Alongside the Professor Jennings, Dr Saul Albert, Dr Georgina Cosma and Dr Martin Sykora each shared insights into their research and the use of artificial intelligence, answering questions sent in by alumni.
The panel discussed how AI could impact the future of education, the workplace, and also had specific discussions about certain industries. They talked about taking a balanced view on AI in order to avoid hyperbole, and the need to have a diverse range of perspectives and expertise in order for AI to achieve its full potential.
The event sought to offer alumni the opportunity to tune in to hear discussions on this hot topic, which is currently dominating the news.
The experts had a range of insights to offer, and if you would like to access the recording of the discussion, we can provide this on request. Please email us on alumni@lboro.ac.uk.
Thank you to our panellists and to everyone who attended the event.
The academics have shared links to further pieces of research and other things for you to read following the event. A selection of resources are linked and referenced below:
The Dangerous Ideas of “Longtermism” and “Existential Risk”, Current Affairs
Information Commissioners Office – UK GDPR guidance and resources
ICO's AI & Data Protection Risk toolkit
Leslie, D. (2019). Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute. Also available via Zenodo.
Some thoughts on accountability in AI: Aceves, P. (2023, 29th May). ‘I do not think ethical surveillance can exist’: Rumman Chowdhury on accountability in AI, The Guardian.
A key academic paper on ethical and bias based issues of LLMs/ChatGPT like AI: Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623).
CMA regulator to look at LLMs/ChatGPT like generative AI: Beioley K. and Murgia M. (2023, May 3rd) UK competition watchdog launches review of AI market. (Financial Times login required).
A study looking at 5,179 customer support agents using a ChatGPT like LLM/AI assistant: Brynjolfsson, E., Li, D., & Raymond, L. R. (2023). Generative AI at Work (No. w31161). National Bureau of Economic Research.
Survey of synthetic media (AI generated content) across mainstream news and misinformation websites: Hanley, H.W. & Durumeric, Z. (2023). Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websites. arXiv preprint arXiv:2305.09820.
Use of LLMs to help counter misinformation online: He, B., Ahamad, M., & Kumar, S. (2023, April). Reinforcement learning-based counter-misinformation response generation: a case study of COVID-19 vaccine misinformation. In Proceedings of the ACM Web Conference 2023 (pp. 2698-2709).
LLM/ChatGPT for ad moderation (with minority languages): Kayser-Brill, N. (2023). Is Big Social ever going to be honest? AlgorithmWatch, 87th issue of Automated Society Newsletter.
Some of the issues around AI/LLM hallucinations: Marcus G. (2023) GPT-4’s successes, and GPT-4’s failures, The Road to AI we can Trust.
G7 group acknowledged the need for governance of generative AI: Reuters (2023, May 19th). G7 leaders confirm need for governance of generative AI technology.
An IS research community perspective on the role of generative AI in academic scholarship: Susarla, A., Gopal, R., Thatcher, J. B., & Sarker, S. (2023). The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly Activities in Information Systems. Information Systems Research.
AI risks statement: Centre for AI Safety (2023) Statement on AI Risk.