How does Value Similarity affect Human Reliance in AI-Assisted Ethical Decision Making?

  • Saumik Narayanan
  • , Guanghui Yu
  • , Chien Ju Ho
  • , Ming Yin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper explores the impact of value similarity between humans and AI on human reliance in the context of AI-assisted ethical decision-making. Using kidney allocation as a case study, we conducted a randomized human-subject experiment where workers were presented with ethical dilemmas in various conditions, including no AI recommendations, recommendations from a similar AI, and recommendations from a dissimilar AI. We found that recommendations provided by a dissimilar AI had a higher overall effect on human decisions than recommendations from a similar AI. However, when humans and AI disagreed, participants were more likely to change their decisions when provided with recommendations from a similar AI. The effect was not due to humans' perceptions of the AI being similar, but rather due to the AI displaying similar ethical values through its recommendations. We also conduct a preliminary analysis on the relationship between value similarity and trust, and potential shifts in ethical preferences at the population-level.

Original languageEnglish
Title of host publicationAIES 2023 - Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery, Inc
Pages49-57
Number of pages9
ISBN (Electronic)9798400702310
DOIs
StatePublished - Aug 8 2023
Event2023 AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2023 - Montreal, Canada
Duration: Aug 8 2023Aug 10 2023

Publication series

NameAIES 2023 - Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

Conference

Conference2023 AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2023
Country/TerritoryCanada
CityMontreal
Period08/8/2308/10/23

Keywords

  • AI ethics
  • ethical preference
  • human reliance on AI

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