书面答复 · 2026-10-06 · 届国会 15
新加坡数字系统应对代理式 AI 韧性评估
新加坡数字系统应对代理式 AI 韧性评估
李乃怡(Valerie Lee)、安迪(Saktiandi Supaat)、莫哈默法理(Fadli Fawzi)等议员就新加坡 AI 安全院的独立测试能力、新加坡对前沿 AI 模型管控国际倡议的后续行动,以及公共部门代理式 AI 的安全防护措施,向数码发展及新闻部部长杨莉明(Josephine Teo)提问。杨莉明答复说,政府采取基于风险、多层次的治理方式,AI 安全院正建设技术能力评估先进 AI 系统,并确认目前没有机构收到涉及无人监督 AI 代理的网络攻击报告。
为什么重要
杨莉明一并答复七名议员:政府目前不要求前沿模型部署前向政府开放,改与前沿实验室建立信息共享,由新加坡 AI 安全研究所自建评测能力;至今无机构报告由无人监督 AI 代理发起的网络攻击
关键要点
- • IMDA 推出《代理式 AI 治理框架》和《LLM 应用测试入门工具包》,并通过全球 AI 保障沙盒测试生成式和代理式 AI 的安全防护。
- • 新加坡 AI 安全院(AISI)正建设技术能力,评估先进 AI 系统并开发测试与保障方法。
- • 截至目前,没有任何政府机构收到涉及无人监督 AI 代理的网络攻击报告。
- • 新加坡已认可国际社会关于加强前沿 AI 模型安全保障的呼吁,并由国家 AI 理事会提供战略方向。
- • AISI 是“国际先进 AI 测量、评估与科学网络”创始成员,自 2025 年起召集全球专家并制定了《新加坡全球 AI 安全研究优先事项共识》。
政府坚持基于风险、分层管理的治理思路,对高风险应用将继续研究是否需要新规定。但政府未承诺把 AI 安全院的评估结果作为前沿 AI 系统部署的强制门槛,也不要求前沿 AI 开发商必须开放模型访问权限。
议员们担心代理式 AI 失控、逃离管控的风险,质疑公共部门现有防护措施及新加坡 AI 安全院的能力是否足以应对前沿 AI 带来的安全乃至生存风险。
这表明新加坡在前沿 AI 治理上采取审慎渐进的路线,优先构建技术评估能力和国际合作网络,而非对前沿 AI 开发商施加强制性访问或监管要求。
“关于莫哈默法理议员的提问,到目前为止,还没有任何机构收到过涉及无人监督 AI 代理的网络攻击报告。”
参与人员 (8)
完整译文(中文)
Hansard 原始记录
45 李乃怡女士询问数码发展及新闻部长:(a) 新加坡 AI 安全研究所目前拥有什么独立测试和评估能力;(b) 这些能力与其他主要人工智能安全研究所的能力如何比较;以及 (c) 政府在未来两年内对该研究所有什么具体的交付成果和成果预期,包括其评估是否会影响新加坡前沿人工智能系统的部署。
49 安迪询问数码发展及新闻部长:(a) 新加坡认可国际呼吁管制前沿人工智能模型后,将采取什么后续步骤;(b) 考虑到新加坡的认可,如何改进国家人工智能战略 2.0 以及吸引人工智能企业和促进人工智能采用的举措;以及 (c) 新加坡 AI 安全研究所的评估和测试如何支持这些努力。
50 莫哈默法理询问数码发展及新闻部长:(a) 国家人工智能理事会是否以及如何评估了最近业界关于人工智能灭绝风险的警告;以及 (b) 理事会本身是否已制定战略或采取措施缓解人工智能安全和对齐风险。
51 莫哈默法理鉴于最近发生的人工智能代理逃脱控制的事件,询问数码发展及新闻部长:(a) 公共服务使用代理人工智能的现有保护措施是否足够稳健以防范漏洞;以及 (b) 是否有任何涉及无监督代理人工智能的网络攻击已报告给任何政府机构。
杨莉明女士:我的回应将涵盖李乃怡女士、陈以君博士、任梓铭先生和莫哈默法理先生在今天议程文件中提出的问题,以及叶汉荣先生、朱佩玲博士和安迪先生为随后会议提出的相关问题。如果议员对回应感到满意,他们可能希望在此交流后撤回问题。「请参阅《确保在新加坡部署的前沿人工智能模型的安全,以及建立严重人工智能事件的追踪和报告框架》,官方记录,2026 年 10 月 7 日,第 96 卷,第 39 期,口头答问部分。」
新加坡对人工智能(AI)的方法一直是在管理风险的同时促进创新。但随着人工智能系统变得更有能力和自主性,风险也在不断演变。
这些系统可能以意外的方式行动,被恶意行为者操纵或与其他系统有意外的相互作用。能力也在迅速发展,有时比政府和外部评估者能够充分评估的速度还要快。因此我们需要基于风险的多层次方法。
根据风险设置限制。首先,在部署人工智能时,我们必须根据风险校准限制。我们应该考虑所涉及数据和系统的敏感性、给予人工智能系统的自主程度以及任何潜在伤害的严重程度和可补救性。潜在伤害越大,保护措施应该越强。
这就是我们在公共服务中部署人工智能代理的方式。我们考虑代理可以访问什么系统和数据,允许采取什么行动,以及意外或未经授权行动的后果。这些保护措施由政策和治理流程补充,以确保适当的监督和问责。
对于更广泛的经济,资讯通信媒体发展局(IMDA)的《代理人工智能模型治理框架》和《基于LLM应用的测试入门工具包》提供了管理风险和维持有意义的人类问责的指导。此外,全球人工智能保证沙箱便于对生成和代理人工智能风险的现实世界测试,包括其保护措施的稳健性。
对于基本服务和其他高风险应用,需要更强的保护措施。这可能包括对风险进行更严格的测试、独立可验证的证据表明保护措施有效、更严格的部署控制或更严格的监管监督。政府将继续研究对新要求的必要性,特别是在高风险应用中。
加强我们对意外行动和滥用的防护。其次,我们必须加强对意外人工智能行动和滥用的防护。我们不能仅仅依靠告诉人工智能代理做什么。我们还必须故意限制他们能够访问和做什么,进行适当的测试套件,保持适当的人类监督,监控其行为,如果出现问题则限制后果。
同时,我们必须假定恶意行为者将使用人工智能以更便宜、更快和更大规模地造成伤害。鉴于数字服务在我们的经济和社会中的深度嵌入,我们必须不断加强我们的网络安全,并有效利用人工智能进行网络防御。网络安全局(CSA)和政府科技局(GovTech)正在使用人工智能加强政府系统和关键信息基础设施的安全,包括识别漏洞和更快地检测潜在威胁。网络安全局(CSA)还加强了关键信息基础设施运营商的网络安全要求,共享了关于主动威胁的情报以帮助他们采取预防措施,并发布了实用指导以帮助组织加强网络防御和保护人工智能系统。
检测风险和提早应对。第三,我们需要更强的能力来识别部署前后的风险。
新加坡 AI 安全研究所(AISI)正在建立技术能力来评估先进的人工智能系统,并开发实际的测试和保证方法。我们将专注于与新加坡需求相关的能力,同时与研究人员、行业和海外对应机构合作,以利用他们的专业知识和发现。
在部署人工智能系统后,我们必须监控其行为,并从发生的事件和险些事件中学习。例如,在网络安全中,通过网络安全局(CSA)、政府科技局(GovTech)和部门负责人建立了既定的渠道,其中应报告网络安全事件,包括涉及人工智能的事件。我们正在研究如何更好地利用这些现有渠道来识别涉及人工智能的事件,支持补救和改进保护措施,以及是否需要进一步的协调或报告安排。
关于莫哈默法理先生的问题,到目前为止,没有任何机构收到涉及无监督人工智能代理的对其系统的网络攻击报告。我们将继续监控发展,包括海外事件,并应用相关经验教训以加强我们的保护措施和报告安排。
与国际和行业伙伴合作。第四,我们继续与国际和行业伙伴合作。前沿模型在国际上开发和部署,没有任何单一国家或公司能够充分独立评估或管理风险。这就是新加坡最近认可国际呼吁对前沿人工智能加强保护措施的原因。
一些涉及流氓人工智能的情景设想灾难性甚至灭绝级别的风险。我们不会忽视这些风险。我们也不假设每个情景都会实现。因此,我们的方法是密切监控证据,建立理解先进人工智能系统所需的技术能力,并在国际上开展措施以解决严重风险,随着证据的发展。这项工作是我们更广泛的国家人工智能风险方法的一部分。国家人工智能理事会提供战略方向,同时有关机构开发和实施必要的措施。我们将继续调整我们的保护措施,随着人工智能能力和风险证据的发展而进行。
我们还与前沿人工智能开发人员接触,以获取信息和访问他们的模型,如适当的话。我们目前不将其作为要求,因为仅对模型的访问本身不一定能提供风险的完整图景。如果刚性要求导致公司限制其合作或信息共享,甚至可能适得其反。因此,我们的偏好是与前沿人工智能实验室建立强大的合作关系,这鼓励实质性和及时的信息共享。
同时,我们继续建立自己的技术能力,并利用更广泛的来源来识别与新加坡相关的风险。这包括开发人员自己的评估和测试、独立研究和评估,以及其他人工智能安全研究所和国际伙伴的工作。通过利用这些不同的来源,而不是依赖任何单一形式的访问或评估,我们可以对新兴风险及其所需的保护措施发展更全面的理解。
我们已加强与这些国际对应机构接触的努力。我们的新加坡 AI 安全研究所(AISI)是《国际先进人工智能测量、评估和科学网络》的创始成员。自 2025 年以来,我们通过《国际人工智能安全科学交流》召集了全球专家,并制定了《新加坡全球人工智能安全研究优先事项共识》。在过去两年中,我们还主办了一些世界上最重要的科学会议。这些有助于在研究人员、政府和公司之间建立关于人工智能安全科学中最重要差距的国际对齐,创建网络和协调这项重要工作的共同基础。
总之,随着人工智能越来越能够代表我们行动,我们必须相应地引入更强大的保护措施。我们必须清楚地说明允许它做什么,确保人类在关键地方保持控制和问责,并继续加强我们理解新兴风险和在问题发生时做出反应的能力。这将有助于建立对人工智能的信任,作为一项服务公众利益的技术。
英文原文
SPRS Hansard 原始记录 · 抓取日期:2026-10-21
45 Ms Valerie Lee asked the Minister for Digital Development and Information (a) what independent testing and evaluation capabilities the Singapore AI Safety Institute currently possesses; (b) how these compare with those of other leading AI Safety Institutes; and (c) what concrete deliverables and outcomes the Government expects from the Institute over the next two years, including whether its evaluations will influence the deployment of frontier AI systems in Singapore.
49 Mr Saktiandi Supaat asked the Minister for Digital Development and Information (a) what steps will follow after Singapore's endorsement of the international call for control of frontier AI models; (b) how can the National AI Strategy 2.0 and initiatives to attract AI enterprises and encourage adoption of AI be refined in light of Singapore's endorsement; and (c) how can the Singapore AI Safety Institute's evaluation and testing support these efforts.
50 Mr Fadli Fawzi asked the Minister for Digital Development and Information (a) whether and how the National AI Council has assessed recent industry warnings on the extinction risks from AI; and (b) whether the Council itself has developed a strategy or adopted measures to mitigate AI safety and alignment risks.
51 Mr Fadli Fawzi asked the Minister for Digital Development and Information in light of recent incidents of AI agents escaping containment (a) whether existing safeguards for agentic AI use by the Public Service are sufficiently robust to guard against breaches; and (b) whether any cyber-attacks involving unsupervised agentic AI have been reported to any Government agency.
Mrs Josephine Teo : My response will cover the questions raised by Ms Valerie Lee, Dr Charlene Chen, Mr Alex Yam and Mr Fadli Fawzi in today's Order Paper, and the related questions filed by Mr Yip Hon Weng, Dr Choo Pei Ling and Mr Saktiandi Supaat for subsequent Sittings. If the Members are satisfied with the response, they may wish to withdraw their questions after this exchange. [ Please refer to " Ensuring Safety of Frontier AI Models Deployed in Singapore, and Setting Up Framework for Tracking and Reporting Serious AI Incidents ", Official Report, 7 October 2026, Vol 96, Issue 39, Oral Answers to Questions section. ]
Singapore's approach to artificial intelligence (AI) has always been to enable innovation while managing the risks. But the risks are evolving as AI systems become more capable and autonomous.
Such systems may act in unintended ways, be manipulated by malicious actors or have unexpected interactions with other systems. Capabilities are also advancing rapidly, sometimes faster than governments and external evaluators can fully assess. We therefore need a risk-based and multi-layered approach.
Set limits based on risk. First, in deploying AI, we must calibrate limits according to risk. We should consider the sensitivity of the data and systems involved, the degree of autonomy given to the AI system and the severity and remediability of any potential harm. The greater the potential harm, the stronger the safeguards should be.
This is how we approach the deployment of AI agents within the Public Service. We consider what systems and data an agent can access, what actions it is allowed to take, and the consequences of unintended or unauthorised actions. These safeguards are complemented by policies and governance processes to ensure appropriate oversight and accountability.
For the broader economy, the Infocomm Media Development Authority's (IMDA's) Model AI Governance Framework for Agentic AI and Starter Kit for Testing LLM-Based Applications provide guidance on managing risks and maintaining meaningful human accountability. In addition, the Global AI Assurance Sandbox facilitates the real-world testing of risks of generative and agentic AI, including the robustness of their safeguards.
For essential services and other higher-risk applications, stronger safeguards are necessary. This could include more rigorous testing for risks, independently verifiable evidence that safeguards are effective, tighter deployment controls or tighter regulatory oversight. The Government will continue to study the need for new requirements especially in high-risk uses.
Strengthening our defences against unintended actions and misuse. Second, we must strengthen our defences against unintended AI actions and misuse. We cannot rely on simply telling AI agents what to do. We must also deliberately limit what they can access and do, conduct appropriate test suites, retain appropriate human oversight, monitor their behaviour and contain the consequences if something goes wrong.
At the same time, we must presume that malicious actors will use AI to cause harm more cheaply, quickly and at scale. Given how deeply digital services are embedded across our economy and society, we must continually strengthen our cybersecurity and also make effective use of AI for cyber defence. The Cyber Security Agency of Singapore (CSA) and the Government Technology Agency of Singapore (GovTech) are using AI to strengthen the security of Government systems and critical information infrastructure, including to identify vulnerabilities and detect potential threats more quickly. CSA has also strengthened cybersecurity requirements for critical information infrastructure operators, shared intelligence on active threats to help them take preemptive action and issued practical guidance to help organisations strengthen their cyber defences and secure AI systems.
Detecting risks and responding early. Third, we need stronger capabilities to identify risks both before and after deployment.
The Singapore AI Safety Institute (AISI) is building technical capabilities to evaluate advanced AI systems and develop practical methods for testing and assurance. We will focus on capabilities relevant to Singapore's needs, while working with researchers, industry and overseas counterparts to draw on their expertise and findings.
After AI systems are deployed, we must monitor their behaviours and learn from incidents and near-misses when they occur. In cybersecurity, for example, there are established channels through CSA, GovTech and the sector leads, where cybersecurity incidents should be reported, including those that involve AI. We are looking into how these existing channels can be better leveraged to identify incidents involving AI, support remediation and improve safeguards, and whether further coordination or reporting arrangements are needed.
To the question by Mr Fadli Fawzi, no agency has received a report of a cyber attack against its systems involving an unsupervised AI agent so far. We will continue to monitor developments, including incidents overseas, and apply relevant lessons to strengthen our safeguards and reporting arrangements.
Working with international and industry partners. Fourth, we continue to work with international and industry partners. Frontier models are developed and deployed internationally, and no single country or company can fully assess or manage the risks on its own. This is why Singapore recently endorsed the international call for stronger safeguards around frontier AI.
Some scenarios involving rogue AI envisage catastrophic or even extinction-level risks. We do not dismiss these risks. Neither do we assume that every scenario will materialise. Our approach is therefore to monitor the evidence closely, build the technical capabilities needed to understand advanced AI systems and work internationally on measures to address severe risks as the evidence develops. This work is part of our broader national approach to AI risk. The National AI Council provides strategic direction while the relevant agencies develop and implement the necessary measures. We will continue to adjust our safeguards as AI capabilities and the evidence on risks evolve.
We also engage frontier AI developers to obtain information and access to their models where appropriate. We currently do not make this a requirement because access to a model by itself does not necessarily give a complete picture of the risks. A rigid requirement could even be counterproductive if it leads companies to limit their cooperation or information-sharing. Our preference is therefore to build strong collaborative relationships with frontier AI labs that encourage substantive and timely information-sharing.
At the same time, we continue to build our own technical capabilities and draw on a wider range of sources to identify risks of relevance to Singapore. This includes the developers' own assessments and testing, independent research and evaluations, as well as the work of other AI safety institutes and international partners. By drawing on these different sources, rather than relying on any single form of access or assessment, we can develop a more comprehensive understanding of emerging risks and the safeguards needed to address them.
We have stepped up efforts to engage these international counterparts. Our AISI was a founding member of the International Network of Advanced AI Measurement, Evaluation and Science. Since 2025, we have convened global experts through the International Scientific Exchange on AI Safety and developed the Singapore Consensus on Global AI Safety Research Priorities. We have also hosted some of the world's most significant scientific conferences over the last two years. These have helped build international alignment on the most important gaps in AI safety science between researchers, governments and companies, creating networks and a common basis to coordinate this important work.
In conclusion, as AI becomes more capable of acting on our behalf, we must correspondingly introduce more robust safeguards. We must be clear about what it is allowed to do, ensure that humans remain in control and accountable where it matters and continue strengthening our ability to understand emerging risks and respond when problems occur. This will help build trust in AI as a technology that serves the public good.