Artificial Intelligence (hereafter, ‘AI’) systems are widely adopted by public administrations. Competition law does not escape the rule. Recently, non-negligible efforts have been made in ex officio detection of anticompetitive behaviours (above all, bid-rigging) through AI-driven cartel screening. This is unsurprising. On the one hand, AI systems promise to address well-documented flaws in human decision-making, e.g., arbitrariness or bias. On the other hand, AI systems carries the potential to strengthen ex officio investigations. Collusive behaviours are, currently, mainly exposed through leniency applications, whose number is decreasing. It has been suggested AI-driven cartel screening constitutes a useful complement to leniency programmes. AI-driven cartel screening flags indicators of collusion that then trigger the need for further investigation. This increases the probability of detection that destabilises the collusive equilibrium and incentivises leniency applications.
This presentation does not discard the benefits of AI-driven cartel screening. It argues, however, that this algorithmic shift it is not a silver bullet. First, as a data-driven solution, algorithmic predictions and recommendations are significantly affected by problems in the availability and quality of data they rely on. Second, limited explicability of some AI systems challenges the duty to state reason that will only be satisfied if public servants using AI systems are able to disclose how the different parameters were weighted and to what extent that recommendation was decisive for their final decision.
None of these drawbacks constitute a dead-end. Although not applicable to EU competition law, the EU Proposal for an AI Act provides interesting (at least, embryonic) solutions, i.e., data quality (art. 10 AI Act), transparency (art. 13 AI Act), human oversight (art. 14 AI Act), and accuracy (art. 15 AI Act). Drawing inspiration from these requirements, the presentation seeks to assess how to ensure the improvement of competition law proceedings while safeguarding fundamental rights.

Jérôme De Cooman is Ph.D. candidate under the supervision of Prof. Dr. Nicolas Petit (European University Institute, Italy) and Prof. Dr. Pieter Van Cleynenbreugel (University of Liege, Belgium). His research focuses on whether, how, and when to regulate technologies (artificial intelligence in particular). As part of his Ph.D. research, Jerome pays very particular attention to the modernisation of competition law proceedings and the algorithmic shift in the fight against cartelisation.
Jérôme is currently a Visiting Student at European University Institute studying the path dependence of regulations.
Jérôme is also teaching assistant at University of Liege since 2018 in EU Competition Law and EU law, (Big) Data and AI Applications courses. Since 2021, he is Administrative Manager at the Brussels School of Competition, Junior Editor for the Yearbook of Antitrust and Regulatory Studies (YARS) at the Centre for Antitrust and Regulatory Studies (CARS, University of Warsaw, Poland), and Junior Member of the Academic Society for Competition Law (ASCOLA).
Jérôme holds a Master of Laws from the University of Liege (2017), a Master of Management Sciences from HEC-Liege (2018), and the Law, Cognitive & Artificial Intelligence Technology Programme Certification from the Brussels School of Competition (2019).