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Developing an Intersectional Framework to Analyze Biases in Artificial Intelligence and Deep Neural

Developing an Intersectional Framework to Analyze Biases in Artificial Intelligence and Deep Neural

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Contextual Labelling

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Contextual Labelling

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Developing an Intersectional Framework to Analyze Biases in Artificial Intelligence and Deep Neural

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  1. 1 Intro
  2. 2 Sources of Bias
  3. 3 Bias and Facial
  4. 4 Sourcing Data
  5. 5 Retracing Bias
  6. 6 Conceptual Framework using Synthetic Data and Critical Theories
  7. 7 Contextual Labelling
  8. 8 Labelling Examples
  9. 9 Challenges

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