Episode 41: What 30 Antitrust Agencies Actually Do With AI
Thirty antitrust agencies report on their computational work, in what remains the only account written by the agencies themselves. This edition asked them one question. What have these tools allowed you to achieve that you could not have achieved otherwise?Three developments stand out against earlier editions. With no legal regime in place, agencies have begun writing their own rules on what may go into a model. They are putting figures on their work, reporting precision, recall and false-positive rates, which earlier editions almost never did. And what holds deployment back is access to data and the agreements needed to obtain it.Recorded at the Autorité de la concurrence, Paris, 17 September 2026. Open access, 121 pages. shorturl.at/wmEaWSpeakers:➝ Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam, Faculty Affiliate at Stanford CodeX, Director of Stanford Computational Antitrust➝ Alba Ribera Martínez, Assistant Professor in Law and Technology at Vrije Universiteit Amsterdam, Editor-in-Chief of Stanford Computational Antitrust➝ Elodie Vandenhende, Deputy Head of the Digital Economy Unit, Autorité de la concurrence➝ Yann Guthmann, Head of the Digital Economy Unit, Autorité de la concurrence➝ Teodora Groza, Postdoctoral Researcher, Chair for Law and Artificial Intelligence, University of Tübingen#antitrust #competitionlaw #artificialintelligence
10 Jul 2026
Episode 40: Colluding Without Colluding, How AI Agents Learn to Fix Prices on Their Own
Can two AI agents fix prices without ever agreeing to? Tanise Brandão and Carlos Neves of Brazi’'s competition agency, CADE, join Thibault Schrepel and Alba Ribera Martínez to walk through their paper on algorithmic collusion.
They put two large language models in a repeated Bertrand duopoly, let them price against each other for 400 rounds, and watch supra-competitive prices emerge on their own. The agents coordinate even when they cannot communicate, and some learn to cover their tracks, with one proposing that they steer clear of red flags.
The conversation turns to why the choice of model and language moves the result, and why the behavior looks less like textbook rationality than a complex dynamical system. It closes on enforcement, where collusion no longer needs a meeting of minds, and Brandão and Neves make the case for shifting liability from whether firms agreed to what they chose to expose themselves to.
https://law.stanford.edu/publications/smart-agent-based-modelling-with-llms-leveraging-large-language-models-for-a-better-understanding-of-algorithmic-collusion/ (https://law.stanford.edu/publications/smart-agent-based-modelling-with-llms-leveraging-large-language-models-for-a-better-understanding-of-algorithmic-collusion/)
https://www.anthropic.com/research/global-workspace (https://www.anthropic.com/research/global-workspace)
16 Mar 2026
Episode 39: Gustavo Augusto Freitas de Lima on Computational Antitrust in Brazil
In episode 39, Alba Ribera Martinez and Thibault Schrepel talk to Gustavo Augusto Freitas de Lima, Interim President of Brazil's Competition Agency (CADE).Follow the Stanford Computational Antitrust project at https://law.stanford.edu/computationalantitrust
Reach and audience
Public platform figures. Ratings count people who left a rating, not total listeners.
YouTube views
13,775
Score snapshot 15 Sept 2025
Apple Podcasts (US)
5.0 / 5
3 ratings
Spotify
4.6 / 5
10 ratings
Podcast Authority Score: 37 / 100
A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.
Quality
17
Social presence
0
YouTube
76
Engagement
67
Contact Stanford Computational Antitrust
Guest appearances
Does not typically book guests
Based on episode analysis; this does not confirm that the show is currently accepting guests.
Pod Engine is an independent podcast discovery and analytics service and is not affiliated with or endorsed by this podcast. Artwork and show content belong to their owners. Full legal notice.
Explore this show Podcast research with Pod Engine
