When AI Enters the Criminal Courts—Two Mock Jury Trials from the PROBabLE Futures Project

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NPL Call for Evidence: AI testing, evaluation and assurance in the UK

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When AI in a Trial Goes on Trial, the Technology Might Not Be the Central Challenge: Insights from a World Café

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View our newly launched 'Mapping AI Tools in Criminal Justice across England & Wales'

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AI in policing: safeguards can't keep up, new research warns

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The Use of Probabilistic AI in Law Enforcement and the Criminal Justice System of England and Wales

Written by Temitope Lawal, Kyriakos N. Kotsoglou, Evdoxia Taka, Marion Oswald, Michele Sevegnani, Muffy Calder


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Government consultation on a new legal framework for law enforcement use of biometrics, facial recognition and similar technologies 

Response from Marion Oswald, Carole McCartney, Kyriakos N. Kotsoglou, Alexandra R. Taylor, Muffy Calder, Jennifer Ekene Dunkwu, Mackenzie Jorgensen, Evdoxia Taka, Temitope Lawal, Claire Paterson-Young, Katherine Jones, Adrian Weller, Kyle Montague


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Don’t Let AI Do the Policing: Findings from a Multi-Stakeholder Workshop on Evaluating Large Language Models for Policing

Don’t Let AI Do the Policing: Findings from a Multi-Stakeholder Workshop on Evaluating Large Language Models for Policing


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Responsible AI in criminal justice: LLMs in policing and risks to case progression

Excited to share our new paper on arXiv! There is growing interest in the use of Large Language Models (LLMs) in policing, but there are potential risks. We have developed a practical approach to identifying risks, grounded in the policing and legal system of England and Wales. We identify 15 policing tasks that could be implemented using LLMs and 17 risks from their use, then illustrate with over 40 examples of impact on case progression. As good practice is agreed, many risks could be reduced. But this requires effort: we need to address these risks in a timely manner and define system wide impacts and benefits.


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Mapping the Probabilistic AI Ecosystem in Criminal Justice in England and Wales – Interim Report

The paper sets out a systematic mapping framework for identifying and characterising probabilistic AI tools across stages of the criminal justice system in England and Wales, focusing on how systems consume and produce probabilistic data, their purposes, and their institutional deployment contexts


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Government consultation on a new legal framework for law enforcement use of biometrics, facial recognition and similar technologies

Response from Marion Oswald, Carole McCartney, Kyriakos N. Kotsoglou, Alexandra R. Taylor, Muffy Calder, Jennifer Ekene Dunkwu, Mackenzie Jorgensen, Evdoxia Taka, Temitope Lawal, Claire Paterson-Young, Katherine Jones, Adrian Weller, Kyle Montague


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Centre for Responsible AI

The Northumbria Centre for Responsible AI brings together the University’s multidisciplinary expertise in citizen-centred AI to focus on how AI should be used in education, government, industry, and wider society. We promote and develop an understanding of AI’s strengths and limitations, how it can be used effectively and responsibly and how it could be harmful or misleading. Our focus is on the application of AI in real contexts. The Centre aims to ensure that technology serves everyone, with no one left behind.



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Responsible Ai UK

Responsible Ai UK (RAi UK) is an international ecosystem for responsible AI research and innovation. RAi UK brings together researchers to understand how we should shape the development of AI to benefit people, communities and society.




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PROBabLE Futures

PROBabLE Futures (Probabilistic AI Systems in Law Enforcement Futures) is a four-year, £3.4M RAi funded Keystone Project led by Northumbria University with Glasgow, Northampton, Leicester, Newcastle and Cambridge Universities.

Our project, working alongside our law enforcement, third sector and commercial partners, is developing a framework to understand the implications of uncertainty and to build confidence in future Probabilistic AI in law enforcement, with the interests of justice and responsibility at its heart. Activities include mapping the AI ecosystem in law enforcement, including the use of large language models; developing guidance, checklist and frameworks to guide assessment of scientific and legal validity, and mock trials with AI outputs as evidence.

PROBabLE Futures is supported by the Engineering and Physical Sciences Research Council [Grant Number EP/Y009800/1 AI KP0003] through funding from Responsible AI UK

When AI Enters the Criminal Courts—Two Mock Jury Trials from the PROBabLE Futures Project

By Dr Angela Paul, Dr Elizabeth McClory-Tiarks, Dr Kyriakos Kotsoglou, Professor Marion Oswald, and Dr Mackenzie Jorgensen

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PROBabLE Futures hosts workshop on ‘AI in Law Enforcement: Lessons from the Past and Priorities for the Future’

Dr Angela Paul and Dr Temitope Lawal

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Ethical Governance, Responsible Innovation and Human Flourishing

By Dr Jennifer Ekene Dunkwu

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Principal Investigator

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