TF: There’s always pressure to produce the ‘employable graduate’. How will universities in future resolve the conflict between strong employability skills and learning to learn? Or maybe it isn’t a conflict, they are both complementary?
CÓhÓ: In some ways it is a conflict. I think the interest in education in Ireland is interesting. There is always a drama every August and September about the Leaving Cert results and CAO. There is a real interest in, and concern for, education that comes out of the sense that education is the best way to progress your career and therefore your life more generally. So there is always going to be pressure to produce the employable graduate, but what makes a graduate employable will change over time. In the context of AI and the changing context of technology, the employment needs always change; how do universities adapt to that?
That brings us back to that learning to learn idea. What we are trying to develop in our graduates and in our research is that capacity to be agile, to respond to change over time, and to respond to challenges. I think COVID has been egregious and really difficult, and tragic for many people. But it also had a learning context in that I think that capacity to learn in uncertainty is an important attribute, and in many ways our students potentially learned more in the context of COVID than in other more certain contexts. There was a real challenge in dealing with ambiguity. It was very stressful, but I wonder in time whether that will be valuable learning for us. That sense of agility is what we are striving for. Is there sometimes tension there? Yes, but what we are passing on to our graduates or sustaining in our research is an ability to think in a particular frame. The employment context will always change so employability will always be a moving target.
We use the word skill a lot in the context of technology and AI. I much prefer the word capacity – skill is very reductive. I often think of the Heaney phrase, “We are here to develop your capacities, your destinies are your own”. So, that sense of opening up, of finding what you can do and what’s your place, and your contribution to society more broadly – capacity is a better way of imagining what a university education will be. Skills you can transfer in a lab, or in a manual, or in an algorithm, or an expert system. Capacity is much broader; capacities are about what it means to be a human being. That’s what universities will need to think about in the context of education in the future. How we teach, how we learn, how we do research, and that sense of community that we have on the campus is a very important part of what it is to be human, and that won’t ever be replaced by an algorithm. We need to think about what that will mean for how we go about our business, both how we engage with students and how we engage as an institution externally.
TF: AI is going to impact employment – some roles will no longer exist, and there are jobs of the future that do not yet exist. What does the university of the future look like in that context?
CÓhÓ: Adult and lifelong learning will become increasingly important. If your employment context is changing well then the university has a role in helping adaptation. We do that already with a lot of partners. Universities will become more diverse in our ability to attract all the talents, and I think that makes for a better university, not just across social classes but also across all the age groups. Universities will not be only for 18-year-olds as undergraduate or 20-something-year-olds as postgraduates, but for a much broader group of people, who will come back to us very often.
Physically, my sense is that the sense of community will always be there, people will want to meet so I think a campus will always be there, and the campus will always be an important heart of any university. What the campus looks like might be more of a mix, we may have more of a flipped classroom approach. AI might help in that – in allowing greater interactivity; in helping us find new ways to engage with students. I’m not a great believer that technology will replace what we do, but it can certainly help us do what we do better.
There are probably three roles for the university – one is in thought leadership and policy; the second is in democratising education; and the third is going back to learning to learn and being agile. We have a role in levelling up and levelling out, and in mediating the impact of those changes, certainly. Democratising education will be important and we will have a greater role in bringing people into the university that don’t normally come to a university setting – they should see this as their own, as their place. That then enables and empowers a much broader group to have that discussion, but then also to progress based on that discussion, and having that diverse debate in the classroom. Then, going back to that sense of agility – of building capacity, of learning to learn, and having a very strong research base that allows us to know what is happening in AI and more generally in other sectors, and to have the radar out.