Abstract
Online economic interactions generate data that artificial intelligence (AI), machine learning (ML) and deep learning (DL) can use: business predictive analytics, process optimisation and market power; consumer search and choice; and government gathering evidence and regulating harmful behaviour. In algorithmic collusion (AC), revenue management algorithms implement tacitly collusive behaviour. This paper summarises theoretical and empirical evidence and considers how ML methods affect AC and whether regulators’ algorithms can help. It examines links between Internet regulation and competition policy.
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