Picking on the Same Person - Does Algorithmic Monoculture Homogenize Outcomes?

Picking on the Same Person - Does Algorithmic Monoculture Homogenize Outcomes?

Stanford HAI via YouTube Direct link

Risks

31 of 31

31 of 31

Risks

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Picking on the Same Person - Does Algorithmic Monoculture Homogenize Outcomes?

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  1. 1 Introduction
  2. 2 Project Overview
  3. 3 Case Scenario
  4. 4 Algorithmic Monoculture
  5. 5 Same Data Sets
  6. 6 Data Sets
  7. 7 Foundation Models
  8. 8 Name Artifacts
  9. 9 Name Sentiment
  10. 10 Question
  11. 11 Key Findings
  12. 12 Systemic Failure
  13. 13 Formalizing the Metric
  14. 14 Looking at Census Records
  15. 15 Facial Recognition Data
  16. 16 Ethical Dimension
  17. 17 Is there a tradeoff
  18. 18 Is this discrimination
  19. 19 Federally protected categories
  20. 20 Homogenation and bias
  21. 21 Fairness gerrymandering
  22. 22 Contractualism
  23. 23 Effect on Democracy
  24. 24 Effect on Autonomy
  25. 25 Threshold
  26. 26 Wallser
  27. 27 Conclusion
  28. 28 Questions
  29. 29 Discrimination
  30. 30 Application
  31. 31 Risks

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