Dynamics of Social Harms in an Algorithmic Context

Abstract

Growing evidence suggests that the affordances of algorithms can reproduce socially embedded bias and discrimination, increase the information asymmetry and power imbalances in socio‑economic relations. We conceptualise these affordances in the context of socially mediated mass harms. We argue that algorithmic technologies may not alter what harms arise but, instead, affect harms qualitatively—that is, how and to what extent they emerge and on whom they fall. Using the example of three well-documented cases of algorithmic failures, we integrate the concerns identified in critical algorithm studies with the literature on social harm and zemiology. Reorienting the focus from socio‑economic to socio-econo-technological structures, we illustrate how algorithmic technologies transform the dynamics of social harm production on macro and meso levels by: (1) systematising bias and inequality; (2) accelerating harm propagation on an unprecedented scale; and (3) blurring the perception of harms.