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Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making

Tolmeijer, Suzanne; Christen, Markus; Kandul, Serhiy; Kneer, Markus; Bernstein, Abraham (2022). Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making. In: ACM CHI Conference on Human Factors in Computing Systems (CHI'22), New Orleans, LA, USA, 29 April 2022 - 5 May 2022. ACM Press, 1-17.

Abstract

While artificial intelligence (AI) is increasingly applied for decision- making processes, ethical decisions pose challenges for AI applica- tions. Given that humans cannot always agree on the right thing to do, how would ethical decision-making by AI systems be perceived and how would responsibility be ascribed in human-AI collabora- tion? In this study, we investigate how the expert type (human vs. AI) and level of expert autonomy (adviser vs. decider) influence trust, perceived responsibility, and reliance. We find that partici- pants consider humans to be more morally trustworthy but less capable than their AI equivalent. This shows in participants’ re- liance on AI: AI recommendations and decisions are accepted more often than the human expert’s. However, AI team experts are per- ceived to be less responsible than humans, while programmers and sellers of AI systems are deemed partially responsible instead.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:01 Faculty of Theology and the Study of Religion > Center for Ethics
03 Faculty of Economics > Department of Informatics
06 Faculty of Arts > Institute of Philosophy
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:5 May 2022
Deposited On:19 Apr 2022 06:12
Last Modified:06 Mar 2024 14:37
Publisher:ACM Press
ISBN:978-1-4503-9157-3
OA Status:Green
Publisher DOI:https://doi.org/10.1145/3491102.3517732
Official URL:https://doi.org/10.1145/3491102.3517732
Other Identification Number:merlin-id:22358
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