Teaching at the Professorship of Cyber Trust

Course Instructor: Prof. Jens Grossklags, Ph.D.
Teaching Assistants: Chiara Ullstein

The lecture offers an overview regarding the role of IT in society. Particular emphasis is given to the complex interactions between modern information and data analytics technologies and individual and societal privacy, and the safety and security of data of individuals and organizations. In addition, the economic impact of IT and the regulation of the impact of IT will be discussed (on concrete cases).

The lecture will primarily consist of a presentation. Opportunities for discussion and questions will be provided. The practice session will be used to further deepen the understanding of the lecture contents and will offer additional opportunities for discussion.

Lecture: Monday, 14:00 - 16:00, room 8120.EG.001 (Hörsaal im Galileo), TUM Campus Garching
Exercise: Monday, 16:00 - 18:00, room 8120.EG.001 (Hörsaal im Galileo), TUM Campus Garching

Note: Information and materials will be made available via Moodle.

TUM Online: Course Description

Course Instructor: Prof. Jens Grossklags, Ph.D.
Teaching assistants: Michel Hohendanner

The lecture covers a diverse range of topics to address challenges in the area of information management for digital business models. We will further address issues related to organizing and leading Information management, and practical aspects of information management in companies and organizations.

The module consists of lectures and accompanying exercises. Key content is delivered in presentations during the lecture and partly during exercise sessions. Exercises address specific questions and engage students with different types of learning activities including studying specialist literature and researching reference materials. As part of the exercises, participation in module-relevant empirical research projects may be offered.

Lecture with integrated exercises: Tuesday, 09:45 - 13:00, room 0509.EG.980 (Audimax, Werner-von-Siemens-Hörsaal), TUM Central Campus

Note: Information and materials will be made available via Moodle.

TUM Online: Course Description

Course Instructor: Michel Hohendanner

Slides virtual pre-course meeting

Description:

AI technologies are not developed or deployed in a vacuum; they affect a broad spectrum of social, economic, and ethical realms. As AI technologies increasingly permeate various societal sectors, it is crucial for future developers to understand the ethical, legal, and social dimensions of their work. By involving a wide range of stakeholders, including technologists, policymakers, ethicists, business leaders, civil society, laypeople, and others, participation may help ensure that AI development and AI governance are well-informed and reflect ethical and societal values.

The seminar “AI Ethics and Society” aims to familiarize students with (participatory) approaches to AI ethics and explore ways of socially just research and development in AI. The seminar puts a particular focus on discussing problems of future-readiness of AI ethics, or how future-readiness can be achieved for AI ethics: Specific methodologies will be introduced and discussed, such as foresight or futuring, i.e., practices that strategically discuss alternative future developments to highlight measures towards desirable developments or to create agency for stakeholders within socio-technical systems.

Together with the seminar “AI Governance and Society”, this seminar will invite experts to talk about topics ranging from AI ethics and responsible AI over participatory AI to the EU AI Act. These talks, together with input by the instructors, will provide students with both theoretical and practical approaches to AI ethics and governance. They cover principles such as fairness, accountability, and transparency, and explore the role of diverse stakeholders in AI lifecycles. Thereby, methods for engaging communities and ensuring that AI solutions reflect a wide range of perspectives and needs will be highlighted.

Building on this input, students further explore the current AI application landscape focusing on the social and ethical dimensions and impact: Teams of students select a particular social and ethical issue related to the current AI application landscape and develop a strategy or suggestions on how (participatory) AI ethics could be a means to ensure or contribute to socially just development today and in the future. Teams will first present a proposal in the seminar. Then, student teams develop their work in the form of a seminar paper and receive feedback in joint feedback sessions. At the end of the seminar, they will give a presentation of their work and hand in a seminar paper.

The seminar will put an explicit focus on AI ethics (in distinction to the seminar “AI Governance and Society”, which focuses on AI governance).

Course objectives:

Understand how AI ethics and participation in AI research and development can be beneficially applied. Reflect on the capabilities, risks and ethical dimensions of current AI technologies. Develop AI ethics driven strategies to work towards socially just AI development. Become familiar with the analysis, critical reading, and application of academic text.

Deliverables
- Active participation (reflection exercise, participation in discussions, engagement with reading list)
- Seminar Paper written as group work (English; ~3000 words per student) and presentation of seminar paper

Requirement:
Interest in Digital/AI ethics and social impacts of AI; Interest in participatory approaches in AI research and development;

Requirement for participation are high commitment to collaborating on a group project and high dedication to self-learning.

IMPORTANT:

• Application via http://docmatching.in.tum.de/
• Information and materials will be made available via Moodle

A virtual pre-course meeting is planned for Tuesday, February 3, 2026, 17:00 - 17:15h

Regular seminar meeting is planned for Tuesday afternoon in person. 

Planned course timeline (tbc):
Tue, 14.04.26, 15:00 - 18:15: Input / Guest Talk 
Tue, 21.04.26, 15:00 - 18:15: Input / Guest Talk
Tue, 28.04.26, 15:00 - 18:15: Input / Guest Talk
Tue, 05.05.26, 15:00 - 18:15: Input / Guest Talk
Tue, 12.05.26, 15:00 - 18:15: Input / Guest Talk / Group Formation / First Seminar Thesis Ideas
Tue, 19.05.26, 15:00 - 18:15: Feedback on Seminar Thesis Ideas
Tue, 26.05.26, 15:00 - 18:15: lecture free (Pfingsten)
Tue, 02.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 09.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 16.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 23.06.26, 15:00 - 18:15: Finalization of Seminar Thesis (no feedback session)
Tue, 30.06.26, 15:00 - 18:15: Final Presentation of Seminar Thesis

Seminar Room: Kleiner Hörsaal (0505.EG.534)

^{Note: According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.}

TUM Online: Course Description

Course Instructor: Chiara Ullstein

Slides virtual pre-course meeting

Description:

AI technologies are not developed or deployed in a vacuum; they affect a broad spectrum of social, economic, and ethical realms. As AI technologies increasingly permeate various societal sectors, it is crucial for future developers to understand the ethical, legal, and social dimensions of their work. By involving a wide range of stakeholders, including technologists, policymakers, ethicists, business leaders, civil society, laypeople, and others, participation may help ensure that AI development and AI governance are well-informed and reflect ethical and societal values.

The seminar “AI Governance and Society” aims to familiarize students with (participatory) approaches to AI governance and explore ways of socially just research and development in AI. The seminar puts a particular focus on discussing problems of future-readiness of AI governance, or how future-readiness can be achieved for AI governance: Specific methodologies will be introduced and discussed, such as foresight or futuring, i.e., practices that strategically discuss alternative future developments to highlight measures towards desirable developments or to create agency for stakeholders within socio-technical systems.

Together with the seminar “AI Ethics and Society”, this seminar will invite experts to talk about topics ranging from AI ethics and responsible AI over participatory AI to the EU AI Act. These talks, together with input by the instructors, will provide students with both theoretical and practical approaches to AI ethics and governance. They cover principles such as fairness, accountability, and transparency, and explore the role of diverse stakeholders in AI lifecycles. Thereby, methods for engaging communities and ensuring that AI solutions reflect a wide range of perspectives and needs will be highlighted.

Building on this input, students further explore the current AI application landscape focusing on the social and ethical dimensions and impact: Teams of students select a particular social, ethical, legal issue or initiative related to the current AI landscape and develop a strategy or suggestions on how (participatory) AI governance could be a means to ensure or contribute to socially just development today and in the future. Teams will first present a proposal in the seminar. Then, student teams develop their work in the form of a seminar paper and receiving feedback in joint feedback sessions. At the end of the seminar, they will give a presentation of their work and hand in a seminar paper.

The seminar will put an explicit focus on AI governance (in distinction to the seminar “AI Ethics and Society”, which focuses on AI ethics).

Course objectives:

Understand what the AI governance and participatory AI is about and how it influences the development of AI systems. Reflect on the capabilities, risks and ethical dimensions of current AI technologies. Develop AI governance strategies to work towards socially just AI development. Become familiar with the analysis, critical reading, and application of academic text.

Deliverables
- Active participation (reflection exercise, participation in discussions, engagement with reading list)
- Seminar Paper written as group work (English; ~3000 words per student) and presentation of seminar paper

Requirement:
Interest in AI governance; Interest in participatory approaches in AI research and development;

Requirement for participation are high commitment to collaborating on a group project, high dedication to self-learning.

IMPORTANT:

• Application via http://docmatching.in.tum.de/
• Information and materials will be made available via Moodle

A virtual pre-course meeting is planned for Tuesday, February 3, 2026, 17:00 - 17:15h
Zoom Link: https://tum-conf.zoom-x.de/j/9366159409?pwd=dXF2VURzNlI3Nm9lQnNrUEl0ekZKQT09
Meeting-ID: 936 615 9409
Code: 194415

Regular seminar meeting is planned for Tuesday afternoon in person. 

Pre-course meeting: Date: 03.02.2026, 17:00-17:15

Planned course timeline:
Tue, 14.04.26, 15:00 - 18:15: Input / Guest Talk
Tue, 21.04.26, 15:00 - 18:15: Input / Guest Talk
Tue, 28.04.26, 15:00 - 18:15: Input / Guest Talk
Tue, 05.05.26, 15:00 - 18:15: Input / Guest Talk
Tue, 12.05.26, 15:00 - 18:15: Input / Guest Talk / Group Formation / First Seminar Thesis Ideas
Tue, 19.05.26, 15:00 - 18:15: Feedback on Seminar Thesis Ideas
Tue, 26.05.26, 15:00 - 18:15: lecture free (Pfingsten)
Tue, 02.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 09.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 16.06.26, 15:00 - 18:15: Feedback on Seminar Thesis Progress
Tue, 23.06.26, 15:00 - 18:15: Finalization of Seminar Thesis (no feedback session)
Tue, 30.06.26, 15:00 - 18:15: Final Presentation of Seminar Thesis

Seminar Room: Kleiner Hörsaal (0505.EG.534)

^{Note: According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.}

TUM Online: Course Description

Course Instructor: Carmen Löfflad, Ph.D.

SPECIAL FOCUS SUMMER 2026
Fairness Perceptions of Automated Decision-Making

SUMMARY
In this seminar, students engage with research on people’s fairness perceptions of automated decision-making (ADM) systems, and their behavioral implications for those affected by ADM systems. All participants work on a shared database with recent literature on fairness perceptions of ADM systems. Participants are first introduced to coding academic articles using a structured framework. Building on this joint, coded database, each team examines a specific topic related to how people evaluate the fairness of ADM systems, and their behavioral implications. The results are presented during the seminar and synthesized in a research report. Each team gives one presentation and hands in one research report. 

DETAILED DESCRIPTION
Algorithms are increasingly used to make automated decisions that affect individuals’ lives. For example, algorithms help make decisions in finance, healthcare, hiring, and public services. These systems can influence whether an individual receives a loan, how risks are assessed, or what kind of service a person receives. An increasing number of studies investigates how people evaluate and react to such systems, specifically, whether people consider these systems fair, and how distinct attributes within automated decision-making, for example, transparency, shape people’s fairness evaluations. However, the findings from this research are still spread across many different studies. In this seminar, we bring insights from these studies together in a structured way. The aim of the seminar is to comprehensively study how people perceive the fairness of automated decision-making systems, how specific attributes shape fairness perceptions, and what behavioral implications distinct fairness perceptions have. To do this, we will jointly review existing research articles and organize them into a broader picture.

No prior research experience is required. The seminar introduces participants step by step to academic literature work. Students will learn how to search for literature, read research articles, classify main ideas, and summarize findings in a structured way. The seminar is based on a structured framework which helps us organize the research. For example, some studies focus on fairness implications of distinct procedures, such as transparency or explainability. Other studies focus fairness implications of outcomes, such as whether a decision benefits or disadvantages someone. Using this framework, we will develop a comprehensive and structured overview of current research on fairness perceptions of ADM systems. 

SEMINAR PROCEDURE
Stage 1: Literature coding
Each team receives a set of research articles. For each article, the team records key information in a shared database, for example, what topic the article covers, which aspect of fairness it addresses.
Stage 2: Descriptive analysis
Using the shared database, students analyze general patterns in the literature. For example: Which fairness issues are studied most often? In which domains is fairness discussed most frequently? How has the focus of research changed over time?
Stage 3: Interpretation and synthesis
Finally, each team works more closely on one part of the framework, reading relevant studies in more detail and summarizing the main insights. Students should identify common themes, differences between studies, and open questions for future research.

Course objectives:

In this seminar, students will learn:
• how to work with academic literature
• how to organize research findings systematically
• how to summarize and compare studies
• how to develop a broader interpretation from many individual articles
• how to work collaboratively on a shared research project

Deliverables: Students are expected to deliver a concise report (English; 3000-4000 words per student in teams of two people) and a comprehensive presentation (10-15min) about their findings.

Requirement:
No specific knowledge required. Strong interest in interdisciplinary work and in reading, understanding, and interpreting quantitative empirical research articles is desirable.

Important:

• Application: 
  🔜 To apply for course participation, please send an email to carmen.loefflad@tum.de by Monday, April 27, 2026. 
  Please include the following information: name, study program and year, matriculation number, transcript of records, short statement on relevant experience and/or motivation, current CV (optional). Applicants will be notified starting from Wednesday, April 29, 2026.
   
• Information and materials will be made available via Moodle

Planned Course Timeline:

1. Kick-off: 8th of May, 2026 from 11:00 am - 1:30 pm -- Seminar overview, introduction, expectations and procedures
2. Meeting: 15th of May, 2026 from 11:00 am - 1:30 pm -- Introduction to coding, distribution of coding tasks
3. Meeting: 29th of May, 2026 from 11:00 am - 1:30 pm -- Discussion of coding results, deciding further thematic focus for each team
4. Meeting: 12th of June, 2026, from 11:00 am - 1:30 pm -- Student presentations of descriptive results, discussion of preliminary findings
5. Meeting: 26th of June, 2026, from 11:00 am - 1:30 pm -- Discussion of progress
6. Meeting: 10th of July, 2026, from 11:00 am - 1:30 pm -- Discussion of progress
7. Final Meeting: 17th of July, 2026, from 11:00 am -- 3:00 pm -- Student presentations of seminar report

⇒ The course meetings will take place in room 01.08.033 (CIT building, Boltzmannstr. 3, Garching)

^{Note: According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.}

TUM Online: Course Description

Weekly group meeting of the Chair of Cyber Trust for members and guests of the chair. The seminar includes research discussions and talks about topics related to the activities of the chair.