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Fair Is Better than Sensational: Man Is to Doctor as Woman Is to Doctor
11 references·6 citing·40 second hop
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References

  • 2017Semantics derived automatically from language corpora contain human-like biases2,845 cited
  • 2018Word embeddings quantify 100 years of gender and ethnic stereotypes1,064 cited
  • 2018AI can be sexist and racist — it’s time to make it fair764 cited
  • 2019The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings675 cited
  • 2019On Measuring Social Biases in Sentence Encoders461 cited
  • 2019Gender Bias in Contextualized Word Embeddings334 cited
  • 2016The Social Impact of Natural Language Processing329 cited
  • 2019Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings262 cited
  • 2019Evaluating the Underlying Gender Bias in Contextualized Word Embeddings190 cited
  • 2019Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them144 cited
  • 2019It’s All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution107 cited

Cited by

  • 2024The political preferences of LLMs86 cited
  • 2022Exposing implicit biases and stereotypes in human and artificial intelligence: state of the art and challenges with a focus on gender82 cited
  • 2021Neural embeddings of scholarly periodicals reveal complex disciplinary organizations

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61 cited
  • 2022Word embeddings are biased. But whose bias are they reflecting?20 cited
  • 2021Financing Sustainable Entrepreneurship: ESG Measurement, Valuation, and Performance in Token Offerings19 cited
  • 2020Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs18 cited