Resisting artificial intelligence, automated-decision making, and algorithmic power: A systematic and narrative review

Despite increased use of Artificial Intelligence (AI) and automated decision-making by governments and employers, an understanding of how users resist them is lacking. We conducted a systematic review of studies capturing algorithmic resistance published between 2000 and 2021, subjecting 7996 to a comprehensive screening process that yielded seven studies for analysis. These studies, focused on digital labor platforms and social media algorithms, showed three themes: how resistance is conceptualized, what forms it takes, and its outcomes. We found that studies of resistance are limited by disparate disciplinary contexts and conceptual redundancy, demanding interdisciplinary dialogue to avoid fragmentation.