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It’s that the NIST databases foreshadow the emergence of a logic that — Kate Crawford

"It’s that the NIST databases foreshadow the emergence of a logic that has now thoroughly pervaded the tech sector: the unswerving belief that everything is data and is there for the taking. It doesn’t matter where a photograph was taken or whether it reflects a moment of vulnerability or pain or if it represents a form of shaming the subject. It has become so normalized across the industry to take and use whatever is available that few stop to question the underlying politics.”"
Kate Crawford
Kate Crawford
Kate Crawford
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Kate Crawford is an Australian researcher, writer and academic who studies the social and political implications of artificial intelligence. She is based in New York and works as a principal researcher at Microsoft Research. She is the co-founder and former director of research at the AI Now Institute at NYU, former visiting professor at the MIT Center for Civic Media, previous senior fellow at th

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"In one case, Amazon negotiated a memorandum of understanding with a police department in Florida, discovered through a public records request filed by journalist Caroline Haskins, which showed that police were incentivized to promote the Neighbors app and for every qualifying download they would receive credits toward free Ring cameras. The result was a “self-perpetuating surveillance network: more people download Neighbors, more people get Ring, surveillance footage proliferates, and police can request whatever they want,” Haskins writes. Surveillance capacities that were once ruled over by courts are now on offer in Apple’s App Store and promoted by local street cops. As media scholar Tung-Hui Hu observes, by using such apps, we “become freelancers for the state’s security apparatus."
Kate CrawfordKate Crawford
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"What epistemological violence is necessary to make the world readable to a machine learning system? AI seeks to systematize the unsystematizable, formalize the social, and convert an infinitely complex and changing universe into a Linnaean order of machine-readable tables. Many of AI’s achievements have depended on boiling things down to a terse set of formalisms based on proxies: identifying and naming some features while ignoring or obscuring countless others. To adapt a phrase from philosopher Babette Babich, machine learning exploits what it does know to predict what it does not know: a game of repeated approximations. Datasets are also proxies—stand-ins for what they claim to measure. Put simply, this is transmuting difference into computable sameness.”"
Kate CrawfordKate Crawford