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On the importance of ethnographic methods in AI research

To truly understand the societal impact of AI, we need to look beyond the exclusive focus on quantitative methods, and focus on qualitative methods like ethnography, which shed light on the actors and institutions that wield power through the use of these technologies.

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  1. Benjamin, R. Race After Technology: Abolitionist Tools for the New Jim Code (Polity, 2019).

  2. Eubanks, V. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin’s Press, 2018).

  3. Noble, S. U. Algorithms of Oppression (NYU Press, 2018).

  4. Raji, I. D. et al. in Proc. AAAI/ACM Conference on AI, Ethics, and Society 145–151 (ACM, 2020).

  5. Hicks, M. Programmed Inequality: How Britain Discarded Women Technologists and Lost Its Edge in Computing (MIT Press, 2018).

  6. Keyes, O. Proc. ACM on Human-Computer Interaction Vol. 2 88 (ACM, 2018).

  7. Prasad, M. & Marda, V. In Artificial Intelligence: Human Rights, Social Justice and Development 145–151 (APC, Article 19, Sida, 2019).

  8. Devich-Cyril, M. The Atlantic (2020).

  9. Lum, K. & Issac, W. Significance 13, 14–19 (2016).

    Article  Google Scholar 

  10. Moss, E. & Sloane, M. Nat. Mach. Intell. 1, 330–331 (2019).

    Article  Google Scholar 

  11. Forsythe, D. Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence 8–9 (Stanford Univ. Press, 2001).

  12. Marda, V. in Artificial Intelligence: Human Rights, Social Justice and Development 9–13 (APC, Article 19, Sida, 2019).

  13. Reeves, S., Kuper, A. & Hodges, B. D. BMJ 337, a1020 (2008).

    Article  Google Scholar 

  14. Nader, L. J. Ethnograph. Theor. 1, 211–219 (2011).

    Article  Google Scholar 

  15. Nader, L. (ed.) Naked Science: Anthropological Inquiry into Boundaries, Power, and Knowledge (Routledge, 2014).

  16. Barabas C., Doyle, C., Rubinovitz, J. B. & Dinakar, K. in ACM Conf. Fairness, Accountability, and Transparency 167–176 (ACM, 2020).

  17. Elish, M. C. & Boyd, D. Preprint at (2017).

  18. From the Commissioner’s Desk (Delhi Police, 2015).

  19. Singh, K. P. Hindustan Times (2017).

  20. CAG’s Performance Audit report on Manpower and Logistics Management in Delhi Police” presented (Comptroller and Auditor General of India, 2020);

  21. Marda, V & Narayan, S in Proc. ACM Conference on Fairness, Accountability, and Transparency 317–324 (ACM, 2020).

  22. Seaver, N. in Knowing Algorithms in DigitalSTS: A Field Guide for Science and Technology Studies (eds. Vertesi, J. & Ribes, D) 412–422 (Princeton Univ. Press, 2019).

  23. Haraway, D. Fem. Stud. 14, 575–599 (1988).

    Article  Google Scholar 

  24. Delhi Police selects Barco for city’s first C4I Surveillance Center (Barco, 2010);

  25. Hanna, A. & Park, M. T. Preprint at (2020).

  26. Christin, A. Theor. Soc. 49, 897–918 (2020).

    Article  Google Scholar 

  27. Latour, B. in The Lure of Whitehead (eds. Gaskill, N. & Nocek, A. J.) 34 (Univ. Minnesota Press, 2014).

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The authors thank N. Raval, R. Renno and M. Ansari for their feedback on various drafts of this piece.

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Correspondence to Vidushi Marda or Shivangi Narayan.

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Marda, V., Narayan, S. On the importance of ethnographic methods in AI research. Nat Mach Intell 3, 187–189 (2021).

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