Click here to order “Blockchain + Antitrust”
***
This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in June 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)
Antitrust:
- Antitrust Enforcement & Big Tech: After the Remedy Is Ordered (Himes, Nieh, & Schnell — Stanford Computational Antitrust)
- No, Monopoly Has Not Grown (Robert D. Atkinson & Filipe Lage de Sousa — ITIF)
- The computational antitrust podcast: Episode #4 (Computational antitrust) 🎧
- Antimonopolism as a Symptom of American Political Dysfunction (Ramsi Woodcock — SSRN)
- Antitrust posturing (Benedict Evans)
- Opinion of 29 April 2021 on the sector of new technologies applied to payment activities (Autorité de la Concurrence)
- Antitrust & Privacy: It’s Complicated (James C. Cooper & John M. Yun — George Mason Law & Economics Research Paper)
- Congress’ Antitrust War On China and American Consumers (Herbert Hovenkamp — ProMarket)
Blockchain & artificial intelligence:
- Occupational, industry, and geographic exposure to artificial intelligence (Felten, Raj & Seamans — Stra. M. Journal)
- Ethereum 2.0 (Vitalik Buterin — Lex Fridman) 🎥
- Google is using AI to design processors that run AI more efficiently (Matthew Sparkes — NewScientist)
- Crypto Finally Has a Reason to Exist (Tyler Cowen — Bloomberg)
- U.S. Launches Task Force to Study Opening Government Data for AI Research (Ryan Tracy — The Wall Street Journal)
- Bitcoin Lightning Network on Twitter ‘Only A Matter of Time’: Jack Dorsey (Stephen Graves — Decrypt)
- The European Commission’s Artificial Intelligence Act: HAI Issue Brief (Marietje Schaake — Stanford HAI)
- NYC Mayoral Front Runner Eric Adams Says City Will Become ‘Center of Bitcoins’ (Sebastian Sinclair — Coindesk)
Big Tech:
- Sir Tim Berners-Lee is selling the first web browser’s code as an NFT (Mitchell Clark — The Verge)
- Decentraland: $30,000,000 Virtual Real Estate Boom (Defi Donut — Metaverse Millionaires)
- Interview: Marc Andreessen, VC and tech pioneer (Noah Smith — Noahpinion)
- Technology Saves the World (Marc Andreessen — Future)
Econ:
- The coming productivity boom (Erik Brynjolfsson & Georgios Petropoulos — MIT Technology Review)
- Economics of Creative Destruction: Day 1 (Festschrift Conference) 🎥
- Economics of Creative Destruction: Day 4 (Festschrift Conference) 🎥
- A Policy Governance Framework for SEP Licensing (Heiden & Baron — SSRN)
Other:
- Daniel Kahneman on Why Our Judgment is Flawed (Steven D Levitt — Freakonomics: People I (Mostly) Admire) 🎧
- Defending the Free and Open Internet in an Age of Authoritarianism (Beverton-Palmer, Bennett, Stapp & Watney)
- Unity in Privacy Diversity: A Kaleidoscopic View of Privacy Definitions (Koops & Galič — South Carolina Law Review)
- Law As Code: A Legal System Shaped By Software (Joshua Browder — Future)
Books (only those I enjoyed this month):
- Miller & Page, Complex Adaptive Systems (Princeton, 2007)
- Cannataci, Falce & Pollicino ed., Legal Challenges of Big Data (Edward Elgar, 2020)
Most of the “law and technology” scholarship that I read is fundamentally anti-technology. I think our training as lawyers can explain this. We push our students to study legal problems without insisting much on how other constraints (that is, other than the law) may solve issues. This eventually leads some academics to focus exclusively on the dangers technology creates for privacy, the competitive barriers it erects, the risks for human rights, etc. Unfortunately, this one-sided approach that ignores the positive effects of technology comes with a substantial risk: advocating for (and enacting) laws and regulations that suppress non-legal benefits, even involuntarily (see “Law and Technology Realism”).
The collective work “Legal Challenges of Big Data” features several chapters that are exploring a less dogmatic approach. It starts with Capobianco & Gonzaga writing on the “competition challenges of big data” and addressing the issues while exploring “opportunities of big data for innovation and economic growth”. It goes on with Podszun & Langenstein paper on “data as an input in competition law cases” which rightfully insists on the “static efficiency bias” before concluding with thoughtful proposals. Lastly, Lagioia & Sartor provide us with a fantastic teaching resource dealing with “artificial intelligence in the big data era”, precisely because it is well-balanced.
I also enjoyed De Gregorio & Ranchordás and Durovic & Lech articles for other reasons, mainly for the technical aspects of their analyses. My central reserve is twofold: (1) not all papers are equally balanced, and (2) the ordering of the chapters does not always make sense. It remains a must.
***
Dr. Thibault Schrepel
(@LeConcurrential)
REGISTER HERE
