This publication contains my latest reading suggestions, i.e., academic papers and articles I enjoyed reading in February 2024. You can follow me on X (@ProfSchrepel) or LinkedIn (here) to be notified of similar articles on a more regular basis. The Network Law Review is also available on X (@NetworkLawRev) and LinkedIn (here).
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Generative AI symposium:
- Introduction to the symposium on Generative AI (Thibault Schrepel & Volker Stocker)
- Sources of Innovation in Generative AI (Jason Potts)
- Generative AI’s Potential Impact on Online Competition (Christopher S. Yoo)
- What New Legal Rules Could Foster Competition and Innovation Dynamics In GenAI? (Axel Voss)
- Generative AI And Productivity: Challenges, Opportunities And The Role of Policy (Calvino & Criscuolo)
- Artificial Intelligence and Market Power (Paul Seabright)
- Two Views on Regulating Competition in Generative AI (Anouk van der Veer and Friso Bostoen)
- Who Owns Generative AI Training Data? Mapping The Issue And A Way Forward (Beatriz Botero Arcila)
- Discit ergo est: Training Data Provenance And Fair Use (Robert Mahari and Shayne Longpre)
- Can Telecommunications Regulation Inform Emerging Regulatory Approaches To Generative AI? (Lawrence)
- Is Generative AI the Algorithmic Consumer We Are Waiting For? (Michal Gal & Amit Zac)
- Does Artificial Intelligence Have the Right to Freedom of Speech? (Cass R. Sunstein)
- Unpacking Disclosure & Generating Trust in an Era of Algorithmic Action (Orly Lobel)
Antitrust:
- A Reevaluation of the Consumer Welfare Standard for Digital Markets (Christos A. Makridis & Joel Thayer)
- A Critical Inquiry Into ‘Abuse’ In EU Competition Law (Pinar Akman – SSRN)
- Quick-Look Inferences: Big Tech’s R&D Expenditure Ratios (Padilla, Ginsburg & Wong-Ervin)
- Start-ups Worry Over EU’s Big Tech Crackdown (Javier Espinoza – FT)
Artificial Inteligence:
- A Pro-Innovation Approach to AI Regulation: Government Response (UK Gov)
- Power Corrupts, Absolutely (Andy Kessler – WSJ)
- The Unreasonable Effectiveness of Algorithms (Ludwig et al. – NBER)
- Artificial Intelligence for Literature Reviews: Opportunities and Challenges (Bolanos et al. – Arvix)
- On the Societal Impact of Open Foundation Models (Kapoor et al. – Stanford)
- Can AI Standards Have Politics? (Alicia Solow-Niederman – UCLA)
- Synthetic Data and the Future of AI (Peter Lee – Cornell)
- Why the AI Act Won’t Trigger a Brussels Effect (Ugo Pagallo – SSRN)
Digital:
- Tech Strikes Back (Nadia Asparouhova – The New Atlantis)
- Gemini and Google’s Culture (Ben Thompson – Stratechery)
- Data, Privacy Laws and Firm Production: Evidence from the GDPR (Demirer – NBER)
Econ:
- Increasing Returns (Mauboussin & Callahan – Morgan Stanley)
- Where Increasing Returns Come From? (Robert Armstrong – FT)
- The Race Between Innovation and Obsolescence (Lee, Kempes & West)
Thibault Schrepel
@ProfSchrepel
