- This HEPI blog was kindly authored by Berry Billingsley, Professor in Science Education at The Epistemic Insight Initiative, the Future of Knowledge
Universities are a global business. Traditionally this is where established knowledge is stored and where new knowledge claims are evaluated. It’s also where the future of knowledge is handed from old scholars like me to the next generation of knowledge creators and workers who are here to learn their crafts.
AI chatbots like Bard and ChatGPT are arguably mechanisms that will produce a third seismic shift for how universities work. Their impact is magnified because they follow and build on two previous seismic shifts. One was the digital transformation which gave students and tutors access to vast amounts of content and enabled tools they can use to browse and search the web; the second was the driving force of the pandemic and moving education and the business of teaching and learning online.
GPT stands for generative pre-trained transformer which means a lot of code has been invested in creating a bot that is designed to work out the intents of your questions. AI engineers can sometimes make immodest claims and these bots are already being called ‘natural language processors’. Hmm, that’s the ambition and design brief. The idea is that you can enter any question you like, and the bot will deliver a bespoke and useful answer, presented in everyday language. In reality you can find ways to interact more effectively with an AI chatbot by experimenting and/or if you know how it works – just as you can Google more successfully once you’ve learnt or read up on how Google behaves.
And the relevance to university life and the existence in future of traditional academic disciplines?
So here is a bot that is designed to take a question, work out your intent, and then trawl the internet for snippets of content that can be used to build and word an answer. Contrast this to how students and academics have traditionally worked with and created knowledge. Traditionally knowledge at universities has been siloed into disciplines. Just think of the typical university campus – the separate blocks for science, the humanities, the arts, etc. These silos were so engrained into our thinking and ways of working that we didn’t even notice them most of the time. We also taught students in silos. That matters in the age of AI for a couple of reasons. One is that AI interacts with different disciplines differently and different disciplines are likely to have different attitudes to AI. A common question among many academics and members of the wider public is: if this is what the AI can do – what’s left or special about us?
But even though attitudes to AI are split as you move between disciplines – at the same time, the traditional visible fortresses of disciplines – the campus university silos – are at risk of disappearing. Here are the factors driving them out of sight and in some universities – out of existence.
There was the pandemic – which means that these days the visible signs of life on some university campuses are merely the tip of an iceberg as large numbers of students make a choice to continue to work remotely and study online. That’s not just a visible change, it’s also changing how knowledge works. Online we talk less about knowledge belonging to disciplines– we talk more about finding information, checking content, and answers. Any technology has benefits and risks. A technology like Zoom helps us to collaborate across cultures. On Zoom we are each in a box and we are all ‘the right way up’ even if we are physically in Japan, Wales, Australia or France. On the downside (if you think disciplines are a good thing) we are drifting into groups united by a topic rather than by a preferred type of question.
In parallel, the significance of global issues (including the pandemic) has highlighted questions that cannot be addressed through one discipline alone has accelerated a move towards multidisciplinary research. There are some universities that proudly advertise themselves as ‘STEAM’. And there are also more courses for students who care about these big global questions and want a multidisciplinary education at university. How this is achieved in practice can mean a careful integration of different disciplinary perspectives. There are also lots of examples of cross-disciplinary courses where the modules are still taught individually by tutors working from and in their separate silos.
And now tutors’ capacities to create boundaries around their subjects are shifting again. Now, thanks to AI, students have a new personal tutor – available at all hours to answer questions and happy to help to write an assignment. That’s much more than a typical tutor offers to do!
Ok – so now put these pieces together and we get fireworks and a crisis of who are we and why are we here, at least in principle and on some campuses, in practice. And the way forward?
In my view a good solution does not mean we mash together or integrate all knowledge into one amorphous package, nor should we go back to silos and create and work with knowledge in separate isolated silos. The solution is to strive for the best of both worlds with distinct disciplines that we bring together. After all, and to draw a parallel with another part of this conversation: some of us wonder what’s distinctive and special about us in an age of Gen AI. I like the idea that people are the ‘originators’ and the sources of the aims and visions of our questions and projects. We are originators and we are each original – or unique – even though we stand and build on what has gone before. So, a chatbot is designed to trawl the internet to produce some novel text, but the origins and driver of its response are a question posed by you.
As such – the activities we offer students via Knowledge Labs are only partly to teach students the value of exploring Big Questions and real-world scenarios by bringing together the different types of knowledge and different methodologies that we can access by pairing very distinct disciplines. But – and perhaps what makes this unusual – the primary objective is to help students from different disciplines to learn about the strengths and weaknesses of their own and another discipline in a shared context.
That means we don’t guess which combinations of disciplines are going to be the most useful to combine based on a pre-existing list of problems/opportunities. Instead, we let serendipity and timetabling dictate who meets who. A blind date between two courses – a chance to meet and work with students who look at the world through a different lens.
Meanwhile our role is to provide them with tools like the Discipline Wheel that they can use to bring their disciplines together. And there’s something else I like about the way that this approach can work. Working in cross-disciplinary groups means that students can start to see what creativity looks like for a peer in another discipline, without the heat and exposure of students taking up their individual stances. I hope they will encounter many surprises.
And that seems to be me to be a good lesson in life to have. We are distinctive and valuable for many reasons, and one is the different perspectives we bring. We can also see value in our distinctiveness because of the different questions we ask.
To have a glimpse of what it might look like, please visit ‘Knowledge Labs’ at https://futureofknowledge.com/knowledge-labs/