Digitalization, Law, and Regulation Open access Peer reviewed

Artificial Intelligence in Administrative Law: Structural Deficits, Control Gaps and Platform Dependency. A Jurisprudential and Administrative Law Analysis

Winfried Huck

Dyskurs Prawniczy i Administracyjny. | Sep 9, 2026

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The central jurisprudential question is: whose normative claim to validity sustains the administrative decision when the underlying AI system is governed by an external, state-uncontrollable platform architecture?

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This paper analyses the deployment of artificial intelligence (AI) in public administration across four structurally distinct yet normatively interconnected levels. It connects jurisprudential foundations — Kelsen’s Grundnorm and Hart’s Rule of Recognition — with an administrative law review of the structural mismatches between the historically sedimented Federal Administrative Procedures Act (Verwaltungsverfahrensgesetz, VwVfG) and the logic of probabilistic language models; the European law framework established by the AI Regulation (EU) 2024/1689 and the AI Market Surveillance and Innovation Act (Künstliches-Intelligenz-Marktüberwachungs und Innovationsförderungsgesetz, KI-MIG); the institutional modernisation policy of the Federal Ministry for Digital Affairs and State Modernisation (Bundesministerium für Digitales und Staatsmodernisierung, BMDS); and the geopolitical dimension of digital dependency on externally controlled platform architectures. The central jurisprudential question is: whose normative claim to validity sustains the administrative decision when the underlying AI system is governed by an external, state-uncontrollable platform architecture?

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Winfried Huck

first | Ostfalia University of Applied Sciences | ORCID 0000-0001-5644-9067

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@article{Huck2026Artificial,
  title = {Artificial Intelligence in Administrative Law: Structural Deficits, Control Gaps and Platform Dependency. A Jurisprudential and Administrative Law Analysis},
  author = {Winfried Huck},
  journal = {Dyskurs Prawniczy i Administracyjny.},
  year = {2026},
  doi = {10.61823/dpia.2026.2.563},
  url = {https://doi.org/10.61823/dpia.2026.2.563}
}

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