Human bias in algorithm design

Carey K. Morewedge (), Sendhil Mullainathan, Haaya F. Naushan, Cass R. Sunstein, Jon Kleinberg, Manish Raghavan and Jens O. Ludwig
Additional contact information
Carey K. Morewedge: Boston University
Haaya F. Naushan: The World Bank
Cass R. Sunstein: Harvard University
Jon Kleinberg: Cornell University
Manish Raghavan: MIT Sloan School of Management, MIT
Jens O. Ludwig: University of Chicago

Nature Human Behaviour, 2023, vol. 7, issue 11, 1822-1824

Abstract: Algorithms are designed to learn user preferences by observing user behaviour. This causes algorithms to fail to reflect user preferences when psychological biases affect user decision making. For algorithms to enhance social welfare, algorithm design needs to be psychologically informed.

Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.nature.com/articles/s41562-023-01724-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nathum:v:7:y:2023:i:11:d:10.1038_s41562-023-01724-4

Ordering information: This journal article can be ordered from
https://www.nature.com/nathumbehav/

DOI: 10.1038/s41562-023-01724-4

Access Statistics for this article

Nature Human Behaviour is currently edited by Stavroula Kousta

More articles in Nature Human Behaviour from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().