IDEAS home Printed from https://ideas.repec.org/h/evj/echapt/alma21-03.html

Book Review: Power and Prediction: The Disruptive Economics of Artificial Intelligence (by: Ajay Agrawal, Joshua Gans, Avi Goldfarb)

In: Tanulmányok az információ- és tudásfolyamatokról 21. / Studies on Information and Knowledge Processes 21.

Author

Listed:
  • Levente Szabados

    (Frankfurt School of Finance and Management; University of Sopron)

Abstract

Reviews Agrawal, Gans and Goldfarb's Power and Prediction as an extension of the Prediction Machines framework, focusing on AI as low-cost prediction and on the complementary role of human judgment. It discusses why broad system-level transformation in firms tends to lag behind isolated AI adoption, while also noting limits in the book's treatment of large language models and automation.

Suggested Citation

Handle: RePEc:evj:echapt:alma21-03
DOI: 10.60030/ALMAMS.c202401yyrWaM
as

Download full text from publisher

File URL: https://infota.org/wp-content/uploads/2025/12/tanulmanyok-az-informacio-es-tudasfolyamatokrol-21-studies-on-information-and-knowledge-processes-21.pdf
Download Restriction: no
File URL: https://libkey.io/10.60030/ALMAMS.c202401yyrWaM?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;
;
;
;

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:evj:echapt:alma21-03. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kiss Ferenc (email available below). General contact details of provider: https://infota.org/kiadvanyok/alma-mater/ .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.