Databite No. 33: Nick Seaver

Captivating Algorithms: Recommender Systems as Traps


04.16.15 - 12:00 pm

Data & Society
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New York, NY, 10011

Databites are Data & Society's weekly lunch conversations focused on unresolved questions and timely topics of interest to our community. To request an invitation, please email events at data society dot net.

Nick Seaver on Captivating Algorithms: Recommender Systems as Traps:

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 will argue 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.

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