Mr Speaker, the Motion before this House calls for an AI transition that does not leave Singapore’s workers behind. The Prime Minister, the Labour Chief, the Government as a whole, have all said the same in the past months; that this is what they intend. What I want to examine this afternoon is whether the policy architecture we have is equal to the commitment we are being asked to affirm.
Mr Speaker, every AI deployment a firm makes is at its heart a choice. The firm can use AI to make its existing workers more capable, more productive, more valuable than they were before — or it can use AI to do without those workers entirely. The economist’s shorthand for this is augmentation as opposed to automation: augmentation, where AI works alongside the worker, and automation where AI replaces them.
Stanford economist Eric Brynjolfsson, one of the leading academic voices on AI and labour markets, has made a convincing case that in an unaided market — without deliberate policies steering in the other direction — incentives systematically favour automation. Firms find it easier and cheaper to deploy AI to replace workers than to retrain them. The tax code, the labour market institutions, the cost structures of capital all tilt the playing field. Even though augmentation creates more total value over time — more good jobs, broader prosperity and a fairer distribution of the gains — the default trajectory of an unguided system is automation.
The Government’s chosen and declared direction is augmentation. The Motion before us today assumes augmentation. The Labour Chief in this Chamber yesterday put the same commitment in his own words — not AI instead of workers, but AI working for workers.
The philosophical direction is settled across the aisle. The substantive question is whether our policy architecture matches it.
There are three places where the architecture is currently miscalibrated. Three places where, today, the system is permitting automation despite promises to the contrary.
A safety net that pushes workers toward the wrong choice #
The Labour Chief yesterday said that AI is also reshaping professional, manager and executive (PME) jobs in higher-end professions, like doctors, lawyers and accountants. The Prime Minister has said much the same — AI will affect Singapore’s professionals, managers and technicians (PMETs) who have spent years building specialist careers and who are now being told that the ground below them is moving.
At his May Day rally last week, Prime Minister Lawrence Wong said: “We may not be able to protect every job, but we will protect every worker.” The question is whether the instrument the Government has chosen — the SkillsFuture Jobseeker Support scheme — delivers on that promise. The Prime Minister has termed the Jobseeker Support scheme the “Singapore way” — a more pragmatic, more Singaporean alternative to the redundancy insurance that is the Workers’ Party’s (WP’s) preferred solution. That reads the Singapore tradition backwards.
Mr Speaker, the Labour Chief said in this Chamber yesterday that financial support during the transition is not welfare, it is an investment in worker outcomes. By that test, the tradition has long been built on investments of exactly that kind. The Central Provident Fund (CPF), MediShield Life, MediSave — these are all universal contributory schemes paid out when life’s major contingencies hit. Each catches every worker because the contingency it insures against can hit every worker. That is the Singapore way.
The Jobseeker Support scheme is not built in that tradition. It is a tax-funded grant gated on pre-redundancy income, closer in design to means-tested assistance than to insurance against contingency. As currently configured, it pays up to $6,000 over six months in tapering monthly instalments, starting at $1,500 and ending at $750 over the last three months — and it is only available to workers who earned $5,000 a month or less before they were made redundant.
The Labour Chief acknowledged in this Chamber yesterday that the ceiling excludes PMEs who face the same displacement risk in the AI era, and has proposed raising the qualifying ceiling closer to the PME median gross income level.
If this proposal is adopted, it is movement in the direction the WP has long argued for. But Mr Ng’s proposal moves the line; ours would remove it. Raising the ceiling lets more workers into the scheme, but it does not change what the scheme does for them. For those who do qualify under the ceiling, the taper carries its own message: a payment that starts high and slowly reduces is not a floor. It is a countdown. And a countdown pushes a worker to take the first offer, not the right one.
MOM’s own data tells us why this matters. Of retrenched residents in the final quarter of last year, 43.6% of PMETs had not found new employment within six months. That is the cohort the Jobseeker Support scheme runs out on. And of those who do find work within six months, roughly four in ten return at lower wages than before. They took what was available, not what their experience was worth. Most of us have experienced how, the higher up the career ladder you climb, the longer it takes to find your next role.
Mr Speaker, a PMET pushed by a six-month countdown into a lower-paid job they did not want has experienced exactly the automation outcome the Government’s framework was supposed to prevent — with a small cushion attached for the fall. Raising the ceiling only widens the cohort; it does not shorten the countdown.
Mr Speaker, the WP’s proposal for a redundancy insurance scheme is built in the actual Singapore tradition. We pay out 40% of last-drawn salary, with no income ceiling and no tapering mechanism. It is funded by employer-employee contributions in the same model as CPF, and it covers every worker who pays in — including the professionals the Labour Chief has identified as the most exposed, because the contingency it insures against does not stop at $5,000, $7,600 or any other ceiling Parliament may set.
The Prime Minister said we must protect every worker. The instrument the Government has selected does not. The WP’s does.
A tax code that is silent at the fork #
Mr Speaker, when a firm is contemplating a major AI deployment, it stands at a fork in the road. Down one path, it retains its existing workers and retrains them to operate alongside the AI. Down the other, it retrenches, runs leaner, and brings in a smaller AI-fluent workforce. The first is augmentation. The second is automation. But what does our tax code say to the firm at that decision point?
The current architecture rewards activity. It rewards capital expenditure on AI. It rewards expenditure on training. These are good things to reward. But what the architecture does not currently do is reward the choice itself.
A firm that retrenches its existing workers and trains a smaller set of new hires receives the same fiscal treatment as a firm that retains and retrains its existing workforce. A firm that buys AI to replace workers receives the same fiscal treatment as a firm that buys AI to augment them.
The tax code is silent at the fork. And as Brynjolfsson observed, silence at the fork is not neutrality in consequence. When the tax code does not actively reward retention, the underlying economics tilts firms toward retrenchment. Labour is, after all, the most expensive line on a balance sheet, and labour costs are permanent in a way that one-off training costs are not. An unaided market would choose retrenchment.
Yesterday, Mr Ng defended the CTC framework in this Chamber as the mechanism that ties enterprise transformation to worker progression, and proposed expanding it through the new Tripartite Jobs Council.
CTC operates at the project level for firms that engage with it, with grant funding attached. Expanding its reach scales the grant model, but does not change the broader fiscal architecture every firm operates within, whether or not it is within the CTC scheme. And it is this broader fiscal architecture that shapes CFOs’ financial decision-making at the decision point.
In February, in this House, I proposed a Retraining Tax Credit — a deduction available only to firms that can demonstrate they have retrained an existing worker into an AI-augmented role rather than retrenching them. It is the missing conditional piece that would give firms a fiscal signal precisely at the point where they have to make a decision. This Retraining Tax Credit would reward a proactive choice, instead of simply investing in AI.
No way to verify whether augmentation is actually happening #
The fourth limb of this Motion affirms that economic progress must remain inclusive. That is a commitment about distribution, not just growth. My colleague Gerald Giam has proposed a National AI Equity Fund to deliver on that commitment structurally. The instrument I am proposing today is the diagnostic tool that any redistributive mechanism — including Mr Giam’s — needs to operate on. Because the third condition for an augmentation strategy to be real is verification.
Mr Speaker, augmentation is, in the end, a testable claim. It makes a prediction: that wages in the sectors where AI is being deployed alongside workers will track the productivity gains those workers helped to create. If that prediction holds, the framework the Government has adopted is being delivered as advertised.
If productivity rises in these sectors but wages do not move alongside it, then what is being delivered is something other than augmentation, whatever language we use to describe it. Right now, we have very few mechanisms and very few systematic ways of telling which is occurring.
The Government is investing serious public money at scale in four National AI Mission sectors — advanced manufacturing, connectivity, finance and healthcare. Public funds are flowing into these sectors and more through the CTC grants, the newly-formed Tripartite Jobs Council, the SWDA and various enterprise transformation programmes. These are appropriate investments. But public investment creates a corresponding public accountability obligation. Where public money goes in, the public has a right to know what is coming out — and to whom.
So what I am asking for is a targeted transparency mechanism: an annual AI Gains Audit, scoped specifically to the four National AI Mission sectors to start, reporting to Parliament on how productivity gains from State-backed AI investment are being distributed between wages and returns to capital. Over time, its scope and coverage can be expanded.
In February, in my Budget speech, I framed this as a distribution question. Today, with this Motion before the House asking us to affirm that economic progress must remain inclusive, I propose it again as something more fundamental.
The AI Gains Audit is the most direct instrument available to Parliament to test whether the Government’s chosen direction of augmentation is actually being delivered. If the gains are being shared with workers, the audit will say so, and the framework will have the evidence to back its claim. If they are not, we will know — before the gap becomes a chasm, and before this Motion becomes a statement of hope rather than of policy.
Conclusion #
Mr Speaker, the choice between augmentation and automation is not made in one day. It is made every day by the architecture of the schemes we run, the tax code we maintain and the data we choose to collect. Whatever this House says today, that architecture will keep making the choice on our behalf.
Right now, my position is that the architecture pushes workers towards the first available job rather than the right one. Our tax code says nothing at the fork between retraining workers and retaining them. And we have built no mechanism to tell whether the gains from public AI investment are reaching the people in whose name that investment has been made. And that is why I support this Motion.
I urge the Government to give it the architecture it requires, so that we can make sure no worker is left behind. Thank you, Mr Speaker.
Clarifications #
Following responses by Minister of State Ms Jasmin Lau and Minister Dr Tan See Leng.
Thank you, Speaker. I have clarifications for the Minister of State Lau and the Minister.
My clarification for Minister of State Jasmin Lau is — I am glad to hear that she has put to me that automation and augmentation are not mutually exclusive. She went on to define that as being intentional about automating repetitive and physical tasks and upgrading the skills of that same worker. I am glad to hear that, because that is exactly how I have defined augmentation in my speech. And she also noted that I used the term automation in my speech as a shorthand for scenarios where a job is entirely, fully automated away at the expense of the worker. That is abundantly clear.
To Minister Tan — he suggested that the proposals by my colleague Mr Gerald Giam and myself are anchored on the premise that Singaporeans are hapless passengers along for the ride on this AI journey. I would urge the Minister to clarify how he has managed to read that basis into our speeches.
And secondly, I will simply use the language of Minister of State Lau as well — that we do not believe that strong social safety nets, and upskilling Singaporeans and urging them to embrace AI, are mutually exclusive. It is not a zero-sum game. It is not a binary equation. In fact, we believe that strong social safety nets are precisely what will enable Singaporeans to take a risk-taking approach and embrace the opportunities that AI will deliver.
