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It’s been clear for a long time that the way we traditionally think about skills and expertise is out of step with our fast-changing and volatile world. This issue runs through the education system in many countries and also influences how employers attract and upskill talent.
So, what are the innovative approaches that could solve this problem?
My guest this week is Ed Fidoe, co-founder and CEO of the London Interdisciplinary School (LIS). LIS has been described as the most radical new university to open in decades. It offers degrees that use an interdisciplinary approach to solving some of the complex problems that business and society face. There are interesting lessons for employers here around the concept of interactional expertise.
In the interview, we discuss:
• What is LIS, and why was it founded?
• Building networks of knowledge
• Connecting academic learning to the workplace
• Enhancing employability by addressing the current mismatch of expertise between college and the workplace
• Intellectual curiosity and problem-solving
• Cultivating diversity of thought through diversity of background
• The power of interactional expertise in the knowledge economy
• What future skills will be needed in an AI-driven world?
•
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Transcript:
Matt: Hi, this is Matt. Just before we start the show, I want to tell you about a free white paper that I’ve just published on AI and talent acquisition. We all know that AI is going to dramatically change recruiting, but what will that really look like? For example, imagine a future where AI can predict your company’s future talent needs, build dynamic external and internal talent pools, craft personalized candidate experiences, and intelligently automate recruitment marketing. The new white paper 10 ways AI will transform talent acquisition doesn’t claim to have all the answers, but it does explore the most likely scenarios on how AI will impact recruiting. So, get a head start on planning and influencing the future of your talent acquisition strategy. You can download your copy of the white paper at mattalder.me/transform. That’s mattalder.me/transform.
[Recruiting Future theme]
Matt: Hi there. Welcome to Episode 622 of Recruiting Future with me, Matt Alder. It’s been clear for a long time that the way we traditionally think about skills and expertise is out of step with our fast changing and volatile world. This issue runs through the education system in many countries and also influences how employers attract and upskill talent. So, what are the innovative approaches that could solve this problem?
My guest this week is Ed Fidoe, co-founder and CEO of the London Interdisciplinary School, or LIS. LIS has been described as the most radical new university to open in decades. It offers degrees that use an interdisciplinary approach to solving some of the complex problems that business and society face. There are some interesting lessons here for employers around the concept of interactional expertise.
Hi Ed, and welcome to the podcast.
Ed: Hi Matt, nice to be here.
Matt: An absolute pleasure to have you on the show. Please, could you introduce yourself and tell us what you do?
Ed: Yeah, sure. I’m Ed Fidoe. I’m the Chief Executive and co-founder at the London Interdisciplinary School, which is one of the UK’s newest universities.
Matt: Fantastic. Tell us more about that. Why did you set it up? What does it teach? What type of students do you have? Give us the whole backstory.
Ed: Part of why we set it up is to sort of address that frustration that I’m sure lots of people listening have. I certainly had it when I was at school, which is that you have to drop lots of subjects as you move through school. You have to narrow down to GCSE’s, you have to narrow down to A-levels, and then when you go to university, you have to pick just one subject. And for lots of young people, that is a quite painful choice to have to make and very difficult choice. And it just occurred to me, why do we have our education system designed like that? We’ve started LIS to provide an interdisciplinary degree for our undergraduate students and our master’s students. We’ve launched a master’s two years ago, and rather than being organized around a single discipline, this degree is organized around complex problems which require you to be able to learn about and understand data science, anthropology, linguistics, mathematics, and a whole range of things besides.
Matt: Fantastic. I mean, tell us a little bit more about the– So, first of all, this is a proper university, isn’t it? Like properly accredited?
Ed: It is properly accredited. Yeah, we’re the first new university to open with our own degree awarding powers since the 1960s, actually.
Matt: So obviously people study a range of subjects. How do you choose those subjects and how are they organized to sort of make sense to go together?
Ed: Yeah, it’s a great question. I mean, the sort of organizing vehicle each term is a complex problem that the students are looking at. So, let’s say in their second year, in the first term, they’ll be looking at a problem involving AI and ethics. And then during that term, they’ll be taught some of the ethics part by a philosopher that joined us from LSE and he was a philosopher there. And they’ll also being taught elements of law, they’ll be being taught some machine learning, they’ll be being taught some data science from a data scientist who joined us from Berkeley. And they’re trying to bring all those different lenses and those tools to bear on the problem of thinking about AI and ethics. And that’s how we kind of make sense of it all. And that’s how it’s different, actually, from a liberal arts and sciences degree, which is a bit a pick and mix model, where you can have a mixture of French poetry, history and calculus. The organizing principle here is this complex problem.
Matt: I think that’s really interesting, because certainly in the UK we specialize very early, so most people who go to university study one topic from the age of 16, they study three or four. It kind of narrows down from there. And as you say, there are kind of more general paths of study in other countries like the US. But this is all about thinking differently about expertise, isn’t it?
Ed: Yeah, I think so. First of all, it’s important to say that it’s really important for us in the UK to have people, and the rest of the world to have people who have studied one specific subject for a long time. You want people with real narrow expertise in parts of biology, for example, when COVID hit, we needed people that have been thinking about how you model disease spread for the previous 10 years. That’s really really important. But we have a model in the UK where everybody goes narrow for three or four years, and this seems peculiar. So, we think we need to think about expertise in a slightly different way. And rather than thinking about depth, which is not really the right term, as far as we can see it, people’s knowledge is really a network of knowledge.
We’ve all got this quite broad, interconnected, quite unique set of knowledge that we’ve developed through school, but also just through being in the world and through reading books and watching things on television. Through our workplace, we develop this kind of broad network of knowledge, interconnected knowledge, and that’s a much more interesting way to think about it. And I think, both as a learner, broadening out and building up your network of knowledge, rather than worrying about being a narrow expert. But also, employers when they’re looking at hiring people.
Matt: Yeah, absolutely. I suppose that brings me to my next question. Has this kind of been designed around employability? Are these sort of problems that people are solving very relevant to the corporate and the business world right now?
Ed: Yeah, we’re completely focused on these problems being the kinds of problems that organizations are looking at. And so to do that, we bring organizations in with real problems. So our students are often in term, say, for example, they’ll be working on sustainability problems, retailers thinking about, or that the local council is thinking about, and they’ll be trying to apply their academic thinking to those problems. So that keeps us real, but it’s also a way of connecting people’s academic learning to the workplace. I think there’s a problem in the UK, and probably beyond where graduates come out and they’ve been doing quite advanced academic work in a specific subject, let’s say, history or physics. And then they’re quite frustrated when they go into the workplace, because that’s not really recognized. They start at the bottom with some quite basic tasks.
The flip side is that the employers you often hear are sort of moaning that graduates don’t know what to do. They can’t– they’re left and they’re right. And of course, that’s not really true, but they’ve not got the right kind of expertise. Whereas what we’re finding, we’re starting to find now is that employers look at our graduates and think, “Oh, wow, you know, something about sustainability that’s actually really useful to me.” And then the graduates and the employers can have a conversation, whether that employer is from a hedge fund, from the NHS, from John Lewis, they can have a conversation about sustainability in quite a sophisticated way. They can also have a conversation about AI. They can have a conversation about how they think about inequality or diversity in their companies, because these are the problems our students have been thinking about. And they can say, “Well, I know some tools to manipulate the data to think about that. Or I can think about this from a philosophical perspective or a data science perspective.” And this is really, this kind of is very, very helpful and useful for the employers, and they can see ways to connect the students learning to their actual business.
Matt: Yeah. I think that’s really interesting because I’ve seen people join organizations straight from universities, even with degrees that you might consider to be vocational, say, for example, marketing, and still kind of struggle to sort of make that connection with the job and the employer to get the best out of them. So, yeah, it’s been a real problem for a long time. Talk us through the outcomes that you’re getting for the students. Are they finding it easy to get these jobs that may be easier than if they don’t have a very narrow topic at a more traditional university?
Ed: Well, our students are starting to get fantastic jobs. It’s important to say we don’t have any graduates from our undergraduate course until this summer. So that’s when our founding cohort who were brave enough to join us in 2021, they graduate this summer, in 2024. But some of them are already getting jobs. I mean, some of them are getting jobs at quite elite, selective institutions like Goldman Sachs. One of them has got a job as head of growth at an AI company, and a lot of them are busily applying for jobs, but they’re getting interviews and they’re getting offers. And this is what’s really exciting. But the proof will be in the pudding. We’ll see later this year. We’re very cognizant that these young people took a risk by coming to us, because the brands of a university is inextricably linked to how old it is and we’re completely new. So, what we wanted to do is make a commitment to young people to help get them internships every year. So, they’re coming off the back of a couple of years of having done placements with Innocent Smoothies or firms like KPMG or local authorities, startups and so, they’ve done at least five weeks each summer working on a complex problem at those organizations. So, they’ve got that basis. But we will see this summer how they get on. I mean, this is essentially an experiment.
Matt: How do you select students for this? Because as you say, there’s obviously you need students who are going to think about things in the right way, but also at the same time, they’re going to have to be pretty sort of brave to join early on. So, how did that selection process work?
Ed: Yeah. Well, I’ll say, first of all, about who we’re looking for. We’re looking for students that are intellectually curious. If you’re not interested in lots of things, this is not the degree for you and this isn’t a degree for everybody. So, if you want to be a lawyer or a doctor or study history for three years, then LIS is not the place for you. But so we’re looking for that intellectual curiosity. We’re also looking for people who care about problems, so care about something that’s just bigger than themselves. They’re not just coming to university so that they can get the best starting salary. They actually want to make a difference because our whole degree is organized around that and so that’s really important. And then still we’re looking for people who are brave and people who are brave enough to say, “I’m not going to follow the crowd.” And in fact, some of them take a view that not following the crowd is less risky because there are hundreds of thousands of people.
I mean, something like 500 thousand people are graduating every year from undergraduate courses across the UK. And we’re in a pretty tough economy at the moment. How do we select for them? Well, that’s an interesting one because, of course, as we’ve just been talking about in the UK, most of these students have done a very narrow set of A levels. I mean, some of them have done an interesting– and they’re quite sheepish. They say to me, “I’ve done a weird sort of A-levels. I’ve done biology, I’ve done math and I’ve done art.” And we go, “Oh, that’s completely brilliant. We love that mixture.” But we understand that most of the students wouldn’t have done that. So, we interview everybody that applies and there we are testing for your intellectual curiosity. We’re trying to understand the way you think about problem solving and we throw some questions at you which are reflective of the sorts of things you can have to think about on the degree. So, we’re testing to see whether people can be successful in the course, and then we’ll make an offer, a very, very contextual offer, based on your circumstances and your predicted grades and everything. So, we’re really proud that it’s probably the broadest academic range of people on any degree in the country.
So, we’ve got some people on our degree with 4A stars at A level, which is perfect set of A levels. And some people who are way off that because they demonstrate to us that there are reasons they didn’t do well in their A levels, and they’ve done really interesting things since. And then they did brilliantly in the interview. But it means on other way, we’ve got academic diversities. We’ve got some people who were applying also to fine arts schools and some people that dropped out of Imperial College doing electrical engineering, and they’re on the same degree together. So, it’s this kind of amazing mixture.
Matt: Yeah.
Ed: Amazing.
Matt: That’s that kind of diversity of thought and background and all that kind of stuff. And also, a very realistic way of thinking about people’s potential and not hanging it onto how they did on one particular day in their exams. What about the master’s degree? Tell us a bit more about that.
Ed: Well, the master’s degree is really exciting. We’ve got one master’s degree, and we’re launching another one in a couple of years and that one will be targeted at taking on the business schools. I can come to that in a second, if you like. The current masters is essentially saying to if you’ve done a narrow degree, which many people have. So, we’ve got people who’ve joined us from computer science degrees or humanities degrees. Again, they’re on the same masters, they’re learning a bunch of different methods, and they choose a problem area that they’re passionate about, and they work on that problem throughout the year, using our interdisciplinary set of tools and concepts to interrogate that problem. And a lot of those problems now, as you’d expect, involve applying AI to -well, one I was hearing about yesterday was applying AI and modeling methods to cancer research, essentially. But equally, they can be much more design focused. One involved looking at how poetry affects society. And so, the range of these projects that people are looking at is really exciting. And this is a group of 2030 master students who are all doing the same program, but they’ve got wildly different backgrounds and looking at wildly different things, but they’re using very similar interdisciplinary tools to kind of move their work forward.
Matt: I think that’s really interesting as well, because just in terms of how we categorize people and how we think they think at a relatively early age. I mean, how do you find someone with a humanities degree? I don’t know, English literature or drama or something like that, their capability to learn how to learn programming languages, for example?
Ed: That’s a killer question because I think that what we found is that the people who have got more of a qualitative background, so the humanities or the arts find the quantitative work, data science and coding harder than the other way around. But they also, once they work through it, are really, really grateful and pleased that they have done that, because they really feel. So, the student who is applying for fine arts schools, who is now in her third year, is able to use coding and apply that to some of her work in the arts. And this is something that she would never– if not made to do it, essentially, she would probably not have kind of really got to grips with that. And that is now big differentiating factor for her. She can say to people, “Yeah, I can code.” Yeah, “I can do data science. I can do statistical analysis, and I’m an artist.” This is a really, really exciting intersection of skills, but it’s very hard to teach. So, it’s hard to teach that range of capabilities on a quantitative level. But we’ve kind of cracked it over the last year or two. But we initially, in our first year, how do you teach this massive range of math’s? Basically, how good is such a huge range of mathematical capabilities? But no, we’ve cracked it now.
[music]
Matt: Hi, it’s Matt, and we will be back to the interview very shortly. In several decades of working in this industry, I’ve never seen a time of greater disruption and change. And we really are still only at the beginning. With technology advancing as quickly as it is now, there’s a tendency to believe that we have no control over the future. This is wrong, and I passionately believe that this is the precise time when we should be inventing the future. I want to see talent acquisition thrive, and I want recruiting to be transformational in getting everyone into the right job for them with the right skills at the right time. So, I’ve built a course to help, and it’s called Trend Spotting. Trend Spotting is an on demand digital course that examines the forces driving change and assesses the emerging trends in talent acquisition. It also teaches a simple but robust model to help you understand, plan for, influence, and invent the future. Trend Spotting is for everyone in talent acquisition. It will help you future proof your career, create future-focused talent acquisition strategies and build your influence within your business. I’ve split Trend Spotting into nine short lessons to easily fit into the flow of your busy day. The feedback from the TA leaders who’ve taken the course so far has been amazing. You can find out more by going to mattalder.me/course. That’s mattalder.me/ course.
[music]
Matt: So, moving back to employers, employability and those kind of things. Over the last sort of couple of years, employers have kind of been rethinking their approach to early careers. So, we’ve seen some employers sort of scrap the requirement for a degree and focus more on apprenticeships and those kind of things. Do you think this is a way of redefining the value of a degree to employers or certainly taking people from this kind of pathway?
Ed: One of the things I felt strongly is that more people going to university is only a good thing if we really think they’re getting a lot of value from those three years. And I’m afraid to say I’m not sure that lots of students are getting value from those three years. And I don’t just include kind of lower ranked [unintelligible 00:18:01] universities. I mean, I did a mechanical engineering degree at Imperial, which was very useful, I’m sure, for lots of people. But I was never going to be an engineer afterwards, and therefore very little of that degree. I’ve been able to transition to my later life. And so, was it useful for me to go there? Well, of course it was useful in terms of brand name. It helped me, you know, it demonstrates that I can do hard math’s and hand working on time and all of that. But is it useful enough, we need to interrogate if we’re going to have almost half of young people in this country going to university for three years and paying lots of money. But it’s more the time, actually, from my perspective, it needs to be worth it.
We need to interrogate what they’re doing whilst they’re there. Too much of the debate about universities, in my view, is about who gets access and what are the fees. Well, that’s fine, but it’s really important what happens when you’re there for three years, because if it’s not actually a value adding thing, do we care about who gets to go? And so, what we sat down and said at the beginning is, “Okay if we don’t even really believe that necessarily we need more people going to university. What we believe is that we need more choice, we need more variety. And if you’re going to have people, come to you for three years, what is it that you could do?” Which is why we throw everything at these students across the three years. This range of expertise, internships, working with employers during the term, all of this stuff. It’s like, “Let’s create a bachelor’s degree that’s worthy of the fees, that’s worthy of the time that these young people are dedicating and get them ready to go and have an impact in the world.” That’s unashamedly, it can be a bit sheepish about that sometimes, but that’s reality, particularly now young people are coming in to make sure they get onto the next stage.
Matt: Yeah. And I think, again, that’s fascinating, because I think that the whole debate around the value of degrees is done in such simplistic terms. So, anything that sounds like almost might be fun, drama, English, all those kind of things, that’s obviously low value, and then people are judging success by how much people are earning after a certain period of time. And what that doesn’t do is it doesn’t really explore the value in some of those subjects, and it also doesn’t explore how people are making a difference. So, it’s great to hear someone challenging that kind of very simplistic way of thinking about degrees.
Ed: Yeah, I think so. I mean, it is crazy that more arts-based degrees are not seen as valuable. And yet we have this huge, thriving arts economy in the UK. And there’s a slightly separate point, but you mentioned earnings. The economy pretty much only rewards numeracy at the moment, and that’s partly because banker salaries are so high. But if you’ve got a numeric degree or a degree that involves numeracy, you will tend to be starting on a much higher salary than someone with a humanities degree. And it’s actually becoming even bigger, that gap, because the salaries for bankers and professional services is going up faster than other salaries. And actually, in the arts, often people have to work, sometimes for no money or terrible money for quite a long period of time, which means that it’s not accessible to a broad range of people. They’ve got a massive diversity problem. But that’s probably a separate– that’s probably for another podcast.
Matt: [chuckles] Absolutely. Yeah, absolutely. Yeah, so I suppose coming back to employers, because there’s obviously lots of talent acquisition, HR people listening into the show, I think it’s interesting because I think that whole kind of pigeonholing of people into specializations is something companies do as well in terms of not moving people internally and also when they’re hiring, not looking at comparable skills in other industries. So, it appears to be a mindset that continues. What would your advice be to companies in terms of how they could sort of think differently about hiring and skills development and moving people internally using some of the principles that you’re working with?
Ed: I think for employers, a really useful idea is this idea of interactional expertise, which is essentially a label, a way of talking about that level of expertise that we all have, which is somewhere between nothing and being a kind of contributory expert, someone who’s contributing to the cutting edge of the field, which very few people are. So, most of us exist on this scale in between. But we’re a little shy, unless we’re a true expert in something. Sometimes we’re a little shy about saying we have some expertise in that area, but that kind of expertise, that level of expertise is called interactional expertise, and it’s really important. It’s the kind of expertise that a science journalist has in science. So, they’re able to talk to scientists, but they won’t necessarily be doing the science, but they’ll understand some of the scientists’ jokes, but they may also have interactional expertise in another area, like economics or politics, and then they’re able to cross populate and talk across those fields, make connections in ways that the scientists are not able to do. So, it’s very, very important.
And in the knowledge economy for employers, these sorts of roles proliferate. They’re everywhere, but we don’t have ways of talking about it. So, if you’re an employer looking to hire somebody or looking at moving people internally, try and think about what’s their interaction expertise here? Where have they got some expertise that could be useful? What’s their combination of expertise, their network of expertise that they can put together, rather than just, what’s the one bucket that I have to put this person in? Are they an expert marketer or are they got a PhD in physics? So that’s their thing. Well, almost certainly they’ve got this broad range of interactional expertise, so try to uncover that.
Matt: No, absolutely, absolutely. So, a final question for you, and I’ve saved the biggest question till last. What does the future look like? I suppose, particularly with the reference to AI, how is AI influencing the way that we learn, the way that we develop expertise, and how is that likely to sort of play out in the future?
Ed: Well, I like everybody else, have been surprised by the progress of AI over the last 18 months or so. And these large language models, they’re so much more sophisticated, so much more quickly than any of us thought. So, in the education sector, we’re trying to respond as quickly as we can, but we’re embracing them. I think the first thing to say, I was speaking to some lawyers, maybe it was six months ago and they still hadn’t used ChatGPT. And I thought this was quite surprising, and they said their firm didn’t really allow it. I think the first thing is we have to embrace it. And therefore, in the education system, we have to embrace it. Otherwise, young people are going to be coming into the workforce not able to use these tools. I think in terms of building expertise, the question for the sort of education sector and for training people that are doing training in corporates is what are the skills now that humans actually need?
So, for example, being able to write reports, I think that is not a skill that will look the same in the sort of 6,12 months as it did four or five years ago. So, what is the skill? So, what’s the skill that’s required? Is it being able to understand what kind of inputs are needed to put into that report? Is it being able to say, “This is the first draft of the report, I can pass it, go through it, really try and understand where chats got it right and got it wrong.” But I think they have to think again about what those skills are. And of course, that means, “Who do we need?” And my bet is referencing sort of interdisciplinarity. Of course I would say this, but having that breadth of expertise means you’ll have fewer blind spots. And that’s the problem that AI will have. AI has blind spots. Even generative AI has many blind spots. We know it’s 98% or whatever it is effective, that 2% is really important. So having fewer blind spots when you’re working with these tools will be really vital.
Matt: Ed, thank you very much for joining me.
Ed: Of course I’ve enjoyed it. Thanks very much, Matt.
Matt: My thanks to Ed. You can follow this podcast on Apple Podcasts on Spotify or via your podcasting app of choice. Please also subscribe to our YouTube channel by going to mattalder.tv. You can search all the past episodes at recruitingfuture.com. On that site you can also subscribe to our newsletter, Recruiting Future Feast, and get the inside track about everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time, and I hope you’ll join me.
