Schizoanalysis of AI: Machinic Desire, Energy, and Planetary Subjectivation
Instructor: Prof Alex Taek-Gwang Lee
Intensive course
This module is not available at this time.
Register by 6 August 2026
First seminar: 8 February 2026
This course is part of the learning module 2026 Ereignis Institute. Registration and full overview are available on the module page.
Learning module detailsThis course approaches artificial intelligence not as a model of cognition or a substitute for human thought, but as a machinic assemblage that reorganises desire, labour, and planetary forms of life. Against the dominant ideology of AI grounded in the thermodynamics of information – where thought is reduced to computation and life to optimisation – this course draws on Deleuze and Guattari‘s schizoanalysis to propose an alternative conceptual framework. Schizoanalysis allows us to understand AI as a desiring-machine, one that connects technical infrastructures, global supply chains, computational architectures, and human bodies in new circuits of production and exhaustion. Rather than asking whether AI can “think,” I investigate how AI participates in the production of subjectivity: how it reconfigures perception, affects, attention, and the conditions of planetary co-existence. By situating AI within the broader question of the machinic earth, the seminar reframes the stakes of AI beyond ethics or regulation, toward the problem of how modes of life and care can be composed in the shadow of accelerating automation.
This course is part of a three-course module – two seminars and one workshop – that are held over three weekends in February, April, and June, and two days in August 2026. The sessions are held online. The last session is followed by the 2026 Ereignis Conference, where students are encouraged to present their paper. Attendance at the conference is included in the course fee. Read more about the module and see the full timetable on the main module page.
- Video recording of session 1 (156 min.)
- Video recording of session 2 (106 min.)
- Video recording of session 3 (142 min.)
- Video recording of session 4 (87 min.)