Jeremy Barnett¹, Fredric Lederer², Philip Treleaven¹, Nicholas Vermeys³, John Zeleznikow⁴

¹University College London, ²William & Mary Law School, ³University de Montreal, ⁴La Trobe University

This is a summary of a full paper available on SSRN by clicking here.

The rapid adoption of new forms of AI and emerging technologies in courts is transforming criminal and civil trials and can be beneficial to all stakeholders. However, the use of Judicial algorithms raises existential issues around the future of the legal system, not least ‘can/should computers replace or merely supplement Judges’ decisions?’

We recognise that there is an explosive growth in LawTech, but wish to concentrate on the use by the Judiciary (and those conducting tribunals and ADR) where unfairness may arise.

We define JudicialTech as Artificial Intelligence (AI) and emerging technologies’ systems for Judges, courts and other forms of dispute resolution. JudicialTech is about supporting the Judiciary, enhancing access to Justice, and potentially increasing fairness in the Judicial system. However, the introduction of new technology needs to be controlled by the Judiciary, to maintain public confidence in the legal system and Rule of Law.

We consider the following stages of the Judicial process.

• Litigation advice – recommender systems for locating relevant legal firms/counsel and to forecast the chance of success in a civil or criminal case.
• Trial preparation – pre-trial discovery and evaluation of documents.
• Judicial guidance– legal analytics tools to analyze documents and to provide insights on courts, Judges, lawyers, law firms, and parties.
• Pretrial negotiations – negotiations taking place in all forms of litigation, either formally or informally.
• Digital courts and tribunals – providing digital technology for all stakeholders to access information remotely, as well as communicate and collaborate online.
• Judicial algorithms – AI algorithms used to support the Judges, courts and tribunals.

JudicialTech is impacted by a range of issues: firstly, by proactive, technologically augmented, policing; secondly the increasing use of digital evidence (e.g., CCTV and social media); thirdly misleading or inaccurate legal submissions being prepared by generative AI; fourthly the rise of sophisticated algorithms and avatars; fifthly, public debate around algorithmic bail and sentencing decisions; finally, the impending explosion and industrialization of cybercrime, in particular crypto-frauds which are often based in remote offshore locations with jurisdiction and regulatory uncertainty (Treleaven et al, 2023).

We recognize that there could be benefits especially with regard to access to justice and ‘levelling the playing field’ if AI becomes commonplace but have concerns around certain forms of unregulated Judicial algorithms negatively impacting the Rule of Law. We consider the advantages and disadvantages.  Of particular concern is the concept of the ‘Robo Judge’ so in the paper we consider the question ‘Can/Should computers replace Judges?’

As a conclusion, we make recommendations around JudicialTech innovation.. The paper recognizes that there is clear scope for the Judiciary to use emerging technology to support their decision making and to create efficiency savings, which in turn can promote access to Justice. Claims that algorithmic decision-making is ‘better’ in terms of reduced bias and increased transparency, risks erosion of the principle that legal decisions should be made by humans.

• Knowledge-transfer – raising awareness amongst stakeholders of JudicialTech AI and emerging technologies. This might involve workshops, or a web portal presenting JudicialTech products.
• Experimentation – working with universities and startups to develop JudicialTech proof of concept (POC) systems. This can be a great source of research projects for both law and technology students.
• Predictive analytics – the use of AI algorithms to analyze massive amounts of information covering litigation advice, trial preparation and Judicial analytics.
• Sandboxes – provide a JudicialTech testing environment where new or untested technologies and software can be trialed and monitored securely.
• Tech sprints – essentially hackathons, coding events that bring programmers and other interested people together to drive innovations.
• Horizon scanning – detecting early signs of potentially important developments through a systematic examination of potential threats and opportunities, with emphasis on new technologies.

The principal recommendation of the paper is that

‘to protect the Rule of Law, there should be a presumption against the use of Judicial decision-making algorithms in conventional criminal and civil litigation unless the technology has completed a robust appraisal and testing regime which must be supervised by the Judiciary’

The Authors

Jeremy Barnett is a practicing Barrister specializing in fraud and regulatory law. He is Honorary Professor of Algorithmic Regulation at University College London.

Fredric Lederer is a Chancellor Professor of Law and Director of the Center for Legal and Court Technology and Legal Skills at William & Mary Law School. He is a former prosecutor, defense counsel, trial judge, and court reform expert, a pioneer of virtual courts.

Philip Treleaven is UCL Professor of Computer. Twenty-five years ago his research group developed much of the early financial fraud detection technology and built the first insider dealing detection system for the London Stock Exchange. (Treleaven is credited with coining the term RegTech.)

Nicholas Vermeys is Professor at the Université de Montréal), the Director of the Centre de recherche en droit public (CRDP), Associate Director of the Cyberjustice Laboratory, and a member of the Quebec Bar.