Veale, Michael; Black, Isra; Dsouza, Mark; Fisher, Matt; Ghaus, Mujtaba; Gibbs, Thea; Lynskey, Orla; ... Trapp, Kimberley; + view all Veale, Michael; Black, Isra; Dsouza, Mark; Fisher, Matt; Ghaus, Mujtaba; Gibbs, Thea; Lynskey, Orla; O'Cinneide, Colm; Scotford, Eloise; Thomas, Olga; Trapova, Alina; Trapp, Kimberley; - view fewer (2025) Artificial Intelligence, Education and Assessment at UCL Laws: Current Thinking and Next Steps for the UK Legal Education Sector. (UCL Legal Studies Research Paper Series 04/2025). UCL Faculty of Laws: London, UK.

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Abstract

We are academics at the Faculty of Laws, University College London involved in the development of educational policy and practice concerning artificial intelligence. In this discussion paper, we lay out our thinking on how the legal education sector should respond to generative AI. We are very supportive of thoughtful use of technology to change our world and our work for the better, but developing excellent legal expertise does and will remain crucial for lawyers, whether working with AI tools or in the many situations where such tools will be less helpful, absent or limited. There is a critical balance between using AI as a true study aide, facilitating meaningful learning, and using it to cognitively offload tasks in a way that hinders learning. We believe this balance to be delicate, and that academic judgement is crucial to achieving it. By highlighting relevant abilities and skills we regard as essential outcomes of learning the law, we identify the barriers AI poses to their acquisition, and the implications the technology has for assessment. We explain the thinking behind the policies we have enacted as a Faculty, including the requirement that all modules have 50–100% secured assessment—forms of assessment that reliably safeguard against the use of generative AI. Our position is that, in assessing our degrees, integrity takes priority and should not be put at risk, even as we recognise the value of diverse forms of assessment. More broadly, we see a compelling case for our sector to come together to respond to the future, double down on its values, cease passively responding to the ongoing evolution of business models of AI and cloud companies, and instead actively work together to determine the sector’s direction and to assert a positive and ambitious vision of learning well in a rapidly changing technological environment.

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