Teaching at the Professorship of Cyber Trust

Course Instructor: Prof. Jens Grossklags, Ph.D.

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 (planned): Friday, 9:45 - 11:15h, room 2750 (Karl Max von Bauernfeind-Hörsaal), TUM Central Campus
Exercise (planned): Friday, 8:00 - 9:30h, room 2750 (Karl Max von Bauernfeind-Hörsaal), TUM Central Campus

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

TUM Online: Course Description

Course Instructor: Prof. Jens Grossklags, Ph.D.

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 (planned): Wednesday, 16:45 - 20:00h, room 1200 (Carl-von-Linde-Hörsaal), TUM Central Campus

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

TUM Online: Course Description

Course Instructor: Mo Chen, Ph.D.

Description:

Behavioral insights are “an inductive approach to policy-making combining fundamental insights from psychology, cognitive science, and social science with empirically-tested results to discover how humans actually make choices” (by OECD). There is a trend of governments and organizations applying behavioral insights to public policy to shape and influence behavior. At the same time, the past decade witnessed a global interest in digital tools to influence behavior. Tools driven by the rapidly advancing technology development around big data as well as artificial intelligence (AI) are increasingly integrated in social governance. As a result, behavioral insights can now function as a policy-making tool to utilize the insights generated by big data, and the relationship between behavioral insights and big data is growing ever closer. In the seminar, we will deepen our understanding of behavioral insights in public policy making from an interdisciplinary point of view.

Course objectives:

Understand behavioral insights in public policy making from an interdisciplinary point of view.
Become familiar with the basic concepts and application of nudging in public policy.

Prepare and write a scientific paper (English; 8-10 pages)
Conduct a presentation of your topic (English; 15 minutes + 10 minutes discussion)

Requirement:
Strong interest in interdisciplinary work.

Note:
The kick-off meeting will take place on April 29, 2022 (there will be no preliminary meeting before the kick-off meeting).
Regular seminar meeting is planned for Friday afternoon, between 12.00 and 14.30 every second week (online, via BBB, unless there is a policy change about the pandemic).

TUM Online: Course Description

Application via http://docmatching.in.tum.de/

During recent years, the requirement for secure and privacy preserving computer systems is reaching higher and higher priority. Luckily, a variety of technologies already exist, specifically designed to meet these requirements. However, most technologies were not designed keeping usability in mind. Consequently, important questions arise when integrating and applying these technologies: What are the implications on usability of computer systems? And vice versa, does usability have an impact on security and privacy? Are security and privacy requirements conflicting with (mostly more important) functional requirements? Do these conflicts lead to users rejecting secure systems? Is security and privacy versus usability an unavoidable trade-off? Currently, this trade-off tends to be either over-biased towards functionality and usability, or security and privacy. This seminar explores this problem space and investigates state-of-the-art research on how to rebalance the trade-off. Students will design and execute a study focused on usable security and privacy. Hereby, the focus will be on replicating a previously published work.

Previous Knowledge Expected: Prior experience with qualitative/quantitative research approaches focused on human subjects (e.g., surveys, interviews) as part of coursework or related work experience is highly beneficial. General interest in interdisciplinary security and privacy topics is desirable.

Vorbesprechung/Introductory meeting on Tuesday, March 29, at 17:00.

Access for the video conference:

• BBB Service at TUM Informatics: bbb.in.tum.de/jen-oq1-vds-5a5
• Room Name: Usable Security and Privacy Seminar
• No Access Code

Course Instructor: Chiara Ullstein

Description:

First, the proposal for the AI Act will be discussed together in the seminar. The instructors will help students understand the structure of the proposal and how to interpret it, so that they can later engage in legislative analysis.

Next, students will interpret a provision of the proposal. They will then give presentations describing, in real-world terms, what their provision entails, potential strengths and weaknesses of the rule, and any open questions. The goal of this task is to help students develop legislative analysis skills and understand the policy debates that have taken place about the AI Act.

Finally, groups of students will select an existing AI application for a more in-depth analysis. Selected AI applications would fall into each risk level, mostly, however, within one of the AI Act’s high-risk categories, as most AI Act requirements apply to these technologies. Students will develop a regulatory compliance plan, as if they are responsible for compliance in that application’s company. This will involve determining which provisions apply to the application, identifying the key compliance concerns, and discussing technical, legal, political, economic, and other factors in the compliance plan. They will present their compliance plans as their final presentations and hand in a written analysis.

The goal of the analysis is for future developers and future politicians/ representatives of civil society to learn what the regulatory priorities for AI development in the European Union will be in the future and what impact this will have on the development of AI systems. Students will learn to read and reflect on draft legislations and critically engage legislative analysis. For group work, the goal is to bring together students from the Informatics Department and the Governance Department to foster interdisciplinary discussion.

Course objectives:

Understand what the AI Act is about and how it influences the development of AI systems.
Become familiar with the analysis, critical reading and application of legislative text as well as with the evaluation of AI applications based on the current version of the AI Act.

Presentation (English; splitted into two brief 7 min presentation + 5 min discussion each)
Written Analysis Report/ Paper (Group; English; 8-10 pages)

Requirement:
Interest in AI regulation and/or experience with the development of AI 

Note:

Participation is reserved for students specializing in either politics (50% of participants) or informatics (50% of participants).

IMPORTANT: To apply for course participation, please send an email to chiara.ullstein@tum.de by Thursday, 23. April 2022. Applicants will be notified on Monday, 25. April 2022.

The seminar will take place in the first half of the semester with weekly 3h sessions. Classroom sessions will take place on 03.05, 10.05, 17.05, 13.06, 14.06. The sessions on 24.05 and 31.06 are reserved for group work.

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.