowered economy where many companies and their workers all benefit. Not just the few who decide to move first.
But the ESR Committee on Technology and Innovation - which I co-chair with SPS Goh Hanyan – also made clear that trust is a core enabler. Without trust, adoption stalls. Not because the technology is not ready, but because our people are not.
Singapore's AI strategy will therefore only succeed if our people - workers and citizens - feel that they are part of it, not just subject to it.
For employees, we need to show them - through reskilling programmes, through workplace governance standards, through honest conversations about where changes will happen - that this transition is being managed with them in mind. Companies have a very big responsibility to play here.
For our citizens, it also means that AI systems have affected their lives - in public services, in healthcare, in financial decisions – all of these must be fair, explainable, and accountable. When an AI system influences whether you get a loan, a job shortlist, or a medical referral, that person has a right to understand why, and a right to challenge it if anything goes wrong.
This is not just about ethics. It is about the basic compact between a government, its institutions, and its people. I hope that the next time Ms Lee (Sze Yeng) asks a question about who is that someone you trust to have your back, more of you will say that you trust that the government has your back, even as we roll out AI systems across the public service.
This brings me to something many of you are already grappling with in this room. If governance requires assurance, and assurance requires audit, then how do we audit AI?
We know that traditional audit works by examining records, sampling transactions, testing controls. These are all proven methods. But AI systems are fundamentally different. They are complex, often opaque to many of us, and they evolve continuously. A model performing well six months ago may behave differently today because the data has shifted, the operating environment has changed, or the model has been retrained.
If you don’t own and design your own model, you may not even know that the model has changed. And so, if your audit cycle runs in months but your AI system updates in weeks or days, then your assurance is always behind.
To audit AI credibly and at scale, the audit function itself must be AI-powered, with continuous monitoring and proactive risk management, not periodic reviews or post-hoc investigations after something goes wrong. This matters especially when AI becomes more autonomous, making decisions with less human oversight.
Closing that gap requires firms that understand both the importance of technology and the discipline of assurance. That is a rare combination, but that is also what KPMG has done over the years.
That is what KPMG's Trusted AI Centre of Excellence is precisely designed to do. KPMG is applying AI to its own audit, tax, and advisory functions using itself as "client zero", the proving ground for what AI-powered assurance looks like. They are doing the hard work themselves, finding where the approach works and where it needs refinement. From that foundation, the CoE can then work with companies to deploy AI responsibly – creating scalable AI solutions with governance and trust built in from the start.
For Singapore as a country, we have been quite deliberate about building AI governance capabilities – again, not as an afterthought to our AI strategy, but right from the start, as a core part of it.
Companies operating across borders face a growing patchwork of standards. Singapore is actively working to shape and harmonise these standards - driving ASEAN-wide adoption of tools like AI Verify, and launching a programme to accredit third-party AI testers, so companies know who they can trust. The goal is to make Singapore and Singapore-based companies the benchmarks for trusted AI in the region, the place where standards are set, tested, and exported.
As more companies deploy AI across borders, the demand for credible, independent assurance will only increase. This is a space where Singapore can lead, and I am glad that this is also the space that KPMG will be playing in.
So, let me end where I began, with the workers and citizens who are watching how this unfolds.
They are not asking us to slow down. Most of them are asking to be included. They want to know that the gains from AI will be shared, that the risks will be managed, and that when something goes wrong, someone will be accountable.
Meeting that expectation is a shared responsibility - for government, and also for industry leaders like KPMG and others in this room.
Singapore is building the conditions for this: the governance frameworks, the regulatory clarity, the talent pipeline. KPMG's decision to anchor its Trusted AI Centre of Excellence here tells me we are on the right track.
But frameworks alone are not enough. The real test is whether the people of Singapore - workers retraining for new roles, citizens interacting with AI-driven services – the real test is for them to feel that the AI transformation is happening with them, not to them. We also have to make sure that our SME owners feel comfortable navigating the new and unfamiliar tools, and the more effort all of us put into building this ecosystem, the more our SMEs and our population working in these SMEs will feel comfortable with the transition that is happening.
That is the standard we should hold all of ourselves to. And in a room like this one, with the expertise and the accountability that KPMG and its partners bring, I believe that we can meet it.
Thank you very much.