Algorithms and economic choices

ABSTRACT:

In the modern economy, consumption and other important economic choices are increasingly shaped by algorithms powered by artificial intelligence (AI). Despite their importance, relatively little is known about the economic effects of these algorithms, their normative desirability and any consequent economic policy prescriptions. This research proposal is based on two interlinked project components both studying the economic consequences of deploying popular classes of AI-powered algorithms.

The first component focuses on Recommender Systems (RS). These are algorithms that estimate user preferences over a given set of items and use these estimates to match users to items. Amazon, Netflix, Youtube, Spotify and social media apps are popular commercial applications of this technology allowing to filter items (products, media, user posts) to produce personalized experiences. Another prominent application is the advertising business. The main goal of the first component is to conduct an experimental analysis of RS in the spirit of Calvano, Calzolari, Denicolò and Pastorello (2020, American Economic Review). We plan to build simplified but reasonably realistic RSs and analyze the way their recommendations evolve in different economic settings. We also plan to analyze how firms' and consumers' behavior changes in the presence of RSs, studying in particular whether recommendations are biased and in what direction, whether the presence of RS intensifies or attenuates competition, and how it changes the competitive landscape, affecting the relative position of incumbents and entrants.

Other Research Units: 

• Emilio Calvano, Università degli Studi di Roma "Tor Vergata"
• Vincenzo Denicolo', Università degli Studi di Bologna