MDDI 演讲稿 · 2025-05-29
高级政务部长陈杰豪在ATxSummit第二天的开幕主旨演讲
高级政务部长陈杰豪在ATxSummit第二天的开幕主旨演讲
要点
- • 由 AI Verify 基金会和 IMDA 发起的全球 AI 保证试点已吸引来自 8 个司法管辖区、10 个行业的逾 30 家企业，在实际条件下测试真实 GenAI 应用场景。
- • 试点结束后发布的公开报告总结了四条实践经验：风险因应用场景而异、测试数据须专项构建、流水线层面测试洞察更深，以及基于大语言模型的评估需审慎设计并保留人工监督。
- • 新加坡今日发布《GenAI 应用测试入门工具包》并公开征询意见，以自愿性指引形式就何时测试、测试什么和如何测试提供指导，旨在降低负责任采用 GenAI 的门槛。
- • 入门工具包的七项基线测试已在 Project Moonshot 平台上线，企业可自主运行负责任 AI 评估，后续将持续新增测试项目。
- • 新加坡 AI Singapore 与联合国开发计划署将签署谅解备忘录，将「AI for Good」计划推向国际，首批试点覆盖东南亚、加勒比地区和太平洋岛国，致力弥合发展中国家的 AI 素养鸿沟。
完整译文（中文）
MDDI 英文原文译文 · 翻译日期: 2026-06-21
陈杰豪高级政务部长（数字发展与信息部）在ATxSummit第二天（2025年5月29日）的开幕主旨演讲
各位阁下、各位嘉宾、女士们、先生们
我很高兴再次回到新加坡亚洲科技大会（ATxSG）——这里汇聚了科技、商业和政策领域的精英，共同塑造我们数字经济的未来。
人工智能的快速发展——尤其是生成式AI（GenAI）——开启了巨大的潜力，但也引发了迫切而重要的问题：它将如何影响就业、重塑经济，以及对我们的社会产生怎样的影响。
世界各地的人们都在问：AI对他们的生计和未来意味着什么。
各国政府和企业正争相释放AI的潜力，同时也在管控风险，引导其朝着惠及所有人的方向发展。
新加坡正在采取深思熟虑的举措——不仅仅是为了跟上步伐，更是为了主动塑造AI的应用方式，以强化经济、增强韧性、提升人民福祉。
我们的选择至关重要，因为它将决定我们的长期竞争力，以及我们传递给下一代的数字未来。
作为一个互联互通的小国，我们也希望为全球AI生态系统作出贡献，以支持开放数字经济——一个值得信赖、具有包容性且可互操作的生态系统，建立在我们坚实的数字基础和信任文化之上。
因此，我们正在打造一个让AI蓬勃发展的家园，不仅是为了我们自身，更是作为更广泛国际社会中一个值得信赖的节点。
为实现这一目标，我们需要在实践中检验信任的具体面貌，以便能够更有把握地加以推广。
正因如此，AI Verify基金会与IMDA于今年早些时候联合推出了全球AI保障试点项目。
该举措将拥有真实GenAI应用场景的企业与专业AI测试人员配对，使其能够超越理论框架，亲眼看到GenAI应用在实际条件下的表现。
短短数月内，来自8个司法管辖区、涵盖人力资源、医疗保健和金融等10个行业的30余家企业参与了这一举措。
这表明企业希望正确推进GenAI的采用，因为信任是一项商业风险——当客户等利益相关方产生顾虑时，竞争力便会受损。
随着全球AI保障试点项目的圆满结束，我们整理了一份报告，从这些合作中提炼出切实可行的经验，每一条都有助于我们了解企业真正需要什么，才能充满信心地构建和使用GenAI。
第一，风险具有情境特异性。
你所面临的风险取决于你的应用场景。
最有效的测试始于清晰了解哪些内容与你的应用场景相关，哪些不相关。
第二，有用的测试数据很少是现成的。
大多数企业并没有现成完备的数据集。
生成真实且涵盖边界情况的测试场景，需要我们在机器辅助下付出周全的努力。
第三，超越输出结果本身。
有时，问题隐藏在流程的更深处。
测试系统内部发生的情况，能够提供更有价值的洞察——以及更高的保障。
第四，大型语言模型（LLM）可以协助评估，但需审慎使用。
它们速度快、可扩展，但仍需经过周全的设计、校准和人工监督。
在某些情况下，更简单的方法同样有效。
这些不仅仅是技术层面的观察。
它们反映了协作与实践的交汇之处，以及洞察转化为行动的关键所在。
对于希望借鉴这些经验的人——无论您是在商业场景中应用GenAI、构建测试工具，还是参与政策制定——该报告今日起作为资源向公众开放。
报告以更详尽的方式记录了相关洞见，并为那些希望从原则走向落地实施的人提供了实用要点。
在全球AI保障试点（Global AI Assurance Pilot）的基础上，我们正在降低企业采取行动的门槛——让企业能够按照自身条件和节奏推进，无需从零开始。
这将有助于我们培育一个AI生态系统，让企业在其中得到支持与赋能，并成为更广泛信任文化的一部分。
作为下一步举措，我们开发了《GenAI应用测试入门套件》（Testing Starter Kit for GenAI Applications），该套件将于今日向公众开放征求意见。
入门套件是一套自愿性指南，其本质是降低那些希望负责任地采用GenAI但可能不知从何着手的企业的门槛。
该套件汲取了全球AI保障试点的洞见，借助从业者的实践经验，确保指导内容切实可用。
它旨在实现两个目标：
第一，汇集GenAI应用测试的新兴最佳实践与方法论，帮助企业了解优质测试的标准。
第二，就如何开展测试提供实操指引——何时测试、测试什么以及如何测试。
为确保指引具有可操作性，入门套件将辅以测试工具，供企业和开发者自行使用并开展评估。
作为起步，入门套件中的七项基准测试已在Project Moonshot上开放，使企业能够轻松将负责任的AI实践融入其运营。
我们将逐步通过Project Moonshot开放更多测试项目。
入门套件还被设计为可随技术演进、新风险出现及应用场景日趋复杂而持续更新迭代。
无论您是试点聊天机器人的初创企业，还是大规模部署AI应用的大型企业，目标都是让负责任的创新更加触手可及、切实可行。
这在实践、工具与政策之间形成反馈闭环，使治理保持灵活、务实且有利于创新。
更重要的是，这使企业能够在构建可信GenAI方面发挥主导作用——以共同标准、开放框架以及致力于安全负责任创新的社群为后盾。
综合来看，全球AI保障试点助我们积累经验，入门套件让更多人得以应用，而Project Moonshot则提供了规模化的手段。
但仅靠赋能工具并不足以构建一个蓬勃发展的AI生态系统。
要充分释放AI的潜力，我们还需要赋能每一个人——从日常与AI交互的普通用户，到与AI并肩工作的员工，再到能够决定AI使用方式的领导者。
正如我们在技术层面持续投入，我们也必须在人力能力建设上加大投入。
这意味着为人们创造学习、适应和参与的空间——使AI不再是强加于他们的事物，而是他们能够塑造、理解并从中受益的力量。
我很高兴地宣布，新加坡人工智能（AI Singapore，简称AISG）与联合国开发计划署（United Nations Development Programme，简称UNDP）将签署一份谅解备忘录，旨在弥合AI素养鸿沟，推动发展中国家社区的转型。
这将把AISG于2024年启动的、旨在提升国家AI能力的成功项目"AI for Good"（AI4Good）从亚洲推向国际舞台，以支持联合国可持续发展目标4。
目标是帮助个人、组织和企业更好地理解AI的机遇、风险与伦理层面。
我们将与教育工作者共同开发AI教学资源，并通过有针对性的外展活动触达弱势群体，确保在我们作为全球社区共同前进的过程中不让任何人掉队。
AISG与UNDP将在东南亚、加勒比海地区和太平洋岛国探索AI4Good试点项目，以便共同支持更具包容性的AI驱动增长参与。
这份谅解备忘录代表着共同的承诺——让AI惠及所有人，不仅限于AI得以发展和推进的地方，更要延伸至最需要它的地方。
在许多情境下，AI的潜力更难以兑现——受制于在获取渠道、基础设施或准备程度上的差异。
通过这一伙伴关系，我们致力于弥合这些差距，为更多人自信参与数字经济创造机会，从新加坡出发，延伸至我们所在的区域乃至更广阔的世界。
这一努力体现了同样的精神，正是这种精神指引着我们更广泛的工作——培育一个能在最关键之处产生切实影响的AI生态系统。
展望未来，我们必须牢记：AI领域的实质性进步，不仅在于规模或速度，更在于我们能否将其与民众、企业和社区的需求紧密契合。
新加坡将继续跨行业、跨国界开展合作，因为我们相信，一个值得信赖、具有包容性且切实有用的AI未来，必须携手共建。
我们诚邀怀有共同愿景的合作伙伴与我们携手，共同打造这一AI家园，使其成为向善的力量。
非常感谢。
英文原文
MDDI 官网原始记录 · 抓取日期: 2026-06-21
Opening Keynote by Mr Tan Kiat How, Senior Minister of State for Digital Development and Information, at ATxSummit Day 2 (29 May 2025)
Your excellencies, distinguished guests, ladies and gentlemen
I am happy to be back at AsiaTech Singapore, or ATxSG – where some of the best from technology, business, and policy come together to shape the future of our digital economies.
The rapid developments in AI – especially in generative AI, or GenAI – have opened up immense potential, but also surfaced urgent, important questions about how it will impact jobs, reshape economies, and influence our societies.
Around the world, people are asking what AI means for their livelihoods and their future.
Governments and businesses are racing to unlock AI’s potential, while also managing risks and guiding its impact in a direction that benefits all.
Singapore is taking deliberate steps – not just to keep pace, but to shape how AI is used to strengthen our economy, build resilience, and uplift our people.
What we choose to do matters, because it will shape our long-term competitiveness and the kind of digital future we pass on to our next generation.
As a small, connected nation, we also want to contribute to a global AI ecosystem in support of open digital economies – one that is trusted, inclusive, and interoperable, building on our strong digital foundation and culture of trust.
We are therefore building a home where AI can thrive, not just for ourselves but as a trusted node in a wider international community.
To realise this, we need to test what trust looks like in practice, so that it can be scaled with greater confidence.
That is why the AI Verify Foundation and IMDA launched the Global AI Assurance Pilot earlier this year.
The initiative pairs businesses bringing real-world GenAI use cases with specialist AI testers, so that they can move beyond theoretical frameworks and see how their GenAI applications perform under practical conditions.
In just a few months, more than 30 companies across 8 jurisdictions and 10 sectors, including HR, healthcare and finance, have participated in this initiative.
This shows that businesses want to get GenAI adoption right, because trust is a business risk – when stakeholders like customers hesitate, competitiveness suffers.
With the Global AI Assurance Pilot now concluded, we have put together a report that distils practical lessons from these collaborations , each one helping us understand what businesses really need to build and use GenAI with confidence.
One, risks are context specific.
Your risks depend on your use case.
The most effective testing starts with a clear understanding of what is relevant to your use case, as well as what is not.
Two, useful test data rarely comes ready-made.
Most businesses do not have the prefect dataset sitting on the shelf.
Generating realistic and edge case test scenarios requires thoughtful effort from us, with support from machines.
Three, go beyond outputs.
Sometimes, the issue lies deeper in the pipeline.
Testing what happens inside the system can offer more useful insights – and greater assurance.
And four, Large Language Models, or LLMs, can help with evaluation, but only with care.
They can be fast and scalable, but still require thoughtful design, calibration, and human oversight.
In some cases, simpler methods work just as well.
These are not just technical observations.
They reflect where collaboration meets practice, and where insights translate into action.
For those keen to draw on these lessons for your own interests – whether you are applying GenAI in a business setting, building testing tools, or shaping policies – the report is available today from today as a resource.
It captures the insights in greater detail and offers practical takeaways for those looking to move from principles to implementation.
Building on the Global AI Assurance Pilot, we are making it easier for businesses to take action – on their own terms and at their own pace – without having to start from scratch.
This will help us nurture an AI ecosystem where businesses are supported, empowered, and become part of a broader culture of trust.
As a next step, we have developed the Testing Starter Kit for GenAI Applications , which will be released to the public for comments today.
The Starter Kit is a set of voluntary guidelines that, in essence, lowers the barriers for businesses that want to adopt GenAI responsibly but may not know where to start.
It draws on insights from the Global AI Assurance Pilot, tapping on the experience of practitioners to ensure the guidance is practical and useful.
It aims to do two things:
First, it pulls together emerging best practices and methodologies for testing GenAI applications, so that businesses can understand what good testing looks like.
Second, it offers practical guidance on how to go about it – when to test, what to test, and how to test.
To ensure that the guidance is actionable, the Starter Kit will be complemented by testing tools that businesses and developers can use and run assessments on their own.
As a start, seven baseline tests from the Starter Kit are made available on Project Moonshot , enabling businesses to easily integrate responsible AI practices into their operations.
We will progressively make more tests available through Project Moonshot.
The Starter Kit is also designed to evolve as technologies shift, new risks might emerge, and use cases will grow more complex.
Whether you are a startup piloting a chatbot or a large enterprise deploying AI applications at scale, the aim is to make responsible innovation more accessible and achievable.
This creates a feedback loop between practice, tools, and policy that keeps governance agile, grounded, and innovation friendly.
More importantly, it allows businesses to take the lead in building trusted GenAI – backed by shared standards, open frameworks, and a community committed to safe and responsible innovation.
Together, the Global AI Assurance Pilot helped us learn, the Starter Kit enables more to apply, and Project Moonshot provides the means to scale.
But enablers alone do not make a thriving AI ecosystem.
To unlock the benefits of AI in full, we need to empower people too – from everyday users who interact with AI, to employees who work alongside it, and leaders who can make decisions about how it is used.
Just as we invest in the technical side, we must also invest in human capacity.
This means creating space for people to learn, adapt, and engage – so that AI is not something done to them, but something they can shape, understand and benefit from.
I am pleased to share that AI Singapore, or AISG, and the United Nations Development Programme, or UNDP, will be signing a Memorandum of Understanding to close the AI literacy divide and transform communities in developing countries .
This will extend AISG’s successful AI for Good (AI4Good) programme – launched in 2024 to bolster national AI capabilities – from Asia to an international scale, in support of the United Nations Sustainability Development Goal 4.
The aim is to enable individuals, organisations, and businesses to better understand the opportunities, risks, and ethical dimensions of AI.
We will co-develop resources to teach AI with educators, and reach underrepresented groups through targeted outreach, so that no one is left behind as we advance together as a global community.
AISG and UNDP will explore initial AI4Good pilots in Southeast Asia, the Caribbean, and the Pacific Islands, so that we can support more inclusive participation in AI-driven growth together.
This MOU represents a shared commitment to make AI work for everyone – not just where it can be developed and advanced but where it could be needed most.
In many contexts, the promise of AI is harder to realise – shaped by differences in access, infrastructure, or readiness.
Through this partnership, we seek to close these gaps and open up opportunities for more to participate confidently in digital economies, starting here in Singapore, and extending to our region and beyond.
This effort reflects the same ethos that has guided our broader efforts to nurture an AI ecosystem that delivers impact where it matters most.
As we look ahead, we must remember that meaningful progress in AI is not just about scale or speed, but how well we align it with the needs of our people, our businesses, and our communities.
Singapore will continue to partner across sectors and borders, because we believe that a trusted, inclusive, and useful future for AI must be built together.
We invite partners who share this vision to work with us so that, together, we can build this home for AI to become a force for good.
Thank you very much.