Introduction to AI and Law

Kurs otwarty

How do the achievements of artificial intelligence affect theories of legal reasoning? How do tools based on artificial intelligence algorithms help us in legal practice?

Zapisz się
  • Uniwersytet Jagielloński
  • AI&L
  • 10  wykładów
  • Kurs otwarty
  • 31 marca 2023

O kursie

The second edition of the course started on January 3, 2023!

The course addresses the field of artificial intelligence and law, i.e. the study of the possibilities of using algorithms in legal practice. The lecturer explains, among other things, what the first programs were that assisted the decision-making process of lawyers, what case-based reasoning is as well as outlines the importance of contemporary research in the area referred to in the literature as AI and Law.

Instructor

Michał Araszkiewicz - Ph.D. in law, assistant professor at the Faculty of Law and Administration of the Jagiellonian University. Author of dozens of publications in renowned periodicals in Poland and abroad in the field of interpretation of law, impact of new technologies on lawmaking, legal informatics, artificial intelligence.

The recording, production, graphic design and translation of the course, as well as the adaptation of the Copernicus College platform, were carried out as part of the project "Digitalized! Society in the Age of the Digital Revolution," implemented at the Jagiellonian University from 2019 to 2022. The project was funded by the National Agency for Academic Exchange under the Academic International Partnerships program; contract no: PPI/APM/2019/1/00016/U/00001.

The content of the course was funded from the budget of the Priority Research Area "Society of the Future" within the framework of the funds allocated to the Jagiellonian University under the "Excellence Initiative" program.




Program

  1. Computational modeling of law and legal reasoning
  2. Logical models of statutory law
  3. Case-based reasoning models
  4. Argumentative models
  5. Legal ontologies and the semantic web
  6. Machine learning and neural networks
  7. NLP
  8. Coherence
  9. Contemporary challenges
  10. The challenges of the future
  11. Brak egzaminu