"It is a hypothesis that not all algorithms will have been to law school. So maybe there is a few out there who may get the idea that they should collude with another algorithm who haven't been to law school either […] So of course, we would like to have our own algorithms to be out there, looking into the market, figuring out if there has been collusion taking place."  Introduction 1. Pricing algorithms  have historically been developed in the financial sector, transportation and more recently in online commerce. They are now spreading to many sectors of the economy and are capable of processing a wide range of real-time market data such as competitor prices, demand, availability of substitute products, or the price sensitivity of different consumer groups.  While some
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Digital technologies can have both positive and negative effects on competition. The consumer benefits fully from the effect of increased transparency and competition through the posting of rates online. Nevertheless, the consumer could be harmed by the facilitating effect of algorithms in the implementation of a classic cartel (explicit cartel) or of an alignment generated by an indirect form of communication between algorithms (tacit cartel). The emergence of self-learning algorithms that define the best strategy for price optimization could duplicate the human reasoning that leads to cartels. However, European competition law, which firmly prohibits agreements or practices that restrict competition under Article 101 TFEU, is still based on proof of intentional and explicit collusion via contacts between natural and legal persons, which excludes a priori the simple tariff alignment via algorithms. This article aims to take stock of the main real and potential competitive problems posed by possible algorithmic collusion and to evaluate possible avenues for the implementation of "innovative regulation" adapted to these collusive risks. The idea of regulating ex ante the compliance of algorithms or ex post by changing the legal regime or strengthening the digital tools of proof of "tacit collusion" will be discussed. Finally, an innovative approach could be to develop the algorithms themselves in order to allow near real-time monitoring of markets without having access to the company’s algorithm.
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