The Labor of Cringe: Value Capture and the Performativity of Algorithms in Online Cultural Production

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Abstract

Algorithms shape culture, but how? Algorithms are now so intertwined with markets, workplaces, and media that scholars describe them as part of our social systems of meaning-making. This article shows how algorithms shape the practical work of making culture via labor process theory. I draw from an ethnography of high-performing content creators who make entertainment videos engineered to go viral on social media, videos they dismiss as so bad they are “cringe,” or personally embarrassing. To explain the puzzle of creators contradicting their own artistic sensibilities, I combine social studies of technology and labor theory to develop a model of creative labor with algorithms. Based on 18 months of ethnography and interviews with 60 viral creators, I show how creators interact with algorithms which steer them into making attention-grabbing content. I trace workers’ algorithmically mediated labor in five steps. First, creators learn to follow metrics over personal taste; second, they adapt to algorithm changes; third, they simplify storylines with stereotypically sexualized and racialized tropes; fourth, they copy past successes; fifth, they experience pleasure in gamified metrics. In the end, I find that content creators transform their standards of quality to align with quantities which are rendered algorithmically. By documenting this labor process which I describe as alienation, adaptation, simplification, replication, and gamification, I show how creative labor results in “value captured” by the platform. Building on theories of financial markets and finance workers, I conclude with a theory of algorithms as performative in cultural production.

Author

• Ashley E. Mears, University of Amsterdam