Data-driven algorithms now enable digital labor platforms to automatically manage transactions between thousands of gig workers and service recipients. Recent research on algorithmic management outlines information asymmetries, which make it difficult for gig workers to gain control over their work due a lack of understanding how algorithms on digital labor platforms make important decisions such as assigning work and evaluating workers. By building on an empirical study of Upwork users, I make it clear that users are not passive recipients of algorithmic management. I explain how workers make sense of different automated fea- tures of the Upwork platform, developing a literacy for understanding and working with algorithms. I also highlight the ways through which workers may use this knowledge of algorithms to work around or manipulate them to retain some professional autonomy while working through the platform.

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