In the digital age, the intersection of data, technology, and antitrust enforcement has brought algorithms into focus as potential tools for uncovering anticompetitive practices and improving decision-making. However, concerns about algorithmic bias have raised questions about their use in this critical field. This article examines the balance between the benefits of algorithms in antitrust enforcement and the genuine concerns surrounding bias. It argues that while algorithmic bias should not be ignored, algorithms can be valuable tools when carefully designed, and the overemphasis on bias concerns stems from a lack of technical understanding. The article explores the use of algorithms in law enforcement, highlights the risks of bias, and presents how algorithmic design can mitigate these concerns. It then delves into the specific context of antitrust enforcement, explaining why the problem of algorithmic bias is less relevant compared to other regulatory areas. By offering a nuanced perspective on the potential and threats of algorithmic tools, the article contributes to the ongoing discourse on the responsible and effective utilization of algorithms in antitrust enforcement.

By Holli Sargeant & Teodora Groza[1]

 

I. INTRODUCTION

In the digital age, where data and technology permeate every facet of our lives, the field of antitrust enforcement finds itself at a crossroads. As policymakers and regulators grapple with the ever-evolving landscape of digital mark

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