Artificial intelligence recommendations: evidence, issues, and policy

被引：0

作者：

Calvano, Emilio ^{[1
,2
,3
,4
]}

Calzolari, Giacomo ^{[4
,5
]}

Denicolo, Vincenzo ^{[4
,6
]}

Pastorello, Sergio ^{[6
]}

机构：

[1] Univ LUISS, Rome, Italy

[2] Einaudi Inst Econ & Finance, Rome, Italy

[3] Toulouse Sch Econ, Toulouse, France

[4] CEPR, Paris, France

[5] Bologna Univ, European Univ Inst, Bologna, Italy

[6] Bologna Univ, Bologna, Italy

来源：

OXFORD REVIEW OF ECONOMIC POLICY | 2025年 / 40卷 / 04期

关键词：

artificial intelligence; recommendation systems; search; price competition; platforms; regulation;

D O I：

10.1093/oxrep/grae048

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：843 / 853

页数：11

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