Occupational Identity Under Strain: Emotional Dissonance and Professional Alienation in Algorithm-Managed Workplaces

Hochschild’s foundational work on emotional labor (Borah et al., 2024) and recent qualitative studies of alienation (Yılmaz & Kılınç, 2024) both focus on human-to-human organizational dynamics. But as Capitani (2025) and Lăzăroiu et al. (2024) argue, algorithmic management is rewriting the rules. This project would use immersive qualitative methods (e.g., in-depth interviews, digital ethnography) to examine the emotional and professional identity consequences for workers in algorithmically managed environments (think gig workers, call centers, or remote teams with automated performance metrics). The core innovation is to bridge emotional labor theory with contemporary forms of technological alienation, asking: Does algorithmic surveillance amplify emotional dissonance? How do workers maintain (or reconstruct) professional identity and meaning when their primary “manager” is a digital system? This research could develop new theory around the intersection of technology, emotion, and occupational self.

References:

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