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‘Big data’ and ‘big tech’ have become central topics in recent antitrust debate and regulation. For example, the Competition and Markets Authority (CMA) recently published a report on online platforms, expressing concerns that the major platforms like Google are now protected from competition by such strong incumbency advantages. Underlying the CMA's theory of harm is the essential facility theory of antitrust, under which Google's ability to control access to its click-and-query data is seen as preventing its rivals from competing effectively. EU jurisprudence has identified three criteria to determine whether data are an essential facility and whether access should be mandated. First, the data must be indispensable to compete in the market. Secondly, absent data sharing, technical improvements by competitors must be hampered or precluded. Thirdly, there must be no objective justification to refuse competitors access to the data. It is difficult to reconcile the authorities’ concerns with Google's click-and-query data with these criteria, however. Actual and potential alternatives exist; Google's competitors have been innovating in the search market for more than a decade; and there are objective reasons to limit data access, including threats to innovation and privacy concerns.

In the modern economy, algorithms influence many aspects of our lives, from how much we pay for groceries and what adverts we see, to the decisions taken by health professionals. As is true with all new technologies, algorithms bring new economic opportunities and make our lives easier, but they also bring new challenges. Indeed, many competition authorities have voiced their concerns that under certain circumstances algorithms may harm consumers, lead to exclusion of some competitors and may even enable firms (knowingly or otherwise) to avoid competitive pressure and collude. In this article, we explain how algorithms work and what potential benefits and harms they bring to competition.