AI in Higher Education: Real Risks, Practical Opportunities, and the Road to Readiness

This session will challenge current discourses around the impact AI has, and has had, on universities from a practical perspective, focusing on real risks, opportunities and use cases. Topics include AI’s role in advancing assessment methods, changes in pedagogical approaches, and student engagement, as well as critical issues like data security risks, and institutional readiness for the adoption and integration of AI.  

Use cases, risks and opportunities AI posed to the sector

Risk/opportunity - Risk is plagiarism. Opportunity is new pedagogical approaches, particularly around assessment.  

Risk/opportunity – Risk is assuming AI can take the place of what is considered low grade customer service. Student experiences are often about humans and human interactions. Opportunity – what can AI do to free people up to spend more time with students. (Academic or PS contact time). AI will always be bad at moral decisions.

Risk/opportunity - risk is that people put sensitive data into an LLM and don’t realise they have given away data that could be then shared with others. Opportunity is that one day, AI might be able to do something with all of the bad data we hold.    

Real world examples of how Universities using AI.

AI in chatbox functions to enable faster responses to student/customer enquiries.

AI proofreading software – to help students proof read their work.

AI Governance – responsible/ethical use of AI/centralising use of AI for full visibility and compliance.

AI Approaches – in digital learning strategies and to improve the pedagogical experience.

Food For Thought for Session Attendees – If you’ve still not implemented the basic 365 functions (e.g. still have spreadsheets on local drives or handwritten docs) are you ready to have this conversation at all?