The artificial intelligence industry recently called for an antitrust exemption to coordinate self-regulation as the risks their models pose to the internet and society...
Alberto Heimler argues that antitrust authorities should focus on whether market power allows one party to exploit relationship-specific sunk investments made by another and how that undermines potential innovation, investments, and competition.Â
All merger reviews come with uncertainty, but the culture among courts, consultants, and regulators is to pretend that sophisticated modeling can eliminate uncertainty, and thus any uncertainty reflects poor econometric analysis. Creating standards of uncertainty would produce more honest analysis and better competition outcomes, writes Bart Lahcen.
In new research, Tingting Song examines how FRAND principles typically used to discipline excessive or discriminatory terms in SEP licensing can be applied to data brokers in data licensing.
In new research, Yulia Chikish, Gregory J. Colman, Dhaval M. Dave, Brad R. Humphreys, Zachary Santamaria, and Zachary Winship find that New York City congestion pricing has reduced emergency medical services response times.
Artificial intelligence agents are beginning to interact in ways that create risks beyond individual misalignment with corporate and social expectations. As happened with global finance after the 2007 crisis, AI governance needs to begin focusing on how good agents can still produce bad systems.
The discussion about concentration in artificial intelligence markets focuses on the least concentrated layer, the models. The chokepoint that actually threatens AI is the production of refined minerals that go into chips, data centers, and electricity production, writes Piyush Akimitsu.  Â
Walid Chaiehloudj argues that when a scientifically substantiated large but uncertain risk, like environmental damage, conflicts with standard competition analysis, competition authorities need to defer to a precautionary citizen-consumer standard that takes into consideration the risks of that harm.