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Data science, artificial intelligence and the third wave of digital era governance

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  • Dunleavy, Patrick
  • Margetts, Helen

Abstract

This article examines the model of digital era governance (DEG) in the light of the latest-wave of data-driven technologies, such as data science methodologies and artificial intelligence (labelled here DSAI). It identifies four key top-level macro-themes through which digital changes in response to these developments may be investigated. First, the capability to store and analyse large quantities of digital data obviates the need for data 'compression' that characterises Weberian-model bureaucracies, and facilitates data de-compression in data-intensive, information regimes, where the capabilities of public agencies and civil society are both enhanced. Second, the increasing capability of robotic devices have expanded the range of tasks that machines extending or substituting workers' capabilities can perform, with implications for a reshaping of state organisation. Third, DSAI technologies allow new ways of partitioning state functions in ways that can maximise organisational productivity, in an 'intelligent centre, devolved delivery' model within vertical policy sectors. Fourth, within each tier of government, DSAI technologies offer new possibilities for 'administrative holism' - the horizontal allocation of power and functions between organisations, through state integration, common capacity and needs-based joining-up of services. Together, these four themes comprise a third wave of DEG changes, suggesting important administrative choices to be made regarding information regimes, state organisation, functional allocation and outsourcing arrangements, as well as a long-term research agenda for public administration, requiring extensive and detailed analysis. This article has been accepted for publication in the Sage journal Public Policy and Administration, August 2023.

Suggested Citation

  • Dunleavy, Patrick & Margetts, Helen, 2023. "Data science, artificial intelligence and the third wave of digital era governance," OSF Preprints f3rza, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:f3rza
    DOI: 10.31219/osf.io/f3rza
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    References listed on IDEAS

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    Cited by:

    1. Margetts, Helen & Dunleavy, Patrick, 2024. "The political economy of digital government: how Silicon Valley firms drove conversion to data science and artificial intelligence in public management," LSE Research Online Documents on Economics 124539, London School of Economics and Political Science, LSE Library.
    2. Chiedozie M. Okafor & Owolabi Ogunse & Mercy Nneoma Iheke & Dickson O. Oseghale & Imuetinyan Ogiehor & Ebuka Emmanuel Aniebonam, 2025. "The Role of Advanced Anomaly Detection in Transforming Program Management in Government with Scikit-Learn, A Machine Learning Library in Python," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(5), pages 148-165, May.
    3. Shao, Cuiying & Liu, Zhanyu, 2024. "Advancing green innovation through the establishment of data regulatory bodies: Insights from the Big Data Bureau in China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 308-325.

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