Teaching at the Professorship of Cyber Trust

Course Instructor: Prof. Jens Grossklags, Ph.D.
Teaching Assistants: Chiara Ullstein, Mo Chen, 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: Monday, 13:00 - 14:30, room 8120.EG.001 (Hörsaal im Galileo), TUM Campus Garching
Exercise: Monday, 16:15 - 17:45, 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: Mo Chen, Ph.D., Emmanuel Syrmoudis, Chiara Ullstein

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: 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 2024: 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.

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 Wednesday, February 7, 2024 at 14:00.
Zoom Link: https://tum-conf.zoom-x.de/j/64065454346?pwd=bUU2OVdCVStpYUtjWndPRzJBQ3llQT09
Meeting-ID: 640 6545 4346
Code: 420864

Regular seminar meeting is planned for Wednesday afternoon, 14:00 - 16:00 in room 00.08.059 (in person).

^{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: 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/
• Information and materials will be made available via Moodle

The kick-off meeting will take place on Wednesday, April 24, 2024, 12:00 - 14:00 in room 00.13.008 (there will be no preliminary meeting before the kick-off meeting).
Regular seminar meeting is planned for Wednesday afternoon, 12:00 - 14:00 every second week (in person).

^{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

Description:

The seminar aims to familiarise students with the development process of an EU regulation using the AI Act as an example and to convey the contents of the AI Act proposal. By working with the AI Act, students learn to read a legal text and understand what it means for AI to be in compliance with the AI Act.

The seminar is divided into two phases:
1) In the first phase, the AI Act proposal will be discussed in the seminar. Students will learn to understand the structure of the proposal and how to interpret it such that they can later engage in legislative analysis. Participants will also learn about the context of the EU’s draft AI Act, the legislative processes of the European Union, and where the draft AI Act is currently at. Furthermore, the concept of datasheets, model cards, and checklists will be introduced. Students will then give presentations describing what selected provisions entail, potential strengths and weaknesses of the rule, and any open questions. The presentations serve to develop a reader that participants can later consult. This task aims to help students develop legislative analysis skills and understand the policy debates about the AI Act that have taken place.
2) In the second phase, groups of 4 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 requirements apply to these technologies. Students will develop a technical documentation as if they were responsible for compliance in that 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 documentation, checklist, or datasheet. They will present their analysis as their final presentation 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 legislation 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 10 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.}
• Information and materials will be made available via Moodle

A virtual pre-course meeting is planned for Wednesday, February 7, 2024, 11:00 - 11:30 am
Zoom Link: https://tum-conf.zoom-x.de/j/64483283077?pwd=dlFnMWdHekt1bENZSGJrUGt0RExPdz09
Meeting-ID: 644 8328 3077
Code: 023308

Regular seminar meeting is planned for Wednesday, 10:00 - 11:30 in room 01.08.033 (in person).

^{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

Description:

The seminar aims to familiarise students with the EU AI Act (artificial intelligence regulation) and explore how participatory AI can help operationalize selected provisions of the EU AI Act. By working with the AI Act, students learn to read a legal text, understand what it means for AI to be in compliance with specific provisions of the AI Act, and familiarize themselves with approaches to participatory AI. Participatory AI can play a critical role in operationalizing AI regulation by fostering an inclusive framework that draws on diverse stakeholders' collective expertise, values, and perspectives. This approach can be perceived as valuable because AI technologies are not developed or deployed in a vacuum; they affect a broad spectrum of social, economic, and ethical realms. By involving a wide range of participants, including technologists, policymakers, ethicists, business leaders, civil society, laypeople, and others, Participatory AI may help ensure that AI development and AI governance are well-informed and reflect societal values. The exploration of approaches to Participatory AI to meet selected Articles of the EU AI Act is the focus of this seminar. The seminar is divided into two phases: 1) In the first phase, the EU AI Act and Participatory AI will be introduced. Students will learn to understand the structure of the proposal and how to interpret it. As part of the introduction to the AI Act, participants will also learn about the context of the EU AI Act, the legislative processes of the European Union, and where the draft AI Act is currently at. Participants will present either provisions of the AI Act or a paper on Participatory AI. The presentations serve to develop a foundational understanding of the EU AI Act and Participatory AI. 2) In the second phase, student teams select one article from the EU AI Act and develop a strategy or suggestions on how participatory AI could be a means to ensure or contribute to legal compliance with the article. Teams will first present a proposal in the seminar. Then, student teams develop their work in the form of a seminar paper after receiving feedback. At the end of the seminar, they will give a presentation of their work and hand in a seminar paper. The goal of the seminar is to make students familiar with AI regulation developed by the EU and to sensitize them for approaches to Participatory AI. For the teamwork, 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. Understand what Participatory AI is and how it can be beneficially applied to realize provisions of the EU AI Act.

Deliverables

- Presentation (English; 15 min presentation per person+ 5 min discussion)
- Written Seminar Paper (English; ~3000 words per student)

Requirement:
Interest in AI regulation and/or experience with the development of AI; Interest in approaches to Participatory 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.}
• Information and materials will be made available via Moodle

A virtual pre-course meeting is planned for Wednesday, February 7, 2024, 11:30 - 12:00 am
Zoom Link: https://tum-conf.zoom-x.de/j/64483283077?pwd=dlFnMWdHekt1bENZSGJrUGt0RExPdz09
Meeting-ID: 644 8328 3077
Code: 023308

Regular seminar meeting is planned for Wednesday, 11:45 - 13:15 in room 01.08.033 (in person).

^{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.