This Essay examines racial formation in the context of the digital public sphere with a focus on how artificial intelligence (AI) systems’ understanding of social identities—especially racial identities—translates into real-world policy decisions about “bias,” “risk,” and “impact” as commonly interpreted by industry, government, and philanthropy. Drawing on examples in business advertising and consulting, I illustrate the ethical costs of uncritically integrating the notion of race as a data point, a drop-down menu of physical features one can mix and match. I turn then to three case studies of artist-technologists of color whose work models radical alternatives to techno- instrumentalist notions of race that often invisibly inform the quantification of social justice impact (sometimes referred to as effective altruism or strategic philanthropy). Rashaad Newsome, Amelia Winger-Bearskin, and Catie Cuan challenge discourses that frame racialized populations primarily in terms of negatively “impacted” communities, as the grateful recipients of largesse deserving of “access” to digital tools or technological literacy, or as those who can be best uplifted through the so- called “blessings of scale” and other maximalist approaches to social impact. In radical contrast, these three artist-technologists refigure those “impacted” as agentive co-producers of knowledge and imagination. Their art and performance engage alternative cultural values and metrics that counter the technological vision embracing Mark Zuckerberg’s refrain of “move fast and break things.” Instead, the aesthetic values of friction, duration, and liveness in their work offer counter- narratives and experience to more fully effect both joy and justice in the digital public sphere.
