Universities have a critical role to play at the intersection of academic thought, organisational practice, and social benefits of technology.
It’s easy when thinking about universities’ digital strategies to see that as a technical question of organisational capability and solutions rather than one part of the wider public role universities have in leading thinking and shaping practice for the benefit of society.
But for universities the relationship with technology is multifaceted: some parts of the institution are engaged in driving forward technological developments; others may be critically assessing how those developments reshape the human experience and throw up ethical challenges that must be addressed; while others may be seeking to deploy technologies in the service of improving teaching and research. The question, then, for universities, must be how to bring these relationships together in a critical but productive way.
Thinking into practice
The University of Edinburgh hosts one of the country’s foremost informatics and computer science departments, one of the largest centres of AI research in Europe. Edinburgh’s computing infrastructure has lately hit headlines when the Westminster government decided to cancel planned investment in a new supercomputing facility at the university, only to announce new plans for supercomputing investment in last week’s AI opportunities action plan, location as yet undetermined.
But while the university’s technological research prowess is evident, there’s also a strong academic tradition of critical thought around technology – such as in the work of philosopher Shannon Vallor, director of the Centre for Technomoral Futures at the Edinburgh Futures Institute and author of The AI Mirror. In the HE-specific research field, Janja Komljenovic has explored the phenomenon of the “datafication” of higher education, raising questions of a mismatch and incoherence between how data is valued and used in different parts of an institution.
When I speak to Edinburgh’s principal Peter Mathieson ahead of his keynote at the upcoming Kortext Live leaders event in Edinburgh on 4 February he’s reflecting on a key challenge: how to continue a legacy of thought leadership on digital technology and data science into the future, especially when the pace of technological change is so rapid?
“It’s imperative for universities to be places that shape the debate, but also that study the advantages and disadvantages of different technologies and how they are adopted. We need to help the public make the best use of technology,” says Peter.
There’s work going on to mobilise knowledge across disciplines, for example, data scientists interrogating Scotland’s unique identifier data to gain insights on public health – which was particularly important during Covid. The university is a lead partner in the delivery of the Edinburgh and south east Scotland city region deal, a key strand of which is focused on data-driven innovation. “The city region deal builds on our heritage of excellence in AI and computer science and brings that to addressing the exam question of how to create growth in our region, attract inward investment, and create jobs,” explains Peter.
Peter is also of the opinion that more could be done to bring university expertise to bear across the education system. Currently the university is working with a secondary school to develop a data science programme that will see secondary pupils graduate with a data science qualification. Another initiative sees primary school classrooms equipped with sensors that detect earth movements in different parts of the world – Peter recounts having been proudly shown a squiggle on a piece of paper by two primary school pupils, which turned out to denote an earthquake in Tonga.
“Data education in schools is a really important function for universities,” he says.”It’s not a recruiting exercise – I see it as a way of the region and community benefiting from having a research intensive university in their midst.”
Connecting the bits
The elephant in the room is, of course, the link between academic knowledge and organisational practice, and where and how those come together in a university as large and decentralised as Edinburgh.
“There is a distinction between the academic mission and the day to day nuts and bolts,” Peter admits. “There is some irony that we are one of finest computer science institutions but we had trouble installing our new finance system. But the capability we have in a place like this should allow us to feel positive about the opportunities to do interesting things with technology.”
Peter points to the university-wide enablement of Internet of Things which allows the university to monitor building usage, and which helps to identify where buildings may be under-utilised. As principal Peter also brought together estates and digital infrastructure business planning so that the physical and digital estate can be developed in tandem and with reference to each other rather than remaining in silos.
“Being able to make decisions based on data is very empowering,” he says. “But it’s important that we think very carefully about what data is anonymised and reassure people we are not trying to operate a surveillance system.” Peter is also interested in how AI could help to streamline large administrative tasks, and the experimental deployment of generative AI across university activity. The university has developed its own AI innovation platform, ELM, the Edinburgh (access to) Language Models, which is free to use for all staff and students, and which gives the user access to large language models including the latest version of Chat-GPT but, importantly, without sharing user data with OpenAI.
At the leadership level, Peter has endeavoured to put professional service leaders on the same footing as academic leaders rather than, as he says, “defining professional services by what they are not, ie non-academic.” It’s one example of the ways that roles and structures in universities are evolving, not necessarily as a direct response to technological change, but with technology being one of the aspects of social change that create a need inside universities for the ability to look at challenges from a range of professional perspectives.
It’s rarely as straightforward as “automation leading to staffing reductions” though Peter is alive to the perceived risks and their implications. “People worry about automation leading to loss of jobs, but I think jobs will evolve in universities as they will elsewhere in society,” he says. “Much of the value of the university experience is defined by the human interactions that take place, especially in an international university, and we can’t replace physical presence on campus. I’m optimistic that humans can get more good than harm out of AI – we just need to be mindful that we will need to adapt more quickly to this innovation than to earlier technological advances like the printing press, or the Internet.”
This article is published in association with Kortext. Peter Mathieson will be giving a keynote address at the upcoming Kortext LIVE leaders’ event in Edinburgh on 4 February – join us there or at the the London or Manchester events on 29 January and 6 February to find out more about Wonkhe and Kortext’s work on leading digital capability for learning, teaching and student success, and be part of the conversation.
