Mathematical foundations of moral preferences

Article


Capraro, V. and Perc, M. 2021. Mathematical foundations of moral preferences. Journal of The Royal Society Interface. 18 (175), pp. 1-13. https://doi.org/10.1098/rsif.2020.0880
TypeArticle
TitleMathematical foundations of moral preferences
AuthorsCapraro, V. and Perc, M.
Abstract

One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary payoffs of others. However, during the last ten years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment, and trustworthiness are in fact better explained by preferences for following one’s own personal norms – internal standards about what is right or wrong in a given situation. Beyond better organ- ising various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.

KeywordsBiotechnology, Biophysics, Biochemistry, Bioengineering, Biomaterials, Biomedical Engineering
PublisherThe Royal Society
JournalJournal of The Royal Society Interface
ISSN1742-5689
Electronic1742-5662
Publication dates
Online10 Feb 2021
Print28 Feb 2021
Publication process dates
Deposited18 Jan 2021
Accepted20 Jan 2021
Output statusPublished
Accepted author manuscript
Copyright Statement

© 2021 The Author(s)
This is an Accepted Manuscript of an article published by the Royal Society in the Journal of The Royal Society Interface, the final published version is available at: https://doi.org/10.1098/rsif.2020.0880. The accepted manuscript is made available in this repository as permitted by the publisher.

Digital Object Identifier (DOI)https://doi.org/10.1098/rsif.2020.0880
LanguageEnglish
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