Contesting efficacy: Tensions between risk and inclusion in computer vision technology
Morgan Klaus Scheuerman
Abstract:| INTRODUCTION AND BACKGROUNDMachine learning (ML) methods are now commonly used to make automated predictions about human beings-their lives and their characteristics. Vast amounts of individual data are aggregated to make predictions about people's shopping preferences, health status, or likelihood to recommit a crime. Computer vision, an ML task for training a computer to metaphorically 'see' specific objects, is a pertinent domain for examining the interaction between ML and human identity. Facial analysis… Show more
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