U5 - AI, Memory, and the Unconscious: Exploring the Politics of Digital Archiving

Course Title

AI, Memory, and the Unconscious: Exploring the Politics of Digital Archiving

Course Description

This course examines the ethical, psychological, and social implications of artificial intelligence as a keeper of cultural memory. We will use a small selection of approachable readings—short articles, blog posts, and excerpted texts—to understand how AI systems can silence marginalized voices, reinforce historical biases, or open new avenues for representation. Drawing on basic Freudian concepts (repression, the unconscious) and key ideas from deconstruction (such as “archive fever”), students will learn to see AI not just as a technical tool, but as a cultural actor shaping how societies remember, forget, and rewrite history.

Learning Objectives

Recognize AI’s Role in Shaping Memory
- Understand how AI curation (e.g., algorithms, search engines) can perpetuate or challenge social narratives.
Explore Basic Psychoanalytic Ideas
- Grasp Freud’s notions of the unconscious and repression in lay-friendly terms to examine why “buried” histories can resurface or remain hidden.
Discuss the Ethics of Digital Archiving
- Reflect on who controls historical narratives and how AI might reproduce harmful erasures—or, conversely, reclaim lost stories.
Develop Critical Thinking
- Build skills in analyzing the social and moral implications of technology in everyday life.

Key Readings & Materials

Blog Posts & Short Articles

“AI and the Freudian Archive: Silencing, Repetition, and the Politics of Digital Memory” (main text)Author’s website
- Focus on how AI “remembers” or “forgets,” referencing Freud’s model of the unconscious.
Selected Excerpts on “Archive Fever” (2–3 pages)A short summary or paraphrased text of Derrida’s idea of “archive fever.”
- Provides an accessible introduction to how “archiving” can be inherently political.
Short Introduction to Freud
- A few pages (or a brief video) summarizing Freud’s concept of the unconscious and “repression.”
Additional News Articles or Case Studies (2–3 short articles)
- Examples of AI either erasing or spotlighting marginalized histories
- May include issues like algorithmic bias, cultural appropriation via AI, or controversies around “scraping” data for training.

Optional Material (For Deeper Exploration)

Very brief excerpt from Eric Foner’s Who Owns History? to spark questions about controlling historical narratives.

Weekly Outline

Week 1: Introduction — What Is AI and Why Does It Matter?

Introduce basic AI concepts (machine learning, algorithms)
Discuss everyday examples of AI’s influence (recommendation systems, search engines)
Reading: Simple article on AI basics

Week 2: Freud 101 — The Unconscious and Repression

Layperson’s overview of Freud’s key ideas
Activity: Identifying “hidden” or “repressed” influences in culture
Reading: Short introduction to Freud’s concept of the unconscious

Week 3: Derrida for Beginners — Archive Fever

Class-friendly summary of Derrida’s “archive fever”
Discussion: The tension between preserving and destroying memory
Reading: Brief excerpt/summary of Derrida’s ideas + short reflection

Week 4: Main Blog Post Analysis

“AI and the Freudian Archive” as central text
Group discussion: AI as “memory machine,” how it might silence or repeat historical injustices
Student reflection: Where do we see real-world examples?

Week 5: Case Studies in Digital Silence

Short news articles/case studies on historical erasure or AI-induced bias
Workshop: Students pick one example and discuss how AI could address or exacerbate the issue
Reading: 2–3 short press articles or blog posts

Week 6: Who Owns the Story?

Optional excerpt from Eric Foner’s Who Owns History?
Debate: Should AI be regulated to prevent erasure of marginalized voices?
Assignment: Write a 1-page proposal for an AI guideline or policy to safeguard cultural memory

Week 7: Ethics of AI & Cultural Memory

Summarize ethical frameworks (e.g., fairness, care ethics, beneficence)
Discussion: Who is responsible for the stories AI tells—or omits?
Reading: Short article on AI ethics or position statement from a reputable tech ethics group

Week 8: Project Workshops — Proposals & Creative Responses

Students work on final projects exploring a specific instance of AI-based archiving or silencing
Group feedback and collaborative brainstorming

Week 9: Presentations — Reimagining the Archive

Students present their final findings (could be a short paper, creative project, or policy recommendation)
Class discussion on next steps: How do we remain vigilant about AI’s role in shaping memory?

Week 10: Course Synthesis & Looking Forward

Review of core concepts: Freud’s unconscious, Derrida’s archive fever, AI’s potential to reshape history
Group reflection on emerging questions, how to continue investigating digital memory ethically
Wrap-up: Students share key lessons learned

Assignments & Evaluation

Reading Reflections (30%)
- Each week, a short response (1–2 paragraphs) addressing main points and questions raised by the reading.
Mid-Semester Short Essay (25%)
- 3–4 pages connecting Freud’s or Derrida’s ideas to a real-life example of AI and memory (or forgetting).
Final Project (30%)
- Options:
  - Research Paper (5–6 pages) analyzing a specific case of AI-induced erasure or retrieval of marginalized history
  - Creative Project (artwork, short film, zine, etc.) accompanied by a 2-page explanation linking it to course themes
Participation (15%)
- Active contribution to class discussions and collaborative workshop activities.

Approach to Teaching

Accessibility & Clarity: Given the challenging theoretical material (Freud, Derrida), the course will use short summaries and class-friendly paraphrases rather than dense original texts.
Conversational Learning: Emphasize discussions, debates, and small-group activities over lectures.
Real-World Applications: Encourage students to explore ongoing AI ethics debates, relevant news stories, and personal insights.
Inclusivity & Curiosity: Create a respectful environment where students feel comfortable engaging with unfamiliar concepts and sharing diverse viewpoints.

End of Course Outline

This simplified syllabus focuses on digestible readings and interactive discussions. By centering on a single, pivotal blog post and a few short texts, students gain both theoretical grounding and practical insight into how AI can shape—sometimes distort—collective memory.