videoApril 16 2015

Captivating Algorithms: Recommender Systems as Traps

Nick Seaver

Databite No. 33

Kate Crawford has suggested that critics of algorithms suffer from a “metaphor gap” in trying to make sense of how algorithmic systems work. In this conversational provocation, Nick Seaver argues that we can usefully think of recommendation algorithms as a kind of trap, engineered to captivate users. By understanding algorithms as traps and their purpose as captivation, we can draw interpretive resources from the anthropology of animal traps. This provides us with techniques for “reading” traps and understanding their positions vis-à-vis “predators” and “prey,” and it highlights the importance of an “ethics of captivation” for algorithmic systems.

Nick Seaver is an anthropologist who studies how people use technology to make sense of culture. Seaver is an assistant professor in the Department of Anthropology at Tufts University, where he also teaches in the Science, Technology, and Society program. Before that, he got his undergraduate degree in Literature at Yale University, a Masters of Science in Comparative Media Studies from MIT, and a PhD in Anthropology from UC Irvine.

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Data & Society’s “Databites” speaker series presents timely conversations about the purpose and power of technology, bridging our interdisciplinary research with broader public conversations about the societal implications of data and automation.