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from Part I - Introduction and Setting the Stage for a Law of Algorithms
Published online by Cambridge University Press: 19 October 2020
Transparency has been in the crosshairs of recent writing about accountable algorithms. Its critics argue that releasing data can be harmful, and releasing source code won’t be useful.1 They claim individualized explanations of artificial intelligence (AI) decisions don’t empower people, and instead distract from more effective ways of governing.2 While criticizing transparency’s efficacy with one breath, with the next they defang it, claiming corporate secrecy exceptions will prevent useful information from getting out.3
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