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Artificial intelligence recommendations: evidence, issues, and policy

Author

Listed:
  • Emilio Calvano
  • Giacomo Calzolari
  • Vincenzo Denicolò
  • Sergio Pastorello

Abstract

Recommender systems (RS) enhance user experiences by providing personalized content and are widely used by popular services like Apple Music, Spotify, Netflix, and YouTube to increase user engagement. However, these systems can also have significant economic implications, including exacerbating market concentration and reducing content diversity. This paper reviews recent economic literature on RS, emphasizing their dual role as both beneficial tools and potential sources of market distortion. The paper underscores the necessity for policies informed by economic research to balance the benefits of RS against their associated risks.

Suggested Citation

  • Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2024. "Artificial intelligence recommendations: evidence, issues, and policy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 40(4), pages 843-853.
    • Handle: RePEc:oup:oxford:v:40:y:2024:i:4:p:843-853.
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    File URL: http://hdl.handle.net/10.1093/oxrep/grae048
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