The Transparency Paradox: How AI Explanations Reduce Perceived Autonomy in Organizational Decision-Making

Abstract: Artificial intelligence transparency is widely assumed to enhance user experience, yet this study reveals a paradox: detailed AI explanations reduce perceived autonomy. In a between-subjects experiment (N = 557), business students made organizational decisions with either transparent AI recommendations (detailed rationales) or basic recommendations (minimal explanation). Participants receiving detailed explanations reported significantly lower autonomy (M = 3.73) than those receiving basic recommendations (M = 3.84), d = -0.19. Personality substantially moderated effects: Openness to Experience reversed the paradox (interaction = -0.227), with intellectually curious individuals benefiting from transparency, while Extraversion amplified autonomy reduction (interaction = 0.173). Males showed twice the autonomy reduction of females (0.137 vs. 0.063), and effects disappeared by ages 23-25. Neither AI familiarity, attitudes, nor decision complexity moderated effects, suggesting fundamental psychological responses. Despite reduced autonomy, participants maintained positive AI attitudes, revealing dissociation between momentary decision control and general acceptance. Findings challenge universal transparency mandates and suggest personality-adaptive systems may better serve diverse users.

Keywords: Human–AI Integration, Autonomy Gap, Business Decision-Making, Transparency, Trust in Intelligent Systems

DOI: 10.54941/ahfe1007091

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