CMU Advanced NLP: Bias and Fairness

CMU Advanced NLP: Bias and Fairness

Graham Neubig via YouTube Direct link

Allocational Harm

3 of 21

3 of 21

Allocational Harm

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CMU Advanced NLP: Bias and Fairness

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  1. 1 Introduction
  2. 2 NLP Systems
  3. 3 Allocational Harm
  4. 4 Stereotyping
  5. 5 Bias in human annotation
  6. 6 Bias detection techniques
  7. 7 Word embedding association test
  8. 8 Null hypothesis
  9. 9 Word embeddings
  10. 10 Sentence embeddings
  11. 11 Error rates
  12. 12 Difference by city
  13. 13 Language disparities
  14. 14 Counterfactual evaluation
  15. 15 Mitigating biases
  16. 16 Feature and variant rep representations
  17. 17 Bias sentence embeddings
  18. 18 Soft devices
  19. 19 Data augmentation
  20. 20 Augmentation with humans
  21. 21 Bias research

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