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The Challenges of Machine Learning and Their Economic Implications
16 references·1 citing·44 second hop
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References

  • 2014Big Data's Disparate Impact3,046 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 1996On the reality of cognitive illusions.1,466 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
  • 2010Consumer credit-risk models via machine-learning algorithms861 cited
  • 2011Women in STEM: A Gender Gap to Innovation778 cited
  • 2013Discrimination in online ad delivery751 cited
  • 2017Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data511 cited
  • 2017Algorithmic Accountability and Public Reason446 cited
  • 1984Liability for Harm versus Regulation of Safety381 cited
  • 2020Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming303 cited
  • 2009Looking at Shirley, the Ultimate Norm: Colour Balance, Image Technologies, and Cognitive Equity295 cited
  • 1983Liability for Harm Versus Regulation of Safety285 cited
  • 2018Algorithms that remember: model inversion attacks and data protection law

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278 cited
  • 2017Disparate Impact in Big Data Policing206 cited
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    • 2023Artificial neural network and decision tree-based modelling of non-prosperity of companies15 cited