Module:

Human vs. Machine: (Un-)Biased Legal Decision-Making?

Type

Seminar

Course Number:

         2400177

Human vs. Machine: (Un-)Biased Legal Decision-Making?  

Module Responsible:

T.-T. Prof. Frederike Zufall

Head of research group (Professor)

Program of Study:

Master Informatics; B.Sc. / M.Sc. Business Informatics

Area of Specialization

Master Informatik: Ergänzungsfach Recht

Master Wirtschaftsinformatik: Seminar aus Rechtswissenschaften

Master Computer Science: Seminar: Law and Legal Studies

For Master modules only

Recurrence

Winter term

Duration

One term

Academic Level
1 - 4:

Level 4: Master Program of Study

Credit points =  ECTS

3 ECTS

We usually have a module for each course (lecture, seminar, practical course).

Language:

English

Competency Goals:

Students acquire basic knowledge of economic theory and its application to public institutions (public choice theory). They learn to identify different types of cognitive biases that influence human behavior. As a result, students understand the implications of these biases for public decision-makers as well as for citizens as recipients of public action. Conversely, they also comprehend how the law can be designed to steer or influence human behavior (behavioral public law).

Students will be able to assess how automation processes can mitigate undesirable biases, or intentionally incorporate them where such biases are desirable from a public interest perspective.

Content:

This seminar provides an overview of the foundational principles of behavioral economics and their relevance to public law. Special attention is given to (biased) decision-making, both from a substantive and procedural perspective. Students will explore how regulation should be designed to account for cognitive biases and achieve intended policy outcomes. In addition, the seminar will address the role of automated decision-making systems - examining how such systems are influenced by, and may also reinforce or mitigate, behavioral biases.

The seminar will cover the following topics:

·    Introduction to (behavioral) economic theory and its application to law

·    Cognitive biases and their impact on (public) decision-making

·    Different types of regulation in light of behavioral insights

·    Implications for automated decision-making systems

·    The role of human biases in the AI Act

Workload

Annotation:

Algorithmic decision-making is often treated as a black box—something that should not be permitted to make decisions in legal contexts. In response, Article 14 of the EU AI Act requires high-risk AI systems to be designed in such a way that they can be effectively overseen by natural persons. This human-in-the-loop requirement stems, among other things, from the perception that AI systems operate ambiguously and produce decisions that are not fully comprehensible.

However, treating humans in comparison as fundamentally transparent or fully rational decision-makers is equally naïve. Understanding how people actually behave—not just how they should behave—is essential for designing effective, fair, and legitimate legal systems. Traditional legal research often assumes rational actors, yet behavioral research shows that cognitive biases, heuristics, and emotional influences shape the decisions of both citizens and public officials.

This seminar addresses that gap by equipping students with behavioral insights to critically assess and improve legal and administrative. A particular focus is placed on how human biases are already embedded in the data underlying automated decision-making systems, potentially reproducing or amplifying unfairness. At the same time, students will explore how such systems can be intentionally designed to mitigate behavioral distortions and support better decision-making.

Prerequisites:

This seminar is interdisciplinary and suitable for students with an interest in behavioral economics, policy design, and governance. Prior legal knowledge is helpful but not required.

Competency certificate:

The assessment of this course is carried out by the following aspects, which will be considered in the grading (§ 4 Abs. 2 Nr. 3 SPO):

·         Term paper (approx. 5 pages),

·         Presentation (approx. 20 min.) and

·         Discussion participation.

The grading scale will be announced in the course. Students may redraw from the examination during the first two weeks after the topic has been communicated.

If the assessment is an examination of another type, the deadline for redraw must be set. These partial achievements can only be repeated once and are to be graded.

Course works are not graded and can be repeated indefinitely, if not otherwise specified.

Recommendations:

.

1. Termin:  13.11.2025 9:00-15:00 Uhr (Seminarrum Nr. 313, bei uns am Institut)

2. Termin:  05.02.2025 9:00- 16:00 Uhr  (Seminarrum Nr. 313, bei uns am Institut).