(Mis)understanding Algorithmic Collusion

For a few years now, there has been a lot of talk about pricing algorithms and their potential for collusion. This article first provides a simple typology of pricing algorithms, in order to take away much of the confusion that is still surrounding the debate. It then goes on to discuss three potential misunderstandings: (i) that there are basically no cases involving algorithmic collusion and hence that there is no real problem; (ii) that nothing changes, legally speaking, if algorithms collude instead of humans; and (iii) that truly autonomous algorithmic collusion is still science fiction. It closes off with a discussion on the need for more empirical evidence.

By Timo Klein¹

“I think we need to make it very clear that companies can’t escape responsibility for collusion by hiding behind a computer program.”

– Margrethe Vestager, European Commissioner for Competition.²

I. INTRODUCTION

In their well-known 2016 book Virtual Competition, Ariel Ezrachi & Maurice Stucke prophesized that algorithms may lead to the end of competition as we know it.³ For instance, the rise of pricing algorithms may enable competing firms to much more effectively implement price agreements. Moreover, advanced self-learning algorithms may at some point even learn by themselves that it is optimal to collude, without any prior instructions. Authorities risk becoming powerless in the face of advanced AI cartels.

This provocative thesis has proven immensely effective in b