Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage, die wichtigsten Kritikpunkte und Problemstellen algorithmischer Systeme zu bennenen. Sie haben einen Überblick über die Aspekte Ungleichheit, Bias, Fairness, Transparenz und Accountability gewonnen und sich mit zumindest einem der Themengebiete intensivst auseinandergesetzt.

Diese Lehrveranstaltung wird in Englisch abgehalten

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 of 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

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 conceptualise 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 judgement through increasing rationalisation 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?

Introductory Materials

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

• "The Trouble with Bias" (Kate Crawford, (formerly NIPS) 2017 Keynote)
• "There is a blind spot in AI research" (Kate Crawford& Ryan Calo, Nature)
• Do algorithms reveal sexual orientation or just expose our stereotypes? (Blaise Aguera y Arcas, Medium)
• Bias und Diskriminierung beim AMS Algorithmus (Cech, 2018 - German only)

Course Modalities

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

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Wöchentliche Block-Sessions einer kuratierten Leseliste fokussieren auf Gesellschaft, Kultur und Algorithmen, sowie eine kritische Reflexion ethischer und politischer Dimensionsn derselben. Fragen und Diskussionsteilnahme fliessen ebenso mit ein wie Präsentationen ausgewählter wissenschaftlicher Literatur und das abschließende Seminar-Paper.

Im Gegensatz zur fälschlichen Beschreibung weiter unten, ist das Seminar für die folgenden Module / Master Curricula anrechenbar:

• 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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Die folgenden Leistungen fließen in die Note mit ein:

• Fragen und mündliche Mitarbeit
• Präsentation
• Seminarpaper

Keine spezifischen Vorkenntnisse nötig. Vertrautheit mit gesellschaftlichen Aspekten der Informatik von Vorteil.