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Inherent Tradeoffs in Learning Fair Representations
16 references·14 citing·24 second hop
Inherent Tradeoffs in Learning Fair Representations (2019)Inherent Tradeoffs in Learning Fair Repre…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Learning Adversarially Fair and Transferable Representations (2018)Learning Adversarially Fair a…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …On Fairness and Calibration (2017)On Fairness and CalibrationFair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Algorithmic Decision Making and the Cost of Fairness (2017)Algorithmic Decision Making a…Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment (2016)Fairness Beyond Disparate Tre…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Fairness Constraints: Mechanisms for Fair Classification (2015)Fairness Constraints: Mechani…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactLearning Fair Representations (2013)Learning Fair RepresentationsFairness-Aware Classifier with Prejudice Remover Regularizer (2012)Fairness-Aware Classifier wit…Fairness through awareness (2012)Fairness through awarenessClassifying without discriminating (2009)Classifying without discrimin…Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory (2004)Game theory, maximum entropy,…The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models (2024)The Impact of Race, Ethnicity…Implementing equitable and intersectionality‐aware ML in education: A practical guide (2024)Implementing equitable and in…Auditing the fairness of place-based crime prediction models implemented with deep learning approaches (2023)Auditing the fairness of plac…Quantifying and alleviating political bias in language models (2022)Quantifying and alleviating p…Perturbation Augmentation for Fairer NLP (2022)Perturbation Augmentation for…Group-Aware Threshold Adaptation for Fair Classification (2022)Group-Aware Threshold Adaptat…Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values (2022)Fairness without Imputation: …Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks (2022)Fair Representation: Guarante…To Split or not to Split: The Impact of Disparate Treatment in Classification (2021)To Split or not to Split: The…Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately (2021)Removing Spurious Features ca…Mitigating Political Bias in Language Models through Reinforced Calibration (2021)Mitigating Political Bias in …Deep fair models for complex data: Graphs labeling and explainable face recognition (2021)Deep fair models for complex …Can We Obtain Fairness For Free? (2021)Can We Obtain Fairness For Fr…Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search (2021)Are Gender-Neutral Queries Re…Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)Trustworthy Artificial Intelligence: A Review (2022)Fairness in Machine Learning: A Survey (2023)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)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Counterfactual Fairness (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)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)Fairness definitions explained (2018)Machine behaviour (2019)Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)The ethics of algorithms: Mapping the debate (2016)
this work references cited by second hop

References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 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
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2017Algorithmic Decision Making and the Cost of Fairness1,149 cited
  • 2013Learning Fair Representations1,126 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art986 cited
  • 2012Fairness-Aware Classifier with Prejudice Remover Regularizer694 cited
  • 2015Fairness Constraints: Mechanisms for Fair Classification644 cited
  • 2016Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment559 cited
  • 2017On Fairness and Calibration509 cited
  • 2004Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory455 cited
  • 2009Classifying without discriminating403 cited

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2018
Learning Adversarially Fair and Transferable Representations
387 cited

Cited by

  • 2022Quantifying and alleviating political bias in language models68 cited
  • 2021Mitigating Political Bias in Language Models through Reinforced Calibration64 cited
  • 2022Perturbation Augmentation for Fairer NLP62 cited
  • 2021Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search50 cited
  • 2024Implementing equitable and intersectionality‐aware ML in education: A practical guide40 cited
  • 2021Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately35 cited
  • 2021Can We Obtain Fairness For Free?28 cited
  • 2022Group-Aware Threshold Adaptation for Fair Classification26 cited
  • 2021Deep fair models for complex data: Graphs labeling and explainable face recognition25 cited
  • 2022Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values25 cited
  • 2023Auditing the fairness of place-based crime prediction models implemented with deep learning approaches24 cited
  • 2024The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models22 cited
  • 2022Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks19 cited
  • 2021To Split or not to Split: The Impact of Disparate Treatment in Classification18 cited