Teaching at the Professorship of Cyber Trust

Course Instructor: Prof. Jens Grossklags, Ph.D.
Teaching Assistants: Severin Engelmann, 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: Friday, 9:45 - 11:15h, room 2750 (Karl Max von Bauernfeind-Hörsaal), TUM Central Campus
Exercise: 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.
Teaching assistant: Mo Chen, 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: 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: Prof. Jens Grosklags, Ph.D.
Teaching assistant: Emmanuel Syrmoudis

Description:
The seminar explores the nascent and growing field of the economics of privacy and cyber security and related security/risk governance aspects. Personal information has become a primary economic good for legitimate companies and is collected for countless purposes. For example, targeted advertisements, personalization and price discrimination are enabled by the automated wholesale accumulation of users’ trails; online and offline. Given this background, the key objective of the seminar is a better understanding of the current and future marketplace for personal information. We will draw on methods from computer science as well as the economic and behavioral sciences to contribute to a rigorous comprehension of the challenges and solution approaches for current privacy and security challenges.

SPECIAL FOCUS TOPIC SUMMER 2023: In this seminar, we will focus on an economic response to the growing abuse of (browser and device) fingerprinting techniques in the online advertisement space to complement the engineering-oriented view on the problem. Seminar theses will focus on assessing the state-of-the-art of fingerprinting techniques, on a conceptualization of monetization approaches in the context of fingerprinting, on evaluating the initiatives from large stakeholders (e.g., Apple, Google) to address fingerprinting, and other solution approaches.

Course objectives:

Students are expected to deliver a concise report and a comprehensive presentation about their findings. The exact timeline will be discussed in the introductory sessions. The formation of teams is possible with approval by the instructor.

Requirement:
No specific knowledge required. General interest in interdisciplinary privacy and security topics highly desirable. The seminar language is English.

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

^{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: 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.

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

Note:
The kick-off meeting will take place on Friday, April 21, 2023 in room 00.13.054 (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 (in person).

^{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

Description:

First, the proposal for the AI Act will be discussed together in the seminar. Students will learn to understand the structure of the proposal and how to interpret it, so that they can later engage in legislative analysis. Participants will also learn about the context of the EU’s draft AI Act, legislative processes of the European Union and where the draft AI Act is currently at. Furthermore, the concept of datasheets and model cards as well as checklists will be introduced.

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 presentations serve to develop a reader that participants can later consult. 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 within the AI Act’s high-risk categories, as most AI Act requirements apply to these technologies. Students will develop a regulatory compliance plan or technical documentation (tbd), 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 by developing an appropriate checklist or datasheet. They will present their analysis 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 in legislative analysis. For group work, the goal is to bring together students from the Informatics & Mathematics 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.

Deliverables
_ 2 Presentations (English; two brief 7 min presentations + 5 min discussion each)
_ Written Group Report (English; ~ 5 pages per student)

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

Notes:

Participation is reserved for students from the Governance Department (50%) and Informatics & Mathematics Department (50%).

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

^{We are happy to prioritize students who briefly express their motivation by emailing chiara.ullstein@tum.de (please note that we do not have any influence on the final selection of students by the matching tool other than prioritization). Both GOV- and Math/Informatics-Students should apply via the matching system and email Chiara if he or she likes to be prioritized.}

A virtual pre-course meeting is planned for January 26, 2023 at 09:30 am
^{Link: https://tum-conf.zoom.us/j/67164445872?pwd=aDRLTE8yTng1bk12RmV0K3ZRbW5Fdz09
Meeting-ID: 671 6444 5872
Kenncode: 761181}

The kick-off meeting will be on Wednesday, April 19, 2023, 13:00-16:00 in room 01.13.007.
Regular seminar meeting is planned for Wednesday afternoon, 13:00-16:00 in room 01.13.007 (in person).

^{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.