AI in Higher Ed & the Workforce

Sir Malcolm Grant shares critical insights on how artificial intelligence is reshaping the role of universities and the future of learning. In this clip, he explores the challenges and opportunities presented by AI as students enter higher education with unprecedented access to technology—and as the technology itself increasingly matches or exceeds human capability. Grant addresses the growing need for institutions to adapt: from rethinking how students engage with knowledge, to transforming how universities deliver education, conduct research, and operate at scale. He highlights the risk of losing the essence of learning if AI is used merely as a shortcut, and emphasizes the responsibility of universities to prepare students not only to use AI, but to grow intellectually alongside it.

It's interesting... so the historical model of higher education and I've seen it personally obviously at Oxford and Cambridge was one of great intimacy. You would have a leading professor as your personal tutor and I saw this particularly in relation to for example subjects like history and English where the some of the world intellectual leaders uh were speaking to undergraduates at the age of 18 and and guiding them through. But that's a very boutique uh elite model of higher education and not all not all students benefit from that actually you know it it's a particular type of student who gets the the benefit from that. So, in terms of new models of higher education I can see a a wide range of variation. We will have students coming through to our universities now and certainly over the next 10 years who have never known a world without a smartphone or a world without AI. So some universities rather clumsily are already saying how do how do we cope with AI How do we cope with students who have this technology well understood. And I think the big problem there is that these technologies can do the tasks that previously we expected students to do. So there was something called learning, something called reading, going to a library, thinking, writing an essay, benefiting students without doubt but not without effort. We need to think very carefully how that can be used and how the students can be developed so as to understand what AI can do to understand how that they can make better use of it. How they can become better students by virtue of having the technology behind them, it will take lazy students up to a certain level but actually that's not learning. That's not what we need from that so that, that I think is the aim of a university I would also emphasize that um we can set students tasks that they can fulfill using AI that they would have found difficulty to fulfill without it. And AI will accelerate and will allow them to become much more astute in the workplace as they come into it. Can I just add a a rider to that which is that the workplace is going to be different AI stands at the moment with these fantastic transformer models we we know that we're going to uh be able to apply it significantly across areas of intellectual activity where there are rules If there are rules then AI can help us to understand them absorb them and and negotiate them. So I think in areas such as the law obviously in accounting and auditing quantitative areas such as that AI will give us significant acceleration of being able to complete tasks that presently take very smart people quite a lot of time and get us pretty much to the to the same end point. So the combination of acceleration and also I don't know what lies ahead; I really don't you know. I've just watched AI very carefully over the last 10 years It is completely different from where we were 10 years ago and it's going to be completely different in another 10 years. So the intellectual capability of students is going to have to absorb that what we have today but also cope and adjust and develop as we go through things in the future. The impact of AI on research is going to be truly astonishing I need only to mention the two Nobel prizes that went recently one for physics and one for chemistry. And both of these were actually prizes for AI. But let me take the chemistry one which was Demis Uh what he did with Google deep mind was to set about trying to solve some of the most problematic instances of human biology and of mathematics. So with human biology for which he had the Nobel Prize was for his alpha fold three model which allows scientists to accurately predict the way in which proteins can fold which is fundamental to our understanding of biology fundamental to drug development and therefore fundamental to a great deal of research within human biology. We're starting to open up areas of investigation that people have puzzled about for decades if not centuries and which have involved painstaking labor in the laboratory or at the at the computer desk and this I just give that as one illustration of where AI will transform research and if we take it there we're going to see it in space science we're going to see it across the whole board of engineering. So I think even also in in in the arts and humanities you can through AI using a big transformer model start to digest you know centuries of literature. You can have much more effective translation between languages. Now I'm going back to my earlier point you you don't want to take away all the effort from research but if you can accelerate research and accelerate insight and understanding I think that's where AI will have a profound impact.