Last updated: 2026-06-09 209 debate records
Source: SPRS Hansard · PAIR Search Digests assisted by AI
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Parliamentary AI Focus

First-hand records of Singapore parliamentary debates on AI, with AI-assisted English digests, MP positions, and policy-pattern insights.

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Total records
209
Years covered
2015-2026
Updated
2026-06-09
Type mix
Written Answers 86 / Budget Debate 59 / Oral Answers 55 / Motions 9
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15 Parliament Heated controversy

An Economy of the Future that Works for All (Main Debate)

On 5 August Parliament debated the Workers' Party motion "An Economy of the Future that Works for All", moved by Mr Kenneth Tiong (Aljunied) and standing also in Assoc Prof Jamus Lim's name. Twenty MPs spoke over more than six hours. The original motion asked the House, "notwithstanding" the Economic Strategy Review, t...

Policy Signal: The AI diffusion gap was pushed to the centre of Parliament's economic debate: a 4% core-process adoption rate and a $20 billion versus $150 million comparison reframed compute access as infrastructure policy rather than a one-off grant. The Government did not accept subsidised compute pricing but committed to track take-up of the Enterprise Compute Initiative and refine it as needed, while the Jobseeker Support Scheme income threshold, legislated retrenchment benefits and the energy and water costs of data centres were all left as items for further review.
Open digest, stances, and transcript

On 5 August Parliament debated the Workers' Party motion "An Economy of the Future that Works for All", moved by Mr Kenneth Tiong (Aljunied) and standing also in Assoc Prof Jamus Lim's name. Twenty MPs spoke over more than six hours. The original motion asked the House, "notwithstanding" the Economic Strategy Review, to believe in a more equal and inclusive economy driven by dynamic local companies; Mr Edward Chia moved four amendments replacing "notwithstanding" with "in line with" and adding global enterprises and external demand, and the two were debated as a single question. AI ran through the whole sitting. Mr Louis Chua set some $20 billion of annual land sales proceeds against $150 million for the Enterprise Compute Initiative, the "digital land" on which local firms must build, and $1 billion over five years for national AI research, noting that only 4% of firms had embedded AI into core business processes by 2026, at 15% among SMEs against 63% for larger firms, and proposed an "HDB model for compute" with a published rate card. NMP Mark Lee reported 5.7% second-quarter growth and 12.2% manufacturing growth on AI-related electronics demand, but said businesses joke that if you are not AI you are "BI". Ms He Ting Ru warned that AI-driven data centres consume energy and water, raise emissions and utility prices and disrupt nearby communities. Mr Andre Low proposed a "Fair Start Promise" as AI automates junior tasks. Replying, Minister of State Dinesh Vasu Dash cited 32,800 entry-level PMET vacancies in the first quarter of 2026, and Senior Minister of State Low Yen Ling said the Enterprise Compute Initiative was meant to kickstart adoption and would be monitored. No vote was taken at this sitting.

Key Points
  • • The original motion read "notwithstanding" the ESR; Mr Edward Chia's four amendments changed it to "in line with" and added global enterprises and external demand
  • • Mr Louis Chua cast compute as the land of the AI economy: about $20 billion in annual land sales proceeds versus $150 million for enterprise compute and $1 billion over five years for national AI research
  • • Only 4% of firms had embedded AI into core business processes by 2026, at 15% among SMEs against 63% for larger firms
  • • Ms He Ting Ru said AI-driven data centres consume energy and water, raise emissions and utility prices and disrupt nearby communities
Government Position
Replying for the Government, Minister of State Dinesh Vasu Dash and Senior Minister of State Low Yen Ling backed Mr Edward Chia's amendments and argued the Economic Strategy Review is an actionable blueprint rather than a patch on a failing model, citing resident unemployment of 2.9% in March 2026 and 32,800 entry-level PMET vacancies in the first quarter. On AI, they said the Enterprise Compute Initiative is meant to kickstart adoption and build momentum, with take-up monitored and support refined as needed, and pointed to 3,800 Company Training Committees, the PACT partnership programme and 10 SME Centres as tripartite capability building. Legislated retrenchment benefits and a stronger Jobseeker Support Scheme would be studied under the Employment Act review workgroup.
Questioning Position
Eight Workers' Party MPs divided eight structural questions between them and all supported the original motion. Mr Kenneth Tiong proposed a special zone around NTU where state land is priced at development cost rather than market scarcity value. Mr Louis Chua treated compute as the land of the AI economy and called for subsidised capacity for SMEs with a published rate card, an "HDB model for compute". Mr Andre Low proposed a "Fair Start Promise" and proper paid apprenticeships with CPF as AI compresses entry-level roles. Mr Fadli Fawzi and Mr Pritam Singh pressed for legislated retrenchment benefits and a universal redundancy insurance scheme. Ms He Ting Ru questioned the energy, water and land costs of data centres, and Ms Eileen Chong asked that regional talent schemes be judged on outcomes rather than headcount.
"In the AI economy, compute is to value creation what land was to the industrial economy, the scarce foundational input on which everything else is built."
Original transcript excerpt
Mr Kenneth Tiong moved that the House, notwithstanding the Economic Strategy Review, believes in a more equal and inclusive economy and an economic engine driven by dynamic local companies, healthy domestic demand and Singaporeans venturing abroad. He said capable AI agents and models will reduce entry-level hiring, and proposed a special zone around NTU where state land is charged at cost recovery rather than market scarcity value. Mr Edward Chia moved four amendments aligning the motion with the ESR and adding global enterprises and external demand, citing AEM, whose thermal control technology screens power-hungry AI chips. Mr Louis Chua contrasted some $20 billion of annual land sales proceeds with $150 million for the Enterprise Compute Initiative and $1 billion over five years for national AI research, noting that only 4% of firms had embedded AI into core business processes by 2026, and called for an HDB model for compute. Mr Andre Low proposed a Fair Start Promise and paid apprenticeships; Mr Gerald Giam a guild for skilled trades; Mr Fadli Fawzi and Mr Pritam Singh legislated retrenchment benefits and universal redundancy insurance. Ms He Ting Ru raised data centres' energy and water use. Dr Wan Rizal said about 31% of NTUC Company Training Committee grant projects this year are AI-related, up from 17%. Minister of State Dinesh Vasu Dash and Senior Minister of State Low Yen Ling defended the ESR and tripartism, saying the Enterprise Compute Initiative was meant to kickstart AI adoption. No vote was taken at this sitting.
15 Parliament Heated controversy

An Economy of the Future that Works for All (Debate Conclusion)

On the evening of 5 August Parliament resumed and concluded debate on the Workers' Party motion "An Economy of the Future that Works for All", moved by Kenneth Tiong Boon Kiat and standing also in Assoc Prof Jamus Jerome Lim's name. Transport Minister and Second Finance Minister Jeffrey Siow said the Economic Strategy...

Policy Signal: The Government will absorb AI-driven economic change into the existing ESR playbook - capability spillovers from MNCs, RIE2030's $37 billion and SWDA career bridges - rather than new measurable targets or legislated protection. Mandatory retrenchment benefits remain under study with no decision on legislation, and MTI becomes the Ministry of Energy, Trade and Industry from 1 October 2026, with a dedicated minister for energy and industry.
Open digest, stances, and transcript

On the evening of 5 August Parliament resumed and concluded debate on the Workers' Party motion "An Economy of the Future that Works for All", moved by Kenneth Tiong Boon Kiat and standing also in Assoc Prof Jamus Jerome Lim's name. Transport Minister and Second Finance Minister Jeffrey Siow said the Economic Strategy Review's five committees had engaged more than 7,700 people over nine months and that the Government already gives local SMEs nearly $2 billion a year in grants and loans. He defended the MNC-anchored model on the ground that global firms bring AI capabilities Singapore would take years to develop on its own, and rejected what he called a zero-sum framing the WP had not in fact drawn, a point Assoc Prof Jamus Lim rose to clarify. Trade and Industry Minister Tan See Leng set out RIE2030's $37 billion over five years, a $1 billion top-up to Startup SG Equity and a second $1.5 billion Anchor Fund tranche, and said workers would keep their share of growth by moving into hybrid roles that combine AI with sector knowledge, supported by ESR "career bridges" and the new SWDA. Closing, Mr Tiong called the ESR the fourth national economic blueprint since 2010 and said the only genuinely new element in it is AI, an exogenous factor every country must react to. He restated Mr Louis Chua's "HDB model for compute" - some $20 billion a year in land sales against about $150 million for a one-year compute programme - and demanded falsifiable targets before 2030 rather than a promise to monitor AI's impact on workers and adjust when needed. The WP accepted Amendments 2, 3 and 4 but opposed Amendment 1, which replaced "notwithstanding" with "in line with". Twelve WP MPs recorded their dissent twice; the motion as amended was carried.

Key Points
  • • Kenneth Tiong's closing: the ESR is the fourth national economic blueprint since 2010 and the only genuinely new element in it is AI
  • • WP restated the "HDB model for compute": some $20 billion a year in land sales against about $150 million for a one-year compute programme
  • • Jeffrey Siow: MNCs bring AI capabilities Singapore would take years to develop on its own, so local versus global is not zero-sum
  • • Tan See Leng: RIE2030 commits $37 billion over five years; workers keep their share via hybrid roles combining AI with sector knowledge
Government Position
The Government held that the ESR already covers most of the WP's asks and refused to re-orient the economy away from MNCs: Jeffrey Siow argued global firms bring AI capabilities Singapore would take years to build on its own, while Tan See Leng pointed to RIE2030's $37 billion over five years, a $1 billion Startup SG Equity top-up and the new SWDA, promising not that every job stays unchanged but that every worker will be helped to prepare earlier and find a credible next step.
Questioning Position
The WP backed Amendments 2, 3 and 4 but opposed Amendment 1's replacement of "notwithstanding" with "in line with", arguing it binds the House to a document rather than to ends. Kenneth Tiong said the only new element in the ESR is AI, while the Government's answer to AI's impact on workers is merely to monitor closely and adjust when needed; he demanded falsifiable targets before 2030, including a rising indigenous share of national income and real wages in line with productivity, and invited the Labour Movement to support legislating retrenchment benefits.
"What is new in this report is AI. But that is a new exogenous factor that all countries must react to. Adding new chapters and footnotes to an existing playbook does not make a new playbook."
Original transcript excerpt
Parliament resumed and concluded debate on the Workers' Party motion "An Economy of the Future that Works for All". NMP Neo Kok Beng urged wider regulatory sandboxes and a Catalist listing pathway for deep-tech firms; Mr Ng Shi Xuan argued enterprise policy should be judged by progression rather than participation, and noted that AI, labour costs and new regulations all land on the same SME owner's desk. Minister Jeffrey Siow said the ESR's five committees engaged more than 7,700 people over nine months, that the Government gives local SMEs nearly $2 billion a year in grants and loans, and that MNCs bring AI capabilities Singapore would take years to develop on its own. Minister Tan See Leng traced five gaps entrepreneurs must cross, citing RIE2030's $37 billion and a $1 billion Startup SG Equity top-up, and said Singaporeans would increasingly move into hybrid roles combining AI with sector knowledge. Minister of State Dinesh Vasu Dash said mandatory retrenchment benefits are being studied but the Government is not wedded to legislation. Closing, Mr Kenneth Tiong called the ESR the fourth blueprint since 2010 whose only new element is AI, recapped WP proposals including an "HDB model for compute" set against some $20 billion of annual land sales, and asked for falsifiable targets before 2030. Ms Mariam Jaafar countered that PSA's data advantage came from capability in digital technology, AI and automation, not from ownership. Four amendments passed; twelve WP MPs recorded their dissent; the amended motion was agreed.
15 Parliament Information

Capabilities to Detect and Prevent Communications of Real-time Deepfake Impersonations

Ms Hazlina Abdul Halim asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs, in writing, what capabilities are being developed to detect real-time deepfake communications in light of scams impersonating Government officials, and whether the Government would consider secur...

Policy Signal: Singapore's response to AI deepfake scams is shifting its centre of gravity from "content detection" to "identity recognisability": beyond OCHA platform duties, a single Government number prefix and caller-name tagging replicate the gov.sg SMS Sender ID model for voice calls, signalling that the Government is building systematic identity signals for official communications rather than relying on platforms to spot each deepfake.
🎙️ Ms Hazlina Abdul Halim · K Shanmugam
Open digest, stances, and transcript

Ms Hazlina Abdul Halim asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs, in writing, what capabilities are being developed to detect real-time deepfake communications in light of scams impersonating Government officials, and whether the Government would consider secure authentication methods such as digital signatures or a verified official channel for high-stakes communications with citizens and businesses. Senior Minister K Shanmugam replied that several anti-scam measures have been imposed under the Online Criminal Harms Act (OCHA) requiring designated online service providers to detect and remove deepfakes used to perpetrate scams, including user verification requirements and the use of facial recognition technology to identify such deepfakes; the Government regularly reviews the adequacy of these measures and will tighten them if necessary. To make legitimate Government communications more identifiable, the Government will introduce a single recognisable number prefix for all Government agencies' calls to the public, which the Singapore Police Force will pilot later this year, and is considering tagging Government agency calls with recognisable caller names, similar to the gov.sg SMS Sender ID. He stressed that the best defence against scams is a discerning public: Government officials will never ask anyone to transfer money, disclose bank log-in details over a phone call or install apps from unofficial app stores, and anyone in doubt can check with the 24/7 ScamShield Helpline at 1799.

Key Points
  • • Under OCHA, designated online service providers must detect and remove deepfakes used for scams, including through user verification requirements and facial recognition technology
  • • The Government regularly reviews the adequacy of anti-scam measures and will tighten them if necessary
  • • A single recognisable number prefix for all Government agencies' calls to the public will be introduced, piloted by the Singapore Police Force later this year
  • • The Government is considering tagging agency calls with recognisable caller names, similar to the gov.sg SMS Sender ID
Government Position
The Government sets up a three-layer defence against deepfake impersonation of officials — platform obligations, identifiable official communications and public vigilance: OCHA pins responsibility on platforms to detect and remove deepfakes with room to tighten, a single number prefix and caller-name tagging make genuine Government calls easier to recognise, and a discerning public is the final line of defence. The Member's suggestion of digital signatures or a verified official channel was not directly taken up.
Questioning Position
The questioner, Ms Hazlina Abdul Halim, was concerned that deepfakes can now impersonate Government officials in real time, whether the Government has matching real-time detection capabilities, and whether stronger authentication such as digital signatures or a verified official channel should be built for high-stakes communications between the state and citizens or businesses.
"Ultimately, the best defence against scams is a discerning public."
Original transcript excerpt
Ms Hazlina Abdul Halim asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs, in light of scams involving deepfake impersonation of Government officials, what capabilities are being developed to detect real-time deepfake communications, and whether the Government would consider secure authentication such as digital signatures or a verified official channel for high-stakes communications with citizens and businesses. Mr K Shanmugam replied that several anti-scam measures under the Online Criminal Harms Act require designated online service providers to detect and remove deepfakes used to perpetrate scams, including user verification requirements and facial recognition technology; the Government regularly reviews their adequacy and will tighten requirements if necessary. To improve the identifiability of legitimate Government communications, a single recognisable number prefix will be introduced for all Government agencies' calls with the public, which the Singapore Police Force will pilot later this year, and the Government is considering tagging agency calls with recognisable caller names, similar to the gov.sg SMS Sender ID. He said the best defence is a discerning public: officials never ask for money transfers, bank log-in details over the phone or app installs from unofficial stores, and doubtful calls can be checked with the 24/7 ScamShield Helpline at 1799.
15 Parliament Mild scrutiny

Near-term Risks Posed By Autonomous AI Agents Operating in Financial Services

Ms Mariam Jaafar asked the Prime Minister and Minister for Finance, in writing, for the Monetary Authority of Singapore's (MAS) assessment of the near-term risks posed by increasingly autonomous AI agents in financial services, whether MAS intends to move from the current industry-led Safeguards for Agentic Finance at...

Policy Signal: MAS is regulating agentic AI through a two-tier structure: hard expectations sit in the general Guidelines on AI Risk Management (covering all AI use cases including agentic AI), while runtime safeguards specific to agent behaviour (SAFR) stay at the industry self-regulation tier. By sidestepping both mandatory status and a timeline for SAFR, the reply signals no agent-specific rules in the near term, with any escalation depending on how industry implements the Guidelines once finalised.
Open digest, stances, and transcript

Ms Mariam Jaafar asked the Prime Minister and Minister for Finance, in writing, for the Monetary Authority of Singapore's (MAS) assessment of the near-term risks posed by increasingly autonomous AI agents in financial services, whether MAS intends to move from the current industry-led Safeguards for Agentic Finance at Runtime (SAFR) framework towards mandatory supervisory requirements, and if so on what timeline. Minister for Trade and Industry Gan Kim Yong, replying for the Prime Minister, said that given AI's fast-evolving nature MAS takes a principles-based approach to guide safe and responsible adoption, helping financial institutions (FIs) apply risk management proportionately. In November 2025 MAS published a consultation paper on proposed Guidelines on Artificial Intelligence Risk Management, setting out supervisory expectations for robust board and senior management oversight, sound risk management frameworks and processes, and sound AI life-cycle controls. The Guidelines apply to all AI use cases by FIs, including agentic AI, and will be finalised soon. Beyond supervisory expectations, industry has developed an AI Risk Management Toolkit under Project MindForge, while the SAFR framework sets out a potential approach to how agent actions are authorised, how human oversight is activated and what is recorded at every consequential decision. MAS will keep partnering industry through the Future of Finance Institute and will review and update its supervisory expectations where necessary. No timeline for making SAFR mandatory was given.

Key Points
  • • MAS takes a principles-based approach to AI in finance, helping FIs apply risk management proportionately
  • • A consultation paper on proposed Guidelines on AI Risk Management was published in November 2025, covering board oversight, risk frameworks and AI life-cycle controls; it applies to all use cases including agentic AI and will be finalised soon
  • • Under Project MindForge the industry built an AI Risk Management Toolkit; the SAFR framework addresses how agent actions are authorised, when human oversight kicks in and what is recorded at each consequential decision
  • • MAS will keep co-developing good practices with industry through the Future of Finance Institute and review its supervisory expectations
Government Position
The Government (via MAS) sticks to a "principles-based plus industry co-development" line on AI in finance: supervisory expectations are delivered through the soon-to-be-finalised Guidelines on AI Risk Management, which cover agentic AI, while implementation detail (the toolkit, SAFR) is left to industry under Project MindForge and the Future of Finance Institute. It makes no commitment to making SAFR mandatory, saying only that expectations will be reviewed and updated where necessary.
Questioning Position
The questioner, Ms Mariam Jaafar, was concerned that risks from autonomous AI agents in financial services are rising quickly, that the industry-led SAFR framework may not be enough, and that MAS should move it to binding supervisory requirements soon, with a clear timeline.
"They apply to all AI use cases by FIs, including agentic AI, and will be finalised soon."
Original transcript excerpt
Ms Mariam Jaafar asked the Prime Minister and Minister for Finance for MAS's assessment of the near-term risks from increasingly autonomous AI agents in financial services, whether MAS intends to move from the industry-led Safeguards for Agentic Finance at Runtime (SAFR) framework to mandatory supervisory requirements, and on what timeline. Mr Gan Kim Yong, replying for the Prime Minister, said MAS takes a principles-based approach so that financial institutions apply risk management proportionately. In November 2025 MAS consulted on proposed Guidelines on Artificial Intelligence Risk Management, which set supervisory expectations on board and senior management oversight, risk management frameworks and AI life-cycle controls; they apply to all AI use cases including agentic AI and will be finalised soon. Under Project MindForge the industry has developed an AI Risk Management Toolkit, and the SAFR framework sets out a potential approach to how agent actions are authorised, how human oversight is activated and what is recorded at each consequential decision. MAS will keep partnering industry through the Future of Finance Institute and review its supervisory expectations, updating them where necessary. No commitment or timeline for making SAFR mandatory was given.
15 Parliament Mild scrutiny

Applying Model AI Governance Framework and AI Verify to Agentic AI Systems

Mr Cai Yinzhou asked the Minister for Digital Development and Information, in writing, whether the Model AI Governance Framework and AI Verify are being extended to agentic AI systems that act autonomously without human review of individual decisions, what standard of care applies to deployers of such systems, and whet...

Policy Signal: MDDI holds the line on agentic AI at "voluntary framework plus organisational accountability": the dedicated January 2026 framework is treated as a sufficient answer, extending AI Verify and a standard of care are left unaddressed, and mandatory rules for high-consequence deployments are folded back into the 7 July position. That points to no binding agentic-AI rules in the near term, with accountability continuing to rest on deploying organisations' internal governance.
Open digest, stances, and transcript

Mr Cai Yinzhou asked the Minister for Digital Development and Information, in writing, whether the Model AI Governance Framework and AI Verify are being extended to agentic AI systems that act autonomously without human review of individual decisions, what standard of care applies to deployers of such systems, and whether the Ministry will move from voluntary to mandatory requirements for high-consequence deployments. Minister Josephine Teo replied that guidance for developers of agentic AI systems can be found in the Model Governance Framework for Agentic AI, which the Government released in January 2026. Human and organisational accountability is central to Singapore's AI governance approach: the Framework makes clear that organisations deploying AI should establish clear governance structures with designated oversight roles, ensure meaningful human accountability, and implement risk management processes and controls commensurate with the AI system's risks and level of autonomy. On whether tighter AI governance requirements may be introduced, she referred the Member to MDDI's reply to Mr Alex Yeo's Parliamentary Question of 7 July 2026, which addressed the regulation of high-risk AI deployments. The reply did not directly address whether AI Verify is being extended to agentic AI, nor spell out a specific standard of care for deployers.

Key Points
  • • Guidance for agentic AI developers sits in the Model Governance Framework for Agentic AI released by the Government in January 2026
  • • Human and organisational accountability is central: deployers should establish governance structures with designated oversight roles and ensure meaningful human accountability
  • • Risk management processes and controls must be commensurate with the AI system's risks and level of autonomy
  • • On tighter requirements, the Minister referred to MDDI's 7 July 2026 reply to Alex Yeo on regulating high-risk AI deployments, with no new commitment
Government Position
The Government's position is that agentic AI already has a dedicated governance instrument — the Model Governance Framework for Agentic AI of January 2026 — and that governance should centre on human and organisational accountability, designated oversight roles and risk controls "commensurate with the level of autonomy". On whether high-consequence deployments will be made mandatory, it merely restates its 7 July reply and adds nothing new.
Questioning Position
The questioner, Mr Cai Yinzhou, was concerned whether the existing voluntary instruments (the Model AI Governance Framework and AI Verify) keep pace with autonomous agent systems that act without human review of individual decisions, what duty of care their deployers should bear, and whether high-consequence deployments should shift from voluntary to mandatory requirements.
"Human and organisational accountability is central to Singapore's AI governance approach."
Original transcript excerpt
Mr Cai Yinzhou asked the Minister for Digital Development and Information whether the Model AI Governance Framework and AI Verify are being extended to agentic AI systems that act autonomously without human review of individual decisions, what standard of care applies to deployers of such systems, and whether the Ministry will move from voluntary to mandatory requirements for high-consequence deployments. Mrs Josephine Teo replied that guidance for developers of agentic AI systems may be found in the Model Governance Framework for Agentic AI, released by the Government in January 2026. She stressed that human and organisational accountability is central to Singapore's AI governance approach: the Framework makes clear that organisations deploying AI should establish clear governance structures with designated oversight roles, ensure meaningful human accountability, and implement risk management processes and controls commensurate with the AI system's risks and level of autonomy. On whether tighter AI governance requirements may be introduced, she referred the Member to MDDI's reply to Mr Alex Yeo's Parliamentary Question of 7 July 2026 on regulating high-risk AI deployments and mandatory human oversight for fully automated decisions. The reply did not directly address AI Verify or define a specific standard of care.
15 Parliament Information

Reduction of Entry-level Roles for Fresh Graduates and Young Jobseekers Attributable to AI Adoption

Dr Wan Rizal asked the Acting Minister for Manpower, in writing, how much of the decline in job vacancies between December 2025 and March 2026 reported in the Ministry's Labour Market Report First Quarter 2026 was attributable to a reduction in entry-level roles for fresh graduates and young jobseekers, and whether tha...

Policy Signal: MOM is, for the first time, using quarterly labour-market data to answer the "AI is eating entry-level jobs" narrative head-on, anchoring its policy frame on "job redesign" rather than "employment contraction". This signals that the Government will not introduce AI-specific job protections for graduates in the near term but will stay on its skills and job-matching course, while keeping the 6%–8% of AI-adopting firms that cut headcount or hiring as a watch indicator.
Open digest, stances, and transcript

Dr Wan Rizal asked the Acting Minister for Manpower, in writing, how much of the decline in job vacancies between December 2025 and March 2026 reported in the Ministry's Labour Market Report First Quarter 2026 was attributable to a reduction in entry-level roles for fresh graduates and young jobseekers, and whether that decline was linked to the AI adoption trends described in the same report. Minister of State Jasmin Lau replied that total vacancies fell from 77,700 in December 2025 to 73,300 in March 2026, driven primarily by a drop in non-PMET (Professionals, Managers, Executives and Technicians) openings. Entry-level PMET vacancies actually edged up from 32,500 to 32,800 over the same period, indicating the decline did not reflect a squeeze on roles for fresh graduates and young jobseekers. MOM's survey suggests AI's impact so far has been more on job redesign than on broad-based hiring cuts: among the three in ten firms that had adopted AI, only 6% reported reducing headcount and 8% reported lowering hiring activity, while 19% reported redesigning roles and 14% reported creating AI-related jobs. The Ministry will continue to support young jobseekers through initiatives that build industry-relevant skills, provide meaningful work experience and help them secure good jobs.

Key Points
  • • Total vacancies fell from 77,700 in December 2025 to 73,300 in March 2026, driven mainly by non-PMET openings
  • • Entry-level PMET vacancies edged up from 32,500 to 32,800 over the same period, which MOM cites to reject the idea that graduate roles are shrinking
  • • Among the roughly three in ten firms that adopted AI, only 6% cut headcount and 8% lowered hiring, while 19% redesigned roles and 14% created AI-related jobs
  • • MOM's reading is that AI's impact so far is mainly job redesign rather than broad-based hiring cuts
Government Position
The Government uses labour-market data to reject the claim that AI is squeezing entry-level graduate roles: the vacancy decline came from non-PMET jobs while entry-level PMET openings edged up, and AI's effect is characterised as "job redesign" rather than "hiring cuts"; MOM commits to keep supporting young jobseekers through skills, experience and job-matching initiatives.
Questioning Position
The questioner, Dr Wan Rizal, was concerned that the vacancy decline in the official labour-market report might mask a loss of entry-level roles for fresh graduates and young jobseekers, and that this loss might be driven by the very AI adoption trends the same report documents.
"Our survey suggests that the impact of artificial intelligence (AI) so far has been more on job redesign than on broad-based reductions in hiring."
Original transcript excerpt
Dr Wan Rizal asked the Acting Minister for Manpower how much of the decline in job vacancies from December 2025 to March 2026, as reported in the Labour Market Report First Quarter 2026, was attributable to fewer entry-level roles for fresh graduates and young jobseekers, and whether it was linked to the AI adoption trends in the same report. Minister of State Jasmin Lau replied that total vacancies fell from 77,700 to 73,300, driven primarily by a decrease in non-PMET vacancies. Entry-level PMET openings increased slightly from 32,500 to 32,800, so the decline did not reflect a reduction in roles for young jobseekers. MOM's survey suggests AI's impact so far has been more on job redesign than on broad-based hiring reductions: among the three in ten firms that had adopted AI, only 6% reported reducing headcount and 8% reported lowering hiring, compared with 19% that redesigned roles and 14% that created AI-related jobs. The Ministry will continue to support fresh graduates and young jobseekers through initiatives that build industry-relevant skills, provide meaningful work experience and help them secure good jobs.
15 Parliament Mild scrutiny

Mandatory Labelling for AI-generated and Digitally Manipulated Content to Align with Code of Practice for Online Safety and GenAI Transparency Guidelines

Mr Alex Yeo asked the Minister for Digital Development and Information, in writing, whether the Ministry has assessed the case for regulation requiring indicative labelling of AI-generated or digitally manipulated content shown to Singapore users, similar to the transparency obligations in Article 50 of the EU AI Act,...

Policy Signal: Singapore is explicitly declining to follow the EU AI Act Article 50 route of legislated mandatory labelling, instead splitting AI-content governance across two existing tracks — platform obligations under the Codes of Practice and voluntary deployer disclosure under the transparency guidelines. By making "maturity of watermarking and digital provenance standards" the precondition for mandating, it hands the decision to technical standards rather than a legislative timetable, so no mandatory AI-content labelling law is likely in the near term.
Open digest, stances, and transcript

Mr Alex Yeo asked the Minister for Digital Development and Information, in writing, whether the Ministry has assessed the case for regulation requiring indicative labelling of AI-generated or digitally manipulated content shown to Singapore users, similar to the transparency obligations in Article 50 of the EU AI Act, and if so how this would relate to the Code of Practice for Online Safety and the new voluntary GenAI chatbot transparency guidelines. Minister Josephine Teo replied that the Government regularly assesses its regulations and frameworks to ensure they remain relevant as technologies evolve. The Infocomm Media Development Authority's two Codes of Practice for Online Safety require designated social media and app distribution services to put in place systems and processes to mitigate Singapore users' exposure to harmful content, including AI-generated content. The Transparency Guidelines for Generative AI Chatbots encourage deployers to clearly explain to users the capabilities, limitations and safeguards of their chatbots. MDDI will continue to monitor international developments on labelling AI-generated or digitally manipulated content, keep track of the maturity of technical standards such as watermarking and digital provenance approaches, and assess whether they should be mandated. The reply made no commitment to a mandatory labelling regime and set no timeline.

Key Points
  • • The Member cited Article 50 of the EU AI Act in asking whether labelling of AI-generated or digitally manipulated content shown to Singapore users should be mandated
  • • IMDA's two Codes of Practice for Online Safety require designated social media and app distribution services to mitigate users' exposure to harmful content, including AI-generated content
  • • The Transparency Guidelines for Generative AI Chatbots are voluntary, encouraging deployers to explain chatbot capabilities, limitations and safeguards
  • • MDDI will monitor international labelling developments and track the maturity of standards such as watermarking and digital provenance before assessing whether to mandate them
Government Position
The Government's position is that existing instruments already cover the risks of AI-generated content — IMDA's two Codes of Practice for Online Safety govern harmful content from the platform side, and the chatbot transparency guidelines govern disclosure from the deployer side — so there is no rush to adopt EU-style mandatory labelling. Whether to mandate it will depend on international developments and the maturity of technical standards such as watermarking and digital provenance, with the Government reserving room to assess.
Questioning Position
The questioner, Mr Alex Yeo, was concerned that Article 50 of the EU AI Act already requires transparency labelling of AI-generated and deepfake content, and asked whether Singapore should likewise legislate labelling of such content visible to local users, and how such rules would fit together with the existing Codes of Practice for Online Safety and the voluntary chatbot transparency guidelines.
"We will also keep track of the maturity of technical standards, such as watermarking and digital provenance approaches, and assess if they should be mandated."
Original transcript excerpt
Mr Alex Yeo asked the Minister for Digital Development and Information whether the Ministry has assessed the case for regulation requiring indicative labelling of AI-generated or digitally manipulated content shown to Singapore users, similar to the EU AI Act Article 50 transparency obligations, and if so how this would relate to the Code of Practice for Online Safety and the new voluntary GenAI chatbot transparency guidelines. Mrs Josephine Teo replied that the Government regularly assesses its regulations and frameworks to keep them relevant as technologies evolve. IMDA's two Codes of Practice for Online Safety require designated social media and app distribution services to put in place systems and processes to mitigate Singapore users' exposure to harmful content, including AI-generated content, while the Transparency Guidelines for Generative AI Chatbots encourage deployers to clearly explain their chatbots' capabilities, limitations and safeguards. The Ministry will continue to monitor international developments on labelling AI-generated or digitally manipulated content, keep track of the maturity of technical standards such as watermarking and digital provenance, and assess whether they should be mandated. No commitment to mandatory labelling or timeline was given.
15 Parliament Substantive debate

Rationale and Cost of Developing AI Models for Healthcare Diagnostics, and Safeguards for Patient Data

PAP MP Yip Hon Weng and Workers' Party NCMP Andre Low put oral questions to the Coordinating Minister for Social Policies and Minister for Health on the Singapore Medical Foundation AI Model (SIMFONI): why develop models for conditions diagnosable by routine tests rather than rare diseases, at what cost; how clinicians...

Policy Signal: MOH has drawn a clear line for healthcare AI: de-identified population health data on the TRUST platform is the training base, there will be no "individual consent" gate, and safety rests on independent pre-deployment evaluation, clinical protocols and human-in-the-loop judgement. Singapore is choosing a "data availability first, backed by oversight and results" path rather than a European-style consent-led model; if SIMFONI proves itself in public-sector specialties, it will become a national clinical AI foundation extended to private practitioners.
Open digest, stances, and transcript

PAP MP Yip Hon Weng and Workers' Party NCMP Andre Low put oral questions to the Coordinating Minister for Social Policies and Minister for Health on the Singapore Medical Foundation AI Model (SIMFONI): why develop models for conditions diagnosable by routine tests rather than rare diseases, at what cost; how clinicians and private practitioners would access it; and whether the models would be privacy-tested by assessors independent of the developers before deployment, with standards, findings and disclosure protocols published. Minister for Health Ong Ye Kung replied that SIMFONI provides clinical decision support for managing chronic conditions, prioritising high-burden conditions where development is feasible, starting with a couple of specialties in the public sector and expanding to more specialties and possibly private practitioners if successful. The models adapt existing internationally trained models using de-identified local patient data on TRUST, the secure national platform set up in 2022, and an independent safety and evaluation unit will test them rigorously before deployment. In supplementaries, Yip asked how "automation bias" would be mitigated; Ong said MOH takes a careful use-case approach, deploying AI under clinical protocols with clinicians still making the judgement, and never treating AI as "a hammer looking for nails". Low asked whether training data would include the NEHR, whether explicit patient consent would be sought, and what happens when anonymisation fails; Ong replied that scoping down data or seeking everyone's consent out of distrust would make the effort "a non-starter", that TRUST data has been used incident-free under international de-identification standards, and that results should speak for themselves.

Key Points
  • • SIMFONI provides clinical decision support for chronic conditions, prioritising high-burden, feasible conditions, starting with a couple of public-sector specialties and expanding to private practitioners if successful
  • • Models adapt existing internationally trained models with de-identified local patient data on TRUST, the national platform established in 2022, with an independent safety and evaluation unit testing them before deployment
  • • Ong said MOH takes a careful use-case approach: AI is deployed under clinical protocols with clinicians making the judgement, never treated as "a hammer going around looking for nails"
  • • Andre Low asked whether NEHR data would be used and whether explicit consent would be sought; Ong replied that scoping down data or seeking everyone's consent out of distrust would be "a non-starter"
Government Position
The Government frames SIMFONI as a "careful use-case approach": it starts with high-burden chronic conditions, adapts models on TRUST — the secure national platform set up in 2022 — using de-identified data, subjects them to independent evaluation before deployment, and deploys them under clinical protocols with clinicians making the final judgement. On privacy, Ong Ye Kung explicitly refused to scope down training data or seek individual patient consent out of distrust, arguing for a balance between leveraging the technology and putting safeguards in place, and for earning public confidence through an incident-free track record.
Questioning Position
Yip Hon Weng questioned why the effort did not target harder-to-diagnose rare diseases and what it cost, and, citing international experience of clinicians gradually deferring to AI ("automation bias"), asked for specific safeguards to be announced. Workers' Party NCMP Andre Low asked for privacy testing by assessors independent of the developers before deployment, with standards and disclosure protocols published; he pressed on whether training data would cover all patients in the NEHR, whether explicit patient consent should be sought, and — pointing to a separate parliamentary question that day on a Singapore Land Authority data leak — argued that anonymisation processes are fallible.
"Never treat AI as a hammer going around looking for nails or a solution looking for a problem."
Original transcript excerpt
Yip Hon Weng and Andre Low asked the Coordinating Minister for Social Policies and Minister for Health about the Singapore Medical Foundation AI Model (SIMFONI): the rationale and cost of targeting routinely diagnosable conditions rather than rare diseases, clinician and private-practitioner access, safeguards against data leaks, and whether independent privacy testing, standards and disclosure protocols would be published. Ong Ye Kung replied that SIMFONI provides clinical decision support for chronic conditions, prioritising high-burden, feasible conditions, starting in a couple of public-sector specialties before possibly expanding to private practitioners. Models adapt internationally trained base models with de-identified local data on TRUST, the secure national platform established in 2022, and an independent safety and evaluation unit will test them before deployment. On automation bias, Ong described a careful use-case approach with deployment under clinical protocols and clinicians retaining judgement. On data scope, consent and anonymisation, he said scoping down data or seeking everyone's consent would be a non-starter, that TRUST data has been used incident-free to international de-identification standards, and that results should speak for themselves.
15 Parliament Information

Use of AI-enabled Traffic Camera Systems to Detect Erratic or Dangerous Driving Behaviours

Melvin Yong, citing the rise in road traffic accidents and fatalities in 2025, asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs in a written question whether the Traffic Police is studying AI-enabled traffic camera systems capable of detecting erratic or dangerous dri...

Policy Signal: The Traffic Police's technology-enforcement track remains rule-based violation detection — red-light running, U-turns, line crossing — behaviours that video analytics and plate recognition can judge objectively. Using AI to infer "dangerous driving", which requires behavioural judgement, is still at the exploration stage. That matches Singapore's usual cadence for public-sector AI: land low-controversy, verifiable use cases first, then extend to enforcement scenarios that require discretion.
Open digest, stances, and transcript

Melvin Yong, citing the rise in road traffic accidents and fatalities in 2025, asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs in a written question whether the Traffic Police is studying AI-enabled traffic camera systems capable of detecting erratic or dangerous driving behaviours, so that enforcement or intervention can happen before accidents occur. K Shanmugam replied that, as stated in Parliament on 7 April 2026, the Traffic Police has deployed nine Traffic Violation Enforcement Cameras since March 2026. These cameras use video analytics and automatic number plate recognition to detect selected offences, including red-light running, illegal U-turns and crossing double white lines. The Traffic Police has been exploring, and will continue to explore, the use of artificial intelligence and other technological tools to identify dangerous driving behaviours and support timely intervention where appropriate. The answer gave no specific plan or timeline for AI-based detection of dangerous driving beyond the existing violation cameras.

Key Points
  • • Melvin Yong cited the 2025 rise in accidents and fatalities to ask whether the Traffic Police is studying AI camera systems that detect dangerous driving
  • • The Traffic Police has deployed nine Traffic Violation Enforcement Cameras since March 2026, as reported to Parliament on 7 April 2026
  • • The cameras use video analytics and automatic number plate recognition to detect selected offences such as red-light running, illegal U-turns and crossing double white lines
  • • The Traffic Police will keep exploring AI and other tools to identify dangerous driving, but the reply gave no specific plan or timeline
Government Position
The Ministry of Home Affairs points to the nine Traffic Violation Enforcement Cameras already in place (video analytics plus automatic number plate recognition) as the technology-enforcement baseline, and on AI detection of dangerous driving commits only to continued exploration and timely intervention where appropriate, with no plan, scale or timeline.
Questioning Position
Questioner Melvin Yong framed the issue as prevention before the fact: with accidents and fatalities up in 2025 and existing cameras only capturing offences after they occur, he wants the Traffic Police to use AI to spot erratic or dangerous driving and intervene before a crash.
"TP has been and will continue to explore the use of artificial intelligence and other technological tools to identify dangerous driving behaviours and support timely intervention where appropriate."
Original transcript excerpt
Melvin Yong asked the Senior Minister, Coordinating Minister for National Security and Minister for Home Affairs whether, given the rise in road traffic accidents and fatalities in 2025, the Traffic Police is studying AI-enabled traffic camera systems that can detect erratic or dangerous driving behaviours so that enforcement or intervention can take place before accidents occur. K Shanmugam answered in writing that, as mentioned in Parliament on 7 April 2026, the Traffic Police has deployed nine Traffic Violation Enforcement Cameras since March 2026. The cameras use video analytics and automatic number plate recognition technology to detect selected traffic offences, including red-light running, illegal U-turns and crossing double white lines. He added that the Traffic Police has been exploring, and will continue to explore, the use of artificial intelligence and other technological tools to identify dangerous driving behaviours and to support timely intervention where appropriate. No further detail on the scope, technology or timing of AI-based detection of dangerous driving was provided in the reply.
15 Parliament Information

Reports of AI-encouraged Cases of Self-harm amongst Teenagers and Children

Hany Soh asked the Minister for Social and Family Development in a written question whether the Ministry had received reports of AI-encouraged or AI-related self-harm by teenagers and children in the past three years, and what safeguards are in place. Minister Masagos Zulkifli replied that MSF does not track reports of...

Policy Signal: Singapore is not yet monitoring "AI and youth mental health" as a standalone item, folding it instead into cyber-wellness education and social-media platform regulation. The only hard obligation sits on social media services designated under the Code of Practice for Online Safety; AI chatbots and companion apps fall outside that code. The line that students are also taught to use AI tools safely and responsibly confirms that AI literacy is already in the MOE curriculum. If documented AI-related self-harm cases emerge, the absence of dedicated data will be the first gap in the policy debate.
🎙️ Hany Soh · Mr Masagos Zulkifli B M M
Open digest, stances, and transcript

Hany Soh asked the Minister for Social and Family Development in a written question whether the Ministry had received reports of AI-encouraged or AI-related self-harm by teenagers and children in the past three years, and what safeguards are in place. Minister Masagos Zulkifli replied that MSF does not track reports of self-harm specifically related to AI, noting that the factors behind self-harm are multi-faceted and differ from case to case. The Government's approach is to educate young users to use technology safely: school Cyber Wellness and Mental Health Education lessons teach students to be safe, respectful and responsible online and to use AI tools safely and responsibly, while IMDA's Digital for Life portal explains the risks of AI and guides parents on safeguarding children who interact with AI platforms. Parents can turn to school counsellors or community providers such as TOUCH Community Services, and youths can seek help from First Stop for Mental Health services such as national mindline 1771, mindline.sg, Youth Community Outreach Teams, CHAT and Youth Integrated Teams. On regulation, IMDA's Code of Practice for Online Safety for Social Media Services requires designated social media services to minimise users' exposure to self-harm content and to provide safety information to users searching for high-risk terms, including those relating to self-harm.

Key Points
  • • MSF does not specifically track self-harm reports related to AI, noting that the factors behind self-harm are multi-faceted and vary by case
  • • School Cyber Wellness and Mental Health Education lessons teach students to be safe, responsible online users and to use AI tools safely
  • • IMDA's Digital for Life portal explains AI risks and guides parents on safeguarding children who interact with AI platforms
  • • Help channels include school counsellors, TOUCH Community Services and First Stop for Mental Health services such as mindline 1771, mindline.sg and CHAT
Government Position
The Government handles AI-related self-harm within its broader digital-wellness framework: no dedicated statistics, on the reasoning that self-harm has many causes; the defence has three layers — school Cyber Wellness and Mental Health Education, IMDA's Digital for Life resources for parents plus the existing mental-health help network, and the Code of Practice for Online Safety's content obligations on designated social media services. There is no regulatory measure specific to AI chat or companion platforms.
Questioning Position
Questioner Hany Soh's concern is whether AI has become a new trigger for self-harm among teenagers and children: she asked for case-report data over the past three years and targeted safeguards; the reply acknowledged no such tracking exists and pointed to existing general education and social-media rules.
"Ministry of Social and Family Development (MSF) does not track reports of self-harm specifically related to artificial intelligence (AI)."
Original transcript excerpt
Hany Soh asked the Minister for Social and Family Development whether the Ministry had received reports of AI-encouraged or AI-related self-harm by teenagers and children in the past three years, and what safeguards exist. Masagos Zulkifli replied in writing that MSF does not track self-harm reports specifically related to AI, and that the factors behind self-harm are multi-faceted and case-specific. The Government's approach is education: school Cyber Wellness and Mental Health Education lessons teach students to be safe, respectful and responsible online and to use AI tools safely; IMDA's Digital for Life portal explains AI risks and guides parents on protecting children who interact with AI platforms. Parents can approach school counsellors or community providers such as TOUCH Community Services, and youths can use First Stop for Mental Health services including national mindline 1771, mindline.sg, Youth Community Outreach Teams, CHAT and Youth Integrated Teams. On regulation, IMDA's Code of Practice for Online Safety for Social Media Services requires designated services to minimise users' exposure to self-harm content and to provide safety information to users searching for high-risk terms, including those relating to self-harm.
15 Parliament Information

Assessing AI-enabled Mobility Aids for Persons with Visual Impairment

PAP MP Diana Pang Li Yen asked the Minister for Social and Family Development in a written question whether SG Enable would assess emerging AI-enabled mobility aids for persons with visual impairment, including robotic guide dogs and wearable AI navigation devices; whether safe and effective devices could be supported...

Policy Signal: Singapore applies a "technology-neutral, needs-based" funding logic to AI assistive devices: there is no dedicated channel or extra hurdle because a product contains AI, and funding hinges on a healthcare professional's assessment of suitability for the individual. SG Enable's readiness to trial devices with community and industry partners leaves the door open for robotic guide dogs and similar products to enter the local market, though without a timeline or dedicated budget.
🎙️ Ms Diana Pang Li Yen · Mr Masagos Zulkifli B M M
Open digest, stances, and transcript

PAP MP Diana Pang Li Yen asked the Minister for Social and Family Development in a written question whether SG Enable would assess emerging AI-enabled mobility aids for persons with visual impairment, including robotic guide dogs and wearable AI navigation devices; whether safe and effective devices could be supported through existing funding schemes; and whether Singapore would facilitate trials of or access to suitable devices. Minister Masagos Zulkifli replied that SG Enable supports persons with disabilities in accessing assistive technologies that enable greater independence and mobility. The Assistive Technology Fund (ATF) provides means-tested subsidies to acquire, replace, upgrade or repair assistive technology devices for purposes including education, employment, therapy and independence in daily living. As AI-enabled devices continue to develop, SG Enable will consider them as part of its broader efforts to promote assistive technology adoption, including exploring trials in partnership with community and industry partners to understand the suitability of these products in the local context. Devices assessed by a qualified healthcare professional assessor to be suitable for use by persons with disabilities can be supported under the ATF.

Key Points
  • • The Assistive Technology Fund (ATF) provides means-tested subsidies to acquire, replace, upgrade or repair assistive devices for education, employment, therapy and independence in daily living
  • • SG Enable will consider AI-enabled aids such as robotic guide dogs and wearable AI navigation devices as part of its broader efforts to promote assistive technology adoption
  • • It will explore trials in partnership with community and industry partners to understand the suitability of these products in the local context
  • • Devices assessed by a qualified healthcare professional assessor as suitable for persons with disabilities can be supported under the ATF
Government Position
The Government is not creating a new scheme for AI-enabled mobility aids but folding them into the existing Assistive Technology Fund framework: any device assessed as suitable by a qualified healthcare professional assessor can be funded. SG Enable will treat emerging AI devices as part of its broader assistive-technology adoption efforts and explore trials with community and industry partners to verify their suitability locally.
Questioning Position
The questioner, Diana Pang Li Yen, focused on whether persons with visual impairment can gain timely access to new technologies such as robotic guide dogs and wearable AI navigation devices, asking the Government to clarify whether SG Enable would proactively assess such devices, whether existing funding schemes could cover them, and whether trials or access would be facilitated rather than waiting for the market to mature on its own.
"As artificial intelligence-enabled devices continue to develop, SG Enable will consider these as part of its broader efforts to promote assistive technology adoption."
Original transcript excerpt
Diana Pang Li Yen asked the Minister for Social and Family Development whether SG Enable would assess emerging AI-enabled mobility aids for persons with visual impairment, such as robotic guide dogs and wearable AI navigation devices; whether safe and effective devices could be supported through existing funding schemes; and whether Singapore would facilitate trials of or access to suitable devices. Masagos Zulkifli replied that SG Enable supports persons with disabilities in accessing assistive technologies that enable greater independence and mobility. The Assistive Technology Fund provides means-tested subsidies to acquire, replace, upgrade or repair assistive technology devices across purposes including education, employment, therapy and independence in daily living. As AI-enabled devices develop, SG Enable will consider them as part of its broader efforts to promote assistive technology adoption, including exploring trials with community and industry partners to understand their suitability in the local context. Devices assessed by a qualified healthcare professional assessor as suitable for persons with disabilities can be supported under the ATF.
15 Parliament Information

Instances when AI-augmented Evidence Has Been Tendered as Evidence before Court of Law in Singapore

Hany Soh asked the Minister for Law in a written question whether the Ministry is aware of instances in which AI-fabricated or AI-augmented evidence has been tendered before a court, and whether judicial staff and officers are sufficiently trained and equipped to guard against such cases. Minister Edwin Tong replied th...

Policy Signal: Singapore is governing generative AI in court proceedings through soft law plus existing sanctions: the Courts' 2024 guide and the Ministry of Law's March 2026 legal-sector guide form the normative layer, the two published cases sanctioning lawyers for fictitious citations form the enforcement layer, and deepfake evidence is left to criminal law and judicial discretion over evidence. The reply states the operating principle plainly — the problem is not using AI but failing to verify independently — consistent with Singapore's AI-governance habit of placing accountability on the user. As deepfake tools spread, the Courts' digital-forensic capacity and expert evidence will become the next pressure point.
Open digest, stances, and transcript

Hany Soh asked the Minister for Law in a written question whether the Ministry is aware of instances in which AI-fabricated or AI-augmented evidence has been tendered before a court, and whether judicial staff and officers are sufficiently trained and equipped to guard against such cases. Minister Edwin Tong replied that such evidence arises in two scenarios. The first is deliberate fabrication or manipulation using AI, such as deepfake images or videos: the Singapore Courts confirm there have yet to be such findings in a published decision, though the Courts have disregarded evidence where a party could not explain its reliance on AI, and knowingly tendering false evidence carries criminal liability. The second is using AI tools to prepare affidavits and reports, where negligent or careless use introduces inaccuracies, fabrications or fictitious citations. The Courts' 2024 Guide on the use of Generative Artificial Intelligence Tools by Court Users makes court users responsible for accurate, relevant and independently verified materials, a duty underscored by the Ministry's Guide for the Use of Generative AI in the Legal Sector issued in March 2026; at least two published cases have sanctioned lawyers for failing it. The Singapore Judicial College trains judges on admissibility, authenticity and reliability of digital evidence, and the Courts may rely on expert evidence and digital forensic analysis where authenticity is contested.

Key Points
  • • AI evidence arises in two scenarios: deliberate fabrication such as deepfake images or videos, and careless use of AI in preparing court documents that introduces errors, fabrications or fictitious citations
  • • The Singapore Courts confirm no published decision has yet found deepfake evidence, though evidence has been disregarded where a party could not explain its reliance on AI
  • • The Courts' 2024 Guide on the use of Generative AI Tools by Court Users and the Ministry's March 2026 Guide for the Use of Generative AI in the Legal Sector both require materials to be accurate, relevant and independently verified
  • • In at least two published cases the Courts have sanctioned lawyers for failing in that verification responsibility
Government Position
The Ministry of Law splits the AI-evidence risk into deliberate fabrication and negligent use and answers each separately: the former with existing criminal law and the Courts' power to exclude evidence of unexplained provenance, the latter with the Courts' 2024 guide and the Ministry's March 2026 sector guide, which pin the verification duty on court users and lawyers and have already been enforced through sanctions. The Government judges the Judicial College's continuous training, expert evidence and digital forensics sufficient for judges, and proposes no new legislation.
Questioning Position
Questioner Hany Soh focused on two points: whether the courts have already encountered AI-fabricated or augmented evidence, and whether judicial officers can detect it. The reply drew the line at no published deepfake finding versus two sanctions over AI-prepared documents, and answered the second point with training and forensic capacity.
"The concern here is not the use of AI in itself, but where the negligent or careless use of AI introduces inaccuracies, fabrications or fictitious citations into Court documents."
Original transcript excerpt
Hany Soh asked the Minister for Law whether the Ministry is aware of instances in which AI-fabricated or augmented evidence has been tendered before a court, and whether judicial staff and officers are sufficiently trained to guard against such cases. Edwin Tong replied in writing that such evidence arises in two scenarios. First, deliberate fabrication or manipulation using AI, such as deepfake images or videos: the Singapore Courts confirm there have yet to be such findings in a published decision, though evidence has been disregarded where a party could not explain its reliance on AI, and knowingly tendering false evidence carries criminal liability. Second, using AI tools to prepare affidavits and reports, where negligent use introduces inaccuracies, fabrications or fictitious citations. The Courts' 2024 Guide on the use of Generative AI Tools by Court Users, reinforced by the Ministry's March 2026 Guide for the Use of Generative AI in the Legal Sector, makes court users responsible for accurate, relevant and independently verified materials; at least two published cases have sanctioned lawyers for failing this duty. The Singapore Judicial College trains judges on digital evidence, and the Courts may rely on expert evidence and digital forensic analysis where authenticity is contested.
15 Parliament Information

Measuring Productivity Gains, Service Improvements and Risks from Generative AI Deployments across Public Service

PAP MP Saktiandi Supaat asked the Minister for Digital Development and Information in a written question what the principal AI use cases across the Public Service are, how many public agencies have deployed generative AI systems in their operations, and how the Government measures the productivity gains, service improv...

Policy Signal: The Government has formally stated that it will not use the number of AI systems as the yardstick for Public Service AI progress, devolving assessment to individual agencies with service outcomes as the final measure. This signals that Singapore's public-sector AI governance will not, in the near term, adopt a unified quantitative KPI or publish a deployment inventory; the emphasis is on experimentation within Government-wide procurement, governance and security requirements, backed by the trio of safeguards, human oversight and officer training.
Open digest, stances, and transcript

PAP MP Saktiandi Supaat asked the Minister for Digital Development and Information in a written question what the principal AI use cases across the Public Service are, how many public agencies have deployed generative AI systems in their operations, and how the Government measures the productivity gains, service improvements and risks arising from such deployments. Minister Josephine Teo, answering together with his oral question that day and a written question for the next sitting, said the Public Service is progressively deploying AI to solve operational problems and improve service delivery. Almost 70% of public officers use AI tools regularly to analyse information, prepare drafts and support document processing, and agencies are using AI to improve services for citizens. Adoption is broadening but its depth and maturity remain uneven across agencies; the current focus is learning from practical deployment and experimentation — where AI delivers the greatest value, how it affects work and teams, and what safeguards are needed. Because AI can be deployed through common platforms, embedded in larger digital services or adapted for agency-specific workflows, a simple count of AI systems would not be a meaningful measure of progress. Instead, agencies assess the benefits, costs and risks of deployments, with success judged by whether AI helps officers work better and deliver more effective and efficient services, within Government-wide requirements for procurement, governance and security. Agencies must implement safeguards and human oversight, and public officers are being trained to use AI confidently, effectively and responsibly.

Key Points
  • • Almost 70% of public officers use AI tools regularly to analyse information, prepare drafts and support document processing, and agencies use AI to improve citizen services
  • • Adoption is broadening, but depth and maturity remain uneven across agencies; the current focus is learning from practical deployment and experimentation
  • • The Government says a simple count of AI systems would not be a meaningful measure; agencies assess the benefits, costs and risks of their own deployments
  • • Success is measured by whether AI helps officers work better and deliver more effective, efficient services, within Government-wide procurement, governance and security requirements
Government Position
The Government positions Public Service AI adoption as "broad rollout, learning by doing": it cites almost 70% of public officers using AI tools regularly as evidence of reach while conceding that depth and maturity vary across agencies. It explicitly declines to answer the MP's request for quantitative measures with a count of AI systems or of agencies using generative AI, relying instead on agencies' own assessments of benefits, costs and risks and on ultimate service outcomes, with safeguards, human oversight and officer training running in parallel.
Questioning Position
The questioner, Saktiandi Supaat, sought verifiable figures from the Government: the principal AI use cases across the Public Service, how many agencies have deployed generative AI, and how productivity gains, service improvements and risks are quantified. His concern was whether public-sector AI investment has measurable returns and risk controls; the reply did not provide an agency count or specific metrics.
"Given the many ways AI can be deployed, whether through common platforms, embedded within larger digital services or adapted for agency-specific workflows, a simple count of AI systems would not provide a meaningful measure of progress."
Original transcript excerpt
Saktiandi Supaat asked the Minister for Digital Development and Information about the principal AI use cases across the Public Service, how many agencies have deployed generative AI systems, and how the Government measures the productivity gains, service improvements and risks from such deployments. Josephine Teo, answering his oral and written questions together, said the Public Service is progressively deploying AI to solve operational problems and improve service delivery: almost 70% of public officers use AI tools regularly to analyse information, prepare drafts and support document processing, and agencies use AI to improve citizen services. Adoption is broadening but depth and maturity remain uneven, so the current focus is learning from practical deployment and experimentation. Because AI is deployed through common platforms, embedded services and agency-specific workflows, a simple count of systems would not be meaningful; agencies assess benefits, costs and risks, with success measured by better officer work and more effective, efficient services, within Government-wide procurement, governance and security requirements. Agencies must implement safeguards and human oversight, and officers are being upskilled to use AI confidently, effectively and responsibly.
15 Parliament Information

Impact of Generative AI on Singapore's Arts and Creative Sectors

PAP MP Alex Yam asked the Minister for Culture, Community and Youth in a written question whether the Ministry had assessed the impact of generative AI on Singapore's arts and creative sectors, and what support was being considered to help artists adapt while safeguarding intellectual property and creative livelihoods....

Policy Signal: Singapore's policy on generative AI and the creative industries remains in an "observation period": there are no dedicated measures on AI training data, copyright ownership or artists' income, and a substantive response has been deferred until after the IPS study in the first half of 2027. The Government treats AI as an optional collaborative tool for artists rather than a target for regulation, responding in the near term through "enabling" routes — legal literacy, copyright resources and experimentation space — rather than legislative intervention.
Open digest, stances, and transcript

PAP MP Alex Yam asked the Minister for Culture, Community and Youth in a written question whether the Ministry had assessed the impact of generative AI on Singapore's arts and creative sectors, and what support was being considered to help artists adapt while safeguarding intellectual property and creative livelihoods. Minister David Neo, also answering Dr Choo Pei Ling's written question on whether MCCY had commissioned studies, said MCCY has been engaging the arts community on the impact of generative AI: some practitioners are concerned about livelihoods and legal and ethical issues, while others see AI as a collaborative tool for ideation, experimentation and new forms of expression. MCCY is supporting a research study on AI conducted by the Ministry of Digital Development and Information in collaboration with the Institute of Policy Studies (IPS) Policy Lab; IPS expects to publish its findings in the first half of 2027, and MCCY will assess them with relevant agencies. The National Arts Council (NAC) is helping artists work and innovate with generative AI while holding that technology should complement, not replace, artists' originality, lived experience and creative judgement. NAC's Arts Resource Hub gives arts self-employed persons resources on intellectual property and copyright protection, and NAC is partnering Pro Bono SG on an arts legal support initiative covering emerging AI-related issues. NAC's Arts x Tech Lab offers a dedicated space, prototyping equipment and artist-led workshops and showcases to support capability development, experimentation and cross-disciplinary collaboration. MCCY and NAC will continue to watch AI developments closely and engage the arts community.

Key Points
  • • MCCY has been engaging the arts community on generative AI: some practitioners worry about livelihoods and legal and ethical issues, others see AI as a collaborative tool for ideation and experimentation
  • • MCCY is supporting an AI research study by MDDI in collaboration with the IPS Policy Lab; IPS expects to publish findings in the first half of 2027
  • • NAC holds that technology should complement, not replace, artists' originality, lived experience and creative judgement
  • • NAC's Arts Resource Hub offers intellectual property and copyright resources, and NAC is partnering Pro Bono SG on an arts legal support initiative covering AI-related issues
Government Position
The Government's posture on generative AI's impact on the arts is "engage first, research next, support along the way": MCCY acknowledges practitioners' concerns about livelihoods and legal and ethical issues but is not rushing out a dedicated policy, choosing instead to await the IPS Policy Lab findings in the first half of 2027 before assessing them with relevant agencies. Present support runs through NAC's existing tools — intellectual property resources, legal aid with Pro Bono SG, the Arts x Tech Lab experimentation space — anchored on the principle that technology should complement, not replace, artists.
Questioning Position
The questioners, Alex Yam and Dr Choo Pei Ling, focused on two points: whether the Government has actually assessed or commissioned research on generative AI's impact on the arts and creative sectors, and what concrete support exists when intellectual property and creative livelihoods are under threat. The reply shows MCCY has no assessment of its own yet, with research findings not due until the first half of 2027.
"The National Arts Council (NAC) has been actively helping artists work and innovate with GenAI, while recognising that technology should complement, not replace, the originality, lived experience and creative judgement that artists bring to their work."
Original transcript excerpt
Alex Yam asked the Minister for Culture, Community and Youth whether the Ministry had assessed the impact of generative AI on Singapore's arts and creative sectors and what support was being considered to help artists adapt while safeguarding intellectual property and creative livelihoods. David Neo, also addressing Dr Choo Pei Ling's written question on studies, said MCCY has been engaging the arts community: some practitioners are concerned about livelihoods and legal and ethical issues, while others see AI as a collaborative tool for ideation and new forms of expression. MCCY is supporting an AI research study by MDDI with the IPS Policy Lab, with findings expected in the first half of 2027. The National Arts Council helps artists innovate with generative AI while holding that technology should complement, not replace, their originality and creative judgement. NAC's Arts Resource Hub provides intellectual property and copyright resources, NAC is partnering Pro Bono SG on legal support covering AI-related issues, and the Arts x Tech Lab offers space, prototyping equipment and artist-led workshops. MCCY and NAC will keep watching AI developments and engaging the arts community.
15 Parliament Mild scrutiny

Prevalence of Use of AI-assisted Clinical Notetaking Tools at Public Healthcare Institutions and Safeguards for Such Use

Workers' Party MP Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health in a written question which public healthcare institutions have deployed AI-assisted clinical note-taking tools, whether such tools are classified as medical devices under the Health Products Act, a...

Policy Signal: MOH has drawn a clear classification line: AI tools that do not diagnose, manage or treat — such as clinical note-taking — are not medical devices, and their oversight rests on professional accountability and the human in the loop rather than product certification. This clears the compliance path for rapid rollout of administrative healthcare AI and signals that Singapore's healthcare AI regulation will be tiered by whether a tool influences clinical decisions, rather than applying one rule to all AI.
Open digest, stances, and transcript

Workers' Party MP Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health in a written question which public healthcare institutions have deployed AI-assisted clinical note-taking tools, whether such tools are classified as medical devices under the Health Products Act, and if not, what mandatory safeguards exist to ensure their accuracy and safety. Minister for Health Ong Ye Kung replied that because AI-assisted clinical note-taking does not diagnose, manage or treat medical conditions, these tools are not medical devices regulated under the Health Products Act. Healthcare professionals are required to go through the AI-generated notes before adding them to their clinical records, so the notes ultimately remain the professional's own rather than the AI tool's — the principle of keeping the human in the loop when implementing AI tools. The reply did not name the institutions that have deployed such tools.

Key Points
  • • AI-assisted clinical note-taking does not diagnose, manage or treat medical conditions, so such tools are not medical devices regulated under the Health Products Act
  • • Healthcare professionals must go through AI-generated notes before adding them to clinical records; the notes ultimately remain the professional's, not the AI tool's
  • • MOH frames this as the principle of keeping the human in the loop when implementing AI tools
  • • The reply did not name which public healthcare institutions have deployed such tools
Government Position
The Government draws the regulatory boundary by function rather than technology: because AI clinical note-taking tools do not diagnose, manage or treat, they are kept outside the Health Products Act medical-device regime, with no additional mandatory certification. Responsibility for safety rests with the user — healthcare professionals must review AI-generated notes before entering them into records, and legal and professional accountability for the notes stays with the clinician, which MOH calls the "human in the loop" principle.
Questioning Position
Workers' Party MP Jamus Lim asked the Government to state which public healthcare institutions have deployed AI clinical note-taking tools, whether they are classified as medical devices under the Health Products Act, and, if not regulated under that Act, what "mandatory" safeguards ensure accuracy and safety. His concern was that errors in AI-generated records could affect patient safety and that the current framework may have a regulatory gap; the reply gave no list of institutions and cited no mandatory measure beyond clinician review.
"Ultimately, the notes are still from the healthcare professional, not the AI tool. This is the principle of keeping the human in the loop when we implement AI tools."
Original transcript excerpt
Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health which public healthcare institutions have deployed AI-assisted clinical note-taking tools, whether such tools are classified as medical devices under the Health Products Act, and if not, what mandatory safeguards exist to ensure their accuracy and safety. Ong Ye Kung replied that AI-assisted clinical note-taking does not diagnose, manage or treat medical conditions, so such tools are not medical devices regulated under the Health Products Act. Healthcare professionals are required to go through the AI-generated notes before adding them to their clinical records; ultimately the notes are still from the healthcare professional, not the AI tool. He described this as the principle of keeping the human in the loop when implementing AI tools. The reply did not identify which institutions have deployed the tools, nor did it describe any mandatory safeguard beyond professional review of the generated notes.
15 Parliament Information

Enhancing Retrenchment Statistics to Capture AI or Automation as Contributing Factors

Nominated MP Sanjeev Kumar Tiwari asked the Acting Minister for Manpower in a written question whether the Ministry plans to enhance its retrenchment statistics to better capture contributing factors such as artificial intelligence (AI) or automation, rather than recording them under the broad category of business rest...

Policy Signal: Singapore's official employment statistics do not yet treat AI as a standalone cause of retrenchment. Even as the debate over an "AI transition with no jobless growth" intensifies, MOM remains cautious about quantifying AI's impact on jobs, and any improvement in data granularity is still at the "continue to study" stage — meaning policy debate will lack an official baseline on AI-driven retrenchments for the near term.
🎙️ Mr Sanjeev Kumar Tiwari · Jasmin Lau
Open digest, stances, and transcript

Nominated MP Sanjeev Kumar Tiwari asked the Acting Minister for Manpower in a written question whether the Ministry plans to enhance its retrenchment statistics to better capture contributing factors such as artificial intelligence (AI) or automation, rather than recording them under the broad category of business restructuring, and if so whether a detailed breakdown by occupational group could be provided, particularly for Professionals, Managers and Executives (PMEs). Acting Minister for Manpower Jasmin Lau replied that it is currently difficult to isolate the impact of AI or automation as a primary driver of retrenchments, because automation is typically implemented as part of broader business transformation or restructuring exercises. The Ministry will continue to study how it can better capture the impact of AI and automation in its retrenchment statistics. The answer gave no timeline for any change and made no commitment to an occupational breakdown.

Key Points
  • • Tiwari asked for retrenchment statistics to break out AI or automation from the broad "business restructuring" category, with a breakdown by occupational group, especially PMEs
  • • MOM said automation is typically embedded in broader business transformation or restructuring exercises, making it difficult at present to isolate AI or automation as a primary driver of retrenchments
  • • MOM committed to continue studying how to better capture the impact of AI and automation in its retrenchment statistics, but gave no timeline or commitment to a breakdown
Government Position
MOM acknowledges a blind spot in its retrenchment statistics but keeps the current classification, arguing that automation is usually embedded in wider business transformation or restructuring and cannot easily be isolated; it commits only to keep studying better ways to capture the effect, with no promise to change categories or provide an occupational breakdown.
Questioning Position
Nominated MP Sanjeev Kumar Tiwari's concern is that the broad "business restructuring" category masks the real impact of AI and automation on jobs, especially for PMEs; he wants finer-grained official data so that the effect of AI on white-collar roles can be assessed and debated.
"It is currently difficult to isolate the impact of artificial intelligence (AI) or automation as a primary driver of retrenchments as automation is typically implemented as part of broader business transformation or restructuring exercises."
Original transcript excerpt
Nominated MP Sanjeev Kumar Tiwari asked the Acting Minister for Manpower whether the Ministry plans to enhance retrenchment statistics to better capture contributing factors such as artificial intelligence or automation, instead of recording them under the broad category of business restructuring, and if so whether a detailed breakdown of such cases by occupational group, particularly among Professionals, Managers and Executives, could be provided. Acting Minister for Manpower Jasmin Lau replied that it is currently difficult to isolate the impact of AI or automation as a primary driver of retrenchments, because automation is typically implemented as part of broader business transformation or restructuring exercises. She said the Ministry will continue to study how it can better capture the impact of AI and automation in its retrenchment statistics. The written answer did not set out a timeline for any change to the statistics and did not address whether an occupational breakdown would be published.
15 Parliament Information

Companies that Have Adopted AI and Their Experienced Outcomes in Areas Such As Job Redesign, Creation of New Roles and Changes to Use of Contract Staff

Sanjeev Kumar Tiwari asked the Acting Minister for Manpower in a written question for a breakdown by firm size of companies that have adopted artificial intelligence and the outcomes they experienced, such as job redesign, creation of or redeployment to new roles, lowered hiring, changes in the use of contract workers...

Policy Signal: This is the first time the Ministry of Manpower has given Parliament AI adoption rates broken down by firm size (27.2% / 54.8% / 76.4%), and it sets the official narrative as "AI reshapes jobs rather than cutting them". Two signals follow: the Government holds firm-level AI adoption survey data and will keep tracking it; and adoption among smaller firms is under half that of large firms, so both the gains and the workforce risks of AI transformation sit with large companies, leaving room for later SME-focused AI support measures.
🎙️ Mr Sanjeev Kumar Tiwari · Jasmin Lau
Open digest, stances, and transcript

Sanjeev Kumar Tiwari asked the Acting Minister for Manpower in a written question for a breakdown by firm size of companies that have adopted artificial intelligence and the outcomes they experienced, such as job redesign, creation of or redeployment to new roles, lowered hiring, changes in the use of contract workers or reduced headcount. Acting Minister Jasmin Lau replied that AI adoption in Singapore is uneven, with larger firms more likely to adopt. In 2026, 27.2% of smaller firms with fewer than 200 employees had adopted AI, compared with 54.8% of mid-sized firms with 200 to 500 employees and 76.4% of larger firms with more than 500 employees, reflecting the greater capacity of large firms to invest in and deploy AI in their operations. Based on the Ministry of Manpower's survey findings, AI-adopting firms reported workforce outcomes such as job redesign, creation of new AI-related jobs and redeployment of workers, rather than reductions in employment; larger firms were more likely to report these outcomes than smaller firms. The Government will continue to monitor AI adoption and its impact so as to support businesses and workers in adopting AI in a way that creates good jobs and new opportunities. The reply gave no figures on lowered hiring, contract-worker changes or headcount reductions.

Key Points
  • • AI adoption in 2026 splits by size: 27.2% of firms under 200 employees, 54.8% of firms with 200 to 500, and 76.4% of firms above 500
  • • MOM's survey found AI-adopting firms reported job redesign, new AI-related jobs and redeployment of workers rather than reductions in employment
  • • Larger firms were more likely than smaller ones to report these workforce outcomes, reflecting their greater capacity to invest in and deploy AI
  • • The Government will keep monitoring AI adoption and its impact; the reply gave no figures on lowered hiring, contract-worker changes or headcount cuts
Government Position
The Ministry of Manpower's reading is that AI in Singapore firms is so far producing job redesign and new roles rather than layoffs, and that the adoption gap is mainly a gap in firm size and investment capacity. The Government casts its role as continued monitoring and helping businesses and workers adopt AI in a way that creates good jobs, without announcing new measures to lift adoption among smaller firms.
Questioning Position
Questioner Sanjeev Kumar Tiwari sought an outcome breakdown by firm size that included the negative results — lowered hiring, changes in contract-worker use and reduced headcount — to see AI's real effect on workers at firms of different sizes; the reply supplied adoption rates and a qualitative conclusion but no numbers on those negative outcomes.
"Based on the Ministry of Manpower's survey findings, AI-adopting firms reported workforce outcomes, such as job redesign, creation of new AI-related jobs and redeployment of workers, rather than reductions in employment."
Original transcript excerpt
Sanjeev Kumar Tiwari asked the Acting Minister for Manpower for a breakdown by firm size of companies that have adopted AI and the outcomes they experienced, such as job redesign, creation of or redeployment to new roles, lowered hiring, changes in the use of contract workers or reduced headcount. Acting Minister Jasmin Lau replied in writing that AI adoption in Singapore is uneven and larger firms are more likely to be adopters. In 2026, 27.2% of smaller firms with fewer than 200 employees had adopted AI, compared with 54.8% of mid-sized firms with 200 to 500 employees and 76.4% of larger firms with more than 500 employees, which generally reflects larger firms' greater capacity to invest in and deploy AI. Based on the Ministry of Manpower's survey findings, AI-adopting firms reported job redesign, creation of new AI-related jobs and redeployment of workers rather than reductions in employment, with larger firms more likely to report these outcomes. The Government will continue to monitor AI adoption and its impact to support businesses and workers in adopting AI in a way that creates good jobs and new opportunities for Singaporeans.
15 Parliament Information

Plans to Enhance Traffic Management Systems by Leveraging AI and Predictive Analytics

PAP MP Melvin Yong Yik Chye asked the Minister for Transport in a written question whether the Land Transport Authority (LTA) has plans to leverage artificial intelligence and predictive analytics to further enhance Singapore's traffic management systems, including optimising traffic signal timings and other traffic ma...

Policy Signal: AI in Singapore's road traffic management is moving from "data collection" to "data-driven control": ERP 2.0 supplies a new network-wide vehicle-position data foundation, which LTA is feeding into the Cooperative and Unified Smart Traffic System now under pilot to dynamically control traffic lights, with AI video analytics filling the incident-detection gap. This is a rare case of public-sector AI applied to real-time control of physical infrastructure, but it remains at the experimental and pilot stage, with full deployment still years away.
Open digest, stances, and transcript

PAP MP Melvin Yong Yik Chye asked the Minister for Transport in a written question whether the Land Transport Authority (LTA) has plans to leverage artificial intelligence and predictive analytics to further enhance Singapore's traffic management systems, including optimising traffic signal timings and other traffic management measures in real time to reduce congestion. Minister for Transport Jeffrey Siow replied that LTA continually explores and leverages new technologies to improve traffic management and the efficiency of the road network. For example, with the transition to Electronic Road Pricing (ERP) 2.0, LTA can use ERP 2.0 data to enhance traffic management and transport planning, and is experimenting with using this data to dynamically optimise the traffic light signal system via the Cooperative and Unified Smart Traffic System, a smart traffic light control system that LTA is currently piloting. LTA is also enhancing its traffic incident detection capabilities using AI-powered video analytics so that motorists can be warned of incidents earlier; these capabilities will be progressively rolled out over the coming years. The answer gave no pilot scope, timeline or quantified targets.

Key Points
  • • LTA continually explores new technologies for traffic management; with the transition to ERP 2.0, it can use ERP 2.0 data to enhance traffic management and transport planning
  • • LTA is experimenting with ERP 2.0 data to dynamically optimise the traffic light signal system through the Cooperative and Unified Smart Traffic System, a smart traffic light control system now being piloted
  • • LTA is strengthening traffic incident detection with AI-powered video analytics so motorists are warned earlier, to be rolled out progressively over the coming years
  • • The answer gave no pilot scope, timeline or quantified congestion-reduction targets
Government Position
The Ministry of Transport frames AI and predictive analytics as part of LTA's ongoing technology evolution rather than a new dedicated programme: ERP 2.0 vehicle data is the new data foundation, dynamic optimisation of traffic lights is still at the experimental and pilot stage, and AI video analytics for incident detection will be "progressively rolled out over the coming years". The tone is pragmatic — exploration and trials, with no quantified commitments.
Questioning Position
MP Melvin Yong's concern is road congestion: he wants LTA to go beyond exploration and actually apply AI and predictive analytics to real-time measures such as optimising signal timings, so that congestion relief is tangible.
"LTA is also enhancing its traffic incident detection capabilities by using artificial intelligence-powered video analytics, so that motorists could be warned of traffic incidents earlier."
Original transcript excerpt
Mr Melvin Yong Yik Chye asked the Minister for Transport whether LTA has plans to leverage artificial intelligence and predictive analytics to further enhance Singapore's traffic management systems, including optimising traffic signal timings and other traffic management measures in real time to reduce congestion. Minister for Transport Jeffrey Siow replied that the Land Transport Authority continually explores and leverages new technologies to improve traffic management and enhance the efficiency of the road network. With the transition to Electronic Road Pricing (ERP) 2.0, LTA can leverage ERP 2.0 data to enhance traffic management and transport planning, and is experimenting with using this data to dynamically optimise the traffic light signal system to improve traffic flow via the Cooperative and Unified Smart Traffic System, a smart traffic light control system that LTA is currently piloting. LTA is also enhancing its traffic incident detection capabilities using artificial intelligence-powered video analytics, so that motorists can be warned of traffic incidents earlier. These capabilities will be progressively rolled out over the coming years to improve traffic flow. The written answer did not specify the scope of the pilot, a rollout timeline, or measurable congestion targets.
15 Parliament Information

Reports from IHLs on Use of AI to Cheat in Examinations

MP Foo Cexiang asked the Minister for Education in a written question whether the Ministry has received reports from any Institutes of Higher Learning (IHLs) about the use of AI to cheat in examinations. Minister for Education Desmond Lee replied that there have been instances of students using artificial intelligence...

Policy Signal: Singapore's approach to generative AI in higher education is "devolved enforcement plus assessment redesign": MOE sets no national reporting or penalty standard for AI-enabled cheating, but uses its guidance on responsible AI use as the frame within which each IHL updates its own academic integrity policies and redesigns assessments. This matches the Government's wider "use AI well rather than ban it" stance, and implies that national data on AI-related academic misconduct will not be published any time soon.
Open digest, stances, and transcript

MP Foo Cexiang asked the Minister for Education in a written question whether the Ministry has received reports from any Institutes of Higher Learning (IHLs) about the use of AI to cheat in examinations. Minister for Education Desmond Lee replied that there have been instances of students using artificial intelligence (AI) tools in ways that contravene the academic integrity policies of the IHLs, including in assessments, and that these cases have been addressed by the IHLs in accordance with their respective disciplinary frameworks and processes. In line with the Ministry of Education's guidance on the responsible use of AI in education, the IHLs regularly review and update their academic integrity policies and corresponding disciplinary frameworks to ensure responsible AI use among students and faculty, and strengthen assessment design so that assessments remain valid measures of students' learning and capabilities. The answer did not disclose the number of cases or which institutions were involved.

Key Points
  • • MOE confirmed there have been instances of students using AI tools in ways that contravene IHLs' academic integrity policies, including in assessments
  • • These cases were handled by the IHLs under their own disciplinary frameworks and processes; MOE did not disclose case numbers or institutions
  • • In line with MOE's guidance on responsible AI use in education, IHLs regularly review and update their academic integrity policies and disciplinary frameworks
  • • IHLs are also strengthening assessment design so that assessments remain valid measures of students' learning and capabilities
Government Position
MOE acknowledges the problem exists but leaves enforcement with the IHLs: cases are dealt with under each institution's disciplinary framework, with MOE supplying only its guidance on responsible AI use. The emphasis is not on banning AI but on requiring institutions to keep updating academic integrity policies and to redesign assessments so they remain genuine measures of learning in the AI era.
Questioning Position
MP Foo Cexiang's concern is the actual extent to which AI tools are being used to cheat in higher-education examinations, and whether MOE is receiving reports from institutions — that is, whether the problem is on the regulator's radar and being tracked systematically.
"There have been instances of students using Artificial Intelligence (AI) tools in ways that contravene the academic integrity policies of the Institutes of Higher Learning (IHLs), including in assessments."
Original transcript excerpt
Mr Foo Cexiang asked the Minister for Education whether the Ministry has received reports from any Institutes of Higher Learning (IHLs) about the use of AI to cheat in examinations. Minister for Education Desmond Lee replied that there have been instances of students using artificial intelligence tools in ways that contravene the academic integrity policies of the IHLs, including in assessments. These cases have been addressed by the IHLs in accordance with their respective disciplinary frameworks and processes. He added that, in line with the Ministry of Education's guidance on the responsible use of AI in education, the IHLs regularly review and update their academic integrity policies and corresponding disciplinary frameworks to ensure responsible AI use among students and faculty, and strengthen assessment design so that assessments remain valid measures of students' learning and capabilities. The written answer gave no figures on the number of cases, did not identify the institutions involved, and did not describe the sanctions imposed.
15 Parliament Information

Mandatory Data Security Requirements for Patient Data Processed by AI Tools Through Third-party Cloud Services

Workers' Party MP Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health in a written question whether mandatory data security requirements apply to AI tools that process patient data through third-party cloud services. Coordinating Minister for Social Policies and Minis...

Policy Signal: Singapore's data governance for healthcare AI runs on a dual track of existing law plus institutional contracts: rather than legislating separately for AI or cloud deployment, it treats the Healthcare Services Act and the PDPA as a common floor, and lets public healthcare institutions gate access through legally-binding provider commitments (no retention of input or output data) and secure access environments. This pushes the data-retention risk of large-model vendors upstream to procurement, effectively setting the entry conditions for AI in the public healthcare system.
Open digest, stances, and transcript

Workers' Party MP Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health in a written question whether mandatory data security requirements apply to AI tools that process patient data through third-party cloud services. Coordinating Minister for Social Policies and Minister for Health Ong Ye Kung replied yes: data security requirements apply to AI tools that process patient data whether they are hosted on third-party cloud services or on-premise, and these requirements arise under both the Healthcare Services Act and the Personal Data Protection Act. Public healthcare institutions have also adopted additional safeguards. For example, the AI model providers they work with must give legally-binding commitments that all input and output data are not stored or retained, and the AI tools must be accessed from secure environments. The answer did not describe specific technical standards or how compliance is audited.

Key Points
  • • AI tools that process patient data are subject to data security requirements under the Healthcare Services Act and the Personal Data Protection Act, whether hosted on third-party cloud services or on-premise
  • • AI model providers working with public healthcare institutions must give legally-binding commitments that all input and output data are not stored or retained
  • • AI tools must be accessed from secure environments
  • • The answer did not set out specific technical standards or a compliance-audit mechanism
Government Position
MOH's position is clear: there is no distinction by deployment model — AI tools on third-party cloud and on-premise are equally bound by the Healthcare Services Act and the PDPA — and above that legal floor public healthcare institutions add a contractual layer (legally-binding provider commitments and secure access environments). The Government considers the existing framework sufficient for AI use cases and proposed no new dedicated legislation.
Questioning Position
Workers' Party MP Jamus Lim's concern is whether patient data, once processed by AI tools running on third-party cloud services, remains covered by mandatory rather than voluntary security requirements — in other words, whether outsourced healthcare AI leaves a regulatory gap in data protection.
"For example, AI model providers whom they work with must give legally-binding commitments that all input and output data are not stored or retained."
Original transcript excerpt
Assoc Prof Jamus Jerome Lim asked the Coordinating Minister for Social Policies and Minister for Health whether mandatory data security requirements apply to AI tools that process patient data through third-party cloud services. Minister for Health Ong Ye Kung replied that they do: data security requirements apply to AI tools that process patient data whether hosted on third-party cloud services or on-premise, and these are requirements under both the Healthcare Services Act and the Personal Data Protection Act. He added that public healthcare institutions have adopted additional practices to safeguard data. For example, the AI model providers they work with must give legally-binding commitments that all input and output data are not stored or retained, and the AI tools must be accessed from secure environments. The written answer did not name specific technical standards, list which AI tools or providers are in use, or describe how compliance with these commitments is monitored.
15 Parliament Information

Whole-of-Government Guiding Principles to Manage Workforce Transitions Due to Organisational Transformation and AI Adoption

Nominated MP Assoc Prof Kenneth Goh asked the Prime Minister and Minister for Finance in a written question whether the Public Service Division (PSD) has established whole-of-Government principles to guide agencies in managing workforce transitions arising from organisational transformation and AI adoption, including h...

Policy Signal: As an early adopter of AI within Singapore, the Public Service is setting the tone for workforce adjustment as "progressive absorption, internal first" rather than efficiency through layoffs: reskilling and redeployment are the default, with financial support only as a backstop when redeployment is not feasible. The Government also signals that it will not craft a separate workforce framework for AI, relying instead on existing organisational-transformation principles — treating public-sector AI transformation as part of routine organisational evolution.
Open digest, stances, and transcript

Nominated MP Assoc Prof Kenneth Goh asked the Prime Minister and Minister for Finance in a written question whether the Public Service Division (PSD) has established whole-of-Government principles to guide agencies in managing workforce transitions arising from organisational transformation and AI adoption, including how to balance retraining, redeployment, workforce restructuring, the preservation of institutional knowledge and operational resilience. Coordinating Minister for Public Services Chan Chun Sing, replying for the Prime Minister, said the Public Service continually reviews its organisations, functions, operating models and workforce requirements. Most transformation efforts and workforce changes are made progressively through reskilling, job redesign, redeployment and natural attrition; more significant restructuring is undertaken only where necessary, in response to fundamental changes in an agency's operating environment, mission or operating model. The governing principle is to support affected officers with care and practical assistance: as a fair and responsible employer, agencies prioritise reskilling and redeploying affected officers within their agency or elsewhere in the Public Service, and where redeployment is not feasible provide transition support such as financial support and employment facilitation. He said this approach maintains capabilities, institutional knowledge and operational resilience while the Public Service transforms to stay effective, responsive and future-ready.

Key Points
  • • The Public Service continually reviews agencies' organisations, functions, operating models and workforce requirements; most transformation and workforce changes are made progressively through reskilling, job redesign, redeployment and natural attrition
  • • More significant restructuring is undertaken only where necessary, in response to fundamental changes in an agency's operating environment, mission or operating model
  • • The principle is to support affected officers with care and practical assistance: prioritise reskilling and redeployment within the agency or elsewhere in the Public Service, and provide transition support such as financial support and employment facilitation where redeployment is not feasible
  • • The Government says this approach maintains capabilities, institutional knowledge and operational resilience while meeting future needs
Government Position
The Government frames Public Service transformation as a continuous, progressive process and positions itself as a "fair and responsible employer": workforce changes driven by AI adoption are absorbed first through reskilling, job redesign, redeployment and natural attrition, large-scale restructuring is an exception used only where necessary, and officers who cannot be redeployed receive transition support. The reply did not point to any dedicated principles or framework document specific to AI adoption.
Questioning Position
Nominated MP Kenneth Goh's concern is that AI adoption is reshaping public-sector jobs and that agencies may take divergent approaches to cutting, restructuring and retraining; he wants PSD to have explicit whole-of-Government principles that also weigh the preservation of institutional knowledge and operational resilience, rather than efficiency-driven headcount reduction alone.
"As a fair and responsible employer, agencies will prioritise reskilling and redeploying affected officers, whether within their agency or elsewhere in the Public Service."
Original transcript excerpt
Nominated MP Assoc Prof Kenneth Goh asked the Prime Minister and Minister for Finance whether the Public Service Division has established whole-of-Government principles to guide agencies in managing workforce transitions arising from organisational transformation and AI adoption, including how agencies should balance retraining, redeployment, workforce restructuring, the preservation of institutional knowledge and operational resilience. Coordinating Minister for Public Services Chan Chun Sing, answering for the Prime Minister, said the Public Service continually reviews its organisations, functions, operating models and workforce requirements. Most transformation efforts and workforce changes are made progressively through reskilling, job redesign, redeployment and natural attrition, with more significant restructuring undertaken only where necessary in response to fundamental changes in an agency's operating environment, mission or operating model. The principle is to support affected officers with care and practical assistance: agencies prioritise reskilling and redeploying them within their agency or elsewhere in the Public Service, and where redeployment is not feasible provide transition support such as financial support and employment facilitation. He said this maintains capabilities, institutional knowledge and operational resilience while the Public Service transforms to remain effective, responsive and future-ready.
15 Parliament Substantive debate

GovTech's Restructuring, Roles Redesign and Retrenchments, and Support for Affected Staff

Six MPs (Kenneth Goh, Patrick Tay, Louis Chua, Andre Low, Sharael Taha, Yip Hon Weng) questioned the Minister for Digital Development and Information on the first phase of GovTech's workforce transformation announced on 15 July 2026: whether the Ministry was consulted, the age, tenure and skills-gap profile of the 93 r...

Policy Signal: This is the first time a Singapore public agency has publicly retrenched technology staff because of an operating-model shift, and disclosed the age, tenure and seniority structure of those affected. The Government is explicit that headcount will rise while composition must change: software engineering, product management, data and cybersecurity become core roles while traditional project and vendor management shrinks, with IMDA's TechSkills Accelerator, IHL product-management coursework and GovTech's Digital Academy lined up to feed the pipeline. Jasmin Lau deferred the impact of AI on the economics of development to a separate debate but wants every engineer and product manager grounded in AI first, signalling that later phases will design roles with AI built in by default.
Open digest, stances, and transcript

Six MPs (Kenneth Goh, Patrick Tay, Louis Chua, Andre Low, Sharael Taha, Yip Hon Weng) questioned the Minister for Digital Development and Information on the first phase of GovTech's workforce transformation announced on 15 July 2026: whether the Ministry was consulted, the age, tenure and skills-gap profile of the 93 retrenched officers, why they were not transferable to other agencies, and whether redeployment was exhausted before external hiring. Senior Minister of State Jasmin Lau, replying for the Minister, said the Ministry supports the plan, to be implemented over two years. GovTech is moving from one-off project delivery to continuous product ownership; headcount will grow, with more software engineers, product managers, data and cybersecurity specialists and fewer project and vendor managers. The first phase affects 305 officers: 102 retained or redeployed, 110 on 12-to-18-month full-salary apprenticeships, 93 retrenched. The 40-49 age group is 42% of exiting officers, those above 50 about 30%, median tenure 5.4 versus 6.0 years. More than 300 openings were curated with PSD, the Skills and Workforce Development Agency and NTUC's e2i; all 93 remain on payroll and every outcome will be tracked. In supplementaries she conceded prolonged exit pathways bred anxiety, promised shorter timelines, clarified vendors remain partners and deferred AI's impact on the Public Service to a separate debate.

Key Points
  • • Phase one affects 305 GovTech officers: 102 retained or redeployed, 110 on 12-to-18-month full-salary apprenticeship pathways, 93 retrenched; the transformation runs over two years
  • • GovTech is shifting from one-off project delivery to continuous product ownership; headcount grows, with more engineers, product managers, data and cybersecurity specialists and fewer project and vendor managers
  • • The 40-49 age group is 42% of exiting officers, matching the affected pool; those above 50 are about 30%; median tenure is 5.4 versus 6.0 years; two-thirds were individual contributors
  • • All 93 remain on GovTech's payroll; more than 300 matching openings were curated with PSD, the Skills and Workforce Development Agency and NTUC's e2i, and the Government committed to tracking every outcome
Government Position
The Government frames GovTech's workforce transformation as necessary and endorsed by the Ministry: product ownership requires teams to take end-to-end responsibility for public digital products, and years of attrition and pilot retraining could not keep pace with the speed and scale of technological change, so retrenchment was unavoidable. It commits to three guarantees — retrain and redeploy internally before hiring externally, keep retrenched officers on full pay through the transition with career guidance and job matching, and judge the transformation on three measures (officer transition, capability building, service quality) — and will apply the same approach in later phases.
Questioning Position
Workers' Party MP Louis Chua pressed that GovTech's Chair had admitted the shift began years before the AI wave, so if it was foreseen, what skills gap did the retrenched 40-to-49-year-olds — flexible mid-career workers — actually have, and why could they not be repositioned within the Public Service. NCMP Andre Low asked for clarity on whether the 93 had stopped work, whether public-sector options had been exhausted, and for a commitment to monitor and publish their outcomes over six months to a year. Patrick Tay probed the exposure of contract staff and the share above 50; Kenneth Goh worried about damage to GovTech's employer reputation and innovative culture; Sharael Taha and Yip Hon Weng asked how the Government would keep investing in skills renewal under AI and automation to prevent further redundancy.
"This is not a story about GovTech needing fewer people who care about Public Service, it is about GovTech needing more people equipped to build and own the technology that Singaporeans depend on in the long run."
Original transcript excerpt
Seven questions from Kenneth Goh, Patrick Tay, Louis Chua, Andre Low, Sharael Taha and Yip Hon Weng probed GovTech's first-phase workforce transformation announced on 15 July 2026. Senior Minister of State Jasmin Lau, replying for the Minister for Digital Development and Information, said the Ministry was consulted and supports a two-year, phased shift from project delivery to product ownership. Of 305 affected officers, 102 were retained or redeployed, 110 placed on 12-to-18-month full-salary apprenticeships and 93 retrenched; the 40-49 age group is 42% of both groups, median tenure 5.4 versus 6.0 years, two-thirds individual contributors. More than 300 openings were curated with PSD, the Skills and Workforce Development Agency and e2i. In supplementaries she admitted prolonged exit pathways caused anxiety and promised shorter timelines, clarified vendors remain partners, said project-management contract staff are more exposed, put those above 50 at about 30%, confirmed all 93 remain on payroll, and committed to monitoring every retrenched officer. She deferred AI's broader impact on the Public Service to a separate debate while insisting all staff gain AI foundations.
15 Parliament Information

Implementation of Stay-down Measures for Non-consensual Intimate Images and Sexualised Deepfakes under the Online Safety Commission

Rachel Ong filed a written question to the Ministry of Digital Development and Information: (a) whether platforms directed by the Online Safety Commission (OSC) to remove verified non-consensual intimate images, including sexualised deepfakes, will also be required to implement stay-down measures such as hash-matching...

Policy Signal: Singapore's governance of deepfakes and intimate-image abuse has moved from "can it be taken down?" to the operational detail of "how do we prevent re-uploads?", while deliberately not hard-coding stay-down technology as a mandatory duty — keeping the flexibility of "any means that achieves the disabling outcome." Cross-border accessibility remains a structural gap that unilateral enforcement cannot fully close.
Open digest, stances, and transcript

Rachel Ong filed a written question to the Ministry of Digital Development and Information: (a) whether platforms directed by the Online Safety Commission (OSC) to remove verified non-consensual intimate images, including sexualised deepfakes, will also be required to implement stay-down measures such as hash-matching to prevent re-uploads or redistribution; and (b) what powers OSC has to prevent such content from remaining accessible globally, since access-disabling directions only pertain to Singapore end-users. Minister Josephine Teo replied that, on a valid report, the Commissioner of Online Safety is empowered to direct Online Service Providers (OSPs) to disable Singapore users' access to the specified harmful material, and the direction may be extended to identical copies on the platform. The Commissioner will not mandate specific technologies as long as the required outcome is achieved; non-compliance is an offence. Directions bind only access by Singapore users, but OSPs may remove access for others under their own policies and community guidelines.

Key Points
  • • The Commissioner can direct platforms to disable Singapore users' access to specified harmful content, extendable to identical copies on the platform
  • • No specific technology (e.g. hash-matching) is mandated as long as the outcome is achieved; non-compliance is an offence
  • • Directions bind only Singapore-user access; global takedown depends on the platform's own policies
Government Position
The Government governs sexualised deepfakes and similar harms in an outcome-focused, technology-neutral way: it gives the Commissioner power to direct platforms to disable access and cover identical copies, without locking in a specific technology; and while acknowledging the jurisdictional limit that directions reach only local users, it leaves global takedown to platform self-governance.
"The Commissioner of Online Safety is empowered by law to direct Online Service Providers to disable access by Singapore users to the specified harmful online material ... The Commissioner will not direct that specific technologies be used as long as the outcome indicated in the direction is achieved."
Original transcript excerpt
Rachel Ong asked MDDI whether platforms directed by the Online Safety Commission to remove verified non-consensual intimate images, including sexualised deepfakes, must also implement stay-down measures such as hash-matching, and what powers the OSC has to prevent such content remaining globally accessible when disabling directions cover only Singapore users. Minister Josephine Teo replied that the Commissioner of Online Safety can direct Online Service Providers to disable Singapore users' access to specified harmful material, extendable to identical copies, without mandating specific technologies so long as the outcome is achieved; non-compliance is an offence. Directions apply only to access by Singapore users, though OSPs may remove content for others under their own policies.
15 Parliament Information

Watermarking and Digital Provenance Standards for AI-generated Media, Metadata Preservation and Cross-platform Coordination

Rachel Ong filed a written question to the Ministry of Digital Development and Information: while testing standards and technical solutions to manage AI-related risks are still developing, (a) whether the Government is studying watermarking or digital provenance standards for AI-generated media; (b) whether authorities...

Policy Signal: Singapore's governance of AI-generated content sits at a "watch-and-align-with-international-standards" stage, deliberately not front-running a unilateral watermarking standard that could break global interoperability — a contrast with its readiness to legislate decisively in high-risk settings like deepfakes and elections. Until provenance technology matures, it will not rush to mandate.
Open digest, stances, and transcript

Rachel Ong filed a written question to the Ministry of Digital Development and Information: while testing standards and technical solutions to manage AI-related risks are still developing, (a) whether the Government is studying watermarking or digital provenance standards for AI-generated media; (b) whether authorities can compel preservation and disclosure of metadata identifying original uploaders; and (c) what cross-platform coordination measures across social media and websites are being considered. Minister Josephine Teo replied that the Government tracks the development of technical standards for identifying AI-generated content, including watermarking and digital-provenance approaches, and engages international and industry platforms such as the Coalition for Content Provenance and Authenticity (C2PA), which has over 6,000 members including major technology and AI companies. As these standards evolve, it will assess their applicability in the Singapore context, including cross-platform measures. Where criminal offences are disclosed, the Police are empowered to require platforms to disclose information — including uploader metadata and identifiable data where available — to assist investigations.

Key Points
  • • The Government tracks standards for identifying AI-generated content (watermarking, digital provenance) but has not mandated one — it will assess applicability as international standards evolve
  • • It engages international/industry platforms such as the Coalition for Content Provenance and Authenticity (C2PA, 6,000+ members)
  • • Where criminal offences arise, the Police can require platforms to disclose uploader metadata and other information
Government Position
On provenance for AI content, the Government follows international standards rather than setting its own: it plugs into global technical evolution through coalitions like C2PA and holds mandates back until standards mature. Today's real compulsion comes from metadata-disclosure powers in a criminal-investigation setting, not a general watermarking duty.
"The Government tracks the development of technical standards for identifying AI-generated content, including watermarking and digital provenance approaches ... As these technologies and standards continue to evolve, we will assess their applicability in the Singapore context, including cross-platform measures."
Original transcript excerpt
Rachel Ong asked MDDI whether the Government is studying watermarking or digital-provenance standards for AI-generated media, whether authorities can compel preservation and disclosure of metadata identifying original uploaders, and what cross-platform coordination is being considered. Minister Josephine Teo replied that the Government tracks technical standards for identifying AI-generated content — including watermarking and digital provenance — and engages platforms such as the Coalition for Content Provenance and Authenticity (over 6,000 members), assessing applicability to Singapore as standards evolve. Where criminal offences are disclosed, the Police can require platforms to disclose information, including uploader metadata where available.
15 Parliament Mild scrutiny

Key Risk Thresholds to Regulate High-risk AI Deployments and Mandatory Human Oversight for Fully Automated Decisions

Referring to the NAIS Update line that the Government will "regulate or legislate where necessary and effective," Alex Yeo asked MDDI: (a) what key risk factors or thresholds determine when a high-risk AI deployment would warrant regulation; and (b) whether the Ministry will mandate meaningful human oversight over full...

Policy Signal: Under direct pressure to "draw a line" around high-risk AI, Singapore explicitly chooses not to preset a general threshold or an EU-style risk tiering, instead decomposing AI risk into existing laws (employment, scams, elections) piece by piece, with sectoral guidelines as the backstop. This is the core of its divergence from the EU AI Act: no single comprehensive AI statute, but the existing toolbox plus sectoral soft law, tightened dynamically.
Open digest, stances, and transcript

Referring to the NAIS Update line that the Government will "regulate or legislate where necessary and effective," Alex Yeo asked MDDI: (a) what key risk factors or thresholds determine when a high-risk AI deployment would warrant regulation; and (b) whether the Ministry will mandate meaningful human oversight over fully automated decisions that materially affect individuals, such as employment decisions or high-risk scenarios. Minister Josephine Teo replied that, as with any technology, the need for regulation depends on how it is deployed, the nature of harm, and whether existing measures are effective. Many AI risks are already addressed by existing law — employers using AI must still comply with the upcoming Workplace Fairness Act, and the Online Criminal Harms Act lets the Police disrupt AI-enabled scams. Where existing measures are inadequate and a suitable response can be designed, the Government legislates in time, as with the Elections (Integrity of Online Advertising) (Amendment) Act. These are complemented by sectoral guidelines — MAS has consulted on Guidelines on AI Risk Management for financial services, and MOH has updated its AI in Healthcare Guidelines (AIHGle 2.0). The Government will keep studying the appropriate regulatory stance.

Key Points
  • • Whether to regulate depends on deployment, the nature of harm and whether existing measures suffice — no blanket "high-risk" threshold
  • • Many AI risks are already covered by existing law: the Workplace Fairness Act for AI hiring, OCHA for AI-enabled scams, the elections law for deepfakes
  • • Sectoral guidelines (MAS AI risk management, MOH AIHGle 2.0) complement the hard law
Government Position
The Government declines to preset a uniform "high-risk AI" threshold or a general human-oversight mandate, insisting on a case-by-case judgement by deployment and harm, and on reusing existing law first: it looks to statutes like the Workplace Fairness Act and OCHA before legislating anew, and closes gaps softly through sectoral guidelines. This is its "soft law first, hard law only where necessary" approach as applied to high-risk AI.
Questioning Position
Citing the NAIS Update's "regulate or legislate where necessary and effective," Alex Yeo pressed the Government to produce operational thresholds for what counts as "high-risk AI," and asked whether it would mandate human oversight over fully automated decisions that materially affect individuals such as employment — pushing the principle-level stance toward concrete rules.
"In Singapore's context, many artificial intelligence (AI) risks are already addressed through existing legislation ... Where existing measures are assessed to be inadequate and a suitable response can be designed, the Government will ensure its timely implementation."
Original transcript excerpt
Referring to the NAIS Update's "regulate or legislate where necessary and effective," Alex Yeo asked MDDI what risk factors or thresholds determine when a high-risk AI deployment warrants regulation, and whether the Ministry would mandate human oversight over fully automated decisions materially affecting individuals such as in employment. Minister Josephine Teo replied that the need to regulate depends on deployment, the nature of harm and whether existing measures are effective; many AI risks are already addressed by existing law (the Workplace Fairness Act, the Online Criminal Harms Act, the elections advertising law), complemented by sectoral guidelines such as MAS's AI Risk Management guidelines and MOH's AIHGle 2.0. The Government will continue to study the appropriate regulatory stance as the technology and risk landscape evolve.

Analytical Views

Interpretive layers distilled from the archive.

💡 Key Insights

Data sovereignty becomes a core issue

Important

As the AI industry grows, data sovereignty and preventing foreign monopolisation become persistent priorities; the government emphasises both international cooperation and security safeguards.

Singapore's AI economy and data sovereignty; AI firm acquisitions and local talent safeguards.

Workforce transformation policy deepens

Important

The government drives inclusive workforce transformation, supporting mid-career reskilling and skills transfer in response to debates over AI substitution and complementarity.

Study of AI's impact on SME workforce; Jobs Transformation Maps and mid-career support.

Multi-faceted integration of AI in education

Education policy emphasises age-progressive AI use guidance, integration with brain science, and diverse pedagogies to balance academic rigour with creative-capacity development.

Age-progressive generative AI framework; brain-science and adaptive AI education collaboration; balancing PSLE rigour with AI skills.

Regulatory mechanisms move toward flexibility

AI M&A uses voluntary notification; regulation emphasises balance between innovation and competition, with debate over whether oversight is sufficient.

Regulatory review of Meta's Manus acquisition.

AI ethics and transparency rise

For AI-generated-content disclosure and advertising rules, the government drives guidance updates that balance consumer protection with industry innovation.

Property agents declaring AI-edited images.

Preventive healthcare AI accelerates

Important

MOH unveils the ACE-AI tool to predict chronic disease risk under an 'AI-enhanced, not AI-decided' principle; BRCA genetic-testing subsidies and MediShield Life expansion mark healthcare AI entering substantive deployment.

2026 MOH Committee of Supply: ACE-AI rollout; BRCA1/2 genetic-testing subsidies.

Skills-training funding remains insufficient

Participation in AI-related training is rising, but funding support and course customisation remain contested; the government continues to refine.

SkillsFuture AI training take-up and support; extending SkillsFuture Credit to AI tool subscriptions.

📈 Policy Evolution

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⚡ Recurring Controversies

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⚖️ Core Policy Tensions

Innovation speed vs regulatory safety

Encourage fast innovation and market vibrancy
vs
Emphasise risk control and fair competition
Current balance: Flexible regulation with voluntary notification.

Data openness vs data sovereignty

Push international data collaboration and sharing
vs
Guard against foreign monopoly and data leakage
Current balance: Emphasises both data security and international cooperation.

AI substitution vs workforce transformation

AI substitutes some roles to lift efficiency
vs
Safeguard employment and support reskilling and conversion
Current balance: Push inclusive transformation and skills upgrading.

Education equity vs creative-capacity development

Focus on academic rigour and core competencies
vs
Emphasise inquiry-based and collaborative learning
Current balance: Integrate diverse pedagogies, balancing equity and innovation.

Funding support vs course customisation

Increase funding to broaden training coverage
vs
Optimise course content to meet diverse needs
Current balance: Continuously refine course content and funding allocation.

🎙️ Key MP Profiles

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📡 Policy Signal Tracker

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