Philosophy of A.I. – "Yet Another Machine For Producing Gods" (Topic: Scale)

About this event

Taking inspiration from Jacques Derrida’s Glas, in which Hegel and Genet face off in two columns, typeset to produce mutual provocation with and against one another so as to invite interrogation of their respective presuppositions and predilections, this seminar will read a selection of technical documents on AI alongside philosophies of science and technology, language, knowledge, action, and materialism from the critical tradition. Alongside (re-)introducing participants to key documents in the evolution and consolidation of issues that are currently live in AI research — (i) functionality; (ii) scale; (iii) language; (iv) emergence / “intelligence”; (v) agency; and (vi) energy — the sessions will (re-)read critical theoretical explorations of technical dysfunction, the power matrices that become legible through technology’s gaps and blind spots, what happens when language only points at itself, the real and the possible, thinking with tools, and consumption. Throughout, the seminar will be guided by two goals: to demystify the rhetoric and occulted force of technical thinking by interrogating its conceptual premises and poetic machinations; and to invite critical philosophy’s own fundamental revision in view of the machinery of technical fabulation today. Readings for 11 November 2026 — Subtopic: Scale • Epoch AI. Scaling Intelligence: The Exponential Growth of AI’s Power Needs. EPRI White Paper, August 2025. https://restservice.epri.com/publicattachment/94532 • Samuel R. Bowman, ‘Eight things to know about large language models.’ Critical AI 2.2 (2024). https://arxiv.org/abs/2304.00612 • Ernst Jünger, “Total Mobilization” [1930], in: The Heidegger Controversy, ed. Richard Wolin (The MIT Press, 1991), pp. 119-139. [PDF (https://www.google.com/url?q=https://www.dropbox.com/scl/fi/bx2fx0ecrh85wsovxcatc/J-nger-Total-Mobilization.pdf?rlkey%3D87r63psxzj4ngd9tpbp66swpf%26dl%3D0&sa=D&source=editors&ust=1794020961341078&usg=AOvVaw3aR4DwG0Ron2CDbHfH_8N5)] Seminar leader: Dan McQuillan Useful Background Resources: • But what is a neural network? \| Deep learning chapter 1 \(3Blue1Brown\) – https://www\.youtube\.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB\-3pi&index=2 • Large Language Models explained briefly (3Blue1Brown) – https://www.youtube.com/watch?v=LPZh9BOjkQs&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi&index=6 • Transformers\, the tech behind LLMs \| Deep Learning Chapter 5' \(3Blue1Brown\) – https://www.youtube.com/watch?v=wjZofJX0v4M&t=484s • Attention in transformers\, step\-by\-step \| Deep Learning Chapter 6 \(3Blue1Brown\) – https://www.youtube.com/watch?v=eMlx5fFNoYc Convened by the Critical AI Network (https://cpct.uk/critical-ai-network/) organising collective: Dan McQuillan, Julia Ng, Scott Wark, Deirdre Daly, Andrés Saenz de Sicilia, and Jenny Doussan. CPCT’s annual research seminar meets on a bi-weekly basis (every 2 weeks) and is open to centre members, graduate affiliates, and other interested staff and students as well as the general public. It aims to serve as a forum for philosophical work and dialogue at Goldsmiths. \* \* \* \* \* \* \* \* \* \* \* \* \* \* \* \* \* About the Critical AI Network – Centre for Philosophy and Critical Thought The Critical AI Network (CAIN) (https://cpct.uk/critical-ai-network/) is a space for the collective development of critical perspectives on AI with the aim of opening up new possibilities for intervention. Our premise is that contemporary AI is a form of computation emerging from a specific economic, political, and institutional matrix, and that challenging AI requires a rigorous effort to escape the weight of conditioned ideas that legimitise it. CAIN is an affinity-based assembly of people across disciplines and inside and outside academia that aims to reclaim the possible from the probable and to reconfigure the present for the common good. CAIN operates on the basis of solidarity and mutual support, as an experiment in the plurality of ways in which