The unintended consequences of AI adoption: How moral displacement and ethical numbing suppress pro-environmental behavior at work

초록

Despite the growing consensus that artificial intelligence (AI) serves as a critical enabler of organizational sustainability, the potential friction between algorithmic rationality and human moral agency remains underexplored. Drawing upon the Social Cognitive Theory of Moral Agency, this study investigates the indirect behavioral costs of algorithmic integration, whereby AI adoption suppresses employees' pro-environmental behavior at work (PEBW). It proposes a theoretical framework where cognitive offloading to algorithms demonstrates that AI functions as a quasi-agent that facilitates the displacement of responsibility and subsequent ethical numbing, diminishing the motivational basis for voluntary green behaviors. Analysis of four-wave timelagged data from 381 employees indicates that AI adoption is negatively associated with PEBW through this serial mediation pathway. However, this detrimental trajectory is not inevitable. The study identifies Corporate Responsible AI (CRAI), characterized by transparency, accountability, and fairness, as a vital structural boundary condition. The findings reveal that robust CRAI governance effectively attenuates the initial displacement of responsibility, mitigating the negative indirect effect of AI on PEBW. By shifting the theoretical lens from resource depletion to the loss of moral ownership, this research highlights the necessity of structural governance in preserving human agency amid digital transformation.

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