The Bias Cut: Toward a Technopoetics of Algorithmic Systems

Abstract

This essay explores a material engagement with discourses of bias. At a time when the developers of algorithmic systems are exploring concepts of bias like never before, textile bias (or the skew of woven material) offers an alternative view into the scripts of computational engagement. To probe this potential, this essay engages a range of feminist and anti-racist interventions in performance arts, critical archival studies, and my own pedagogical collaborations. With these experiments, I ask, how might material bias inform ongoing analysis of cultural bias within machine learning systems? The experiments reveal interwoven dynamics of power, labor, and historicity with particular attention to complicity and change. Through angular encounters with bias, I explore the development of an emerging technopoetics of algorithmic systems.