Artificial intelligence has presented the world with another industrial revolution, and this time, the UK is sitting far from the top. We aren’t developing these disruptive technologies in the same way as, for example, countries in the far East. We don’t have the kind of scale or impact that we’ve had in the past, and although our institutions are quick to research and develop AI, we are slow to commercialise it and slow to use it – particularly in the higher education sphere.
We have a lot to learn, challenges to face, and real things to confront in order to change our ways of teaching and learning to meet student expectations and the evolving labour market.
In higher education, we are all relatively familiar with AI or a bot of some kind, and the idea that it can be used within a teaching and learning paradigm. It’s not only plausible, but it already exists in some regard, with automated test marking (for multiple choice tests), for example. There are even tools that can create subtitles in real time, translating what a lecturer is saying for those who speak different languages.
In our own way, we are recognising that these technologies are vital to teaching and learning in the 21st century. Modern teaching has seen calls for a faster pace and increased accessibility, and tech such as bots that translate and mark tests are being developed to respond to these calls. We are in the beginning stages of recognising the need for some level of automation.
But the challenges begin here: UK higher education is typically a very conservative sector, and from a technological point of view, is a late adopter compared with other countries, particularly in Asia. We have this conundrum of a sector that develops AI that can facilitate learning, but doesn’t use it enough in the teaching of its students. This is a problem for students, who must be able to compete on an international level in an increasingly globalised economy.
UK higher education could use AI in a much more fundamental way by going beyond using it for research or to simplify admin processes to using it to enhance learning, widen participation by breaking language barriers, personalise learning by finding knowledge gaps and customise the curriculum.
Our focus has, typically, been skewed away from the people who will be using these evolving technologies. We must still focus on researching and developing, of course, but we cannot forget the people who will be working with AI and using it to learn.
Those working in higher education are struggling to get to grips with questions of ethics and control around AI. Bias within data sets that can negatively impact certain individuals, AI that nudges individuals towards certain behaviours and the fact that no real research has been conducted into these issues are challenges we must address.
And what happens when we develop levels of intelligence so high that it displays something we recognise as emotions, feelings or personality? We must consider how humans and AI will coexist in the future. Ultimately, this will affect the way that students are taught to engage with the world.
Higher education demands are changing and AI is one way of developing cost-efficient models to give to students, to try and support what they’re looking for in their educational development. Those who move in the sphere of higher education must understand the technologies that are changing our world, and start using them to engage with students’ learning.
This blog is based on John MacIntyre's speech at the Higher Education Partnership Network event, which was held from 30 April to 1 May.
John MacIntyre is pro vice-chancellor (internationalisation) at the University of Sunderland.
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