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.
Law, Artificial Intelligence, Discrimination and Bias, Algorithmic Decision-Making, Responsibility, Safety, European Law, Privacy, Data protection, Dignity.
Law, Public Policy, Engineering, Philosophy.
The integration of artificial intelligence (AI) technologies in society is accelerating. AI-based systems can be software-based, acting in the virtual world mainly with some physical support, such as voice assistants like Alexa or Google Home, image analysis software used for diagnoses, recommendation systems for mortgages, crime, or patient management, search engines, or speech and face recognition systems. AI can also be embedded in more complex hardware devices that operate in the environment, such as advanced robots, self-driving cars, drones, or Internet of Things applications.
The High-Level Expert Group on Artificial Intelligence appointed by the European Commission defined AI as 'systems that display intelligent behavior by analyzing their environment and taking actions – with some degree of autonomy – to achieve specific goals.' These technologies process vast amounts of data, can learn from experience and self-improve their performance, which challenges the applicability of existing regulations that were not designed for progressive and adaptive AI. Since the automated processing of data that will evaluate, analyze, and predict outcomes that may affect the privacy, safety, or dignity of individuals, there is a growing interest in understanding what are the legal and regulatory implications of the use of AI in society.
In this course, we first map the latest advances in AI, including predictive policy, face recognition, personalized diagnosis, early disease detection drug discovery, algorithmic decision-making used in courts, and government. We then identify what the main regulatory initiatives revolving around AI technologies in the European Union are, including the Ethics Guidelines from the European High-Level Expert Group on Artificial Intelligence. During the course, we will focus on the benefits but also the particular challenges revolving around the deployment of AI, including, transparency and explanation (following the European General Data Protection Regulation); potential discrimination scenarios and exacerbation of existing biases; the construction of responsibility in highly automated environments; and the blurring of well-established concepts such as safety, in the context of AI and interconnected products. We will explore solutions and also learn how to assess the risk posed by these technologies via the use of impact assessments. We close the course reflecting on the long-term consequences of AI, the added value this brings to society, and how the law should balance innovation and user rights protection in the context of AI.
Objectives of the course
The course Law and Artificial Intelligence has five main objectives: ● Learn about emerging AI technologies, applications, and benefits. ● Identify the main challenges of AI are from legal and regulatory perspectives. ● Map the regulatory initiatives revolving around AI in Europe and the world. ● Assess the legal and ethical risks posed by AI through different law fields. ● Think critically about the deployment of AI in society.
Upon successful completion of this course, students will: ● 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.
This knowledge should equip students with 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.
Mode of instruction
Number of (2 hour) lectures/seminars: 10
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 attendance is mandatory. Registration is required (in MyStudymap/Usis all interactive lectures are mentioned as working groups).
Group work (35%)
Final exam (65%)
The assignment is obligatory. The weighted final grade must be at least a 5.5. Only the final (online) exam can be retaken: the grade for the assignment remains valid for the retake.
The grades for the group work and the final exam are no longer valid once the academic year has ended.
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. 126.96.36.199 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. To retake a passed exam, students need to ask the Student Administration Office (OIC) for permission. For more information, go to 'course and exam enrollment' > 'permission for retaking a passed exam' on the student website.
Obligatory course materials
- All required readings are available via Brightspace in week-by-week folders
Course information guide:
- See Brightspace
Recommended course materials
- See Brightspace
SCheck the website under “course and exam enrollment” for information on how to register for the course.
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.
Coordinator: Eduard Fosch Villaronga
Institute: eLaw Center for Law and Digital Technologies
Department: Interdisciplinary Study of the Law (Metajuridica)
Telephone number secretary: 071 – 527 8838
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.
In case of (corona)restrictions imposed by the government, this course description is subject to change.