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Equal accuracy for Andrew and Abubakar—detecting and mitigating bias in name-ethnicity classification algorithms
16 references·0 citing·49 second hop
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References

  • 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings1,615 cited
  • 2018Fairness definitions explained1,125 cited
  • 2018Word embeddings quantify 100 years of gender and ethnic stereotypes1,064 cited
  • 2004‘Spatial’ relationships? Towards a reconceptualization of embedded ness1,000 cited
  • 2018AI can be sexist and racist — it’s time to make it fair764 cited
  • 2020Legal and human rights issues of AI: Gaps, challenges and vulnerabilities493 cited
  • 2017Algorithmic Bias in Autonomous Systems472 cited
  • 2002Thicker Than Blood: How Racial Statistics Lie420 cited
  • 1997Globalization or World society: How to conceive of modern society?373 cited
  • 2020Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI)338 cited
  • 2016Algorithmic Bias334 cited
  • 2004World-Systems Analysis304 cited
  • 2020Saving Face298 cited
  • 2021Mitigating bias in machine learning for medicine269 cited
  • 2002The Production of Legal Identities Proper to States: The Case of the Permanent Family Surname235 cited

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2004
Statistics of Racial Segregation: Measures, Evidence and Policy
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