New Research Project to Address Challenges of AI in Law and Healthcare

Academics from Computer Science and the School of Law are part of a research team that has been awarded a £4.38 million grant to tackle the sociotechnical challenges around using AI-powered Large Language Models (LLMs) for legal & healthcare purposes

Professor Nikos Aletras
Professor Nikos Aletras

Professor Nikos Aletras, Professor of Natural Language Processing and Dr Jiahong Chen, Lecturer in Law, are the Sheffield members of the new research collaboration with experts from Queen Mary University of London (lead institution), University of Nottingham and University of Warwick. Funded by UKRI via Responsible AI UK under the Keystone Projects scheme, the project focuses on the legal and healthcare uses of LLMs, a cutting-edge AI technology that enables systems like ChatGPT.

Professor Aletras said: “We aim to investigate new methods for addressing the limitations of large language models (e.g. hallucinations, bias, privacy) in two very important areas for the UK's economy, i.e. legal and medical."

In Sheffield, we will particularly focus on developing fundamental methods for improving LLMs and lead work on the legal use case

Dr Chen, who is leading the legal use case of the project, added: “There has been an increasing interest in using Generative AI chatbots for legal tasks such as summarising legal documents and providing legal information.

“It is important that we understand the limitations of these new technologies before they become more common in our society and justice system.”

Legal and healthcare uses have been identified as the prioritised areas due to their importance in the UK digital economy and also their potentially high level of risks and benefits.

Funding has been awarded by Responsible AI UK (RAI UK) and forms the pillars of its £31 million programme that will run for four years. RAI UK is backed by UKRI, through the UKRI Technology Missions Fund and the Engineering and Physical Sciences Research Council (EPSRC).

More information about the project can be found here:

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