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Algorithmic Attention Rents: A theory of digital platform market power

Authored by Tim O'Reilly, Dr Ilan Strauss and Professor Mariana Mazzucato

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1 November 2023

Download working paper

果冻影院 Institute for Innovation and Public Purpose (IIPP) Working Paper Series: IIPP WP 2023-10

Authors:

  • Tim O鈥橰eilly聽| Founder,聽CEO, and Chairman of O鈥橰eilly Media | Visiting Professor of Practice at 果冻影院 Institute for Innovation and Public Purpose聽(IIPP)
  • Ilan Strauss | Senior Research Associate | 果冻影院 Institute for Innovation and Public Purpose (IIPP)
  • Mariana Mazzucato聽| Founding Director and Professor in the Economics of Innovation and Public Value | 果冻影院 Institute for Innovation and Public Purpose (IIPP)

Reference:

O鈥橰eilly, T., Strauss, I. and Mazzucato, M. (2023). Algorithmic Attention Rents: A theory of digital platform market power. 果冻影院 Institute for Innovation and Public Purpose, Working Paper Series (IIPP WP 2023-10). Available at: /bartlett/public-purpose/wp2023-10

Abstract:

We outline a theory of algorithmic attention rents in digital aggregator platforms. We explore the way that as platforms grow, they become increasingly capable of extracting rents from a variety of actors in their ecosystems 鈥 users, suppliers, and advertisers 鈥 through their algorithmic control over user attention. We focus our analysis on advertising business models, in which attention harvested from users is monetized by reselling the attention to suppliers or other advertisers, though we believe the theory has relevance to other online business models as well. We argue that regulations should mandate the disclosure of the operating metrics that platforms use to allocate user attention and shape the 鈥渇ree鈥 side of their marketplace, as well as details on how that attention is monetized.