What Career Should You Choose in the AI Age?

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1:56Welcome back to Merrin Talks Money, the podcast in which people who know the markets explain the markets. I am Merrin Somerset-Webb. This week, I'm speaking with Daniel Susskind, an economist and one of the leading thinkers on how technology and artificial intelligence are changing our world of work. Daniel is a professor at Gresham College and King's College London and a researcher at Oxford University and the Stanford Digital Economy Lab. He has spent the last 15 years studying technology and work, and his previous books include A World Without Work and Growth, A Reckoning. Now, regular listeners to Merrin Talks Money will know that I often ask our guests, what should our children be studying?

2:33What kind of work will survive the rise of AI? And how should young people prepare for what is coming? And how can we help them prepare for what is coming? Well, well done, Daniel. He has written a whole book about exactly that. Not because we asked him to, but just because I guess it's interesting. It's called What Should My Children Do How to Flourish in an Age of AI? It asks what the next generation should learn, which skills will matter, and how much we can prepare for a future we can't predict. Daniel, welcome to Maren Talks Money.

3:00Daniel Susskind: Thank you so much for having me. Right, we are very lucky because we have got the perfect hook for our conversation, which is that the PISA education numbers came out this morning. And I'm sure that you've looked at them as well. We are talking, by the way, on the 8th of September. They came out this morning and they were really depressing. They showed a global decline pretty much across the board in maths and reading. They were even down from what we saw in 2022. And when we saw depressing numbers for reading and mathematical skills around the world in 2022, we went, COVID, it'll get better. It'll be fine.

3:36But it isn't. It hasn't got better. It's got worse. And I know that all generations look at the one below them and go, well, they're useless. It's getting worse. And normally it isn't. But these numbers suggest that there is something going on.

3:52Daniel Susskind: I think that's right. I think that's right. I mean, the numbers appear actually early on in the book, but only up to 2022 because it's global data and it takes the OECD a good few years to gather it together. Many people have pointed to the particularly sort of precipitous fall in literacy, but it's also numeracy as well. I mean, I think it's a disaster in itself, but it's a particular disaster for thinking about how we prepare the next generation for the age of artificial intelligence. And I think there's two reasons why. One is, and this is a theme that runs through the book, and you alluded to it in your opening comments there, which is that it is incredibly difficult and impossible to predict the future.

4:42Daniel Susskind: you know the way in which we have traditionally i think thought about preparing the next generation for the future of work is to try and think as cleverly and as deeply as we can about what's going to happen in the future and what jobs will have to be done and then reason back and say well look these are the sort of future-proof skills that we need to teach the next generation i just i just think that's too difficult to do we just can't predict with confidence particularly in this extraordinarily uncertain world, exactly what more advanced skills, perhaps it's creativity, perhaps it's judgment, perhaps it's problem solving, are really going to be in demand.

5:19Daniel Susskind: But I think what we do know is that whatever those advanced skills turn out to be, they are going to rely in some way on people having those basics in place. Now, those basics are basics, not simply in the sense that literacy and numeracy are the most fundamental skills, but they're also basic in the sense that they're the building blocks, they're the foundations for everything else. And so I think that is one reason that I think it's particularly worrying that whatever skills do to turn out to be valuable, they are going to rely on these basics. Would you blame technology for this decline in literacy and mathematical ability?

6:01Would you look at that and say, well, this is social media, this is children not paying attention? Or is it something's gone wrong in teaching? And we know there's always fads, aren't there, in the way that children are taught, and there's different ways that children are taught. And if you drill down into the numbers that we've seen globally, there's something quite interesting has happened to England, where mathematical and literary skills have remained fairly static, and there's been no devotion to any particular type of educational fad in England. It's stuck to basic old-fashioned ways of teaching, give or take.

6:34And so England now finds that having its moved from number 20, 25 in the world in most things up into being in the top 10 in almost every educational skill, whereas at the same time, we've seen devolved areas of the UK where maybe there's been something more faddish going on, Scotland, Wales, where we've seen declines. So it's just that that could be part of it globally, a different way of teaching. But another part of it, it seems fairly obvious to adults anyway, that it is social media related.

7:00Daniel Susskind: I think there's two really interesting things here. One is, I think technology does play a role. I don't think it's a coincidence that this decline in literacy and numeracy begins in 2009. 2009 is the year that young people's lives start to become saturated with smartphones and social media and the sort of distracted and attentions fragmented. And, you know, in the book, I am very critical of social media. I have lots of worries about social media. I think many of the ideas that are gaining traction for restricting children's access to social media, things like no smartphones before 14, no social media before 16, phone-free schools, lots of play.

7:47Daniel Susskind: I think all of these are terrific things. But I think there is something really important, though, to remember, which is that social media is not the same thing as artificial intelligence. And one of the worries that I have is that legitimate concerns about social media are being bundled into conservatism and fears about artificial intelligence. So sensible restrictions on social media are leading to knee-jerk bans in things like ChatGPT. and I think that's a mistake because whereas I think social media does disempower and distract us artificial intelligence if used in the right way has the potential to make our lives go vastly better and and that is and that is um that's part of what the book is or it's a it's a big part of of what the book is is about uh there's another way to put this which is that I think at the moment we have trapped ourselves in a debate about what the right amount of screen time is.

8:46Daniel Susskind: Do we want more screen time or do we want less screen time? And we're sort of collectively searching for the sort of Goldilocks level of screen time, not too much, not too little, just right. And my view is that actually that's the wrong debate. What we should really be debating is what is actually on these screens? How are we using this technology? And if we are using it right and using it to prepare the next generation for this world that they're about to enter, then I think that's a really, really good thing. One of the reasons I think that people may be confused or are concerned about the connection between AI and social media is because, of course, AI has invaded social media.

9:20So, you know, kids are now seeing AI slop all over the place, which I think keeps them moving through reels faster and faster and faster and through larger chunks of time than they might have pre-AI. So there is a connection there. You can see where the danger signals are for parents and for teachers.

9:37Daniel Susskind: Clearly, the distinction isn't a sharp one. But I think it's sharp enough to say there is something materially different from using AI as a personal tutor to browsing on TikTok. One of the big worries that I explore in the book is around technological distraction. It's not a new worry. Continually, as new technologies have arrived, people have worried that they were going to distract us. From the day of the first printing press. Books are dangerous for people. Books are dangerous. And then the radio was dangerous. And then the television was dangerous. Social media was dangerous. That's right.

10:13Daniel Susskind: I went back in time and looked at different technologies. So even the introduction of the stamp, for instance, the penny stamp, which made postage something that was far more affordable and no longer just something for the kind of aristocratic class in Britain to enjoy each other. What was fascinating was a worry that people were going to be distracted by all this tittle-tattle in the letters that they received. You might receive up to 12 deliveries of post a day. And people were terrified that there was just going to be too much gossip and too much sort of idle reflection in all of these letters.

10:52Daniel Susskind: And exactly right. It continues up to the day. But the serious point is that I think part of the book is arguing that we need to have an AI curriculum. And we need to be spending, just to give you a flavor of quite how ambitious I think we need to be, I think we need to be spending about a third of our time in education, teaching people how to use these technologies critically. But part of that is also teaching them about distraction. I think it's one of the great challenges with these technologies. and um yeah one of the things that i think some people might find surprising is that the paying attention or not being distracted the more we learn about it is is that it is a skill that can be learned um the other thing is of course that um these technology companies have done an extraordinary extraordinarily effective job of leveraging the body of work that we have been building up over the last few decades into distraction, habit forming, and so on, and sort of turned it against us with these technologies.

11:58Daniel Susskind: And so I think part of it is also about educating the next generation on the nature of distraction and how these technologies are catching their attention and not letting it go.

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15:41The other thing when we're talking about teaching AI and how to use AI, when we go back to the basics you were talking about earlier of critical thinking, it would seem to me that that is one of the most important skills that we need as long as we're dealing with AI in the form of LLMs as opposed to anything else, because LLMs, as we know, are very error-prone, or hallucinations we call them. So it is very, very frequent, and particularly the longer you go on with your prompts and your tokens, the more likely you are to have hallucinations and errors come through. So if we are encouraging people to use LLMs to help them study.

16:18We also need to be sure that we give them the tools that they need to understand how and where these errors will creep in and how best to recognize them. That seems to me to be a huge part of AI learning.

16:30Daniel Susskind: I think that's exactly right. And, you know, that again, that is a big difference with the calculator, which is that you don't worry the calculator is going to run out of steam and make a mistake in the fourth decimal place. You know that, you know, what you get if you put the question in correctly is the correct answer. that's not the case with ai and so you're we have to be teaching people to make critical use of these technologies and again this isn't just you the book is called what should my children do but it's far more than that it's a book about how we prepare everyone um to flourish in this new technological technological world um and um but i think there are you know there are kind of playful and interesting and imaginative ways that we can teach that sort of thing yeah i i was thinking about, and I do this in the book, I spend some time thinking about what would it look like to teach subjects with AI, perhaps subjects outside of my domain.

17:22Daniel Susskind: So I'm a mathematician and an economist, and I have a pretty good sense of what it would look like to teach those subjects. But what would it look like to teach, say, poetry? One of the consequences of being a dad of three children, eight, five, and two, is that I have very little time now to focus on a novel. you know concentrated amounts of large stretches of concentrated time and so i found myself over the last five six years reading an awful lot of poetry but the thing about poetry of course is that um you really need to read it in a group with other people have a kind of lecturer directing it it's often quite difficult to to make sense of and and that's actually one of the ways in which i've been using ai as a sort of study partner to help me make sense of a one-on-one tutor quite And using AI as a personal tutor is a big part of the book.

18:20Daniel Susskind: But I was wondering, what would it look like to teach poetry with AI? And I thought, well, there's a very simple way where you could study a familiar poem without AI, and then you could use AI to help you understand an unfamiliar poem. But perhaps there are more creative ways. Perhaps you might be able to use AI to rewrite a poem in the voice of another poet, or perhaps the same voice of a poet, but change the topic. This is not going to make you popular with poets, Daniel. Well, hold on a second, because then you might use AI to gather all the commentary on a particular poem, which I did. And you might say, well, hold on a second, how do we know that these commentaries exist?

19:03Daniel Susskind: And you might use that as an opportunity for thinking about hallucination, whether or not these pieces of analysis really did work. And you might then say, well, let's get the AI to analyze this poem. And you might say, well, hold on a second. This AI isn't a human being. How does that shape its sort of interpretation? You might use that as an opportunity to think about what it is that human beings are uniquely placed to do and what it is that. So I'm not suggesting that those rewritten poems are in some way of greater aesthetic quality. But I think it prompts a really interesting conversation.

19:35Daniel Susskind: Again, to your point about when we're teaching AI, it's not just about how do you write an efficient prompt, but it's this sort of broader conversation about what this technology is, what it can do, what it can't do, what it does things, what are its strengths, its limitations. And, I mean, those were the sorts of things I found myself grappling with. And it's the sort of thing, you know, again, it's not my domain, but it's the sort of thing that I would love, you know, people, teachers in each of these different areas to be thinking about. Because I think, you know, with their expertise, they could come up with incredibly exciting and imaginative ways of putting this technology to use in their particular discipline.

20:18Finally, something to cheer teachers up. Listen, we've spent quite a long time talking about what education should look like, what we would like, or you would like the future to look like, back to basics, test both, include AI education, etc. But it's not there yet. That's not what we've got now. So if you are a young person today, let's say you're coming up to choosing A-levels, for example. What do you choose? You say we can't predict the future. I absolutely agree with you. We have no idea what's coming next. And it's very hard to tell what very specific skills will be useful. It's hard to say, well, this is future-proofed and this isn't.

20:55Everyone keeps telling young people to go out and learn a skill, be a blumber, be an electrician, be a baker, whatever. But we don't even know that, realistically. So if you were sitting there, you're 15 and a half, 16, looking at your A-levels, you've got to choose three subjects. What are they going to be? Yeah.

21:12Daniel Susskind: So I think this question, what are they going to be, is really interesting. I mean, there's so much advice I would want to give. Give it. I think one of the biggest pieces would be, I think, the way in which we prepare people for work is to say, what job do you want to do? And then to say, because you want to do that job, these are the skills and capabilities you need. And I think actually that approach is going to lead to disappointment. it. So what I write about in the book is that actually you've got to ask the question, not what job do I want to do, but what problem am I interested in spending my life solving?

21:52Daniel Susskind: If you go into law because you want to be the sort of lawyer you saw on suits, or you go into medicine because you want to be the sort of doctor you saw on house, you're going to be bitterly disappointed because what those jobs look like are going to change dramatically in the coming years. But if you go into these worlds because you're interested in, say, improving access to justice or solving legal problems. So you go into medicine because you're interested in solving medical problems and you're far more agnostic about what that job might look like, then I think the future is a very exciting one because these problems aren't going away.

22:23Daniel Susskind: It's just the way in which we solve those problems are going to look very, very different. And I think in part, I've not been surprised seeing the kind of angry protests from young, particularly in the US, kind of graduating students who have finished spending a huge amount of money and a huge amount of time and a huge amount of effort preparing to be a particular type of you know have a particular job and then some tech boss stands up and says no that world's going to disappear because of ai and i i think part of the problem is that that this idea of a job is just an unhelpful way an unhelpful way of kind of anchoring your expectations about what your future is going to look like i think we should be encouraging young people to be far more focused on what sort of problems are they interested in solving.

23:10Daniel Susskind: And I caught a glimpse of this. This isn't a new observation, but it's one that I think has become more important in the last few years. One of the things that made me think that this was going to become increasingly important was a paper written in 2017 by a team at Stanford. And it was announcing the development of a system in which if you gave it a photo of a freckle, it would tell you as accurately as leading dermatologists whether or not that freckle was cancerous. Today, AI-enabled diagnostics is pretty widespread, but back then, 10 years ago, this was a pretty dramatic announcement. It caused a stir, but what was particularly interesting about it was the final co-author on the paper, who was a man called Sebastian Thrun, who some listeners might know he is not, in fact, a medical doctor, but he's the guy who developed the first driverless car.

24:04Daniel Susskind: So here is a guy who knows absolutely nothing about medicine at all, and yet he's able to use these systems to solve a problem that would have required an extraordinarily talented dermatologist, decades of experience and training and expense and insight. He was able to design a system that could solve this problem. There is a sense in which these technologies just don't have a lot of respect for the traditional boundaries that we have drawn between different subjects and different disciplines and different occupations and different jobs. And I think we need to be frank with people about that and just say, look, you have to focus on the problems you're interested in solving and be open to the job that you have and the skills that you're required to learn as time passes, just looking very different from the sorts of things that you required in the 20th century.

24:49Let's go back to A-levels. Does that mean that when you look at A-levels, you are particularly focused, again, on anything that teaches you critical thinking as opposed to learning so any critical thinking and maybe even linguistics because you know your uh your relationship with your agents is a linguistic one right going back to uh effective prompting

25:08Daniel Susskind: uh that kind of subject i think it's a balance of two things i think partly it's you know back to basics are these subjects helping you you know refine and improve those those basics which i think are so important but there's also something just more mercenary which is what is going to prepare me best for the particular either subjects I want to do at university or if you're not thinking of university for other parts. There's a more sort of transactional approach to A-levels as well that you just have to confront. I had someone on the podcast the other day and we were talking about what should you learn, what should you think about and we were all be doing is learning philosophy, spending a lot of time reading and learning about philosophy because the existential crisis that is going to come to us all when quantum computing is really a go, combine that with the problems that AI will solve and our minds will be so blown we're going to need philosophy to fall back on.

26:07Daniel Susskind: Yes. So I'd say I'd go back to critical thinking, which in a sense is sort of philosophy applied, which is philosophy is critical thinking applied to the kind of the biggest the biggest questions but i mean just you know the reason i wrote this book you know what should my children do was because i you know i've spent the last 10 or 15 years as as you said writing about the impact of technology on work and often from the you know there's kind of bigger macro questions you know what does it mean for work what does it mean for growth what what should the state do and what i have found time and again as i travel around talking to very different groups of people very different places is that people come and say look That's all very interesting about this sort of coming quantum apocalypse.

26:48Daniel Susskind: But I've got three kids at home. What on earth should they do? And so what I'm really trying to do is just bring some of these ideas back down to earth and say what all of us, parents, individuals, teachers, policymakers, politicians can do if we're thinking about preparing the next generation. What about us? What about me? I mean, we're also obsessed with the kids, right? The next generation, them, them, them. What about me, me, me? What do the adults do? What do the adults do to prepare ourselves? Right, because one of the chapters in the book is, don't forget the adults. I know, I read it. Yeah, yeah, yeah.

27:25Daniel Susskind: Because I think it's so important. Because these challenges aren't simply for the next generation, they're for this generation too. And just to come back to a word we used at the start, uncertainty. There is a huge amount of uncertainty about the future. about exactly what jobs are going to have to be done, what skills are going to be most important. I think this uncertainty is perhaps the defining feature of the age of artificial intelligence. But the best response any of us really have to uncertainty is flexibility, a capacity and a willingness to retrain and reskill, particularly later in life, with the same intensity and seriousness that people engage in education at the start of their life.

28:05Daniel Susskind: And I just don't think we're anywhere near that yet. So really the call in that part of the book is really saying we just need to take adult education far more seriously we need to sort out the quantity of money that we're spending both individuals both states companies in helping people retrain and reskill uh what should i go what should i go and do a course in you know what one of the philosophy aside one of the things that i find particularly interesting and exciting is the how. If you were to step into a time machine and go back 100 years and walk into a classroom or a lecture theatre, it looks remarkably similar to how it does today, despite the existence of lots of technological alternatives.

28:52Daniel Susskind: But I think a turning point has now come after the sort of disappointment of education technology over the last few years, where the technology just hasn't been there. But I think it is now able to do something quite interesting. And it's this, which is, we know that one-to-one tuition with a human tutor is extraordinarily effective. So an average student who receives one-to-one tuition with a human being will tend to outperform 98 % of students in a traditional classroom setting, incredibly effective. And I spent the best part of a decade as a teaching economics and mathematics at Oxford. I've seen how effective the tutorial system can be where I sat with one, two, three students tailoring what I taught to the particular strengths and weaknesses of the people in front of me.

29:41Daniel Susskind: But the problem with that, of course, is that it's just unaffordable. We haven't been able to offer that kind of personalized tuition to everybody who wants it. Now with these systems, you really can. And the kind of personalized interaction you can have with these systems in trying to understand new and unfamiliar problems really does rival, in my view, 95 % of teachers that I've seen. And I include myself in that. They are incredibly effective at helping you understand new problems and new ideas if you tell them who you are, what you're trying to understand, what it is that you want to do. And this is a roundabout way of saying, find a problem or an issue or a question that you're interested in and just run with one of these systems and get it yeah treat it like a tutor and ask it to help you understand perhaps it's in an afternoon perhaps you want it to design a program for you over a few months you know experiment and and test and explore with these systems because it they really are remarkable in this um in the way that they can offer this you know personalized interaction yeah if i was to give people one piece of advice whoever they are whatever they do it's just to kind of glimpse what these technologies can now do it's to find a problem that interests you or something you'd like to understand more about and and try and use these technologies to do that with you um i mean just just an example just an example of something that i've been doing um uh just in the last few weeks it's it's not in the book but it's something that i've i've i've been uh i've been spending my time doing my grandfather had this beautiful watch which um um my my mum his daughter took to a repair person and said um can you repair this and he said no it can't be repaired and she suspected that something was up that he was just you know wasn't sort of being entirely truthful and so i've taken it upon myself now as a sort of to become a horologist with the help of chat gpt so i i you know sit there with the system alongside me it gave me guidance and all the tools that i needed it told me to you know i ordered a sort of a simple mechanism from China to experiment on so I could learn the basics of how the movement worked.

31:52Daniel Susskind: I've now begun on this watch that is apparently unfixable. I'm in this weeks-long exercise, sending it photos through the microscope, gradually tinkering and tweaking. The idea that I could become a horologist without going for a kind of four-week residential camp somewhere in the north of England to understand how watches work and has repentance, unimaginable until very recently. And now it's something that I'm able to do. So watch this space to see if I manage to... Two points on that. One, worrying implications for employment globally, if everyone can become their own horologist as well as their own accountant or lawyer.

32:32And second...

32:32Daniel Susskind: We haven't yet seen if I can fix the watch. So let's check in. Second, I would like to voice the thoughts of every single listener and viewer, which is he's never gonna finish that job with three kids under 10 in the house yeah yeah so we're making in full disclosure we're making slow progress um we're making slow progress but maybe maybe i will um i'll post some videos of my but the very fact that it's possible is fascinating um daniel one last question before you go because i've taken up two months of your time um what are you reading at the moment you've written this wonderful book everyone's going to read it but what are you reading yourself?

33:07Daniel Susskind: One of the issues that really interests me is AI, creativity, and intellectual property. In fact, I have a new series of lectures in my role. I'm the professor of business at Gresham College in London, and I do a series of public lectures each year. Last year was on AI and its impact on work. This year is on AI, creativity, and copyright. I just think it's completely fascinating set of issues and tensions. And so I've actually been reading a lot from the early internet era. People like Larry Lessig, the Harvard Law Professor, and Yo-Hai Benkler, also at Harvard, who were, you know, the copyright regime is a consequence of this sort of ongoing battle between technology and our ability to create and share new ideas and be creative in society.

34:02Daniel Susskind: And there's a really interesting analogy, I think, between what's going on in the world of artificial intelligence at the moment and what happened at the start of the internet era, particularly with respect to sharing music and sharing videos and the copyright battles. So I'm just sort of immersing myself back in that period a few decades ago, and in particular reading some of Larry Lessig's wonderful early work on those issues. Excellent. And can all our listeners come and listen to your public lectures? Yeah, absolutely. Not quite that public. No, no, no, absolutely. So this is a wonderful thing about Gresham is that I give six entirely public lectures a year.

34:35Daniel Susskind: So you can either come in person to Gresham College, which is just in the city of London. If you can't attend in person, you can watch them online as well. It's a fantastic thing. And if AI creativity and intellectual property is not your thing, there's a set of other professors in fascinating other disciplines too. Lots of great public lectures. Okay, brilliant. Daniel, thank you very much. Such a pleasure. Great to have you on. Thank you for having me.

35:27by Samasadi and Moses and special design by Blake Maples and special thanks, of course, to Daniel Susskind.

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