How Big Data Confers Market Power to Big Tech: Leveraging the Perspective of Data Science

Abstract

Data-hungry applications are central to the largest online platforms. Using a novel approach that leverages data science to inform the economics, we demonstrate how data is a source of market power. We highlight the importance of data heterogeneity, whereby small feature differences translate into large value differences. We examine how concept drift, the existence of a nonstationary relationship between the predictive and target variables, implies that access to a continuous stream of data is competitively advantageous. We analyze how an information bottleneck and high sample complexity in existing applications lead to increasing returns to data. Finally, we show how user interaction control enables personalization that raises switching costs. The combined effect is a potent data barrier to entry that endows substantial market power to only the largest online platforms. Competition policy should focus on enabling entrants unfettered access to vast continuous data streams similar to those available to platform incumbents.

Shayne Longpre

Applied ML Scientist (NLP)

My research interests include AI/ML/NLP, and the governance of AI platforms.