Responsible AI in criminal justice: LLMs in policing and risks to case progression
This addresses risks in criminal justice systems for policymakers and practitioners, but it is incremental as it focuses on identification rather than novel solutions.
The paper tackles the problem of potential risks from using Large Language Models (LLMs) in policing, specifically in England and Wales, by developing a practical approach that identifies 15 policing tasks and 17 risks, illustrated with over 40 examples of impact on case progression.
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.