Innis Lecture: Algorithmic pricing and competition
本文探讨AI驱动的算法定价如何改变卡特尔形成与协调方式，分析算法被故意用于合谋、作为第三方促成合谋以及自主学会合谋三种风险，并评估法律影响。
Abstract This article examines how advances in AI‐driven algorithmic pricing are reshaping the nature of cartel formation and coordination. Traditionally, cartels relied on explicit communication, extensive organization, and sustained human effort to reach and maintain agreement while avoiding detection. Recent technological developments now raise concerns that coordination may arise with far less human involvement. In particular, three main risks are identified: the deliberate use of algorithms to implement collusive strategies, the role of algorithms as third‐party facilitators of collusion, and the possibility that algorithms may autonomously learn to collude. While algorithmic pricing can enhance efficiency and competition, the article assesses these risks and considers associated legal implications.