When Trust Becomes a Crutch: The Biased Effects of Ethical AI on Employee Creativity

Organizations champion ethical AI (EAI) to build trust, assuming fairness fosters creativity. Challenging this consensus, we draw on fairness heuristic theory to propose a fairness trap: high fairness triggers a heuristic that induces cognitive withdrawal, a state of strategic offloading rather than active scrutiny. We predict that this creates a critical tension: while fairness fosters the cognitive flexibility necessary for radical creativity, the triggered withdrawal inhibits incremental creativity by reducing the active scrutiny required for refinement. Study 1’s latent change score analysis (481 employees) showed procedural fairness predicts distributive fairness changes when outcomes are ambiguous, supporting substitutability. Study 2’s experiment (200 participants) confirmed ethical AI boosts distributive fairness via procedural fairness, mediating between cognitive flexibility and withdrawal. Study 3’s multi-wave survey (381 employees and 48 supervisors) validated that distributive fairness and flexibility mediate ethical AI’s positive effect on radical creativity. We contribute to the AI-human collaboration literature by demonstrating that excessive trust in fair systems risks engineering a workforce that is efficient but intellectually passive.