ENLIGHT joint courses

AI and Law

AI systems are being developed at an increasing pace and are already present in virtually every aspect of our lives. There is a consensus that, due to their potential impact, such systems must be carefully regulated. Europe has taken the lead, recently passing the AI Act, the first regulation concerning AI systems in the world. This opens a new scenario where AI and law professionals will have to work together at the different steps of the life cycle of AI systems, from their conception and development to the resolution of any potential problem derived from their use. The first step for a proper collaboration is good communication and understanding, and that requires both kinds of profiles being able to understand the basic ideas behind the others' work.

About the course

Content

The program will have 6 ECTS, divided into three different sections. The first section will include all the profile-dependent introductory knowledge needed for the other two sections. The second section will include the presentation of the challenges that arise both in the AI and the legal domain and the last section will consist of the joint interdisciplinary discussion of real-life situations. In this last section, the students will work in interdisciplinary groups discussing the legal and technical details in real life scenarios.

Learning outcomes

  • Define and explain key AI concepts such as machine learning, deep learning, evaluation of models, etc. 
  • Identify the primary national and international regulatory frameworks related to AI (GDPR, AI Act, etc.). 
  • Analyze the ethical and legal challenges associated with AI development and use (privacy, algorithmic bias, liability). 
  • Identify and analyze the primary technical challenges in AI system development (data quality, interpretability, scalability). 
  • Collaborate with professionals from various disciplines (legal, ethical, engineering) to develop AI solutions. 

Programme

The virtual part of the program will develop the profile-specific introduction and the technical and legal challenges. This part will include asynchronous activities (readings, videos, self-assessment tests, etc.) and synchronous sessions. Also, during the online part, the groups will work on the technical and legal challenges. Although the work in the practical cases will be developed mainly during the onsite part, during the online part the groups will be created, so they can get familiar with the cases. The virtual component will be prior to the on-site part.

The on-site part will take place in in San Sebastián (Donostia).

Assessment

Online tests. These tests will assess the understanding of the basic concepts  

Participation in the discussions. Making, answering, and commenting on questions in both the online forums and the synchronous sessions  

The work in groups will be evaluated both based on the participations observed during the on-site sessions and on the exposition of the results achieved by the group. 

Lecturers

  • University of the Basque Country: Usue Mori, Iñaki Inza, Borja Calvo

  • Universtity of Göttingen: Zully Ritter, Anne Christin Hauschild, Nicolai Spicher

  • University of Ghent: Eva Lievens, Griet Verhenneman, Yvan Saeys

  • University of Uppsala: Andreas Kotsios

Course dates

On-site period: 7–11 April San Sebastián (Donostia).

Online period: 6 January to 14 March.

Please note that the application deadline mentioned below can be different in your home institution.

  • Entry requirements: Bachelor´s Degree level (3rd or 4th year), Master or PhD students with an AI or law profile
  • Courses – Focus area: Digitalisation, Equity
  • Study Field: Science and Technology, Economics and Law
  • Type: blended intensive programme (Erasmus+ funding)
  • Host: University of the Basque Country
  • Course dates: 6 January - 11 April 2025
  • Apply by: 15 November 2024
  • ECTS: 6
  • Number of places available: Students per partner university : 3 with a technical profile (AI related, computer science, maths, etc.) and 3 with a laws profile.
  • Level: Master, PhD