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Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved
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Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved (2018)Fairness Under Unawareness: Assessing Dis…The accuracy, fairness, and limits of predicting recidivism (2018)The accuracy, fairness, and l…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Does mitigating ML's impact disparity require treatment disparity? (2017)Does mitigating ML's impact d…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactFairness through awareness (2012)Fairness through awarenessThree naive Bayes approaches for discrimination-free classification (2010)Three naive Bayes approaches …Sex Bias in Graduate Admissions: Data from Berkeley (1975)Sex Bias in Graduate Admissio…The Interpretation of Music (1955)The Interpretation of MusicOn Simpson's Paradox and the Sure-Thing Principle (1972)Short and Long Sleep and Sleeping Pills (1979)How Retirement Saving Programs Increase Saving (1996)A Review on Fairness in Machine Learning (2022)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Semantics derived automatically from language corpora contain human-like biases (2017)A Survey on Bias and Fairness in Machine Learning (2021)A META‐ANALYSIS OF THE PREDICTORS OF ADULT OFFENDER RECIDIVISM: WHAT WORKS!* (1996)Predicting relapse: A meta-analysis of sexual offender recidivism studies. (1998)The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis of 118 prediction studies. (2009)From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices (2019)Machine behaviour (2019)In AI we trust? Perceptions about automated decision-making by artificial intelligence (2020)Fairness-Aware Classifier with Prejudice Remover Regularizer (2012)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Art As Collective Action (1974)How motives, skills, and values determine what people do. (1985)Improving Communication of Uncertainty in the Reports of the Intergovernmental Panel on Climate Change (2009)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Fairness and Abstraction in Sociotechnical Systems (2019)Algorithmic Decision Making and the Cost of Fairness (2017)Fairness definitions explained (2018)Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020)Why Machine Learning May Lead to Unfairness (2019)On the Applicability of Machine Learning Fairness Notions (2021)Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices (2023)The ethics of algorithms: Mapping the debate (2016)
this work references cited by second hop

References

  • 2012Fairness through awareness3,501 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2018The accuracy, fairness, and limits of predicting recidivism1,071 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art986 cited
  • 2010Three naive Bayes approaches for discrimination-free classification756 cited
  • 1975Sex Bias in Graduate Admissions: Data from Berkeley659 cited
  • 1955The Interpretation of Music298 cited
  • 2017Does mitigating ML's impact disparity require treatment disparity?103 cited

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