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Fairness and explainability in automatic decision-making systems. A challenge for computer science and law
16 references·0 citing·27 second hop
Fairness and explainability in automatic decision-making systems. A challenge for computer science and law (2023)Fairness and explainability in automatic …A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Algorithmic Fairness: Choices…Model Cards for Model Reporting (2019)Model Cards for Model Reporti…Fairness and Abstraction in Sociotechnical Systems (2019)Fairness and Abstraction in S…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation (2017)Why a Right to Explanation of…Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Men Also Like Shopping: Reduc…Fair 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…Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Man is to Computer Programmer…Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Inherent Trade-Offs in the Fa…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Learning Fair Representations (2013)Learning Fair RepresentationsAlgorithmic governmentality and prospects of emancipation (2013)Algorithmic governmentality a…Fairness through awareness (2012)Fairness through awarenessUniform Guidelines on Employee Selection Procedures (2007)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Big Data's Disparate Impact (2014)The role of artificial intelligence in achieving the Sustainable Development Goals (2020)Equality of Opportunity in Supervised Learning (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)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)Semantics derived automatically from language corpora contain human-like biases (2017)Algorithmic Bias in Education (2021)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)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)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)'It's Reducing a Human Being to a Percentage' (2018)Governing artificial intelligence: ethical, legal and technical opportunities and challenges (2018)From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices (2019)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2012Fairness through awareness3,501 cited
  • 2019Model Cards for Model Reporting2,653 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2019Fairness and Abstraction in Sociotechnical Systems1,621 cited
  • 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings1,615 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2017Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation1,305 cited
  • 2017Algorithmic Decision Making and the Cost of Fairness1,149 cited
  • 2013Learning Fair Representations1,126 cited
  • 2016Inherent Trade-Offs in the Fair Determination of Risk Scores942 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2013Algorithmic governmentality and prospects of emancipation

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702 cited
  • 2020Algorithmic Fairness: Choices, Assumptions, and Definitions687 cited
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