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Human intervention in automated decision-making
11 references·16 citing·48 second hop
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References

  • 1997The Tacit Dimension12,409 cited
  • 2016How the machine ‘thinks’: Understanding opacity in machine learning algorithms3,179 cited
  • 2004Groups of diverse problem solvers can outperform groups of high-ability problem solvers2,103 cited
  • 2017Human Decisions and Machine Predictions1,039 cited
  • 2018'It's Reducing a Human Being to a Percentage'690 cited
  • 2017Meaningful information and the right to explanation513 cited
  • 2016Seeing like a market474 cited
  • 2015The Trouble with Algorithmic Decisions422 cited
  • 2017The Right Not to be Subject to Automated Decisions Based on Profiling162 cited
  • 2019Privacy as Protection of the Incomputable Self: From Agnostic to Agonistic Machine Learning154 cited
  • 2018Enslaving the Algorithm: From a “Right to an Explanation” to a “Right to Better Decisions”?141 cited

Cited by

  • 2020Artificial intelligence and the value of transparency130 cited
  • 2022Contestable AI by Design: Towards a Framework117 cited
  • 2021Conceptualising Contestability: Perspectives on Contesting Algorithmic Decisions98 cited
  • 2023Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability

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78 cited
  • 2020Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems77 cited
  • 2021Contestability For Content Moderation77 cited
  • 2024Trust, trustworthiness and AI governance68 cited
  • 2022Enhancing human agency through redress in Artificial Intelligence Systems66 cited
  • 2023Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute46 cited
  • 2021The right to contest automated decisions under the General Data Protection Regulation : Beyond the so‐called “right to explanation”44 cited
  • 2023Legal Aspects of the Use Artificial Intelligence in Telemedicine38 cited
  • 2024Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services33 cited
  • 2020Preventing Racial Bias in Federal AI28 cited
  • 2022What’s the Appeal? Perceptions of Review Processes for Algorithmic Decisions27 cited
  • 2020Put Dialectics into the Machine: Protection against Automatic-decision-making through a Deeper Understanding of Contestability by Design24 cited
  • 2026Designing meaningful human oversight in AI24 cited