Partner or Rival? How Human-Artificial Intelligence Conflict Shapes Artificial Intelligence Aversion

• 成果类型: Article
• 署名作者: Ansari, Kimia; Ghasemaghaei, Maryam
• 署名单位: University of Manitoba; University of Manitoba I.H. Asper School of Business; McMaster University
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222; 1557-928X
• DOI: 10.1080/07421222.2026.2647459
• 发表日期: 2026-04-03
• 页码: 368-401
• 关键词: Artificial intelligence; human-AI conflict; human-AI goal interdependence; Cognitive dissonance; epistemic motivation; social motivation; AI aversion; decision criticality; cognitive-dissonance; field experiment; INFORMATION; interdependence; management; systems; teams; ai

摘要

Integrating artificial intelligence (AI) into organizations introduces challenges, particularly when AI-generated recommendations conflict with human judgment. Drawing on the theory of cooperation and competition and cognitive dissonance theory, we examine how human-AI conflict (low vs. high) and human-AI goal interdependence (cooperation vs. competition) shape cognitive dissonance and AI aversion across critical and non-critical decisions. Using an experiment with 432 employees, results show that higher human-AI conflict increases cognitive dissonance, which in turn reduces epistemic and social motivation and heightens AI aversion. The impact of human-AI conflict on cognitive dissonance intensifies when AI is perceived as a competitor and when decisions are critical. Moreover, in critical decisions, perceiving AI as a competitor amplifies the dissonance arising from human-AI conflict, whereas in non-critical decisions, cooperative and competitive perceptions of AI produce similar dissonance levels. These findings underscore the importance of aligning AI deployment with users' relational perceptions and decision criticality.