Work

Why Do Decision Makers (Not) Use AI? A Cross-Domain Analysis of Factors Impacting AI Adoption

Year: 2025

Type: conference-paper

Abstract: Growing excitement around deploying AI across various domains calls for a careful assessment of how human decision-makers interact with AI-powered systems. In particular, it is essential to understand when decision-makers voluntarily choose to consult AI tools, which we term decision-maker adoption. We interviewed experts across four domains—medicine, law, journalism, and the public sector—to explore current AI use cases and perceptions of adoption. From these interviews, we identify key factors that shape decision-maker adoption of AI tools: the decision-maker's background, perceptions of the AI, consequences for the decision-maker, and perceived implications for other stakeholders. We translate these factors into an AI adoption sheet to analyze how decision-makers approach adoption choices through comparative, cross-domain case studies, highlighting how our factors help explain inter-domain differences in adoption. Our findings offer practical guidance for supporting the responsible and context-aware deployment of AI by better accounting for the decision-maker's perspective.

Source: Proceedings of the AAAI/ACM Conference on AI Ethics and Society

DOI: 10.1609/aies.v8i3.36758

Authors: Rebecca Yu, Valerie Chen, Ameet Talwalkar, Hoda Heidari

Institution: Carnegie Mellon University

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: bronze

Funder: National Science Foundation

Awards: FAI: Fair AI in Public Policy - Achieving Fair Societal Outcomes in ML Applications to Education, Criminal Justice, and Health and Human Services, AI Institute for Societal Decision Making (AI-SDM)