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Article

The political dimension of administrative decision-making under automation: Structural shifts in public administration

Mykhailo Yanyshivskyi
Abstract

The article aimed to explain how automation structurally transforms the political dimension of administrative decision-making in public administration. Rather than treating automation as a purely technical or organisational innovation, the study conceptualises it as a governance practice that reallocates judgment, responsibility, and legitimacy within administrative systems. Drawing on contemporary theories of bureaucracy and algorithmic governance, the article argues that automation does not eliminate political choice but displaces it from the moment of individual decision-making to the design of procedures, models, and infrastructures that predefine possible outcomes. To capture this transformation analytically, the article introduces the concept of “points of shift” through which automation reshapes political decision-making. Four such shifts are identified: the shift of legitimacy from public justification to technical authority; the shift of responsibility from individual judgment to system architecture; the transformation of political conflict into technical critique; and the increasing invisibility of political choice through its infrastructural embedding. Particular attention is paid to why artificial intelligence intensifies these shifts. Unlike rule-based automation, AI combines data-driven knowledge production, prediction, and semi-autonomous execution, resulting in adaptive and scalable forms of governance in which normative assumptions are embedded in models rather than articulated through political processes. The article concludes that automation – especially when based on AI – does not depoliticise public administration but produces a new mode of political ordering that is less visible, less localised, and more resistant to democratic scrutiny. These findings of the article have practical relevance for policymakers, regulators, and public administrators by highlighting how political choices are embedded in system design and infrastructural arrangements, thereby informing more reflective approaches to the regulation and oversight of automated decision-making

Keywords

artificial intelligence; political dimension of governance; algorithmic governance; responsibility; legitimacy; politicality; procedural rationality

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Received 03.02.2026, Revised 01.05.2026, Accepted 28.05.2026 Published 25.06.2026

Retrieved from Volume 19, No. 1, 2026

Suggested citation

Yanyshivskyi, M. (2026). The political dimension of administrative decision-making under automation: Structural shifts in public administration. Democratic Governance, 19(1), 5-19. https://doi.org/10.56318/dg/1.2026.05

https://doi.org/10.56318/dg/1.2026.05

Pages 5-19

References

  1. Allhutter, D., Cech, F., Fischer, F., Grill, G., & Mager, A. (2020). Algorithmic profiling of job seekers in Austria: How Austerity politics are made effective. Frontiers in Big Data, 3, article number 5. doi: 10.3389/fdata.2020.00005.
  2. Balamush, M.A., & Dobrovolskaya, N.V. (2021). The problems of determining the administrative and legal status of employees occupying political positions in the executive authorities. Constitutional State, (43), 22-27. doi: 10.18524/2411-2054.2021.43.240947.
  3. Beer, D. (2016). Metric power. London: Palgrave Macmillan.
  4. Bevan, J. (2020). Eubanks, Virginia, Automating Inequality. Canadian Journal of Sociology, 45(1), 91-94. doi: 10.29173/cjs29658.
  5. Burdon, P. (2015). Hannah Arendt: On judgment and responsibility. Griffith Law Review, 24(2), 221-243. doi: 10.1080/10383441.2015.1058215.
  6. Camillo, C. (2017). Street-level bureaucracy. In A. Farazmand (Ed.), Global encyclopedia of public administration, public policy, and governance. Cham: Springer. doi: 10.1007/978-3-319-31816-5_654-1.
  7. Cantarelli, P., Belardinelli, P., Belle, N., & Palumbo, R. (2023). Decision noise in public administration. Public Administration Review, 83(6), 1667-1686. doi: 10.1111/puar.13735.
  8. Diver, L. (2021). Karen Yeung and Martin Lodge (eds) Algorithmic regulation reviewed by Laurence Diver. Prometheus, 37(4). doi: 10.13169/prometheus.37.4.0387.
  9. Esposito, M., & Tse, T. (2024). Mitigating the risks of generative AI in government through algorithmic governance. In Proceedings of the 25th annual international conference on digital government research (pp. 605-609). New York: Association for Computing Machinery. doi: 10.1145/3657054.3657124.
  10. Fortes, P.R.B., Baquero, P.M., & Amariles, D.R. (2022). Artificial intelligence risks and algorithmic regulation. European Journal of Risk Regulation, 13(3), 357-372. doi: 10.1017/err.2022.14.
  11. Gordon, F. (2019). Virginia Eubanks (2018) Automating inequality: How high-tech tools profile, police, and punish the poor. New York: Picador, St Martin’s Press. Law, Technology and Humans, 1, 162-164. doi: 10.5204/lthj.v1i0.1386.
  12. Gritsenko, D., & Wood, M. (2020). Algorithmic governance: A modes of governance approach. Regulation & Governance, 16(1), 45-62. doi: 10.1111/rego.12367.
  13. Habermas, J. (1968). Technology and science as “ideology”. In Toward a rational society: Student protest, science, and politics (pp. 81-126). Boston: Beacon Press.
  14. Haitsma, L., & Brink, B. (2025). From human intervention to human involvement: A critical examination of the role of humans in (semi-)automated administrative decision-making. Digital Government: Research and Practice, 6(3), article number 33. doi: 10.1145/3716173.
  15. Jasanoff, S. (2016). The ethics of invention: Technology and the human future. New York: W.W. Norton & Company.
  16. Kaun, A., Larsson, A.O., & Masso, A. (2024). Automating public administration: Citizens’ attitudes towards automated decision-making across Estonia, Sweden, and Germany. Information, Communication & Society, 27(2), 314-332. doi: 10.1080/1369118X.2023.2205493.
  17. Kitchin, R. (2014). The data revolution. Washington: SAGE. doi: 10.4135/9781473909472.
  18. Koenig, P.D. (2025). Understanding the politics of artificial intelligence. Cheltenham: Edward Elgar Publishing. doi: 10.4337/9781035348022.00005.
  19. Maalsen, S. (2023). Algorithmic epistemologies and methodologies: Algorithmic harm, algorithmic care and situated algorithmic knowledges. Progress in Human Geography, 47(2), 197-214. doi: 10.1177/03091325221149439.
  20. Mintrom, M. (2016). Herbert A. Simon, Administrative behavior: A study of decision-making processes in administrative organization. In M. Lodge, E.C. Page & S.J. Balla (Eds.), The Oxford handbook of classics in public policy and administration. Oxford: Oxford Academic. doi: 10.1093/oxfordhb/9780199646135.013.22.
  21. Mouffe, C. (2005). On the political. London & New York: Routledge.
  22. Naudts, L. (2024). The digital faces of oppression and domination: A relational and egalitarian perspective on the data-driven society and its regulation. In Proceedings of the 2024 ACM conference on fairness, accountability, and transparency (FAccT ’24) (pp. 701-712). New York: Association for Computing Machinery. doi: 10.1145/3630106.3658934.
  23. Öjehag-Pettersson, A., Carlsson, V., & Rönnblom, M. (2024). Political studies of automated governing: A bird’s eye (re)view. Regulation & Governance, 18(4), 1049-1064.
  24. Oraldi, A. (2023). Technology and society in Habermas’ early social theory: Towards a critical theory of technology beyond instrumentalism. Krisis, 43, 66-84. doi: 10.21827/krisis.43.1.37753.
  25. Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard: Harvard University Press.
  26. Roehl, U.B.U., & Hansen, M.B. (2024). Automated administrative decision-making and good governance: Synergies, trade-offs, and limits. Public Administration Review, 84(6), 1184-1199. doi: 10.1111/puar.13799.
  27. Rouvroy, A., & Berns, T. (2013). Algorithmic governmentality and prospects of emancipation. Réseaux, 177(1), 163-196. doi: 10.3917/res.177.0163.
  28. Schmitt, C. (2007). The concept of the political. Chicago: University of Chicago Press.
  29. Sever, T. (2023). Automated decision-making in the public sector. Retrieved from https://www.nispa.org/files/conferences/2023/e-proceedings/system_files/papers/2023_Auto_decision_making_9_5_23.pdf
  30. Tkachenko, Ye.V. (2016). The concept and features of political positions. In Principles of modern constitutionalism and the Constitution of Ukraine (pp. 105-107). Kharkiv: Publishing House “Human Rights”.
  31. Weber, M. (1946). Politics as a vocation. New York: Oxford University Press.
  32. Yeung, K. (2017). Algorithmic regulation: A critical interrogation. Regulation & Governance, 12(4), 505-523. doi: 10.1111/rego.12158.
  33. Zouridis, S., van Eck, M., & Bovens, M. (2019). Automated discretion. In T. Evans & P. Hupe (Eds.), Discretion and the quest for controlled freedom (pp. 313-329). Cham: Palgrave Macmillan. doi: 10.1007/978-3-030-19566-3_20.
e-ISSN 2070-4038
DOI: 10.56318/dg