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Artificial Intelligence (AI) and Automation in Administrative Procedures: Potentials, Limitations, and Framework Conditions

Author

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  • Peter Parycek

    (University for Continuing Education Krems)

  • Verena Schmid

    (University for Continuing Education Krems)

  • Anna-Sophie Novak

    (University for Continuing Education Krems)

Abstract

Integrating artificial intelligence (AI) systems into administrative procedures can revolutionize the way processes are conducted and fundamentally change established forms of action and organization in administrative law. However, implementing AI in administrative procedures requires a comprehensive evaluation of the capabilities and limitations of different systems, including considerations of transparency and data availability. Data are a crucial factor in the operation of AI systems and the validity of their predictions. It is essential to ensure that the data used to train AI algorithms are extensive, representative, and free of bias. Transparency is also an important aspect establishing trust and reliability in AI systems, particularly regarding the potential for transparent representation in rule-based and machine-learning AI systems. This paper examines the potential and challenges that arise from integrating AI into administrative procedures. In addition, the paper offers a nuanced perspective on current developments in artificial intelligence and provides a conceptual framework for its potential applications in administrative procedures. Beyond this, the paper highlights essential framework conditions that require continuous monitoring to ensure optimal results in practice.

Suggested Citation

  • Peter Parycek & Verena Schmid & Anna-Sophie Novak, 2024. "Artificial Intelligence (AI) and Automation in Administrative Procedures: Potentials, Limitations, and Framework Conditions," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 8390-8415, June.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:2:d:10.1007_s13132-023-01433-3
    DOI: 10.1007/s13132-023-01433-3
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    References listed on IDEAS

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    1. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    2. Fon, Vincy & Parisi, Francesco, 2006. "Judicial precedents in civil law systems: A dynamic analysis," International Review of Law and Economics, Elsevier, vol. 26(4), pages 519-535, December.
    3. James Mohun & Alex Roberts, 2020. "Cracking the code: Rulemaking for humans and machines," OECD Working Papers on Public Governance 42, OECD Publishing.
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