Teaching at the Professorship of Cyber Trust

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

Description:

Cybercriminal activities as well as other undesirable or malicious activities have increased in prevalence over the last decade. At the same time, the efforts and capabilities of industrial and academic researchers to understand these phenomena have made significant improvements. In this seminar, we will discuss a range of recent data-driven studies focusing, for example, on Spear-Phishing, Ransomware, Cybercriminal Marketplaces, Online Fraud etc., but also other challenges of societal interest such as Cyber-Bullying and Fake News. Each participant of the seminar will deeply engage with a key study to understand its focus, methodology, (data) limitations, and achievements. It is further expected to understand each work in the context of related studies, e.g., from security industry research labs. Participants of the seminar are expected to build on the literature to develop research objectives for further study.

Requirement:

No specific knowledge required. General interest in interdisciplinary privacy and security topics highly desirable; knowledge in diverse methods of data analytics desirable for practical topics. The seminar language is English.

Note:

The seminar will meet for 1-2 introductory sessions at the beginning of the semester (Tuesday afternoon, between 13:00 - 16:00, in room 00.13.008 (FMI building). There will be no pre-course meeting.
The presentation of results will follow in the second half of the semester in the form of longer seminar sessions (Blocktermine). 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 2-person teams is possible with approval by the instructor.

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

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

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 October 28, 2022 (there will be no pre-course meeting before the kick-off meeting).
Regular seminar meeting is planned for Friday afternoon, between 12.00 and 14.30 every second week in room 00.08.059 (FMI building).

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

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

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, 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 by developing an appropriate checklist or datasheet. 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 & 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:
_ Presentation (English; split into 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 

Note:

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

IMPORTANT:

• Students from the *Informatics & Mathematics* Department apply via the Matching Platform (https://matching.in.tum.de/). We are happy to prioritize students who briefly express their motivation by emailing chiara.ullstein@tum.de with the email subject [Seminar - EU AI Act | Application] (please note that we do not have any influence on the final selection of students by the matching tool other than prioritization).
• Students from the *Governance* Department apply by sending an email to chiara.ullstein@tum.de with the email subject [Seminar - EU AI Act | Application] stating his/her motivation, immatriculation nr., study program and progress (semester). For registration students must be identified in TUMonline as a student.

Note: The size of the seminar is limited to 24 students. 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.

The seminar will take place in the first half of the semester (end before the winter break in december) with weekly 3h sessions.

A virtual pre-course meeting is planned for Thursday, July 21, 2022 at 9:00 (link follows).

TUM Online: Course Description

Course Instructor: Chiara Ullstein

Description:

First, an overview on basic applications of facial recognition technology (FRT) will be provided. Next, students will present selected articles and papers concerning FRT to discuss ethical concerns. Finally, students work as a team of 6 participants on a final project which shall be an interactive application, didactically show-casing the capabilities of a specific FRT application (with a focus on inference making from faces). Presumed/ fictional consumers of these applications are members of the civil society that are assumed to know nothing/ little about FRT. The didactic application (= final group project) shall inform them and initiate critical reflections. The application area of the developed project could be a public deliberation or any other public or private setting that allows citizens to interact with technology and reflect upon it. Groups will present their application at the end of the seminar and document it with a written project report.

The goal of the seminar is for future developers to critically reflect FRT applications and to learn how to educate civil society about what is technically possible today.

Note: A continuation of this seminar is envisioned for the summer semester 2023, where public deliberations will be organized and scientifically analyzed. The developed interactive FRT applications will serve as didactic tools to explain FRTs and allow participants to experience FRTs firsthand. Participation in the summer semester 2023 is voluntary and does not influence participation in the seminar in the winter semester 2022/23.

Course objectives:

Reflect on the capabilities and risks of facial recognition technologies (FRT). Build an AI application (mock-up), i.e., as a didactic tool, with a focus on communicating how FRT applications work and what risks might emerge.

Deliverables:

_ Presentation of selected articles/ paper (English; 7 min presentations + 5 min discussion)
_ FRT application, written project documentation (Group; English; ~12 pages in total), and presentation of group project (English; 7 min presentations + 5 min discussion per student)

Please note, the first presentation will be graded individually. For the group project, the group members will be graded collectively. The group grade will account for the concept, functionality, and usability of the developed FRT application (not the code itself), the written project documentation and the group presentation.

Requirement:
Requirement for participation are solid programming skills, experiences with AI development, high commitment to collaborating on a group project, high dedication to self-learning in order to build a functioning didactic tool. The instructor will give feedback on the concept, but not on the implementation.

Note:

Please apply via the Matching Platform (https://matching.in.tum.de/). We are happy to prioritize students who briefly express their motivation by emailing chiara.ullstein@tum.de with the email subject [Seminar - FRT | Application] (please note that we do not have any influence on the final selection of students by the matching tool other than prioritization).

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.

A virtual pre-course meeting is planned for Thursday, July 21, 2022 at 10:00 (link follows).

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.