Paper Number

ICIS2025-2308

Paper Type

Short

Abstract

AI-powered workplace surveillance is increasingly becoming the new normal in organizations. Despite its touted benefits, such as operational efficiency, cost reduction, and security protection, compliance with AI-surveillance remains a significant challenge. Key concerns include fairness, privacy, ethical issues, accuracy, and data security. Grounded in the Cognitive-Motivational-Relational Theory of Emotion and Self-Determination theories, the study employs a survey research method to investigate how employee perceptions of AI surveillance transparency, emotional responses and their psychological needs influence behavioral intent to comply with AI surveillance. Using covariance-based structural equation modeling (SEM), the findings are expected to contribute to the emerging scholarship on workplace AI surveillance. It will also provide practical insights to develop fair and transparent AI surveillance practices and policies.

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Dec 14th, 12:00 AM

Fear, Transparency, and Psychological Needs: Shaping Behavioral Intent in AI Workplace Surveillance

AI-powered workplace surveillance is increasingly becoming the new normal in organizations. Despite its touted benefits, such as operational efficiency, cost reduction, and security protection, compliance with AI-surveillance remains a significant challenge. Key concerns include fairness, privacy, ethical issues, accuracy, and data security. Grounded in the Cognitive-Motivational-Relational Theory of Emotion and Self-Determination theories, the study employs a survey research method to investigate how employee perceptions of AI surveillance transparency, emotional responses and their psychological needs influence behavioral intent to comply with AI surveillance. Using covariance-based structural equation modeling (SEM), the findings are expected to contribute to the emerging scholarship on workplace AI surveillance. It will also provide practical insights to develop fair and transparent AI surveillance practices and policies.

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