Well, you need access to electricity. You need access to digital infrastructure. People have to be geared to adoption. And the government should be able to give some safety, protect against bad actors so that adoption can work. We have done some estimates. I admit we all look into the future and it's a bit foggy. By our estimates, growth in Asia for the advanced Asia can go up somewhere between half a percentage and one percentage point. 1% additional growth is a very big deal and even in the emerging Asia it could be somewhere between 0.2 and 0.8%.
Now when I talk percentages very often people say, so what, what is 1%? Let me tell you what it is. If advanced Asia, that is aging very rapidly, was to gain 1%, this would more than offset the loss that comes from aging population. So AI would compensate for aging and even exceed that compensation. Now, why is it that we are excited about AI? It is a transformative technology. It so completely changes how we work, how we live. I'll finish with this. This morning, my AI assistant in the 30 seconds instruction that he gives me every day said, 'Your number one thing today is the panel with President AJ Banga and President Harmon. Be ready.'
Thanks, Cristina. Imagine if he got it wrong. I told you you were doing something else.
They say, yeah, I can give you false results. The only real president in this group is this guy. The rest of us are not. So I think there's the false result.
Well, I'm going to call you president of the World Bank right now. So that's not an AI instruction. So let's get back to you then, AJ. So we heard from Cristina there talking about the economic opportunities particularly in developing countries. So I want to pick up on what this event is all about in some ways, which is small AI in developing countries. What does it look like in practice, AJ, and how can it create jobs and opportunity? And I think just picking up from what Cristina said about electricity and, you know, getting people online in the first place, how can small AI be accessible in the way that it's sort of developed? It's different, isn't it?
Yeah. So, you know, I've been very fortunate that President Tharman has helped us at the bank run what's called a jobs council. He's the co-chair of it and we have a group of people from academia, from public and private companies as well as from civil society. And we came out with five sectors that were critical to grow jobs. All of which are not reliant on outsourcing jobs from the developed world to the developing world, kind of the last 30, 40 years model, but instead build locally relevant jobs. And those five sectors connect to this conversation. And the first is infrastructure. It's construction, but then what it enables: bridges, roads, airports, digitization, electricity, water, but also human infrastructure in terms of skilling and education and the like.
The second is agriculture for small farmers. Most of our economies are very heavily dependent on food grown by small farmers. They get competed to the point where it's tough for them to play in the system. But access to cooperatives, access to technology of the type we're building, I'll give you a couple of examples, enables them to get past that. The third one is primary healthcare and its delivery. Now, President Tharman was just speaking to it, but think of Indonesia with primary health care centers, each with a nurse, a midwife, and a medical diagnostic technician. Think of the quality and number of jobs you create through that extension and then use technology and AI to connect to remote doctors and the skills that may not be present in a primary healthcare center.
And the fourth is tourism and what it can multiply in terms of jobs. I mean, Thailand is a principal example, but they've got ambitions to go even further than what they've done this far. And then manufacturing, particularly value-added manufacturing, which is not pure extraction but creation of local jobs. Minerals and metals, the emerging markets are gifted with large quantums of deposits, but they need real quality jobs. But also look at Africa, the creative industries or the like, there's so many opportunities on manufacturing across whether you do this as an entrepreneur, to President Tharman's point about individual agency, or you do it out of working for others, all are possible.
That's the idea. Examples: healthcare clinic in Indonesia. You're the patient. I'm the nurse. You walk in and you say, 'I have a rash here,' and I look at it and I can't figure out what it is, but I can take a photograph and send it to the doctor I share with 20 other clinics.
I do actually have a rash.
Sorry about that. But I'll ask the doctor to intervene. And so he in turn can either look at it himself or run it through a simple local AI tool developed at the edge in a 3G phone. Local. It's very simple to do. Gets that and says it's an eczema. Give her this ointment. Tell her to go home. Or don't like it. Tell her to come to the regional hospital to meet the specialist in 14 days at 10:30 in the morning. That is a very difficult thing to do even in the advanced economies today. Getting a specialist appointment organized digitally is a very hard thing to do. So you can cut through the arbitrage of all this by creating simple AI tools.
Another one, something we're doing right now with farmers in India and elsewhere with Google's help actually, and I think the Google team are going to see this. It's the idea of a platform that's been built to connect farmers and cooperatives to better fertilizer, better seeds, better crop insurance, better credit, and most importantly, better offtake prices for their product. And so an illiterate woman farmer in India can point a 3G phone...
You may say, 'Oh, they're better off.' No, that is just because AI is further away. The small AI hasn't quite yet reached all of them. So you're asking a question that is really important to answer. What can be done?
Well, first we need to carefully research what is happening in the labor market. We have to gather information, analyze this information, and this is what we do at the fund. We did a study in the United States that shows that already 10% of jobs require AI skills, higher skills. They pay better. It shows that the routine repetitive jobs are shrinking, and very interestingly, it shows that low-paying jobs are increasing, and they're increasing in two directions.
drinking, they would be in a tough spot. So to make that long story about the slow-moving tsunami short, we cannot today imagine what exactly the world of work will be 5 years from now. But we can be disciplined and carefully assess what is happening and then draw lessons, but most importantly, act on them.
Okay. Thank you, Cristina. Well, you mentioned a lot of things that government should do. Conveniently, we do have a president sitting next to you. Obviously, you have a role on the jobs council as well. There's lots of really interesting points that Cristina raised about fiscal issues, about skills in particular, and let me ask you about skills then, because you've emphasized the need to invest in skills regularly, particularly the importance of public-private partnerships. What do you think governments and businesses can do differently then to make lifelong...
Mark, the evidence is already very clear. It's clearest in the most AI-exposed sectors, by the way, which are the tech sectors. But it's becoming clear across the board. And what governments did during COVID and what some governments did during the global financial crisis now has to be thought of not as a crisis measure but as part of the menu of structural policies that governments have for a new era, which is that governments have to get involved with the private sector to make that first job possible, to make that pathway into the first rung of your career ladder possible. We can't afford to lose that.
Because if you lose that, you not only have that cohort of young people waiting a year and then competing with the next cohort the next year, you lose more than one year of skills. You lose a whole set of intangible attributes and you lose trust in the future. So we've got to do now as part of public policy ways of incentivizing the private sector to take in fresh graduates so they get that first foot, first toe in the market and they learn from there. That's one policy implication.
But I also want to work backwards from what's happening in the world of work. Work backwards into the tertiary education system because I think there are two very important shifts that are required there. If you look around Asia, you look around the developing world, in fact, if you look around the advanced world and you think about how you have to avoid that middle getting displaced, the middle of the workforce getting displaced, it means we also have to change how the middle gets educated. And the reality of tertiary education systems, higher education, universities and the like, is that it's overwhelmingly academically focused.
And here again the data is already clear. The link between academic credentials and career prospects is weakening. In the US for the first time in a century, demand for graduates has gone down. The wage premium that college graduates earned has gone down very significantly. So we've got to take these as early signals of a new era, work our way back into the education system and reduce that skew that you currently find towards an academically oriented education towards an education that's more applied, has more bursts of work as part of education, more attachments, more internships, more of the dual model of education where you spend serious time in a firm as part of your tertiary education. Okay, that's one major shift that has to be made.
It's a critical issue for developing countries where you still have to develop that applied education stream. But one final point I'll have to make is one that comes from what Cristina said about the fact that we don't know what'll happen in 5 years' time. We need some humility amongst the education planners. Don't fixate on one particular model of education, particularly on the issue of depth versus breadth.
We don't know what will be required. The reality is in some areas you need great depth of expertise to be able to learn continually on the job. And there'll be other areas where you need more breadth of exposure to different disciplines because you have to integrate AI across functions. You've got to do many other jobs that require a breadth of human skills. But there is no one model. So don't fixate on one model. Have some humility. Be clear-eyed enough to realize that the future is fuzzy and agility is the way we have to go, not just for firms and industry, but agility in education itself.
Okay, thank you so much, President Tharman. We've run out of time, but it was really interesting to talk to you. I wonder if just in two words or three words you can give me a quick-fire thought on where you think things are going to be. You mentioned five years, things are going to change a lot. What would you like as your one big goal in five years' time? Start with you, AJ.
A realistic application of small AI in as many emerging markets as possible. That's what I'd like to get to.
Thanks, AJ. President Tharman.
Well, avoid a new divergence between the developing world and the advanced world and see continued convergence as we've seen in East Asia especially, using AI, using technology, and developing the best of human capabilities.
Okay, thank you. And last but not least, Cristina.
Get AI to do all the stuff we don't want to do and let us enjoy the things we love to do. High productivity, high standard of living, but also the dignity of being socially viable.
Thank you so much for your time, all of you. A round of applause, everyone. Thank you, AJ. Thank you, President Tharman. Thank you, Cristina.
I'm sure you'll all agree that was a really thought-provoking beginning to this discussion looking at the issue of skills and education when it comes to the future of AI and of course looking at technology and infrastructure as well. Now one of the central challenges around almost every conversation anyone has about AI is trust. The question is often asked, is it safe to use and do people really have the confidence to use it?
And thanks to being on a panel with the two of them is a privilege and I'm lucky to be here. I believe that the bank's entire focus has to be on jobs for a very simple reason. 1.2 billion young people in the coming 15 years are going to become 18 years of age. So that could be a huge demographic dividend if when they're growing up they get clean air, clean water, healthcare, education, skilling. But once they're grown, they need the opportunity to have and be a productive part of society. So the word job does not mean working for a big company or a small company or as an entrepreneur. It's being productive in society, having a sense of optimism and a sense of dignity that comes from earning and being a part of that system.
That's what we're talking about. The bank's entire focus has moved towards that over the last few years. It's not that we don't build a school or we won't build a highway or we won't build a skilling center or a healthcare clinic. We have to do all those, but we got to do them with the perspective of job creation which starts from having the right foundations, which is physical and human infrastructure, having the right governance and policies in place, something that Singapore has done very well in its history, and then having the right way to de-risk private capital to be able to come in and invest at scale because it is private capital that creates jobs. Governments enable and the private sector generates between 75 and 85% of jobs in any country. That's what we're trying to do.
How does AI fit in? In the emerging markets where the conversation is not about large language models, where people are concerned about the possible impact on jobs, possible, not proven yet, but possible in the emerging markets, it's about applications that could add enormously to productivity for a school, an educator, a healthcare system, an agricultural system for small farmers to get to scale. And hopefully as we speak as well as from the subsequent panels, you'll get a bunch of examples of that type. That is what we are focused on, the rollout of small AI into the emerging markets as the productivity enhancer.
Okay. Thank you very much, AJ. Let's move on to you, President Tharman. AJ mentioned your country and the work that you're doing when it comes to developing AI. You've said in the past that AI may disrupt jobs in advanced economies but could create a different risk for developing economies, and AJ made that distinction in some way just then. You say that new jobs may simply not be created fast enough in developing countries. What do developing nations need to do now, President Tharman, to make sure that their young people are able to participate and benefit from the next wave of technology and economic growth? And as we just heard there from AJ, you know, it's the future of young people and jobs that's so crucial to all of these conversations.
