Can Self-Preferencing Algorithms Be Pro-Competitive?

In response to the growing concerns around artificial intelligence, algorithms, and their influence over consumers’ choices, competition authorities have adopted more stringent rules regarding self-preferencing algorithms used by digital platforms. However, from a theoretical perspective, self-preferencing algorithms can have pro-competitive benefits. There is no consensus from the economic literature on whether pro-competitive benefits or possible anti-competitive considerations prevail in the context of self-preferencing algorithms used by digital platforms. Determining the net impact of recommendation algorithms on competition and consumer welfare requires individualized analysis accounting for the workings of specific algorithms, competitive context, and market environment.

By Emilie Feyler & Veronica Postal^[1]

The role of algorithms and artificial intelligence (“AI”) with respect to people’s consumption choices and everyday decision-making has been growing hand-in-hand with the size of the digital economy. For example, about 80 percent of the content streamed on Netflix is the result of algorithmic recommendation, while only 20 percent is streamed through active user search.^[2] The public launch of ChatGPT in November 2022 has pushed the boundary of what people believed AI systems could achieve further than ever. While the advances in deep learning technologies and their application to a wide range of industries opens numerous opportunities, the use