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How fair can we go in machine learning ? Assessing the boundaries of accuracy and fairness
13 references·2 citing·44 second hop
How fair can we go in machine learning ? Assessing the boundaries of accuracy and fairness (2021)How fair can we go in machine learning ? …Fair classification and social welfare (2020)Fair classification and socia…Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Bias in data‐driven artificia…An Intersectional Definition of Fairness (2020)An Intersectional Definition …What Does It Mean to ‘Solve’ the Problem of Discrimination in Hiring? (2019)What Does It Mean to ‘Solve’ …Model Cards for Model Reporting (2019)Model Cards for Model Reporti…Measuring Algorithmic Fairness (2019)Measuring Algorithmic FairnessFairness Constraints: A Flexible Approach for Fair Classification (2019)Fairness Constraints: A Flexi…Fairness and Abstraction in Sociotechnical Systems (2019)Fairness and Abstraction in S…A comparative study of fairness-enhancing interventions in machine learning (2019)A comparative study of fairne…'It's Reducing a Human Being to a Percentage' (2018)'It's Reducing a Human Being …Fairness Beyond Disparate Treatment & Disparate Impact (2017)Fairness Beyond Disparate Tre…Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Discrimination Aware Decision Tree Learning (2010)Discrimination Aware Decision…Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers (2022)Leveling Down in Computer Vis…Bias Reducing Multitask Learning on Mental Health Prediction (2022)Bias Reducing Multitask Learn…Discrimination-aware data mining (2008)Classifying without discriminating (2009)Three naive Bayes approaches for discrimination-free classification (2010)A Methodology for Direct and Indirect Discrimination Prevention in Data Mining (2012)Decision Theory for Discrimination-Aware Classification (2012)FA*IR (2017)Fairness through awareness (2012)Equality of Opportunity in Supervised Learning (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Survey on Bias and Fairness in Machine Learning (2021)Big Data's Disparate Impact (2014)A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle (2021)A Review on Fairness in Machine Learning (2022)Trustworthy AI: From Principles to Practices (2022)Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement (2015)Data Feminism (2020)On the Opportunities and Risks of Foundation Models (2021)The Social Construction of Facts and Artefacts: or How the Sociology of Science and the Sociology of Technology might Benefit Each Other (1984)Science in action : how to follow scientists and engineers through society (1987)Science in Action: How to Follow Scientists and Engineers through Society (1988)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Algorithms of Oppression (2018)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Disability, fairness, and algorithmic bias in AI recruitment (2022)Ethical Perceptions of AI in Hiring and Organizational Trust: The Role of Performance Expectancy and Social Influence (2022)AI and Global Governance: Modalities, Rationales, Tensions (2023)CRITICAL QUESTIONS FOR BIG DATA (2012)Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges (2023)Six Human-Centered Artificial Intelligence Grand Challenges (2023)Black Feminist Thought: Knowledge, Consciousness, and the Politics of Empowerment. (1992)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics (1998)Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory, and Antiracist Politics [1989] (2018)Rethinking Fairness: An Interdisciplinary Survey of Critiques of Hegemonic ML Fairness Approaches (2022)Fairness, AI & recruitment (2024)Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms (2024)The Social Psychology of Procedural Justice (1988)Justice at the millennium: A meta-analytic review of 25 years of organizational justice research. (2001)Likert scales, levels of measurement and the “laws” of statistics (2010)The Principles and Limits of Algorithm-in-the-Loop Decision Making (2019)Towards a standard for identifying and managing bias in artificial intelligence (2022)Trustworthy Artificial Intelligence: A Review (2022)Fairness of Exposure in Rankings (2018)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Fairness in Machine Learning: A Survey (2023)
this work references cited by second hop

References

  • 2019Model Cards for Model Reporting2,653 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2019Fairness and Abstraction in Sociotechnical Systems1,621 cited
  • 2020Bias in data‐driven artificial intelligence systems—An introductory survey1,040 cited
  • 2018'It's Reducing a Human Being to a Percentage'690 cited
  • 2017Fairness Beyond Disparate Treatment & Disparate Impact630 cited
  • 2019A comparative study of fairness-enhancing interventions in machine learning601 cited
  • 2010Discrimination Aware Decision Tree Learning303 cited
  • 2020An Intersectional Definition of Fairness200 cited
  • 2019What Does It Mean to ‘Solve’ the Problem of Discrimination in Hiring?197 cited
  • 2019Fairness Constraints: A Flexible Approach for Fair Classification184 cited
  • 2019Measuring Algorithmic Fairness104 cited
  • 2020Fair classification and social welfare75 cited

Cited by

  • 2022Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers44 cited
  • 2022Bias Reducing Multitask Learning on Mental Health Prediction18 cited

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