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The Legal and Political Implications of AI Bias: An International Comparative Study
11 references·1 citing·37 second hop
The Legal and Political Implications of AI Bias: An International Comparative Study (2024)The Legal and Political Implications of A…The global landscape of AI ethics guidelines (2019)The global landscape of AI et…Fairness and Abstraction in Sociotechnical Systems (2019)Fairness and Abstraction in S…How AI can be a force for good (2018)How AI can be a force for goodWeapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)Weapons of Math Destruction: …Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation (2016)Why a Right to Explanation of…Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016)Weapons of Math Destruction: …The ethics of algorithms: Mapping the debate (2016)The ethics of algorithms: Map…On the (im)possibility of fairness (2016)On the (im)possibility of fai…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactData preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook (2006)Imagined Communities: Awarene…Examining Ethical Aspects of AI: Addressing Bias and Equity in the Discipline (2024)Examining Ethical Aspects of …Imagined Communities. Reflections on the Origin and Spread of Nationalism (1985)Information revelation and privacy in online social networks (2005)Is There Social Capital in a Social Network Site?: Facebook Use and College Students' Life Satisfaction, Trust, and Participation (2009)Connection strategies: Social capital implications of Facebook-enabled communication practices (2011)Privacy and human behavior in the age of information (2015)Truth and Method (1960)Why Most Published Research Findings Are False (2005)Stanford Encyclopedia of Philosophy (2015)Artificial Intelligence and the Public Sector—Applications and Challenges (2018)Principles alone cannot guarantee ethical AI (2019)Setting the future of digital and social media marketing research: Perspectives and research propositions (2020)Big data: a revolution that will transform how we live, work, and think (2013)Big Data: A Revolution That Will Transform How We Live, Work, and Think (2014)Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject (2018)Algorithms at Work: The New Contested Terrain of Control (2019)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)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)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)Ethics of AI in Education: Towards a Community-Wide Framework (2021)Counterfactual Fairness (2017)Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)A Survey on Bias and Fairness in Machine Learning (2021)On the Opportunities and Risks of Foundation Models (2021)Artificial Intelligence and the 'Good Society': The US, EU, and UK Approach (2016)Algorithmic Accountability and Public Reason (2017)The Ethics of Artificial Intelligence (2023)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)Recommender Systems and their Ethical Challenges (2019)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)
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References

  • 2019The global landscape of AI ethics guidelines6,172 cited
  • 2016The ethics of algorithms: Mapping the debate3,541 cited
  • 2017Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy3,071 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2016Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy2,335 cited
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  • 2019Fairness and Abstraction in Sociotechnical Systems1,621 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2018How AI can be a force for good757 cited
  • 2016Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation361 cited
  • 2016On the (im)possibility of fairness247 cited

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  • 2024Examining Ethical Aspects of AI: Addressing Bias and Equity in the Discipline21 cited

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