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AI algorithmic oversight: new frontiers in regulation
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AI algorithmic oversight: new frontiers in regulation (2022)AI algorithmic oversight: new frontiers i…Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice (2022)Human–AI Interactions in Publ…Accountable Artificial Intelligence: Holding Algorithms to Account (2020)Accountable Artificial Intell…The Principles and Limits of Algorithm-in-the-Loop Decision Making (2019)The Principles and Limits of …Review of “Race After Technology: Abolitionist Tools for the New Jim Code” (2019)Review of “Race After Technol…The accuracy, fairness, and limits of predicting recidivism (2018)The accuracy, fairness, and l…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (2018)Automating Inequality: How Hi…Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration (2018)Artificial intelligence for t…Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)Weapons of Math Destruction: …Algorithmic regulation: A critical interrogation (2017)Algorithmic regulation: A cri…The Black Box Society: The Secret Algorithms That Control Money and Information (2016)The Black Box Society: The Se…Understanding Regulation: Theory, Strategy, and Practice (2013)Understanding Regulation: The…Accountability and automation bias (2000)Accountability and automation…Does automation bias decision-making? (1999)Does automation bias decision…Humans and Automation: Use, Misuse, Disuse, Abuse (1997)Humans and Automation: Use, M…Perception of Risk (1987)Perception of RiskJudgment under Uncertainty: Heuristics and Biases (1974)Human Error (1990)A model for types and levels of human interaction with automation (2000)Trust in Automation (2014)Engineering Psychology and Human Performance (2015)Human Trust in Artificial Intelligence: Review of Empirical Research (2020)Judgment under uncertainty: Heuristics and biases (1982)Judgment Under Uncertainty: Heuristics and Biases. (1984)The benefits of imperfect diagnostic automation: a synthesis of the literature (2007)Automation bias and verification complexity: a systematic review (2016)When combinations of humans and AI are useful: A systematic review and meta-analysis (2024)Behavioral Decision Theory (1961)The Framing of Decisions and the Psychology of Choice (1981)Judgment under Uncertainty (1982)The Social Amplification of Risk: A Conceptual Framework (1988)Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality (2004)Using social and behavioural science to support COVID-19 pandemic response (2020)Responsive Regulation (1992)THE NEW PENOLOGY: NOTES ON THE EMERGING STRATEGY OF CORRECTIONS AND ITS IMPLICATIONS* (1992)CRITICAL QUESTIONS FOR BIG DATA (2012)Ethics and Privacy in AI and Big Data: Implementing Responsible Research and Innovation (2018)Fairness in Machine Learning: A Survey (2023)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)A META‐ANALYSIS OF THE PREDICTORS OF ADULT OFFENDER RECIDIVISM: WHAT WORKS!* (1996)Predicting relapse: A meta-analysis of sexual offender recidivism studies. (1998)The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis of 118 prediction studies. (2009)From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices (2019)Machine behaviour (2019)In AI we trust? Perceptions about automated decision-making by artificial intelligence (2020)Dilemmas in a general theory of planning (1973)Fairness and Abstraction in Sociotechnical Systems (2019)What Do Platforms Do? Understanding the Gig Economy (2020)The social power of algorithms (2016)Thinking critically about and researching algorithms (2016)Weaponized Interdependence: How Global Economic Networks Shape State Coercion (2019)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)A Survey on Bias and Fairness in Machine Learning (2021)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Taxonomy of Risks posed by Language Models (2022)
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References

  • 1987Perception of Risk9,263 cited
  • 1997Humans and Automation: Use, Misuse, Disuse, Abuse4,525 cited
  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor3,279 cited
  • 2017Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy3,071 cited
  • 2019Review of “Race After Technology: Abolitionist Tools for the New Jim Code”1,474 cited
  • 2016The Black Box Society: The Secret Algorithms That Control Money and Information1,319 cited
  • 2018The accuracy, fairness, and limits of predicting recidivism1,071 cited
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  • 2022Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice462 cited
  • 2019The Principles and Limits of Algorithm-in-the-Loop Decision Making386 cited
  • 2000Accountability and automation bias

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324 cited
  • 2018Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration281 cited
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