Future Challenges for Automation in Competition Law Enforcement

Abstract

Competition authorities have started to benefit from the potential of Artificial Intelligence (AI) for enforcing competition law. This leads to Automated Decision-Making (ADM) systems supporting and replacing human decisions in specific phases of competition law enforcement, from the initiation phase to the monitoring phase. An overview of the digital tools developed by some agencies seems to confirm the trend of moving toward computational antitrust. However, the increasing reliance on ADM systems by public enforcers will bring about challenges for compliance with basic principles of law, stemming from possible automation biases, difficulties in reasoning, hearing, and access to document requirements. These challenges need to be also addressed in competition law enforcement.