In Conversation with Mariana Mazzucato, Tim O’Reilly and Ilan Strauss on Algorithmic Attention Rents

Описание к видео In Conversation with Mariana Mazzucato, Tim O’Reilly and Ilan Strauss on Algorithmic Attention Rents

A conversation about how today’s big tech platforms use the power they hold over the attention of billions of users to shape the markets in which they participate for their own benefit.

In their work, Tim O’Reilly (Founder and CEO of O’Reilly Media), Ilan Strauss and Mariana Mazzucato (UCL Institute for Innovation and Public Purpose) advance a theory of algorithmic attention rents. This explores the way that as platforms grow, they become increasingly capable of extracting rents from users and suppliers through algorithmic control over attention. The report focuses on advertising models that harvest, monetize, and resell attention, but the work has relevance to other online business models. It calls for regulation that mandates the disclosure of metrics that platforms use to measure attention and the details of how that attention is monetised.

The article has been published in Data & Policy, a peer-reviewed, open-access journal at Cambridge University Press published in association with Data for Policy, a Conference series dedicated to the impact of data science on governance. In this event, the authors discuss the work and the process through which it was produced with Zeynep Engin and Jon Crowcroft, Editors-in-Chief of Data & Policy.

Authors: Tim O’Reilly | Founder and CEO of O'Reilly Media Mariana Mazzucato | Professor in the Economics of Innovation and Public Value at UCL; Founding Director at the Institute for Innovation and Public Purpose, UCL Ilan Strauss | Senior Research Associate at the Institute for Innovation and Public Purpose, UCL Hosts: Zeynep Engin | Chair, Director and co-Founder of Data for Policy; UCL Department of Computer Science Jon Crowcroft | University of Cambridge & The Alan Turing Institute; co-Founder of Data for Policy

Read the article: https://doi.org/10.1017/dap.2024.1
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