Skip to main content
Kent Academic Repository

People expect artificial moral advisors to be more utilitarian and distrust utilitarian moral advisors

Myers, Simon, Everett, Jim A.C. (2025) People expect artificial moral advisors to be more utilitarian and distrust utilitarian moral advisors. Cognition, 256 . Article Number 106028. ISSN 0010-0277. E-ISSN 1873-7838. (doi:10.1016/j.cognition.2024.106028) (KAR id:108149)

Abstract

As machines powered by artificial intelligence increase in their technological capacities, there is a growing interest in the theoretical and practical idea of artificial moral advisors (AMAs): systems powered by artificial intelligence that are explicitly designed to assist humans in making ethical decisions. Across four pre-registered studies (total N = 2604) we investigated how people perceive and trust artificial moral advisors compared to human advisors. Extending previous work on algorithmic aversion, we show that people have a significant aversion to AMAs (vs humans) giving moral advice, while also showing that this is particularly the case when advisors - human and AI alike - gave advice based on utilitarian principles. We find that participants expect AI to make utilitarian decisions, and that even when participants agreed with a decision made by an AMA, they still expected to disagree with an AMA more than a human in future. Our findings suggest challenges in the adoption of artificial moral advisors, and particularly those who draw on and endorse utilitarian principles - however normatively justifiable.

Item Type: Article
DOI/Identification number: 10.1016/j.cognition.2024.106028
Uncontrolled keywords: artificial intelligence; utilitarianism; person perception; algorithm aversion
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Divisions > Division of Human and Social Sciences > School of Psychology
Funders: Economic and Social Research Council (https://ror.org/03n0ht308)
Depositing User: Katherine Bellenie
Date Deposited: 12 Dec 2024 10:16 UTC
Last Modified: 13 Dec 2024 11:35 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/108149 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.