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Digital discretion and public administration in Africa: Implications for the use of artificial intelligence

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  • Plantinga, Paul

Abstract

The digitalisation of public services is implicated in fundamental changes to how civil servants make decisions and exercise discretion. Most significant has been a shift in responsibility away from ‘street-level bureaucrats’ to ‘system-level bureaucrats’; a technology-savvy community of officials, consultants and private enterprises involved in the design of information technology systems and associated rules. The relatively recent inclusion of artificial intelligence (AI) and data-driven algorithms raises new questions about the conflation of policy formulation and system development activities, but also intensifies concerns about the epistemic dependence and policy alienation of public officials. African public administrations are in an especially vulnerable position with respect to the adoption of AI, and so this chapter seeks to synthesise lessons from previous digital implementations on the continent, and considers the implications for AI use. Four broad considerations emerge from the review of literature: Integrity of recommendations provided by decision-support systems, including how they are influenced by local organisational practices and the reliability of underlying infrastructures; Inclusive decision-making that balances the (assumed) objectivity of data-driven algorithms and the influence of different stakeholder groups; Exception and accountability in how digital and AI platforms are funded, developed, implemented and used; and a Complete understanding of people and events through the integration of traditionally dispersed data sources and systems, and how policy actors seek to mitigate the risks associated with this aspiration.

Suggested Citation

  • Plantinga, Paul, 2022. "Digital discretion and public administration in Africa: Implications for the use of artificial intelligence," SocArXiv 2r98w, Center for Open Science.
    • Handle: RePEc:osf:socarx:2r98w
    DOI: 10.31219/osf.io/2r98w
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