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AI’s social sciences deficit
10 references·14 citing·42 second hop
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this work references cited by second hop

References

  • 1999Sorting Things Out6,175 cited
  • 2012CRITICAL QUESTIONS FOR BIG DATA5,449 cited
  • 2018Algorithms of Oppression2,709 cited
  • 2019Review of “Race After Technology: Abolitionist Tools for the New Jim Code”1,474 cited
  • 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor1,167 cited
  • 2018The Misgendering Machines505 cited
  • 2017Situating methods in the magic of Big Data and AI414 cited
  • 2019Owning Ethics: Corporate Logics, Silicon Valley, and the Institutionalization of Ethics281 cited
  • 2018Algorithmic psychometrics and the scalable subject166 cited
  • 2019Facial recognition is the plutonium of AI139 cited

Cited by

  • 2023Artificial intelligence in government: Concepts, standards, and a unified framework95 cited
  • 2022Toward accountable human-centered AI: rationale and promising directions46 cited
  • 2022Machine learning and power relations44 cited
  • 2020A Social Science Perspective on Artificial Intelligence: Building Blocks for a Research Agenda42 cited
  • 2021On the importance of ethnographic methods in AI research38 cited

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2021
Mind the gap! On the future of AI research
36 cited
  • 2020Applying a principle of explicability to AI research in Africa: should we do it?29 cited
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  • 2019Consider ethical and social challenges in smart grid research23 cited
  • 2024The reanimation of pseudoscience in machine learning and its ethical repercussions18 cited
  • 2022Data Science Ethos Lifecycle: Interplay of Ethical Thinking and Data Science Practice17 cited
  • 2023Embedded Ethics for Responsible Artificial Intelligence Systems (EE-RAIS) in disaster management: a conceptual model and its deployment17 cited
  • 2020Are Digital Twins Becoming Our Personal (Predictive) Advisors?15 cited
  • 2023Assessing academic impacts of machine learning applications on a social science: Bibliometric evidence from economics10 cited