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Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms
9 references·0 citing·33 second hop
Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms (2025)Can Synthetic Data be Fair and Private? A…TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks (2022)TabFairGAN: Fair Tabular Data…Algorithmic fairness in education (2022)Algorithmic fairness in educa…Assessing Algorithmic Fairness in Automatic Classifiers of Educational Forum Posts (2021)Assessing Algorithmic Fairnes…Algorithmic Bias in Education (2021)Algorithmic Bias in EducationA Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …Fairness definitions explained (2018)Fairness definitions explainedCertifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Data preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Uniform Guidelines on Employee Selection Procedures (2007)Fairness through awareness (2012)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Big Data's Disparate Impact (2014)Equality of Opportunity in Supervised Learning (2016)Algorithmic Decision Making and the Cost of Fairness (2017)Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Semantics derived automatically from language corpora contain human-like biases (2017)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Confirmation Bias: A Ubiquitous Phenomenon in Many Guises (1998)Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)Energization and Direction Are Both Essential Parts of Motivation (2023)Inside the Black Box: Detecting and Mitigating Algorithmic Bias Across Racialized Groups in College Student-Success Prediction (2024)The life cycle of large language models in education: A framework for understanding sources of bias (2024)Sense of community, perceived cognitive learning, and persistence in asynchronous learning networks (2002)Facilitating online discussions effectively (2007)Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018)Fairness for machine learning software in education: A systematic mapping study (2024)Investigating perceived fairness of AI prediction system for math learning: A mixed-methods study with college students (2025)Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color (1991)Dissecting racial bias in an algorithm used to manage the health of populations (2019)The Ethics of Artificial Intelligence in Education (2022)Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review (2023)8 Decolonizing Methodologies: Research and Indigenous Peoples (2024)The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024)Counterfactual Fairness (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias (2022)FAIR: Fair adversarial instance re-weighting (2022)
this work references cited by second hop

References

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2018Fairness definitions explained1,125 cited
  • 2021Algorithmic Bias in Education988 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art986 cited
  • 2022Algorithmic fairness in education301 cited
  • 2022TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks72 cited
  • 2021Assessing Algorithmic Fairness in Automatic Classifiers of Educational Forum Posts34 cited

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