Despite a growing interest in how prevailing influences of algorithmic systems are being resisted, debates about algorithmic resistance unfold within conceptually diverse but disconnected scholarly conversations. Adopting a new materialist ontology, this integrative review traces algorithmic resistance’s multiple conceptualizations across a growing interdisciplinary landscape. Academic publications are understood and analyzed as the outputs of research-machines: assemblages of theories, methods, technologies, researchers, disciplinary norms, and institutional logics that collectively produce particular visions of algorithmic resistance (while muting others). Reviewing 106 items, this study analyzes how diverging understandings of algorithmic resistance and its properties are territorialized within particular problem spaces: configurations of agencies, problematizations, and locations. Seven contrasting clusters of research-machines are identified (e.g.,Algorithm Aversion, Mundane Opposition, or Epistemic and Ontological Refusal) according to their shared productions of algorithmic resistance. Properties of these outputs are understood along six essential axes (intentionality, scale, visibility, materiality, temporality, relationality) and arranged into a provisional topography of intensities, silences, overlaps, and tensions within current scholarship on algorithmic resistance. This review offers two principal contributions: First, it provides an integrative perspective on the fragmented landscape of interdisciplinary scholarship that reveals how algorithmic resistances are produced within specific problem spaces and unfold along a topography of properties. Second, it advances a conceptual understanding of research-machines that sensitizes toward knowledge practices as sites at which the conditions and capacities of resistance to algorithmic power are constituted and configured.
