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Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures
3 references·16 citing·44 second hop
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References

  • 2010Three naive Bayes approaches for discrimination-free classification756 cited
  • 2009Classifying without discriminating403 cited
  • 2010Discrimination Aware Decision Tree Learning303 cited

Cited by

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  • 2017The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good111 cited
  • 2021Artificial intelligence video interviewing for employment: perspectives from applicants, companies, developer and academicians102 cited
  • 2024Fairness issues, current approaches, and challenges in machine learning models83 cited
  • 2020Highly Accurate, But Still Discriminatory81 cited
  • 2019On the Fairness of Disentangled Representations55 cited
  • 2019FAE: A Fairness-Aware Ensemble Framework54 cited
  • 2021Lessons to Be Learned from the Dutch Childcare Allowance Scandal: A Comparative Review of Algorithmic Governance by Tax Administrations in the Netherlands, France and Germany53 cited
  • 2019Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport53 cited
  • 2023Predictive policing and algorithmic fairness52 cited
  • 2021Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models

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46 cited
  • 2019Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges43 cited
  • 2020Case study42 cited
  • 2022The methodology of studying fairness perceptions in Artificial Intelligence: Contrasting CHI and FAccT41 cited
  • 2021Fairness in Learning-Based Sequential Decision Algorithms: A Survey41 cited
  • 2014Profiling Technologies and Fundamental Rights and Values: Regulatory Challenges and Perspectives from European Data Protection Authorities39 cited