Hatim Rahman (Kellogg School of Management at Northwestern University)

Control in the Age of Algorithms: Exploring the Cold Start Problem and Reputational Interdependence on Online Labor Markets

Sociologists have developed an intimate understanding of how people navigate traditional labor markets. In my ethnographic study of workers in one of the largest online labor platform markets, I found people were confronted with challenges that existing theory does not adequately account for, in part because online platforms primarily rely on algorithms to control people's mobility in these labor markets. First, in the absence of existing social ties on the platform, I found inexperienced workers encounter the "cold start" problem, which I characterize as an algorithm having difficulty recommending new workers to jobs because they have no prior rating evaluations or data for the algorithm to base a recommendation upon. Second, for experienced workers who obtain a rating evaluation, the platform's algorithms create what I call "reputational interdependence": the platform's algorithms share workers' rating evaluations within and across other digital platforms and organizations, without workers' consent. Together, I theorize how platforms' use of algorithms to control workers challenges both new and experienced workers' mobility on online labor markets in ways that depart from prior literature, and the consequences these challenges have for workers' careers.