2023/12/11 by Armin Granulo, Sara Caprioli, Christoph Fuchs +1 · 1 voice · 2 citations
Psychology · Social Sciences · #Behavioral Health and Interventions #Evolutionary Psychology and Human Behavior #Experimental Behavioral Economics Studies
paper · doi:10.1016/j.chb.2023.108094
openalex publication_date 2023/12/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Thanks to advances in artificial intelligence, firms increasingly deploy algorithms in a wide range of management tasks (e.g., evaluating workers' performance). Scholars and major political institutions have therefore called for a better understanding of the behavioral and psychological consequences of this phenomenon. In this research, we investigate how deploying algorithms in management tasks affects prosocial motivation, a crucial dimension of workplace productivity and social interactions. Across five pre-registered studies (N = 3,153, Mage = 33.96, SDage = 11.89; 51% female), including field and experimental data, we find that deploying algorithms (vs. humans) in management tasks reduces employees’ prosocial motivation (e.g., the desire to help others). We demonstrate that this negative effect (i) occurs because management by algorithms leads to greater objectification of others, (ii) also occurs when algorithms perform tasks together with human managers, and (iii) depends on the type of management task algorithms perform. These findings add another layer to the political, academic, and organizational debate on algorithmic management.