“Part of the problem is that even a singular system like ChatGPT encompasses a dizzying array of use cases for academics, students and administrators that are still in the process of being discovered. Its underlying capacities are expanding at a seemingly faster rate than universities are able to cope with, evidenced in the launch of GPT-4 (and the hugely significant ChatGPT plug in architecture), all while universities are still grappling with GPT-3.5. Furthermore, generative AI is a broader category than ChatGPT with images, videos, code, music and voice likely to hit mainstream awareness with the same force over the coming months and years.
In what Filip Vostal and I have described as the Accelerated Academy, the pace of working life increases (albeit unevenly), but policymaking still moves too slowly to cope. In siloed and centralised universities there is a recurrent problem of a distance from practice, where policies are formulated and procedures developed with too little awareness of on the ground realities. When the use cases of generative AI and the problems it generates are being discovered on a daily basis, we urgently need mechanisms to identify and filter these issues from across the university in order to respond in a way which escapes the established time horizons of the teaching and learning bureaucracy”
Source : Are universities to slow to cope with Generative AI? | Impact of Social Sciences