(Re)assembling Algorithmic Resistance: An Integrative Review of Research-Machines

Despite a growing interest in how prevailing influences of algorithmic systems are being resisted, debates around algorithmic resistance (AR) remain conceptually fragmented. Adopting a new materialist ontology, this integrative review traces AR’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 AR (while muting others). Reviewing 106 items, this study analyses how diverging understandings of algorithmic resistance and its properties are territorialized by configuring it along specific actors, problematizations, and locations. Seven contrasting clusters of research-machines are identified (e.g., as Algorithmic Aversion, Mundane Opposition, or Epistemic Refusal) according to their shared productions of AR. 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 AR scholarship. 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 towards knowledge practices as sites at which the conditions and capacities of resistance to algorithmic power are constituted and configured.