AI is disrupting the traditional entry point into professional careers by automating junior roles from law to finance to creative fields, positions that graduates have long relied on to gain experience. As a result, 40% of workers are worried about job security and whether AI will eliminate the pathway to a long-term career.
How can companies and workers adapt to ensure that career growth is still possible despite disruptions?
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At Davos 2026, panelists argued that AI is reshaping career ladders less by eliminating all entry jobs than by raising the baseline of “AI fluency” required to be employable. Andrew Ng contended that entry-level roles still exist, but education is “preparing them for the jobs of 2022… rather than the jobs of 2026 and beyond,” citing coding as the leading indicator: “I’m not going to ever hire another engineer again that doesn’t know how to use AI to help them code.” UAE Education Minister Sarah Al Amiri described a national response: the first public school system to mandate K–12 AI literacy, emphasizing tool use, ethics, and critical thinking so students can detect bias and avoid overreliance. Economist Christopher Pissarides urged separating hype from task reality: for many jobs AI may automate 30–40%, increasing productivity rather than replacing workers, while certain roles (e.g., translators, call centers, voice actors) face near-total displacement and require “a moral obligation” to support transitions. CEOs, said Himanshu Palsule, must redesign onboarding and apprenticeships toward “judgment, decision making, context,” and stop treating AI as point-solution efficiency. The next phase is workflow redesign that creates new products, not just cost savings—while governments and employers build lifelong learning capacity: “learn and relearn and unlearn.”
Good evening, ladies and gentlemen. Thanks very much for joining us here at the World Economic Forum's annual meeting in Davos 2026. I'm Shereen Bhan, the moderator for this session, also the managing editor of Cnbc-tv18, CNBC's operations in India. It's great to see so many wonderful people here, and it's great to have a panel here to discuss a topic that is getting a lot of attention and mindspace here in Davos. You know, we're talking about corporate ladders, AI reshuffle. But in the context of Davos 2026, reshuffled has taken on a whole new meaning. Where of course waiting for President Trump to arrive. And and it could take on an entirely different meaning here in the context of what happens with headlines. But I want to dive into the issue at hand. I think there is palpable anxiety about what AI is going to do in the near term, in the medium term, and in the long term to the jobs market. If you take a look at the World Economic Forum's jobs report, while there will be disruption, it does say that there will be net growth as far as jobs are concerned, at least at this point in time. The irony also is that while we talk about a catastrophic impact on entry level jobs, there are sectors where we continue to see significant gaps. There aren't enough skilled workers. The WAF in its report also talks about sectors like healthcare, where the gap is almost 11 million. You don't have 11 million people to service the healthcare needs. So that is also the irony that we are dealing with. But there's a lot of questions on what companies need to do, what companies are doing today, and whether that is adequate to upskill workers. What happens to entry level workers? Do we need software engineers anymore, or is code going to be written by large language models and generative AI? I think that's what we intend to dive into. This is going to be a free flowing conversation. I would appreciate it. If you do have questions, then do engage with our panel here. Do keep your questions short. We will come to you in just a second. But let's get things started by introducing our panelists to you, Sarah Bint Yousuf Al-amiri, the Minister of Education of the United Arab Emirates. Thank you very much for joining us. Christopher is the Regius Professor of Economics at the London School of Economics and Political Science from the UK. Andrew Ng, founder of Deeplearning.ai from the US. Himanshu, the chief executive officer of Cornerstone On Demand, also from the US. Thank you very much for joining us here, Andrew. Let's get started. And I think a lot of the headlines scream catastrophic disruption. What is going to happen as far as entry level jobs are concerned? Will it be a white collar bloodbath, so to speak? Let me get your view on that. To start with.
I think the entry level jobs are there and many businesses just can't find enough skilled entry level workers with the right AI skills. Unfortunately, I feel like higher education, which I love and has great force for good, is failing many fresh college graduates by preparing them for the jobs of 2022 before modern AI, rather than the jobs of 2026 and beyond. We're already seeing that in coding. For example, I'm not going to ever hire another engineer again that doesn't know how to use AI to help them code. Because AI tools have advanced so rapidly in software engineering and coding. Coding is, I think, a harbinger of what will happen in other sectors as well as tools enter other sectors. And I feel a lot of urgency to revise the academic curricula to give the students they need to be job ready because the jobs are there.
The jobs are there, the skills gap continues to exist, and it is only going to widen if we don't do something about the way that our education system functions. That's the point you're making.
Absolutely.
Minister, let me come to you now with that, because that's exactly the problem that you're trying to address at the UAE. And you've actually brought in AI as part of the curriculum. K to 12.
Yes, absolutely. So that's a very interesting point when it comes to higher education, which is the skilled workforce. I'll address that first and then take it back because we have a bit more time in preparing people to come to the workforce. When it comes to K to 12, when we're talking about higher education, higher education needs to start infusing AI. And we do have that in the UAE, starting to work with some of our universities to provide them with skills and the necessary tool sets to be able to advance with that. Right now, starting with basic AI literacy in higher education. But that needs to improve in subject level. So based on the subject level that each student in higher education is currently going through and the degree that they're pursuing, there needs to be a better tackling on the tools that today exist on the market and the rapid evolution of the tools. Now, how we're taking it to K to 12, we're the first public school system globally to mandate K to 12 AI literacy for all of our students. So today we have more than 280,000 students taking AI literacy at least once or once every two weeks. The core of the curriculum is the following. Students need to understand how to use AI, when to use it, what tools to use to be able to support them in their learning, and to be able to advance that. We've also instilled new training for educators on how to use existing AI tools to ease their job, and be able to do their job more effectively and more efficiently, and free up some of their time that is used on day to day work. We also need to relook the outcomes of the student themselves, and that's more about the broader long term impact and changes that need to happen in the education system.
You know, that's very interesting what you point out that the UAE is the first country in the world to mandate AI curriculum. And why did you feel the need to do that?
We looked at social media. Students have used social media extensively, haven't been given a code of ethics on how to use it effectively. What are the challenges of not using it in the correct mechanisms? And we've seen adverse effects on both their personalities, their social wellbeing and their social interactions as well. We saw that that might happen in their cognitive ability and the development of their cognitive ability when it comes to AI. So it was very important for us to design a curriculum for them to understand how to use it. We've embedded subtly critical thinking also within within the realms of AI. So the class goes as follows A student uses AI. For example, let's talk about prompt engineering, prompting it to get information about a particular subject, let's say World War One, and they try different prompts. And the teacher speaks with them based on critical thinking, on what prompt work better, what information was not biased, what information came out in accordance to what you understand. And that's also instilling a bit of change that we need to see in the education system, which is it's no longer about providing the knowledge and information to students and asking them to repeat it back. It's more about there's a lot of information and knowledge out there. Can you pick out what is relevant? Can you understand what is construed or skewed, and are you able to bring together groups and pieces of information and knowledge to be able to get a proper outcome and analyze that properly?
Yeah. Andrew, before I get, Himanshu and, professor into the conversation, I just want to go back to the point that you were making because in a way, what we heard there from the minister addresses the issue that you were raising. Do you believe that this needs to be the way forward across different countries?
I think K12 is an excellent time to start training people up on AI. Maybe in terms of the AI disruption of jobs at the entry level and beyond, I think the hype is beyond the reality. There have been layoffs, so on over the past year or two from where I'm sitting, a lot of it seems to be from overhiring from the pandemic rather than AI affected. But look into the future. I know just as an economist, a lot of my economist friends, every Brynjolfsson and others have done these task based analysis of jobs where you take a job, break it down into tasks, and figure out what AI can or cannot do. It turns out for many jobs, maybe AI could do 3,040% of the job. That means we still need people to do that 6,070%. But it is also true that someone that knows how to use AI will replace someone that doesn't, even if AI itself won't replace a person. So, getting through the hype to give people the skills they need is critical. And I would just add one asterisk to what I said, which is whereas for most jobs, we still need people to do 60, 70%. There's a small minority of jobs where AI can indeed do almost 100% of it, so those jobs will run into trouble. I'm worried about the translators. I'm worried about the voice actors. We're about the call center operators. And for those people, we actually have an obligation, I think, as a society, to moral obligation to take care of them. Because just because someone's job is going away does not mean they deserve to be thrown onto the street. And so the education system, upskilling, I feel like we need to get that right as well.
And I think the moral obligation that you speak of is an important but a complex issue that will have to be dealt with contextually in different jurisdictions. But, professor, let me come to you on the hype versus reality. And you know, where we we see these screaming headlines of so many jobs gone on account of AI. To Andrew's point, a lot of this could potentially have been because of overhiring through the pandemic, especially as far as the tech companies are concerned. You've been speaking with tech CEOs today. What are they telling you about entry level jobs?
Yeah, I'm afraid Andrew has stolen my thunder now. That's exactly what I was going to say. He said, you see, like I was going to say, I don't want to spoil the Davos party where everyone is. Hey, ho ho, you know, the if you look at it carefully, if you look at the labor market carefully, what do people do? You know, young people if you like entry level, although there are entry level people who are not young, about half I think Andrew said 40%. Well, I will take 40%. We'll never use AI. They don't need AI now. They go into health and care, hospitality, retail. These are usually not university graduates though, so I don't want to minister that they're wasting their time training because she was obviously talking about universities. So half the workforce is out of what remains. Most of them will need to use AI, but their jobs are not threatening. AI cannot do what the job will be doing. In contrast to that, what what they will be required to do by their companies is that they will apply some AI skills that they have, and the company will give them AI. It will invest in AI and they will become more productive. They will do things faster, better quality and everything like that. Now those those people are usually university graduates and and they're the ones that are benefiting from university education in AI. And and I think as we're moving in that direction too, we've been talking to anthropic and so on, then what remains are the people that if not 100% like Andrew said, maybe it's 80% that they can do it. And and usually those and the reason you get to hear so much about those is that they're usually in the professions. It's the way, you know, if you look, law accounting, I mean, those professions were structured more or less by the British in the 19th century, mainly. And they did it according to the education that existed at the time. You know, if you have usually a son, but let's say a child, a son or a daughter, what would they do? They would go to a private, what they call public school, but essentially private boarding school. They will come out, they will go to Oxford and Cambridge. They will get classic education like Boris Johnson or something similar. And then they and then they will enter one of the professions, law, accounting, where they will get their pupillage and, and their training and gradually they become partners that that's the one that is hit most. Because that's what generative AI in the large language models can do. And in fact, it's about time they got a kick in the backside and reform the professions. I mean, you know, you you cannot live in the 19th century English structure of education and professionals.
To to borrow from Professor Pissarides very eloquently, who is going to get a kick in the backside.
So Shirin, you talked about ironies. I think the greatest irony of our time is we are leaving behind a generation that is actually the most capable of implementing AI, and we are spending time reskilling middle management and senior management, which which is harder. So I think, Minister, the model that you have, I would say absolutely every school needs to follow that model. I think when you get junior people at work, I think it will be a mistake to introduce them to autonomous, repeatable roles because they're going to go away. I would focus on skills that involve judgment, decision making, context because those are going to be more important. I would rather have a junior financial analyst or a legal analyst coming in and spend their time examining the output of an AI tool rather than competing with with AI, you know, so as we look at these job structures, I believe what these young adults coming in are kids. Our grandkids need to sort of look at this T-shaped model where the breadth is, get good enough with AI, and the depth is pick a domain and then get good in that specialized in that domain, because that is going to become irreplaceable. And then for companies hiring these people, you know, create those environments, create those apprenticeships, create the area where they come in, especially if you have this education system K through 12, where there are AI fluent. I think we need to trust these people who are born digitally native in being able to adapt to this. So, you know, I'm very optimistic, but I think we need a fundamental reset in not just education, but in hiring, onboarding and training of these people.
You know, but, but and I want to pick up from what professor just said that, you know, are we are we largely talking about what's likely to happen in the tech sector or tech affiliated sectors, will will sectors like hospitality, healthcare and so on and so forth be as impacted by what we're speaking?
I think so if you heard what Yuval Harari had to say on stage, he said, any job that involves words, language and numbers is going to get disrupted because words, language and numbers, the cohort of information available to an AI agent is far going to surpass our ability to compete with that. So whether you're a lawyer who has to read all the books from the past, you're a financial analyst who has to understand complex models. You are a healthcare worker who has to understand efficacy of medicine, pharmaceuticals and diseases and all of that. Don't compete with your corpus of knowledge with what's going to be available there. Highlight the fact that context, judgment and decision making is going to be more important. So I respectfully disagree that while.
No, I love the fact that there's disagreement because that's that's the whole point of a debate. Yes.
You've mentioned word. I also add images because it also influences a lot the healthcare sector and diagnosis very well as well.
I love the fact that you're waiting to jump in. Go right ahead.
I agree, I agree both with Harari and and sorry I didn't pick up. Yeah, I if it involves words where where the disagreement is and I'm sure you're going to agree when you hear it is that is that these jobs that do not use AI they are not words jobs. If you become a nurse, your skill is not that you know how to put words together. You need empathy. You need to understand for sure the person you are looking after, Harari said. We have absolutely no evidence that AI has any feelings at all. If you go into the health sector, you don't need to have any kind of feeling, you need to have a special feelings. And by the time AI gets there, the current generation of nurses will no longer be there. It will be their grandchildren going to hospitality industry with these people who serve us out here, who give us those amazing espressos and, and other things that they serve, is their skill putting words together? Of course not. Their skill is not knowing how to treat the customer. I mean, you know, here we are, a sort of, not imprisoned, a captive, captive customer. But if they're going to attract you to go to their restaurant or their hotels, they need to feel that they understand you. They understand the customer. They are nice. It's it's not a word. If you if you put an AI agent at reception and you put the really nice people next door to another hotel, which which one would you go?
Well.
24 by seven.
No vacation, no paid leave. I don't know. that's probably.
The CEO, but but but but Andrew, let's double down on the point that's being made there. And you know, we're talking about a world of agents. We're talking about a world where digital labor and human labor will coexist in an environment like that. How do corporate leaders look at staffing? How do corporate leaders look at the challenges of workforce workforce management? You know, you talk to CEOs. What are they telling you at this point in time? What are the what is the dilemma that they're faced with?
So I find the term digital labor, challenging because I'm the one that coined the term agentic AI. So we saw this coming quite early. But, digital labor is a challenging concept because AI software is so different than humans that analogizing them to needing food and water and pay leave and so on is problematic analogies. When I speak of CEOs, I think the two biggest challenges. One is, upskilling, bringing people along with us because ultimately it's not the technology by itself, it's the people we bring with us that will implement the technology that drives the change. In fact, my cousin does a lot of work on skill measuring to help people figure out the skill gaps and what they need to learn. So that's one. And the second thing is, to the business leaders, I find that we've done this let a thousand flowers bloom bottom up innovation thing. And for the most part, it's led to a lot of nice little things, but nothing transformative for businesses. And what I'm seeing for businesses is, to execute the more transformative projects. The problem with a lot of bottom up innovation is if you look at a set of tasks needed to create value in the business, a lot of innovation ends up with point solutions. That takes one step out of five and makes it more efficient. Then you get these 510% efficiency gains, which are nice but not transformative. But it's usually when the bottom up innovation meets top down broader view. Then you can redesign the entire workflow from scratch. And that's what's creating more business growth. So actually here this week at Davos speaking with a lot of CEOs, they're thinking about how to go beyond the bottom up point solutions to taking the broader view to business process redesign. And I think that will finally realize a lot of the growth that AI has been promised.
But are we closer to that? Because the discussion and the debate and the conversations that I've still been having with people is it is still pretty much bottom up. It's still efficiency and optimization. It's not so much transformation just yet. So do we still have time before we see this kind of transformative impact for governments to be able to skill people, for corporations to figure out what they intend to do as far as the corporate structure is concerned, or are we out of time?
We still have time, frankly. There's workflow redesign is really hard. Maybe one one example that's been around for a little bit, take underwriting loans. There are multiple steps needed to do that. You have to do the loan approval, preliminary approval, diligence, execute the loan, manage and give out the loan over multiple things needed to create value. So what some people said is, oh, why don't we use AI to do the preliminary loan approval, which is nice. But if you take this whole process and make one step a bit more efficient, you get this, you know, nice small cost savings. But what some businesses realize is if I get AI to automate this step, what I can do is build a brand new product where instead of just a cost savings, I'm going to say, I'm going to get back to you on your loan approval in ten minutes instead of one week. So this is a materially different product and it drives business growth. But it takes that broader view where it's not someone automating one piece of the puzzle, but rethinking all the steps needed to create value to redesign that. That's what's driving growth. And frankly, this is really hard. We spent a lot of time with CEOs. One one large organization sent us almost 300 project ideas and asked my friend and I at AI aspire to sort out which are the ones that can drive strategic value. And we find this word really difficult and really intellectually deep. So I think it will be some time before businesses get to these, not the cost savings, but the significant growth opportunities.
Absolutely, before they move on to the transformation stage. But Himanshu, you know, again, I want to double down on this. What are what are companies telling you and how do you believe the workforce is likely to be restructured in the near term?
Yeah. So the skill shortage is very real. And it's driven also by an unprecedented amount of automation. You have these complex dialysis machines sitting idle because nurses cannot get trained fast enough. We have a customer that manufactures aircraft and the new avionics. There's no maintenance staff doing that. We spent a decade worrying about data flows. And it's Davos. Let's talk a little bit about cross border and that we came up with data sovereignty data governance. We build laws and all of that. We better start thinking about skills in the same way because there could be a quarter in Nigeria. There could be an analyst in Riyadh who has better skills than the people you may have just hired. And we need to be able to figure a way to fill those gaps quickly. That skills divide is going to keep getting wider, especially with more amount, more automation, more AI. And, you know, it's up to us to try to close that divide. The concern I have is, as you know, depending on, as you said, it's going to be a fascinating week here in Davos. Depending on where people retrench to, we may take a bad problem and make it worse. And then you have untethered AI that's unfairly used across geographies. That is my biggest worry. As a global company. We hire people from all over the world. Half our teams are outside the United States, and we really need to start thinking about this global skilling. We work with the Abu Al Ghurair Foundation in Dubai, and companies like that need to come to the table to have this discussion with with businesses.
Well, you know, easier mobility of of talent. That is an increasingly large challenge in the world that we live in at this point in time, with policies becoming more inward and more protectionist, including those that involve the mobility of of people. But that's a separate conversation. That's a separate debate. You know, I want to go back to the point that Andrew made about moral obligation, and I want to understand this from your perspective as somebody in government. Minister, the moral obligation, of course, is to skill, to educate. But in a situation where jobs are not growing fast enough or people who may have been left behind on account of the disruptions in specific sectors, what is then the obligation of the government in that situation?
It is the obligation of government to skill. And we do have a program that was launched at the back of Covid to skill certain individuals within society to be able to start filling in jobs within our private sector and ensuring that the private sector opens up new jobs to people to be able to fit into it. So the government is footing the bill to reskilling people. But there's another part of it, and I'll go back to my portfolio. Within the K-12 education system, governments are also, have to also build a future workforce, that is, that can reskill intrinsically. So teaching them the ability to learn and relearn and unlearn and continuous learning that we've been putting it as an objective for decades now, as an outcome of the education system, needs to be a top priority. Otherwise, governments who would need to continuously reskill people will be footing the bill more and more and more down the line if it's not intrinsically built into the workforce.
You know, professor, while we talk a lot about AI and the impact it's likely to have as far as the jobs market is concerned, I don't think that we can see it in isolation. We'll have to see it in the overall economic context where we are seeing geopolitical risks, we're seeing geo economic confrontation, geoeconomic fragmentation. There's a retreat from globalization as we've come to accept it, as we've come to know it, that in addition to AI, are we headed into a structurally disruptive environment which will change the way that the labor market operates?
Well, I'm afraid we are. It's a it's an unusual circumstance that we're facing now because we have the globalization shock and we have the deterioration in geopolitics, which obviously affects the location of, of companies. So in addition to companies now needing to know, how am I going to produce something and what skills do I need? They also need to worry about where am I going to produce this? What kind of supply chains am I going to use? And that's a very difficult balance, to, to bring up the that that's very much a company's problem now. And of course it will not be good for the productivity or for, world economic growth if each one of them says, oh, I'm going to get back home, retrenched home and all that, which is I don't know if you've been to, Macron's, talk a bit earlier, he was talking very much about Europe needs to get together, get deeper, integrate more to a single market, single capital market. It sold because of that, you know, can we trust anyone outside Europe, given what we are seeing behaviors east and west from where we are? You know, it's a very, very difficult problem. But from the workers point of view, they can never lose if they do exactly what the minister said. You have to learn how to learn in future. Don't think that you are going to acquire a skill at school and maybe a little bit of training later, and then you're going to get into a job and you're always going to do that skill. What what I mean is partly universities that need need to reform, actually, so it can be, well, I have no more power to reform my university.
So.
So but essentially what they need to do is, is to teach a variety of skills to their students. In addition, maybe extend, you know, like we have three years of university undergraduate education in Britain extended to four maybe. And and use it in combination with companies with industry. So you have internships. So you might call them internships or and apprenticeships apprenticeship training. But the idea is that is that the university learns from the industry what skills are needed and teaches different skills. So when they graduate, they have a composition of skills. Yeah. To show in their portfolio. They have their degree obviously, and they have experience. They have work experience. Because the most common complaint that you hear now from young people, graduates coming out of school, is that everyone wants experience, but they don't offer me a job because I didn't have experience. How am I going to acquire the experience if they don't from the job? Get your experience at university.
Well, you know, and Andrew, I want you to come in on that and also build on the need and the possibility for a much more robust public private partnership. A collaboration between industry, academia and and, you know, to be able to address the skills gap that we speak of, but also identify the skills for the jobs of the future.
Yeah, I think one of the challenges is because AI technology is still evolving rapidly. The skills that are going to be needed in the future are not yet clear today. Hence, lifelong learning, the ability to keep on learning those skills in the future that we do not yet know today. But there's one skill that is already emerging that's very clear to me that I want to mention that may be controversial, which is it's time to get everyone to learn to code. And what we're already seeing in Silicon Valley is that, you shouldn't code the old way, you know, don't write code by hand. Get AI to do it for you. But we're already seeing in Silicon Valley that not just the software engineers, but the marketers, HR professionals, financial analysts, and so on, the ones that know how to code are much more productive than the ones that don't. And that gap is growing. So, my best recruiters, they don't read resumes by hand. They write code to screen resumes for them. When one of my marketers wants to launch a new marketing campaign or a website or whatever, they don't wait around for an engineer to build an app or website for them. My marketer builds it themselves. My CFO no longer, you know, spends hours clicking through documents to do routine processing and know that she has to go around to, evaluate lots of vendors to see who needs to pay tons of money to for some little automation. She her team, they write code themselves to automate financial processing. So I'm already seeing very clearly in Silicon Valley, my business and many other businesses, a noticeable and growing productivity gap between people. Not software engineers, but people that know how to use AI to build custom software for them and people that don't. And, maybe if I'm wrong, in two years you now come and yell at me, but I believe this will spread. And so I think there's an imperative to basically teach everyone to learn to code.
Can I add.
To that? Yes. So so that's that's an.
Important one, Andrew, saying that everyone needs to learn to code. That's that's his his his big prescription here Davos 2026. Yes.
Go ahead.
Yeah. The other adjustment a lot of the computer science graduates who are graduating graduate immediately thinking they're going to get a job at a meta or an Amazon or Google or some company like that. Those jobs are gone. And then there's a lot of disappointment where they wait for months and in some cases, years waiting for those jobs to come back. At the same time, there are HR departments, finance departments, sales departments looking for AI skill set. And these people could could get a hero status within that. We face that challenge today. You know, when we ask our HR that, you know, we don't want recruiters, we want all the recruiting to be done, using agents and bots. Well, someone has to code that. And when they go out and look for people, they don't find those computer science graduates because they're waiting for their next big job to come from the big tech books. So that's the reset. I'm talking about that once that starts happening, I think you'll see a more even playing field in the world of, skills and jobs.
Yeah. So so don't don't wait for the big tech job, go outside of that universe as well. So I think there is a mentality and a mindset reset that's also required for those who are coming into the workforce. I'm going to throw this open to questions. I can see a hand and many hands already being raised. Wonderful. Can we get a microphone across to the lady, please? Thank you so much.
Hello. I am one of the global shapers that presents in Davos this week, and I'm based in Hong Kong. And one question I have is if everybody learns how to code. And I'm just thinking from an economic standpoint where the whole concept of comparative advantage and how are we able to still showcase or focus on areas where we're, you know, either like very skilled or have leverage versus everyone trying to be the coder? And then the second piece of the question is, what does the future of work look like? If the typical jobs like the big tech jobs are gone, or entry level jobs, as you think about it and no longer, what is the future? How should young people start thinking about things? There's a concept of the new economy creator's economy, but is that sustainable enough to build a career that can span through different phases of industries?
Thank you.
Andrew. Would you like to start?
Sure. To comparative advantage. Coding skills goes really deep. So my most productive developers, they're actually not fresh college grads. They have ten, 20 years of experience in coding and are on top of AI. It turns out that, one tier down from them, is the fresh college grads that really know how to use AI. And then I'll tell you, one tier down from that is the people with ten years of experience. But maybe that a comfortable job and have not learned to embrace AI. It's actually quite a few times my teams have voted to hire fresh college grads that really knows AI over like a full stack developer or something that for some reason has not, is still coding like it's 2022 before modern AI, and then unfortunately, the least productive that I would never hire are the fresh college grads that also do not know AI. So I feel like, my marketer does not go nearly as well as a really good developers that I know with 1020 years of experience. So there is that deep expertise. Experience that still makes a huge difference.
Let me give a personal example where you sort of debunk this myth on what everyone's a coder really means. So I have a son who graduated with a degree in cognitive science, and he's now working in a research lab building, building behavioral models, but he uses Python for that. He never learned coding. And, you know, with a father who sort of professes on proper education and proper coding style, he uses ChatGPT to generate code. He examines the code and then he wants it. So is he a computer science engineer? Is he a is he a, you know, a software coder, or is he a cognitive scientist? I think with the concept of everyone codes, that doesn't mean you're writing necessarily complex algorithmic structured code. Now you have the ability to, get started, jump in and write code in any domain. And I think that sea change is going to start impacting jobs. And when people start accepting that, then you could be in any profession, being able to contribute to coding without being a traditional coder.
So dads are under threat from ChatGPT as well? Yes. Go ahead. You're a question. Yeah. To the lady here. And then I'll get to you, sir. Go ahead.
Thank you for sharing that. An insight on the information. I'm the founder of waffle, which is to close the gender gap in industry in Japan. And also we engage in policy recommendation in Japan. So my question is, what do you believe is the appropriate level on depth of AI education required at each educational stage, elementary school and junior high and junior high and high school and university. And one more question is, how should a systematic continuation progression in AI education be structured from elementary school through university? And I want to ask, Sarah and Andrew, please.
Sir, would you like to start?
Yeah, sure. So I'll give you the basic outcomes that we've tackled. Do I have an answer of how it needs to evolve? No. Our AI curriculum is is a living curriculum because of that, because it needs to transform as we're moving forward. But I'll take you stage by stage. If you're talking about kindergarten students, it's very important for them to understand. And we don't call it AI for children. We call it robots, that there are robots that do things, and the robots that do things need adult supervision for them to be able to interact with it, as they're moving older, especially for younger kids who are getting exposed, it's very important for them to understand how does AI, in a very simple way, how does AI work, which take us back to machine learning. So we teach the machine learning, which is AI, builds a perspective based on the information that it's been fed in. If it's fed in single type of information, and we do that with the typical green apples and is the is a red apple and apple or not, then you move on to middle school and high school and that's where you start. You start building in the critical thinking element. Does it align with your ethics? Does it align with your values? Is the response you've gotten or the prompt that you've provided sufficient enough for it to give you the depth of knowledge that you require? In what context are you supposed to use it in one context? Is it really plagiarism and you're not putting the effort in? Then comes in the rethinking of what an educator needs to be exposed to, different stages of their life to be able to tackle AI. And this is something that you've all mentioned, which is the expertise level. There needs to be a minimum level of knowledge required for people, especially today, to be able to use AI effectively and be able to use it as an effective tool. So what we're focusing on and doubling down on is students having a core body of knowledge and then building on harnessing those skills. I've mentioned, critical thinking as one resilience as another because and and adaptability and resilience and adaptability and critical thinking together actually builds the ability to learn and relearn within students. And that's more of a long term transformation of an education system that needs to be built in, that has so many different elements that will take time and pieces within the system to take us out of the box of what education looks like today, into what it needs to look like to give us the outcomes that we're looking for.
Yes. Could we have the microphone, can I? We have about six minutes left, so I'll try and take some more questions and come back to Andrew if there's time left. Thank you.
Thank you very much for sharing your perspectives. We do a lot of work as well on assessing AI's impact on the workforce. And we do understand that there are some jobs that are likely to sit in the augmentation category and others which are at the risk of of being displaced. My question, and keen to get your perspectives on it, is, when human capital policies typically were designed, it was designed technically for humans, but we are now in an era of AI, which basically means humans will interact with robots. AI a broad question is how do you see the human capital policies evolve, be it on the recruitment, career progression, retention in an AI enabled world?
Professor, do you want to address that?
Yeah, I mean, it's I mean, obviously it would change because the labour market is restructuring in the way you use skills structuring. But I mean, Agentic AI is creating jobs so far. You know, it's like it's like having an assistant and you become more productive and you produce more. And companies that bring it in first expand and all that. So I don't I don't really see any, big reforms that you have to do now of for the future. The importance are now in education. And I want to go back to how much do you teach of AI and all that and programming. I agree entirely that everyone should learn programming skills in the way that every kid in in England has to learn French. Do you think they ever use it or do they or do they, or would they ever do as good a translation as AI can do from English to French or French to English? No, but they learn it. They learn Latin. My, I've got a son in school in England. It's compulsory to do Latin. Let them do programming as well. He's doing programming as well, actually my science school. But but it's maybe it's a more progressive school so that when you go out and get into a job, when you come across people speaking foreign languages, you don't panic the way that so many kids come out panic. That's the point of teaching foreign language. And when you see AI, they don't panic. They because they've got the programming and they know more about it. So that that's why the reform should take place, combined with experience that I was mentioning before, once they are in in a company, then their human capital will be augmented all the time because there will be, there will be learning new skills as new technologies is arriving. But, you know, that's that's always existed in, in history, you know, when, when a horse, when people driving cars or horses carrying things in the late 19th century were told, there is this wonderful thing now that uses internal combustion and, and drives and give up your horse and come and drive it. It was a much bigger shock to them than what we're facing now. And yet within ten years, horses disappeared and and roads were congested with cars. Maybe 20 years back.
Can I add one point?
Yes, please.
Thanks.
A lot of the policies today are static and progressional. You hire an employee, an employee gets promoted. You have, you know, events that happen in a very sequential manner. If you think about it from the beginning of time, output of work was always a human. Times efficiency, times productivity. We spent 100 years improving efficiency and productivity for the first time. We are changing human and adding an agent to that. So all these policies now need to be re-examined because they're not going to move linearly. There's going to be a lot more disruption. And again, there were several speakers today who touched on that. So, you know, we are a believer again at cornerstone that this people graph has to be very dynamic. And that's putting a lot of pressure on, on organizations around the world.
Can I can I add to why I think policy is so important? About two weeks ago, my team, we do a lot of person in the street interviews. We spoke with a coffee shop owner in heart of Silicon Valley in California, who was physically shaking because he was so angry at AI with my team being representatives, and he was almost yelling at us for AI destroying the livelihoods of his artist friends. I know here at Wave we're all very AI positive ROI. We see the business value, obviously the future. I think many people underestimate the degree to which our sector is mistrusted and sometimes even hated. One good news is, I think Edelman ran a study showing that the more people learn about AI, the less they distrust it and the more they like it. And so, to gain societal acceptance of AI, to let us unlock the things that actually move society forward, I think this educational piece and the policy piece of it is really important.
Yes, building on trust as well is important. Yes. I'm going to give you an opportunity to get the microphone, and that will be the last question that we take for this evening.
Thank you very much for your insights and learning. I'm the founder and CEO of Walkera. I think if we look at our skill sets, we'd see that part of our skills are durable. They will be useful in a long time. And I agree with Professor Ng that coding is becoming a skill now. But other skills are perishable and they change so fast with a half life that is so low. So my questions for you all is how do you personally keep up with the change and acquire those perishable skills that are going to go away even six months from now.
Aren't you? Mr.. Yes, professor.
I would repeat what professor said so he doesn't kick me in the backside is the the art of learning is learning how you learn, and as long as you're good at that, what you're going to learn is going to change that. That cone of uncertainty is so broad right now that not only do we not know what the next jobs are, we don't know what outcomes or jobs are going to generate. So it's very hard to teach a student about that. It's easier to teach a student how to learn what's the area of discipline and all the soft skills that you heard.
Yeah. You know, I mean, people specialize in different things. Have by by now, I have the courage to tell anyone who's going to ask me questions. Don't ask me anything about this.
Other.
And if they do, I say out, yes, you cannot, you cannot venture an answer to everything and expect to be listened to and be taken seriously. You have to admit that there's some things you don't know.
Yes, I run.
I run. Deeplearning.ai world's leading AI training platform, chairman of Coursera. So actually eat a lot of our own dog food. I find that taking our courses actually helps me, you know, keep up with the cutting edge and all the latest developments.
All right. With that, ladies and gentlemen, we are going to have to close this session. But thank you to our panel for joining us here this evening. Thank you very much for your participation. This is this is an ongoing debate. I don't think we have the answers yet. There's going to be many more questions and hopefully we'll be back in Davos again to address some of those from all of us here. Goodbye and many thanks for watching.
Thank you.