After successful completion of the course, students are able to identify crucial points of critique and problematic issues in relation to algorithmic systems and understand strategies to overcome them. They have gained an overview of topics like Inequality, Bias, Fairness, Transparency, Integrity, Trust & Safety Engineering, and gained in-depth understanding of at least one of those topics.

The seminar will introduce participants to the emerging and interdisciplinary field of Critical Algorithm Studies. Blocked weekly discussions of assigned reading material will focus on interdependencies between society, culture, and algorithms, and critical reflections on their ethics and politics. The course aims to bridge the gap between bleeding-edge technological advancements and the scientific and social discourse, by introducing perspectives from academic disciplines such as STS, Sociology, and Law.

Preliminary list of topics

1. Introduction to Critical Algorithm Studies
2. (Future) Imaginaries
3. Computer Science Culture
4. (Re-)producing & Combating Inequality through Technology
5. Critical Data Studies
6. Transparency and Accountability of Algorithmic Systems
7. The Politics of Algorithms
8. Case Study Session

This is a preliminary outline of the course. When appropriate, we will try and integrate relevant topics from the current public debate in the news, media and science. Students are encouraged to follow relevant resources and stay up to date on the latest developments in the context of the course. A list of resources will be provided at the start of the course.

Open Learning Questions

• Why study social and political aspects of algorithmic systems?
• What constitutes an algorithm? What do users/developers/society understand about algorithms?
• Why do algorithms have embedded values and biases?
• How can we conceptualize algorithmic fairness, develop ethics for algorithmic systems, and deal with accountability in complex algorithmic assemblages made of developers, users, management, law, code, computers, and many others?
• How does culture and society influence the creation of algorithms and vice versa?
• How does more algorithmic management foster the erasure of human judgment through increasing rationalization and automation? What are benefits and issues here?
• What methods and approaches are available to study algorithmic systems?
• What futures involving algorithms are currently being imagined?
• What measures are being taken to address algorithmic issues?

Introductory Materials

Many of the seminar's topics are controversial and highly discussed. We provide the following materials as a motivational introduction to some exemplary topics of the course:

• Why is artificial intelligence sexist? (Kate Crawford at #AllAboutWomen, 2021)

• How algorithms shape our world?! (Kevin Slavin, Ted 2011)

• Social media, extremism, and radicalization (Aaron Shaw, 2023)

• SAFER SCROLLING: How algorithms popularise and gamify online hate and misogyny for young people (Kaitlyn Regehr et. al., 2024)

• This Algorithm Could Ruin Your Life (Burgess et. al. 2023, Wired)

• What is shadowbanning? How do I know if it has happened to me, and what can I do about it? (Risius & Blasiak, 2022, The Conversation)

Course Modalities

After an initial introduction (introduction and preliminary topic assignment), the remaining sessions will be held weekly on a specified topic. During each session, one or more participants will present the topic of the week following a general introduction by the lecturers. The presenters are required to read the papers on the topic, present the content, conclusions, and a list of discussion points to the other participants. Each participant has to write a final seminar paper after the presentations reflecting on the content of the seminar.

Blocked weekly online discussions of assigned reading material will focus on interdependencies between society, culture and algorithms, and critical reflections on their ethics and politics. Questions and contributions to the discussions are supplement to the mandatory reading, presentations of selected literature, and the final seminar paper.

The course modalities may change on short notice, in which case some or all units may be held via Zoom. Grading won't be affected in this case.

Link to TUWEL: https://tuwel.tuwien.ac.at/course/view.php?id=62450

Contrary to the listed eligibility for different curricula below, the course is at least eligible for the following modules:

• Module “Emergent Ethical Challenges in Informatics”

• Master Media Informatics [066 935]

• Module “Fachübergreifende Qualifikationen”

• Master Logic and Computation[066 931]

• Master Visual Computing[066 932]

• Master Medical Informatics[066 936]

• Master Software & Information Engineering[066 937]

• Master Computer Engineering[066 938]

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The following student participation determines the grade:

• Questions and discussion contributions
• Presentation
• Final Seminar Paper

No specific requirements. Preexisting knowledge of societal aspects of computer science can be helpful.