Legal

The AMELR workshop focuses on Legal Argument Mining (LAM) - using NLP to automatically detect legal arguments. Recent developments in NLP and LAM have provided legal scholars with a powerful tool for studying reasoning patterns, interpretative theories, and biases across jurisdictions and legal systems. The workshop gathers experts in computer science, AI & Law, legal theory, and empirical legal studies to address key challenges of LAM: creating training datasets, developing reliable models, establishing reproducibility standards, and integrating LAM into legal research. The workshop aims to strengthen the emerging field of LAM and its role in empirical legal studies by sharing latest implementations, addressing core challenges, and establishing best practices.

The ASAIL workshop series and interest group serves as a platform for researchers and practitioners working on natural language processing of legal text. Its goals include (i) Organising regular peer-reviewed workshop events for presentation and discussion of research and practical implementations around legal NLP; (ii) Facilitating communication and collaboration among academic researchers as well as practitioners from industry, government, and the public sector, and other interested individuals and organisations; (iii) Providing an entry point into the research field and community.

🏆 Awarded the “Peter Jackson” Award for Best Innovative Application Paper

PRIMA (PRivacy Infringements Machine-Advice) studies the law and practice of privacy policies, develops methods and techniques for their automated analysis, and implements a prototype to assess their lawfulness.