Admission requirements
None.
Note: The course is of interest also to students from the faculties of Governance and Global Affairs (Institute of Security and Global Affairs), Humanities (Institute for Philosophy), and the School of Law.
Description
Topics
Regulation of AI: AI Act, Law, standards, science for AI/robot policy; Algorithmic decisions & fairness; AI & Society: AI applications, generative AI; Discrimination: diversity, equity & inclusion, inferential analytics, gender bias; Algorithmic speech & freedom of expression; Civil responsibility and liability for AI; Criminal liability; Transparency, explainability, & opacity.
Disciplines
Law, Public Policy, Engineering, Philosophy.
Content description
The integration of artificial intelligence (AI) technologies into society is rapidly advancing, reshaping industries, governance, and everyday life. AI-based systems are used in various applications, from automated decision-making in finance and healthcare to predictive policing, algorithmic speech moderation, and generative AI tools like ChatGPT and DALL-E. These technologies process vast amounts of data, adapt over time, and operate with varying degrees of autonomy, raising complex legal and regulatory challenges.
As AI systems increasingly evaluate, analyze, and predict outcomes that impact privacy, safety, and fundamental rights, there is a pressing need to understand their legal implications. The European Union has responded with comprehensive regulatory initiatives, such as the AI Act, the AI Liability Directive, and GDPR, alongside emerging AI standards and ethical frameworks. However, existing legal structures must continuously evolve to address concerns about bias, discrimination, liability, and transparency in AI systems.
This course explores the intersection of law and artificial intelligence, analyzing how AI advancements shape and shape regulatory frameworks. We begin by mapping key AI technologies and their legal implications before delving into the EU's regulatory response, with a particular focus on the AI Act as a cornerstone of AI governance.
Through a series of lectures, we will explore how automated decision-making affects fundamental rights, discussing issues related to freedom of expression, discrimination, workplace automation, and liability attribution. Special attention will be given to transparency and explainability, addressing the challenges of ensuring AI systems remain accountable and fair. Given that AI technologies challenge traditional legal concepts, we will critically examine how legal systems respond to harm caused by AI, assess the fairness of AI-driven decision-making, and explore how law can balance innovation with risk mitigation.
By the end of this course, students will have a comprehensive understanding of AI law, enabling them to critically assess regulatory developments, ethical concerns, and legal disputes in the fast-evolving landscape of AI governance. Through a mix of theoretical insights and real-world case studies, this course will equip students with the tools to engage with AI in a legally sound and socially responsible way.
Course objectives
The course Law and Artificial Intelligence has five main objectives:
Understand emerging AI technologies, their applications, and societal impact.
Analyze the legal and regulatory challenges of AI, with a focus on governance frameworks.
Examine the AI Act’s risk classification system and its implications for AI deployment.
Evaluate legal and ethical risks posed by AI across different legal domains, including liability, data protection, and human rights.
Develop a critical perspective on AI regulation and its role in shaping responsible AI use in society.
Learning objectives
Upon successful completion of this course, students will have the ability to weigh and evaluate the development of specific AI applications, to see where potential regulatory and ethical challenges might arise in their use or deployment, and to learn methodologies to be able to give advice on designing AI technologies in a way that mitigates such issues. In particular:
Understand the basic architecture and operation of AI and the directions in which it will develop in the near future.
Identify and recognize the potential benefits and drawbacks of the deployment of AI.
Learn and understand the fundamental regulatory issues that have emerged in relation to the deployment of AI, and the relevance of design choices in the architecture of AI.
Understand the complexity of the regulatory and policy landscape to address the legal and regulatory issues arising from the use of AI.
Timetable
Check MyTimetable.
Mode of instruction
Lectures
Number of (2 hour) lectures/seminars: 9. Closing lecture/seminar 4 hours.
Names of lecturers: E. Fosch Villaronga and invited lectures.
Required preparation by students: Reading the required materials on Brightspace, submitting one assignment.
Interactive lectures for which registration is required (in MyStudymap/Usis all interactive lectures are mentioned as working groups).
Attendance on all the dates is not mandatory but each session contains essential information to help you prepare for the final exam and the group work
Assessment method
Examination form(s)
Group work (35%);
Final exam (65%).
The group work assignment is obligatory. The group work assignment counts for 35% of the final grade, must be successfully completed with at least a grade of 5.5., and cannot be retaken.
The written final exam counts for 65% of the final grade. The exam must be completed with at least a grade of 5.5. A lower grade than 5.5 in the written exam will make students go for a retake. Only the final exam can be retaken, whereby the assignments and group work grades remain valid.
If the course is not completed with a passing grade within the academic year, any grades obtained for the group work and its assignments will expire by the end of the academic year.
Submission procedures
To be announced through Brightspace.
Areas to be tested within the exam
The examination syllabus consists of the required reading (literature) for the course, the course information guide and the subjects taught in the lectures, the seminars and all other instructions which are part of the course.
Regulation retake passed exams
In this course it is possible to retake an exam that has been passed (cf. art. 4.1.8 and further of the Course and Examination Regulations) on the condition that this course is not part of the minor. Students who have passed the exam may retake the final written assessment (test) of the course if they meet certain requirements. For more information, go to the website > ‘Law’ tab > ‘Retake a passed exam’.
Reading list
Obligatory course materials
Literature:
- All required readings are available via Brightspace in week-by-week folders
Course information guide:
- See Brightspace
Recommended course materials
- See Brightspace
Registration
Registration for courses and exams takes place via MyStudymap. If you do not have access to MyStudymap (guest students), look here (under the Law-tab) for more information on the registration procedure in your situation.
Exchange students have priority and will be registered for the course first. Any remaining seats will be available for students from Leiden University and other Dutch Universities.
Contact
Coordinator: Eduard Fosch Villaronga
E-mail: elaw@law.leidenuniv.nl
Institution/division
Institute: eLaw Center for Law and Digital Technologies
Department: Interdisciplinary Study of the Law (Metajuridica)
Telephone number secretary: 071 – 527 8838
E-mail: elaw@law.leidenuniv.nl
Remarks
Minor students have priority to follow the course, but they are responsible for the registration in MyStudymap/uSis. If minor students do not register on time, this priority will lapse.