Despite the many calls for monitoring and improving the fairness of artificially intelligent applications, the problems they present may be more complicated and thus more challenging to address than is generally assumed. Writing in Vox, Sigal Samuel outlines the competing conceptions of fairness that might be employed to assess AI applications in various settings from evaluating loan worthiness, to facial recognition, to text generation.
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