The purpose of this conference is to structure a conversation on both the fundamental and practical issues of legal data mining between scholars from AI, law, and logic. The fast development of machine learning and data mining has opened new opportunities and challenges for automated processing of legal materials and legal analytics. AI techniques are increasingly being developed in law to help lawyers, in house counsels, prosecutors and judges carry out their jobs, while commercial software and other LegalTech offer wide support for legal and regulatory tasks. However, current data mining, machine learning and visualisation techniques show limitations such as explanation generation, understanding of legal materials and argumentation. The workshop will explore the specific technical challenges from data mining and AI techniques addressing together practical and legal theoretical issues. It is an opportunity for computer scientists to showcase and explore in conversation with legal scholars further developments in AI and data mining applied to the legal domains. Legal academics specializing in the interface of law and AI are given the opportunity to articulate the challenges of automated functions in law including natural language processing applied to law, information extraction from legal databases and texts and data mining applied for legal analytics.

Conference Convenors

  • David Restrepo Amariles, HEC Paris (France)
  • Ken Satoh, National Institute of Informatics (Japan)

Conference Academic Contact

Delphine Dogot

Postdoctoral Research Fellow, HEC Paris (France)

Email : dogot@hec.fr

Conference Scientific Committee & Publications

  • Michalis Vazirgiannis, Ecole Polytechnique  (France)
  • Gregory Lewkowicz, ULB (Belgium)
  • Karim Benyeklef, Université de Montreal (Canada)
  • Kevin Ashley, University of Pittsburgh (United States)
  • Arnaud van Waeyenberge, HEC Paris (France)

Conference Administrative Contact

Olfa Mzita

Email: mzita@hec.fr

The conference is powered by the SmartLawHub