Whose Bias is it, Anyway? The Need for a Four-Eyes Principle in AI-Driven Competion Law Proceedings - Jerome De Cooman (European Papers)
(Series Information) European Papers - A Journal on Law and Integration, 2024 9(3), 998-1016 | Article | (Table of Contents) I. Introduction. – II. Biases and noise: mapping the debate. – II.1. Cognitive biases. – II.2. Noise. – II.3. Bias and noise in competition law procedure. – III. The promises: debiasing, accelerating, prioritizing. – IV. The pitfalls: biasing again. – V. The need for a four-eyes principle. – VI. Conclusion. | (Abstract) Artificial Intelligence (hereafter, ‘AI’) systems are widely adopted by public administrations. Competition law does not escape the rule. This is unsurprising, given AI systems promise to address well-documented flaws in human decision-making, e.g. arbitrariness or bias. What is more, AI systems carries the potential to strengthen ex officio investigations. AI-driven cartel screening flags indicators of collusion that then trigger the need for further investigation. This Article does not discard hat AI systems increase effectiveness that in turn increase substantive fairness. Rather, it questions whether increasing effectiveness with AI systems has an impact on procedural fairness. The argument is that although the use of algorithms increases procedural fairness by removing noise and cognitive biases from the decision-making process, the overall impact on procedural fairness remains far from clear given that the introduction of AI systems in public administration might perniciously generates new type of biases or harmful behaviours. This Article suggests that a four-eyes principle is a workable solution to mitigate that pitfall.