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The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it

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  • König, Pascal D.
  • Wenzelburger, Georg

Abstract

Algorithmic decision-making (ADM) systems are increasingly adopted by the state to support various administrative functions and improve the effectiveness and efficiency of public services, such as in unemployment services or policing. While these systems create challenges of opaqueness, unfairness, and value trade-offs, the present paper argues that a more fundamental challenge lies in the way these systems alter the epistemic bases of decision-making. It contributes to the literature by highlighting why procedural standards of legitimacy in operative decision-making no longer suffice for certain applications and by discussing how the resulting legitimacy gap can be addressed through stakeholder involvement. By adapting research on participatory technology assessments to the particularities of ADM system design, it is possible to identify the core challenges of such a stakeholder process and the necessary steps to deal with them.

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  • König, Pascal D. & Wenzelburger, Georg, 2021. "The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it," Technology in Society, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:teinso:v:67:y:2021:i:c:s0160791x21001639
    DOI: 10.1016/j.techsoc.2021.101688
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    References listed on IDEAS

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    1. Buhmann, Alexander & Fieseler, Christian, 2021. "Towards a deliberative framework for responsible innovation in artificial intelligence," Technology in Society, Elsevier, vol. 64(C).
    2. Kim, Eun-Sung, 2020. "Deep learning and principal–agent problems of algorithmic governance: The new materialism perspective," Technology in Society, Elsevier, vol. 63(C).
    3. Simon Joss, 1998. "Danish consensus conferences as a model of participatory technology assessment: An impact study of consensus conferences on Danish Parliament and Danish public debate," Science and Public Policy, Oxford University Press, vol. 25(1), pages 2-22, February.
    4. Edwards, Lilian & Veale, Michael, 2017. "Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for," LawArXiv 97upg, Center for Open Science.
    5. Dimitris Bertsimas & Arthur Delarue & Sebastien Martin, 2019. "Optimizing schools’ start time and bus routes," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(13), pages 5943-5948, March.
    6. A. Wendy Russell, 2013. "Improving Legitimacy in Nanotechnology Policy Development Through Stakeholder and Community Engagement: Forging New Pathways," Review of Policy Research, Policy Studies Organization, vol. 30(5), pages 566-587, September.
    7. Veale, Michael & Brass, Irina, 2019. "Administration by Algorithm? Public Management meets Public Sector Machine Learning," SocArXiv mwhnb, Center for Open Science.
    8. Robinson, Stephen Cory, 2020. "Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI)," Technology in Society, Elsevier, vol. 63(C).
    9. Kolkman, Daan, 2020. "The usefulness of algorithmic models in policy making," SocArXiv hpma8, Center for Open Science.
    10. Marvin N. Wright & Sasmita Kusumastuti & Laust H. Mortensen & Rudi G. J. Westendorp & Thomas A. Gerds, 2021. "Personalised need of care in an ageing society: The making of a prediction tool based on register data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1199-1219, October.
    11. Kathrin Hartmann & Georg Wenzelburger, 2021. "Uncertainty, risk and the use of algorithms in policy decisions: a case study on criminal justice in the USA," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(2), pages 269-287, June.
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    6. Zhang, Yi & Kimathi, Flora A., 2022. "Exploring the stages of E-government development from public value perspective," Technology in Society, Elsevier, vol. 69(C).

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