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The Digital Closet: How Heteronormativity Got Baked into Google’s SafeSearch

Thu, September 5, 4:30 to 6:00pm, Sheraton New Orleans Hotel, Floor: Eight, Endymion

Abstract

This presentation analyzes Google SafeSearch’s use of machine vision to automate censorship. First I provide a history of SafeSearch, followed by an overview of Google's machine vision system and the datasets it is built atop. Next I examine its political implications from five perspectives. First, I demonstrate how English-language semantic biases about sexuality are embedded in WordNet’s ontology. Second, I outline how ImageNet embeds the biases of both image makers and labelers and examine the possibility for automatically outing ‘closeted’ LGBTIQ people. Third, I examine instances of Google censoring non-pornographic content and the adjudication mechanisms Google offers for redress. Fourth, I look at instances where explicitness is blurry, focusing on Google understanding the term ‘bisexuality’ as indicative of pornography. Fifth, I analyze the post-2012, always-on SafeSearch model that requires explicit keywords to trigger pornographic results, which reifies mainstream heteroporn’s dominance online. In closing, I suggest some tactics of resistance.

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