Algorithmic management diminishes status: An unintended consequence of using machines to perform social roles

Abstract

As artificial intelligence (AI) proliferates throughout society, it brings the potential to reshape how people perceive social roles and relationships. Across five preregistered studies, we investigated how AI-based algorithmic management influences perceptions and forecasts of social status. We found that people believe algorithmic management, compared to prototypical human management, leads to lower status in the eyes of others (Study 1). Moreover, forecasts of lower status mediated people's anticipated negative emotions when assessing remote jobs that were framed as primarily algorithmically managed (Study 2). Further, we found that people infer lower status given algorithmic management because they believe it signals that job tasks lack complexity, both when evaluating themselves or others (Studies 3 and 4). Finally, using OpenAI's natural language processing algorithm (GPT-3), we created an actual managerial algorithm and found that the lowered status inferences persist when people are managed by an algorithm that provides instructions, feedback, and monetary incentives (Study 5). We discuss theoretical implications for research on status, hierarchy, and the psychology of technology.