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Algorithmic Cultures: AI Systems Between Technical Design and Social Impact (Seminar)

Course Information (Winter Semester 2026/27)

This website provides an overview of the seminar. For official course details, enrollment information, and materials, please refer to the university course catalogue.

Instructor: Dr. Anett Hoppe

Introduction session: October 12, 3 p.m.; Lecture Hall II (HS II, MZG) 03A16

Working phase: Independent research with one optional individual consultation (20 minutes)

Block seminar: 2 days in February/March 2027 (presence mandatory)

Assessment:

  • Seminar presentation (20-30 min)
  • Synthesis paper (5-6 pages)
  • AI usage documentation
  • Active participation

Target Audience

Bachelor/Master students in Computer Science, Data Science, and Cultural Data Studies

Prerequisites

CS students: basic competencies in machine learning and/or data science
CDS students: none beyond standard programme prerequisites
All participants: willingness to engage seriously with literature and perspectives from outside one's home discipline

Course Overview

Artificial intelligence systems are technical artefacts that shape culture, and cultural forces shape technical design. Yet, these two sides are rarely studied as one problem. This interdisciplinary seminar brings students from CS (Computer Science, Data Science, and Computer Science Education) with students from Cultural Data Studies (CDS) to explore concrete AI systems and AI application areas from both distciplinary angles.

Each unit centers on one topic — for example recommender systems, large language models, generative image and video models, automated content moderation, or facial recognition. Two talks address it from complementary angles: the CDS presentation frames the topic from a media and cultural studies perspective, while CS works out the technical problem framing using one or two current systems as concrete examples. A joint discussion then reads both perspectives against each other.

For CS students, this is a chance to work through a real system in depth — not just how it works, but what it is actually being asked to do and to see that framing tested against a cultural studies reading in the room. For CDS students, it grounds cultural analysis in the concrete technical mechanics of the systems under discussion, instead of treating them as a black box.

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