WonkHE recently published a thought-provoking piece on moves within higher education to make use of Artificial Intelligence (AI) in marking student work.
In essence, the post points to ‘the sacrosanct get out of jail card of academic judgement’ when students seek to challenge the mark awarded for their work; the centrality to this of the application of academic expertise in the marking process; and what it might mean if marking is no longer carried out by an academic expert, but by AI – i.e. a statistical model rather than intelligence, much less expertise, as we would understand it.
The WonkHE piece does a good job of following through on this issue, and I’m neither going to repeat what’s said there or take issue with it.
But it did make me think about whether when universities think and talk about how to adjust in response to the changed world we now live in due to AI, we pay sufficient attention to the issue of expertise.
Expertise is foundational to a university. Its claim to academic standing and authority, to be ‘higher’ is based on it. The development of expertise, both through its research and the education it offers, is at the core of its mission. And in order to achieve that mission, it is essential that a university deploys to best effect the expertise that it possesses.
So perhaps the concept of expertise is a useful vantage point from which to think about AI and higher education.
How do we most effectively use our expertise to choose the ways and extent to which we deploy AI in our education and research? How do we use AI to support us in building and developing our academic expertise? Where and how do we deploy our expertise most effectively to achieve our mission in a new world, where the best possible outcome is a hybrid of human and artificial intelligence?
Questions that perhaps may help universities, at least a little, in charting their path in this new world.
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