Artificial Intelligence and law

The law is a societally important and scientifically rich and challenging application domain of artificial intelligence. Much of my research in this field has been on computational models of legal argumentation. Early work was my my 1997 book (a revised and extended version of my 1993 PhD thesis). Subsequently I developed with Giovanni Sartor a logic for rule-based legal argumentation [Prakken & Sartor 1996]. In this logic the standards for comparing arguments are also debatable. Other topics I have studied are Dialogue game models of legal procedures; see, for instance, my AI & Law Journal article on A formal model of adjudication dialogues and an application of this model in a case study; and Formal modelling of burdens of proof, with Giovanni Sartor, applying our argumentation logic in the context of my work on dialogue models of legal procedure; see e.g. our ICAIL-2007 and JURIX-2011 papers.

My current work in AI and Law focuses on four main themes:

• Modelling case-based and teleological legal reasoning. This work builds on my early work with Giovanni Sartor on formalizing factor-based reasoning with precedents [Prakken & Sartor 1998]. My current work includes a JLC 2015 paper with Adam Wyner, Trevor Bench-Capon and Katie Atkinson on formalising argumentation schemes for legal case-based reasoning in ASPIC+ and an AI & Law 2021 paper A formal analysis of some factor- and precedent-based accounts of precedential constraint.. I believe that this kind of work can help in explaining legal and other machine-learning applications; see e.g. [Prakken & Ratsma 2021].

• AI & Law and autonomous systems. This research line concerns the problem of making autonomous systems behave in a legally and ethically responsible way. See my 2016 position paper on the general problem and my 2017 AI & Law Journal paper on making autonomous vehicles conform to traffic law.

• The computer judge. The recent successes in machine learning have led many in the legal world to believe that the computer judge is near. Some recent algorithms that predict outcomes of legal cases are often cited as evidence. I believe that these expectations are largely based on misconceptions of what such predictive models can do for the law. I have recently (co-)written two papers in Dutch journals about this: Prakken (NJB 2018, English translation) and Bex & Prakken (AA 2020, English translation). With Floris Bex I also have an ICAIL 2021 paper on the relevance of algorithmic decision predictors for judicial decision making, and a JURIX 2021 paper on whether predictive justice can improve the consistency of judicial decision-making. My NJB 2018 paper was cited by the Dutch minister of Justice in a letter to the Dutch parliament. I was interviewed about the 'robot judge' in the Dutch newspaper Trouw.

• Legal reasoning about evidence. See, for example, two articles in Law, Probability & Risk (2004, 2014), my 2004 AI & Law Journal paper with Floris Bex, Chris Reed and Doug Walton on formalising evidential argument schemes, my ICAIL-2005 paper on accrual of arguments, an edited volume on Legal Evidence and Proof: Statistics, Stories, Logic, a recently co-edited special issue of Topics in Cognitive Science on Models of Rational Proof in Criminal Law, and two double PhD projects:
  • Making sense of evidence on software support for crime investigation;
  • Designing and Understanding Forensic Bayesian Networks with Arguments and Scenarios.

Associations, interest groups, resources, blogs, ...

• IAAIL - International Association for Artificial Intelligence and Law
• JURIX - Dutch Foundation for Legal Knowledge-based Systems
• computationallegalstudies.com, by Daniel Katz, Michael Bommarito and John Zelner.
• Legal Text Analytics. A list of selected resources, methods, and tools dedicated to Legal Text Analytics.

Workshops and Conferences

• 35th International Conference on Legal Knowledge and Information Systems (JURIX 2022). Saarbruecken (Germany), 14-16 December 2022.

• 19th International Conference on Artificial Intelligence and Law (ICAIL 2023). Braga (Portugal), 19-23 June 2023.

• International Conferences on Artificial Intelligence and Law (ICAIL).
• International Conferences on Legal Knowledge and Information Systems (JURIX).
• Summer Schools on Law and Logic, Fiesole, Forence (Italy).
• AI & Law Summer Schools. Fiesole, Florence (Italy).
• LEX Summerschools on managing legal sources. Florence/Ravenna (Italy).
• International Workshops on Juris-informatics (JURISIN): 2007-2018, 2019.
• International Conferences on Alternative Methods of Argumentation in Law, Brno, Czech republic: 2011, 2012, 2013.
• Conferences on Fairness, Accountability, and Transparency (FAccT).
• Symposium on Law and Artificial Intelligence: Not a World Apart, Utrecht (The Netherlands), 18 May 2022.
• 1st Workshop on Programming Languages and the Law (ProLaLa 2022), Philadelphia (USA), 16 January 2022.
• AAAI 2021 Symposium on Implementing AI Ethics.
  Palo Alto, CA (USA), 22-24 March 2021.
• MIREL workshop on MIning and REasoning with Legal texts.
  Luxemburg, 17 September 2018.
• Conference on Recent developments in Artificial Intelligence: Law and Justice.
  Montreal (Canada), 27 October 2016.
• ECAI 2016 Workshop on AI for Justice.
  The Hague (The Netherlands), 30 August 2016.
• Workshop Responsible Intelligent Systems in Perspective; where Computer Science, Philosophy and Legal Theory meet
  Utrecht (The Netherlands), 18-19 April 2016.
• Zif Workshop on Models of Rational Proof in Criminal Law.
  Bielefeld (Germany), 28-30 September 2015.
• 2nd International Conference on Quantitative Aspects of Justice and Fairness (QAIJF 2011)
  Fiesole, Florence (Italy), 25-26 February 2011.
• Conference on Graphic and Visual Representations of Evidence and Inference in Legal Settings (conference brochure)
  New York, USA, 28-29 January 2007.
• Workshop `Dialectical Legal Argument: Formal and Informal Models'.
  Tilburg (The Netherlands), 12 December 1996.

Journals

• Artificial Intelligence and Law
• SCRIPTed: A Journal of Law, Technology & Society

Research projects

• Designing and Understanding Forensic Bayesian Networks with Arguments and Scenarios.
• Making sense of evidence.
  • Some press about this project:
    • The Dutch press about Susan van den Braak's PhD thesis on Sensemaking Software for Crime Analysis.
    • The Dutch press about Floris Bex's PhD thesis.
    • Floris Bex's weblog entry for a Cornell law School weblog.

Research Groups, Labs

• Dutch Police Lab AI.
• The Maastricht Law and Tech Lab..
• CODEX: Stanford Center for Computers and Law.

People