Click here to order “Blockchain + Antitrust”
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This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in March 2021. As I tend to favor the active sharing of open-source publications, you can follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis.
SUBSCRIBE TO THE NETWORK LAW REVIEW NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL ANTITRUST NEWSLETTER (100% free) * JOIN MICHAL GAL AND I ON APRIL 7 TO DISCUSS THE BATTLE PRIVACY LAW VS. COMPETITION LAW
Antitrust:
- Do our Privacy Laws Strengthen the Already Strong? (Michal Gal – Concurrentialiste)
- Stanford Computational Antitrust Podcast (Thibault Schrepel – Apple, Spotify, Stitcher, YouTube) 🎧
- Gleaning Insight from Antitrust Cases Using Machine Learning (Schrepel, Massarotto & Ittoo – Apple Podcasts) 🎧
- David Teece on Static & Dynamic Competition (David Teece — Ipse Dixit) 🎧
- Podcasts for antitrust law enthusiasts [updated in 2021] (Thibault Schrepel – Concurrentialiste)
- Revisiting the Anticompetitive Effects of Common Ownership (José Azar and Xavier Vives — Forthcoming)
- Gleaning Insight from Antitrust Cases Using Machine Learning (Massarotto & Ittoo — Stanford Computational Antitrust)
- EU struggles to build antitrust case against Amazon (Financial Times)
- The FTC Did Not ‘Fumble the Future’ in Its Google Search Investigation (Geoffrey Manne & Dirk Auer — Truth on the Market)
- Competition Law and Digital Ecosystems: Learning To Walk Before We Run (Frederic Jenny — SSRN)
- Exploitative Abuse of a Dominant Position: A Bad Idea That Now Should Be Abandoned (Gregory J. Werden — SSRN)
- Not from Concentrate: Collusion in Collaborative Industries (Barry, Hatfield, Kominers & Lowery — SSRN)
- How the Narrowing of Product Markets Has Altered Substantive Antitrust Rules (Wilson & Klovers — SSRN)
- Antitrust Criminalization as a Legitimate Deterrent (Whelan — The Cambridge Handbook of Competition Law Sanctions)
- Separation: A Cure for Abuse of Platform Dominance? (Richard J.Gilbert — Information Economics and Policy)
- The Evolution of Merger Enforcement Intensity: What do the Data Show? (Macher & Mayo)
Blockchain & artificial intelligence:
- The Most Important Scarce Resource is Legitimacy (Vitalik Buterin — Vitalik Buterin’s website)
- Artificial Intelligence Index Report 2021 (Stanford University — Stanford University Human-Centered Artificial Intelligence)
- Who Is Liable for a Quantum Adversary in a Cryptocurrency System? (Peder Østbye — SSRN)
- Bias Preservation in Machine Learning (Wachter, Mittelstadt & Russell — West Virginia L. R.)
- Climate and Crypto (Continuations)
- NFTs as New Markets (Jason Potts, Ellie Rennie, A. Chris Berg, Sinclair Davidson — Mint & Burn) 🎧
- Multimodal Neurons in Artificial Neural Networks (Goh et al. — OpenAI)
- Quantifying the Value of Data (Katharine Miller — Stanford University Human-Centered Artificial Intelligence)
- We’ll never have true AI without first understanding the brain (Patrick T. Powers — MIT Technology Review)
Big Tech:
- “Control = liability”: exploring Section 230, the DSA, Big Tech, Wikipedia and Blockchains (Schrepel — Concurrentialiste)
- Forcing Interoperability on Tech Platforms Would Be Difficult to Do (Randy Picker — Promarket)
- Can the EU Regulate Platforms Without Stifling Innovation? (Cennamo & Sokol — Harvard Business Review)
- Tech Giant Exclusion (John B. Kirkwood — SSRN)
- Google (Sorta) Pivots To Privacy on Stitcher (Techmeme Ride Home — Stitcher) 🎧
- Google to Stop Selling Ads Based on Your Web Browsing on Stitcher (WSJ Tech News Briefing — Stitcher) 🎧
Econ:
- Capitalism, Cronyism, and Management Scholarship: A Call for Clarity (Klein, Holmes, Foss, Terjesen & Pepe — SSRN)
- Michael Munger on Desires, Morality, and Self-Interest (Michael Munger & Russ Roberts – EconTalk) 🎧
- New York Times NFT Goes Parabolic, PNG File Sells For $562K (Will Gottsegen — Decrypt)
- Russ Roberts, Economist and host of EconTalk… “don’t let numbers rule your life” (Russ Roberts — Spotify) 🎧
Other:
- Why “future proof” regulation is a bad idea (Thibault Schrepel — Concurrentialiste)
- The Tradeoff Between Openness and Trust in Digital Marketplaces (Alec Stapp — Gglomerations)
- Clubhouse Is Booming. So Is the Ecosystem Around It (Arielle Pardes — Wired)
- Computer Science courses with video lectures (GitHub) 🎧
- CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review (Hendrycks, Burns, Chen & Ball — Cornel University)
- Elementary Mathematical and Computational Tools (Jamal T. Manassah — CRC Press)
- Foundation App
- Quantum Computing and Computational Law Applications (Eran Kahana — SLS Blogs)
- The Greatest NFT Film Ever Made (The Defiant) 🎥
- Working Paper: The Digital Markets Act Obligations (Council of the European Union — European Union)
- You can buy the first-ever tweet. The current bid: $2.5 million (Jazmin Goodwin — CNN Business)
Books (only those I enjoyed this month):
- Complexity Economics: Proceedings of the Santa Fe Institute’s 2019 Symposium (Arthur, Beinhocker & Atanger — SFI Press)
- Computational Legal Studies: The Promise and Challenge of Data-Driven Research (Whalen ed. — Edward Elgar Publishing):
The number of books dealing with computational law — here, “computational legal studies” — will increase drastically in the years to come. There is every reason to believe that “Computational Legal Studies” (Edward Elgar, 2020) will be a reference in the field. The book, co-authored by about twenty academics, gives both an overview of computational law potential, and details some very concrete applications.
Let us have a closer look. It starts with “Sense and similarity: automating legal text comparison” (Alschner), opening up new research perspectives when it comes to Natural Language Processing (“NLP”). The results shown in “Automated classification of modes of moral reasoning in judicial decisions” (Mainali, Meier, Ash & Chen) are also quite fascinating. They show that computational tools are about increasing the speed of analysis and reaching previously inaccessible results. “Computational legal studies in China: progress, challenges, and future” (Tang & Liu) explores the difficulties of implementing computational law in China, while “Understanding content moderation systems” (Suzor) explains how one can combine related tools with a “code is law” approach. Finally, “Purposes and challenges of legal citation network analysis on case law” (van Kuppevelt, van Dijck & Schaper) explores the potential and limitations of network analysis.
In the end, the only downside relates to the arrangement of the different chapters. “Rule by rules” (Livermore) is one of the most fundamental articles on the subject (exploring how important it is to antitrust, see “Computational Antitrust: An Introduction and Research Agenda“). It would have been a great introduction to this book, while other chapters such as “Predicting the authorship of investment treaty awards” would have found their place in the application part. That being said, I closed the book with a better understanding of the issues and potential of computational law, and I am grateful for that.
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Dr. Thibault Schrepel
(@LeConcurrential)
