Examining Algorithmic Metrics and their Effects through the Lens of Reactivity

Algorithmic systems that provide quantitative assessments of labor practices have proliferated in response to growing calls for accountability and transparency. Workers, according to the existing literature, are able to make sense of algorithmic metrics and even find ways to manipulate them. Human reactions like these show how metrics for tracking and measuring labor productivity can have unintended consequences, such as gaming the system, beyond the original goal of collecting accurate data on worker output. However, these metrics’ effects have not been much discussed from the perspective of reactivity. Drawing from Espeland and Sauder’s work theorizing reactivity to measures, I offer a deeper understanding of responses to algorithmic systems. Distilling three intertwined facets from their insights—quantification towards accountability, agency, and reflexivity—I frame my fieldwork findings on warehouse workers’ experiences with labor-tracking technologies. I describe the patterns of algorithmic system effects. Lastly, I explore potential design directions, viewed through the lens of reactivity.