University processes are “ripe” for automation by generative artificial intelligence, according to a new report, with “massive implications” for professional services jobs.
With institutions across the world facing pressure on their finances – and staff cuts the “only place that real and sustained savings can be made” – embracing AI in administration “offers us a path to a better higher education system which uses its limited resources well”, according to Ant Bagshaw, deputy chief executive of the Australian Public Policy Institute.
Writing in a new collection of essays about the future of universities in the age of AI published on 16 October, Bagshaw says that “some of the skills, knowledge and processes held dear in universities are no longer as rare or precious as they once were”.
Reports, agendas, policies and minutes that are a mainstay of university life are all “ripe for GenAI to work on”, he adds, while more specialist tasks such as navigating and interpreting statutes, ordinances and regulations have now also been made more accessible.
“It seems implausible that universities will run completely absent of professional staff, not least because there are many roles where physical actions are essential or where human contact makes a material positive impact,” Bagshaw writes in his contribution to the collection collated by the UK’s 糖心Vlog Policy Institute (Hepi) and the University of Southampton.
“We need to recognise, however, that GenAI has massive implications for universities and the net result is likely fewer jobs.”
He says changes will be “painful and difficult” but the “university exists not to serve its staff but to be a place where students receive high-quality and useful education and from which research makes a positive impact on the world”.
Massification has also already depersonalised the staff and student experience, he adds, and if countries want to retain high-participation systems, this “can only be achieved with improved productivity”.
He also acknowledges that GenAI tools are “imperfect” and prone to bias, intellectual property infringement, error and hallucinations but “we should not pretend the system we have now is perfect” and if “our choice is between two flawed systems, we should choose the cheaper one”.
Universities should offer retraining opportunities to staff affected, Bagshaw adds, as it “is more humane to help colleagues into new roles now than to sustain jobs which machines can do better and cheaper”.
Writing elsewhere in the collection, Rose Luckin, professor of learner centred design at the UCL Knowledge Lab, says the rise of AI means “humans need to become significantly more intelligent, not less”.
This, she says, represents a “profound challenge” for educators because the products have so far been promoted as ways to make life “easier” and learning “effortless”.
There is an “urgent need”, argues Luckin, for “policy interventions that ensure AI serves as a tool for enhancing – rather than replacing – human intelligence”.
For traditional education systems that only measure narrow outcomes, the challenge will be to broaden assessment to look at the development of cognition, she adds.?
AI will be useful in this, Luckin says, as it “can now help us understand much more about the nuance of the way in which a learner is learning”.
It could be used, for example, to “identify patterns in how students engage with feedback, how they approach problem-solving or how their motivation fluctuates throughout a learning journey” and then help universities tailor support in response.
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