Intro: Is your job safe from AI? Or is the real question, is your country ready? As artificial intelligence reshapes, Singapore faces a critical challenge. How do we equip citizens to thrive? And how must public policy evolve to redefine the social contract between government, businesses and workers?
Welcome back to Policy Unpacked, where we unpack ideas, stories and people shaping the future. Today we're joined by Dr. Reuben Ng, assistant professor at Lee Kuan Yew School of Public Policy. His work focuses on trust, social resilience, and the narratives shaping technology. Together, we'll unpack the future of work in the age of AI and what Singapore must do to stay ahead. Welcome, Reuben. Thanks for joining us.
Reuben: Thank you, Zubaidah. Great to be here.
Zubaidah: Great. Let's dive into the first one. I'm quite excited to talk about AI today with you because PM Lawrence Wong at the recent rally speech also delved into this, right? So let's get the ball rolling. What types of jobs are most vulnerable to AI disruption in Singapore?
Reuben: Thanks, that's a great question. So like you correctly mentioned, Prime Minister Lawrence Wong, he devoted a significant amount of time at the very start of his speech talking about AI. So that's not very common. Typically, we are talking about setting broad agendas, but he dives straight into some of the forces shaping our society today.
Now, I think it's really important to understand that this AI (Artificial intelligence) sort of movement is paradigm shifting. Everything is going to change because of this. But it's also important to understand that it didn't just happen overnight. It was actually happening 10 - 20 years ago.
Now, you know, two careers ago, before I joined the Lee Kuan Yew School of Public Policy, I helped a huge consulting firm set up their data and AI practice. This was about 15 - 20 years ago. So at that time, nobody knew what AI was. In fact, we were preparing for months for a big presentation to a conglomerate, telling them to think about implementing AI or artificial intelligence. So we prepared for months for this. Then, we went. There was a big room with the founder of the conglomerate there. So we started talking.
As a project director, I stood up, started talking about artificial intelligence. Within the first minute, the guy just stood up and said that "We don't want anything artificial. We just want things that are natural.” And he just walked out of the room.
So all these months of preparation kind of went down the drain. But fast forward 10 - 15 years later, what do we have in 2022? ChatGPT came to public consciousness. I recall it was November 2022. And after that, there's not one day that nobody talks about AI. So from then, nobody knows what AI is. "I only want natural stuff. I don't want artificial." Fast track to almost everyone is talking about AI. It's almost an explosion of AI narratives.
Zubaidah: I mean, we're using AI every day.
Reuben: Exactly.
Zubaidah: Some form of it.
Reuben: Exactly. So I think the fundamental question is then, how will it change jobs? So I think jobs will be changed in so many ways. I'll just give you an example of the jobs I used to previously do. So I used to be in consulting, data strategy for governments and companies and things like that. So during that time, that was about 10 - 15 years ago. Coding was so important. But coding could, because of cost pressures, coding was starting to be outsourced to countries overseas, centers of excellence overseas. So in the past, we used to insource, but it was a bit more expensive than when we started to outsource.
Now, I'm seeing us coming back full circle. So these days, actually, this coding stuff could be done at a more cost-effective manner using AI. So there's no need to outsource anymore. So we are coming to insource. In fact, we are moving towards from outsourcing to insourcing to 'me-sourcing'. So essentially, almost every consultant these days, I speak to the big firms, they have what they call AI agents. So for every consultant or every employee, there are one or two AI agents. So it's all 'me-sourcing' now.
So if I need to do stuff before I go to sleep, it used to be a different time zone. So we'll get them to do stuff. So when I wake up in the morning, I get reports done. I get insights delivered to me. But now, it's an AI agent doing that.
So this is fundamentally disruptive. So what it means is that the jobs, the task mix within jobs will change. So if the task mix within jobs will change, which means that the people they are hiring to fill these jobs with a different task mix will be very different. So, I think it's quite fundamental.
The other point I would mention is that some years ago, I was doing a project for SkillsFuture Singapore, and we were trying to understand how could we get Singaporeans and how can we push them towards the top echelons of leadership? How can we have a couple more Singaporean CEOs of Fortune 100 companies, right? So I went on this mission to interview various CEOs to ask them about their insights.
So one of the things that, one of the views that really struck me was that this CEO was telling me that, "You know, Singaporeans are very good at finding answers to questions. If I set them a question, they're all very good at finding answers, but they're not so good at asking the question." But if you think about the AI revolution, ChatGPT as we are most familiar with, right?
It's all about asking the question, isn't it? We're not asking the question, AI can't work for us.
Zubaidah: That's right. It's all about the prompts, right?
Reuben: Exactly. So I think there's going to be a fundamental shift of not just how to find answers to the questions, but how to ask the right questions.
Zubaidah: I think it's great that you mentioned you touched on SkillsFuture, because that leads me to the next thing.
Singapore has SkillsFuture and now AI Strategy 2.0. Are these enough?
Reuben: You know, it's never enough because we are talking about a digital evolution, rather a digital revolution, right? But we are talking about policy evolution. So an evolution will never be able to catch up with revolution. So I think it will never be enough. But we just need to try as much as possible, not just to be reactive, but also to be more proactive in our policy-making, scenario planning, and things like that.
So, you know, you correctly mentioned about the AI Strategy 2.0. So kudos to the Singapore government, they came up with the AI Strategy 2.0 in 2023, and they have been iterative. So just before coming to talk with you, I looked at the latest iteration was some days ago, August 2025. So kudos to the Singapore government, it is very forward-looking, and they always iterate on the AI Strategy.
But I think we need to understand that policy-making AI Strategy is but the first mile. We also need to think about things like what happens in the middle mile and what happens to the last mile. Because in the middle mile, the last mile stuff doesn't happen, then the first mile won't get us to where our destination is. So I think the middle mile, there are a couple of things that come to my mind.
Now, one of the biggest employers in Singapore is really the small, medium-sized enterprises, the SME sector. So I think the middle mile really got to be focused on what we call Enterprise SkillsFuture. Now, the very early iterations of SkillsFuture gives certain skills credits to individuals to study what they want. Pick up skills of what they want.
But sometimes the skills are not too related to professional upscaling. So the second iteration or the third iteration can focus on enterprise sort of SkillsFuture credits. So I think that's the way to go because different sectors are at different maturity points when it comes to AI implementation. Or even AI appetite or what really works for them.
Because at the end of the day, we don't want it to be just implementing AI for the sake of implementing AI. It must be purposeful. So does it decrease your cost? Does it increase your sort of revenue and things like that? So I think the middle mile needs to focus on a very sectoral approach. So it could be down to first of all, understanding AI readiness.
So there used to be this digital readiness index by then, I would say MCI or now MDDI. So I think similarly, I think it's good to create what we call AI Readiness Index so that any company, any SMEs could come, the CEO could do this readiness index to understand.
Okay, I'm actually in this quadrant. And this is what I need to be moved to the next quadrant of AI implementation. Then the package that I get will be very different from say your company, who is maybe AI mature and now want to be accelerated to the next level. So the package of things that you can implement and the skillset mix is very different from you compared to me. So this is essentially a more different strokes for different folks approach. So I think that's really something to think about.
So meaning, let's talk about what it actually means. So from the F&B industry, for example, I may be running a restaurant or cafe. Maybe I open at 8.30 AM, I close at 5.30 PM. Now, usually after lunch and before dinner, it's usually the time when nobody really comes. So it could be an AI engine that takes into account the data that I have of people coming to visit and things like that. And then I can just ask the question to that AI intelligent chatbot to say, should I open from 2.30 to 4.30? Or what time should I open? So maybe I can save costs during those hours when nobody comes, but then there is potential in the evening, right?
So things like that, I think AI is able to do. But we need to sort of connect the dot for different sectors because they need kind of different things. Even for bigger companies, for lift maintenance, for example, there were a lot of talks about how many lifts we have. I think we have maybe among public housing, we have 28,000 to 30,000 lifts, right? And lift breakdowns are very difficult, right? Because of an ageing population, I need to go to the hospital. I'm on a wheelchair. I'm mobility challenged and things like that. So keeping the lifts running is extremely important.
That's where AI can come in. You know, instead of being reactive, let's say the lift breaks down, I get the lift technician to go, we can be a bit more proactive to understand what's the risk that this lift will break down and send the maintenance team before it actually breaks down. So kind of predictive maintenance, right? So different sectors will need different sorts of approaches for the society to get better. Because they function. Either for the economy or society. So that's what I mean by that middle mile, different strokes for different folks from an enterprise perspective.
Now the last mile is really to get all our citizens on board. Now, if you think of the previous SkillsFuture iteration, it was actually intended for professional upskilling. But a couple of years ago, I think there were some parliamentary questions about actually how many people use these credits. I think only, if I remember the stats correctly, I think only one in four have actually used their SkillsFuture credit and less than 10% actually used it fully.
But if you look at the top three courses that people use it for, I think it was: Number one: flower arrangement. Number two: Korean. Number three: maybe karaoke. So there seems to be this mismatch of the policy intention and actually the policy implementation. So I think what really matters to close that gap is policy communications.
How can we use policy communications to nudge people. To actually use their SkillsFuture credit and to use it in a way that will benefit them professionally. So I think if we can think of strategy as the first mile, different strokes or different folks as the middle mile and policy communications to really drive it home as a final mile. I think we would be seeing great Return On Investment (ROI) of our good policy.
Zubaidah: So many things I'm picking up from you, like the AI Readiness Index. That's really interesting. Maybe you should spearhead that from LKYSPP. Then the other thing is about this last mile thing that you talk about, the policy communication aspect. I remember when I was doing a course for public policy design and there was a policy problem that I was thinking about, it was SkillsFuture. And the exact thing was actually about how's the implementability, should something change? So thanks for giving me an idea actually.
Reuben: I think we should spearhead this together.
Zubaidah: Well, let's do this after the chat. But let's move on to the next thing. I wanted to ask you:
Should Singapore explore new policy ideas like Universal Basic Reskilling?
Reuben: Yeah, that's a very interesting idea: Universal basic reskilling. The question is, what would those universal skills be? That's always really challenging. Some thoughts come to mind.
I think the first is, so you know I'm really interested to do global studies and a couple of years ago, we partnered with Gallup to do the largest survey study of 140 countries about how people think about risk. We kind of need to understand how people think about risk then we can communicate risk better to them.
Case in point was the COVID-19 pandemic. Risk perceptions could influence whether they wear a mask or not and things like that. So what we found was quite interesting. So every time we ask… This was about maybe 155,000 participants from 140 countries covering almost 99.5% of the world's population. Now, when we ask them, what do they associate risk with? 70% of the participants of the survey actually say that they associate risk with danger. Only 30% associated risk with opportunity. So I think therein lies an opportunity. We always think about some of these things as sort of dangerous, I don't wanna do it. But not many people think about it as an opportunity.
So I think beyond just a universal basic skill is that universal mindset that we need to have, that universal motivation that we need to have to sort of imbue in people in Singapore and around the world that yes, we want to manage risk but we also want to see the opportunity. So I think once we see that opportunity then we are able to think about what are some of the skills that can help us accelerate finding the opportunity.
But of course, when it comes to AI and things like that, there'll be increased risk of scams. So I think the other thing is to help people be a bit more vigilant to understand how do we balance not falling prey to scams but also seeing this AI sort of revolution as an opportunity.
Then of course, the other thought that I have is back to how do we ask the questions. So it's not about finding the answers anymore because AI is very good at doing that for us, a lot better and a lot faster than maybe how we think we would usually get answers. So I think the fundamental thinking behind it is how do we ask the questions? So behind that is about deep thinking, deep work. And I think that itself is very critical alongside the universal skills mix.
Zubaidah: And that speaks to critical inquiry. And I think that that's how you need to have that emotion. And the other thing I want to pick up was that when you mentioned fighting scams, I mean, you of course won that award for Scam Fighter, right? Scam Fighter of the Year Award. So it speaks to the work that you do that sort of like encompasses this whole facet of data AI and such.
There's another question that I want to ask and let's move along. Inequality and Digital Exclusion: who gets left behind?
Reuben: Actually, we tend to think… You know, I was reflecting on this important question that you asked. Immediately my mind went to older adults and things like that. But actually those are demographic segments that we have very good initiatives to cater to. We have digital initiatives for older people. We have very good programmes in schools.
So I think I want to take a step back to think about actually who falls through the cracks? Who are the unconventional, because it's a revolution. So there'll be people who fall through the cracks. So I think there are two groups of people who tend to fall through the cracks.
One is people who have left the labour market involuntarily or voluntarily.
So I have four kids at home, so they're all very young. So my wife made a sacrifice and left the job market to take care of our kids. As they were growing up and we started having more kids. So I think for example: full-time parents, full-time mothers, full-time fathers. Those are probably one group that we don't want to sort of neglect.
The other group that is stepping away voluntarily from work would be caregivers. And in this segment of society, psychologists call that established adulthood from 35 to 49. I'm in this group so I can speak for my age group.
We face what we call a career-care-crunch. Why is it a crunch period now? Because we are delaying childbirth. So it used to be that we take care of kids when we're in our 20s, then when we are maybe late 40s or 50s or even 60s, we take care of our parents. But now we take care of our kids. Young kids - from when we are in our 30s and early 40s. And our parents also had kids later.
So what's happening is that in our late 40s, early 50s, we are also taking care of our parents. So we have a career to try to navigate, but now we have sort of interlocking stages of life where we have to take care of kids and older adults. And they all come together, you see.
So would I have time to reskill? Would I have time to think about looking out for whether my job is secure? I won't. So even though I'm in the labour market, people like myself cannot really participate fully or there's no spare bandwidth or time.
So I think we probably need to, with this digital and AI revolution, think about some of these groups of people who are left behind, non-traditional groups, because these are new groups that come to mind. And think about how we can leverage some of the different stages or interlocking stages in life to make sure they're not left behind. So for example, I know of many colleagues, brilliant data scientists, AI scientists, who left their jobs because they wanted to take care of ageing parents or their kids. Maybe before they leave, it's to tell them that these are different areas to stay in touch with your skills.
We probably want to take what we call, what I call hyper-local approaches. Now there's always a digital screen in the lift landing of every HDB flat. The void deck. So I think it's to bring on board.
I think as Prime Minister Lawrence Wong also mentioned in the recent National Day Rally speech. It could be CDC-led. CDC of voucher fame, if you remember them. But now maybe it's really to take a hyper-local approach to be as inclusive as possible so that this unconventional group, which maybe we have not thought of before, would not be left behind.
Zubaidah: Right. Well, thanks for that. I mean, I understand completely about the sandwich generation that they talk about because I think a lot of my peers, and myself is like that as well. And I think it's a really big issue that we face a lot. It's relatable.
So let's see, we can actually take this further into the next question: What can Singapore learn from Denmark, Finland and South Korea?
Reuben: So many things. These countries are brimming with good ideas. They have good policy agendas, great policy implementations. But I just want to preface to say that sometimes there are all these best practices. But best practices may not be best for us.
So I think it's important to get some of these policy ideas and adapt them so that it works as best as possible in Singapore. A couple of examples come to mind. I think we know that Singapore is on the cusp of being a super-aged society, which means that one in five persons in Singapore will be 65 years and above.
So for that, I think we can look towards Japan, who has been quite brilliant in using some of these AI solutions to help keep older adults engaged.
Now, one of the things that they do very well is to have micro jobs. So it's so interesting because PM Lawrence Wong recently mentioned that one of the key initiatives that I thought was very hyper-local was jobs near you. So actually, Japan has been doing all these jobs near you for a long time. They call it micro jobs, but maybe micro jobs near you. So in wherever you are, whether it is Miyazaki, Kyushu, Sapporo, Hokkaido and things like that, there will be this micro jobs portal. It's kind of online, so you can use your mobile phone to maybe book a short work packet of 3 - 4 hours from 2 to 5 a.m. at 7-11. So they make it really easy, really seamless. And it's sort of part of the culture.
Now, it's really interesting because I was having a chat with my Japanese colleagues about how it is that AI is so well accepted in Japanese society. So they told me something I thought was quite interesting. They said, "Oh, because of manga." Because manga, you know, all the time. You have all these AI robots, all different manifestations of AI. And it's very well accepted.
So people in their 90s, centenarians, they remember reading manga, which has been around for a long time. So it's almost as if it's a part of life from sort of fictional, and now it is actually happening in reality. And Japan is great because I remember when they had Digital Revolution 4.0. They said that to manage Digital Revolution 4.0, we have Society 5.0. I think Japan is great to learn from AI implementations for an ageing society.
The other thing that comes to mind is Denmark. They really help you manage transitions. There's this term called flexicurity. So I think, you know, in this world of Digital Revolution, there may be many job cycles. There will be a lifetime of different jobs, or sometimes involuntary. Which means that there'll be a lot more transitions compared to the past. Which is, it might make the work or job market more dynamic, but then it means a lot of relearning. So I think one thing we can sort of learn from them is how do we help workers manage that transition? Some of those transitions could be involuntary. No choice, right? I'm retrenched, like what's happening a lot now in the economy. Or it could be, I really want to go to an adjacent job.
So, AI solutions are abound. One of them could be, let's say for example, I may want to move from my job currently in oil and gas to maybe the caregiving sector. The aged sector is one of the fastest growing sectors of our economy. So it might be interesting to first understand, say, this is my skillset mix. And how is this related to the supply and demand of skills in the caregiving industry.
Caregiving industry has changed in the last 5 - 10 years. Skills in demand in the caregiving industry 10 years ago may be quite different today. So maybe there are, because it's not possible for me to pick up 10 skills. But to understand what are the skills that are highest in demand, lowest in supply will help me quickly pivot to some other industry. And AI can actually make that happen. So we run a lot of these models as well. How do we know? So how do we know from job listings, they're out there for six months and nobody's filling it.
Which means that there's a demand for a skill, but in the supply we don't have. So things like this AI can actually help.
And the Scandinavian countries do that, I thought, very brilliantly.
The third thing that comes to mind is climate change in Singapore. So a lot of swings these days. And sometimes we wonder, such heavy rain again, thunderstorms. Could we know about it the day before? I don't know, but I think in a lot of these countries, US and countries around the world. They're very good at sort of weather nowcasting and forecasting.
And AI can help. With satellite imaging. Yes, I understand the challenges, Singapore is really small and things like that. But actually that could be a game-changer to plan our day, especially coming from a father of four kids.
Zubaidah: Hot, cold, not really. It's hot, and we're always here.
Reuben: Exactly. So I think the social contract is very, it's changing. So I really like what Prime Minister Lawrence Wong mentioned about having sort of a 'we first' society. So I think from a 'we first' perspective, what I interpret him as trying to achieve is that now because Singapore has been having a great trust dividend with the government and the people.
But if you think about the citizen and government, that's kind of the vertical trust perspective. What about this horizontal trust between different diverse groups of people in Singapore?
That's where I think the 'we first' tries to inculcate that sort of horizontal trust. So trust between sort of different groups of people. So I think that social contract, we probably wanna think about that. So we got to that, it also means that we want to think about how people can help each other.
So there were a couple of projects that I was doing for the banks in Singapore trying to get older adults to use mobile banking, internet banking. So we always think about, what can MAS (Monetary Authority of Singapore) do? What can the government do to try to communicate or nudge?
But actually when we did our research, we found that actually among older adults, there are those who love tech, so they were adopted even before their grandchildren. There are also older adults who are sort of, no, I don't wanna do that. So they are lagging behind for good reason. They don't wanna do that, I don't really trust it. So what it means is that you have the same age group of people. Some are very enthusiastic, some are not. So you can actually get them to help each other out. We call that a cross activation of different segments.
So I think that is the way to actualise a 'we first' society where we start to build trust laterally. Then the other thing that comes to mind, I think for social compact is that there's gonna be a lot of social isolation because of digital and AI. So these days we hardly talk to each other. It's just me and my mobile phone. So I think to manage that social isolation, what we wanna think about is how can we have more intergenerational bonding? So can we have more programmes or policies that bring together grandchildren and grandparents?
So on one hand, we try to achieve a sort of learning about AI together, decreasing social isolation, but also intergenerational sort of bonding. So I'm always thinking about how can one policy or one programme can achieve several outcomes.
Then the other thing is that we, I think it's quite important also to celebrate diversity. Now with this AI sort of revolution, there are so many pathways to success. I can now almost build a system with agentic AI tools.
So it's very easy now to start a business. It can be an OPO, OMO, one-man operation or one-person operation. Which means there are now so many possibilities.
I think we want to start thinking about to sort of engender that social compact, to feature divergent pathways and to celebrate them. So it can be as far-fetched as maybe somebody designing something for animals or for different interest groups. It can also be parents with four kids or more, we want to celebrate them.
So I was in Mongolia a couple of years ago, I was just curious about how it is that the young people there want… They'd like to have four or more kids and things like that. And I realised that it's because in Mongolia, they give this medallion for people with four kids or more. So as somebody who's very cheapskate.
My next question is, "Hey, you know, if you get a medallion, do you actually get a 10% discount at NTUC?"
So they apparently said, no. It's just for honour and glory.
Zubaidah: Honour and glory! That's really… I didn't think of that at all.
Reuben: Exactly, because we're always thinking about what are the financial incentives to nudge action.
But here I coined this as the 'honor nudge'. Very little money involved. But you nudge people's behaviour based on honour and recognition. I feel that we need to do a lot more of that. And that would actually be the catalyst to build a more cohesive society. I think that could be the attitude and strategy that underlies our social compact.
Zubaidah: I really enjoy the stuff that you raised, like AI readiness, like, you know, making sure that we don't leave people behind and how we actually look at policies to do that. And this bit, exactly this bit about policy communication to make sure that we are a kinder society despite and in spite of AI. That comes through.
So I really enjoyed this discussion.
Reuben: Thank you, I thoroughly enjoyed it too.
Zubaidah: Thank you so much, Dr Reuben Ng.
AI won't just replace jobs, it's redefining our expectations of government, employers and society. For Singapore, the challenge is not only to reskill workers, but to reimagine the social contract to ensure every citizen can thrive in a rapidly evolving smart nation.
My thanks to Dr Reuben Ng for his insights and to you for listening.
Stay tuned for our next episode of Policy Unpacked.