Article 101 TFEU’s Association of Undertakings Notion and Its Surprising Potential to Help Distinguish Acceptable from Unacceptable Algorithmic Collusion

• Published date: 01 September 2020
• Author: Pieter Van Cleynenbreugel
• Date: 01 September 2020
• DOI: 10.1177/0003603X20929116

Article

Article 101 TFEU’s Association

of Undertakings Notion and

Its Surprising Potential to

Help Distinguish Acceptable

from Unacceptable

Algorithmic Collusion

Pieter Van Cleynenbreugel*

Abstract

The machine learning capabilities of new technologies raise provocative questions and challenges for

the development of competition law within the digital economy. Academic discussions have focused on

how antitrust law should avoid, anticipate, and respond to such behavior. The predominant emerging

narrative is that antitrust law, in its current form, is unable to distinguish between acceptable and

unacceptable algorithmic collusion. The purpose of this article is to challenge that claim in the context

of Article 101 Treaty on the Functioning of the European Union (EU). The reference within Article 101

TFEU to “associations of undertakings” plays a crucial role in that regard and offers a promising tool to

better identify and regulate forms of unacceptable algorithmic collusion. Against that background, this

article will propose an alternative compliance-focused way forward that could be set up without

requiring modifications to the EU legal framework.

Keywords

digital platforms, algorithmic collusion, associations of undertakings, co-regulation, EU competition law

enforcement

I. Introduction

The machine learning capabilities associated with the introduction of new digital technologies have

captured the imagination of competition law scholars globally. Fears of algorithmic collusion—

namely, anticompetitive behavior linked to self-learning algorithms, which may arise with little or

no human intervention—have given rise to debates about where to draw, and whether to redraw more

*Li`

ege Competition and Innovation Institute, University of Li`

ege, Liege, Belgium

Corresponding Author:

Pieter Van Cleynenbreugel, Li`

ege Competition and Innovation Institute, University of Li`

ege, Quartier Agora, Place des Orateurs,

1, Bˆ

at. B 33, BE-4000 Liege, Belgium.

Email: pieter.vancleynenbreugel@uliege.be

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2020, Vol. 65(3) 423–444

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DOI: 10.1177/0003603X20929116

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firmly, the line between acceptable and unacceptable forms of coordinated market behavior.

1

The

typical response among those who believe that algorithmic collusion requires an immediate regulatory

response is either that technology must be reined in or that the antitrust laws must be extended. More

skeptical voices, however, argue that any modification of the existing legal framework should be

postponed at least until it is clearly established that machine learning technologies are indeed able to

trigger collusive behavior, so that it is possible to better define when such behavior should be deemed

unacceptable in antitrust terms. From both perspectives, however, the predominant general perception

is that the current antitrust framework must be modified or stre tched to some extent. Within the

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424 The Antitrust Bulletin 65(3)