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Algorithmic Bias and Racial Inequality: A Critical Review

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  • Kasy, Maximilian

    (University of Oxford)

Abstract

Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the interests of disadvantaged groups (e.g., racial minorities): Bias is defined as a deviation from profit maximization. Future research should instead focus on the causal effect of automated decisions on the distribution of welfare, both across and within groups. The literature emphasizes some apparent contradictions between different notions of fairness, and between fairness and profits. These contradictions vanish, however, when profits are maximized. Existing work involves conceptual slippages between statistical notions of bias and misclassification errors, economic notions of profit, and normative notions of bias and fairness. Notions of bias nonetheless carry some interest within the welfare paradigm that I advocate for, if we understand bias and discrimination as mechanisms and potential points of intervention.

Suggested Citation

  • Kasy, Maximilian, 2024. "Algorithmic Bias and Racial Inequality: A Critical Review," IZA Discussion Papers 16944, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp16944
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    References listed on IDEAS

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    1. David Arnold & Will Dobbie & Peter Hull, 2022. "Measuring Racial Discrimination in Bail Decisions," American Economic Review, American Economic Association, vol. 112(9), pages 2992-3038, September.
    2. Knox, Dean & Lowe, Will & Mummolo, Jonathan, 2020. "Administrative Records Mask Racially Biased Policing—CORRIGENDUM," American Political Science Review, Cambridge University Press, vol. 114(4), pages 1394-1394, November.
    3. Alan Manning & Barbara Petrongolo, 2017. "How Local Are Labor Markets? Evidence from a Spatial Job Search Model," American Economic Review, American Economic Association, vol. 107(10), pages 2877-2907, October.
    4. J. Aislinn Bohren & Peter Hull & Alex Imas, 2022. "Systemic Discrimination: Theory and Measurement," NBER Working Papers 29820, National Bureau of Economic Research, Inc.
    5. Maximilian Kasy, 2023. "The political economy of AI: Towards democratic control of the means of prediction," Economics Series Working Papers 1014, University of Oxford, Department of Economics.
    6. Mario L. Small & Devah Pager, 2020. "Sociological Perspectives on Racial Discrimination," Journal of Economic Perspectives, American Economic Association, vol. 34(2), pages 49-67, Spring.
    7. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    8. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    9. John Knowles & Nicola Persico & Petra Todd, 2001. "Racial Bias in Motor Vehicle Searches: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 203-232, February.
    10. Knox, Dean & Lowe, Will & Mummolo, Jonathan, 2020. "Administrative Records Mask Racially Biased Policing," American Political Science Review, Cambridge University Press, vol. 114(3), pages 619-637, August.
    11. Eric Luis Uhlmann & Geoffrey Cohen, 2005. "Constructed Criteria. Redefining Merit to Justify Discrimination," Post-Print hal-00516601, HAL.
    12. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    13. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, October.
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    More about this item

    Keywords

    AI; algorithmic bias; inequality; machine learning; discrimination;
    All these keywords.

    JEL classification:

    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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