User acceptance of advice by AI agents : Expectation-system fit perspective

• Main Authors: CAI, Jingyuan, NAH, Fiona Fui-hoon
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: AI agents; AI advice adoption; Advice acceptance; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9992
• Institution: Singapore Management University

Algorithms have increasing influence on our daily decisions, especially when the recommendations are presented by human-like AI agents. This study applies the Theory of Effective Use to investigate how the fit between the user’s role expectation for an AI agent and the agent’s interaction style impacts AI advice adoption. We proposed a new concept termed Perceived Expectation-System Fit (PESF) and empirically examined its impact on user perceptions and advice acceptance. We found that low PESF reduces advice acceptance by diminishing cognitive and affective trust in the AI agent. Furthermore, increased algorithm transparency increases PESF's impact on decision-making. Our findings provide both practical implications and theoretical contributions to our understanding of effective system use in the context of human-AI interaction.