This publication contains my latest reading suggestions, i.e., academic papers and articles I enjoyed reading in June 2026. You can follow me on X (@ProfSchrepel), LinkedIn (here) or BlueSky (here) to be notified of similar articles on a more regular basis. The Network Law Review is also available on X (@NetworkLawRev), BlueSky (here), and LinkedIn (here).
Antitrust:
- The Taxonomy Trap: AI Paradigm Shifts and the DMA (Schrepel – SSRN)
- Antitrust Antidote: April-June 2026 (Wong-Ervin et al. – Network Law Review)
- When and how to rescue efficiencies from oblivion in horizontal merger control? (Padilla – JAE)
- A Case Outcome Predictor for Computational Antitrust (Malca Vilchez et al. – S. Computational Antitrust)
- Generative AI Use by Competition Authorities (May – Stanford Computational Antitrust)
- Hub-and-Spoke Collusion with a Third-Party Pricing Algorithm (Harrington – JIE)
- Merger simulations in EU merger control: what have we learned? (Andrew & Ormosi – ECJ)
AI:
- Europe 2031: What getting AI wrong means for us (Juijn et al. – Europe 2031)
- This startup’s new mechanistic interpretability tool (Will Douglas Heaven – MIT Tech Rev)
- AI Economist Agent: An Agentic Framework for Model-Grounded Economic Analysis (Kato – arXiv)
- The Road to AI State Socialism (The Wall Street Journal)
- Did AI write this article? (The Economist)
- In the Weights (intheweights.com)
Econ:
- Agentic markets (Bichler – Electronic Markets)
- Testing Centralized and Polycentric Computational Planning (Fernández Salguero – arXiv)
Others:
- Common Knowledge, From Eye Contact to the Super Bowl (Schrepel & Pinker – Scaling Theory)
- How to give a bad talk (Yanai – Nature Reviews Cancer)
- Life lessons from an ad man (Sutherland – TED)
Thibault Schrepel
@ProfSchrepel