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A Non-Expert's Introduction to Data Ethics for Mathematicians

arXiv 2201.07794 ↗First posted 18 Jan 2022math.HO cs.CY cs.LGcited by 0

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Abstract (arXiv)

I give a short introduction to data ethics. I begin with some background information and societal context for data ethics. I then discuss data ethics in mathematical-science education and indicate some available course material. I briefly highlight a few efforts -- at my home institution and elsewhere -- on data ethics, society, and social good. I then discuss open data in research, research replicability and some other ethical issues in research, and the tension between privacy and open data and code, and a few controversial studies and reactions to studies. I then discuss ethical principles, institutional review boards, and a few other considerations in the scientific use of human data. I then briefly survey a variety of research and lay articles that are relevant to data ethics and data privacy. I conclude with a brief summary and some closing remarks. My focal audience is mathematicians, but I hope that this chapter will also be useful to others. I am not an expert about data ethics, and this chapter provides only a starting point on this wide-ranging topic. I encourage you to examine the resources that I discuss and to reflect carefully on data ethics, its role in mathematics education, and the societal implications of data and data analysis. As data and technology continue to evolve, I hope that such careful reflection will continue throughout your life.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 122 references that are in the map. First posted on arXiv 18 Jan 2022.

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11 of 122 references.

References · 11

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  2. 2018Model Cards for Model Reportingcited by 1,068
  3. 2019Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practicescited by 170
  4. 2021Re-imagining Algorithmic Fairness in India and Beyondcited by 102
  5. 2021Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Researchcited by 100
  6. 2018The Measure and Mismeasure of Fairnesscited by 94
  7. 2017Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the UScited by 66
  8. 2019Roles for Computing in Social Changecited by 49
  9. 2021Narratives and Counternarratives on Data Sharing in Africacited by 14
  10. 2018Mechanism Design for Social Goodcited by 13
  11. 2020Limits of Individual Consent and Models of Distributed Consent in Online Social Networkscited by 2

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