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An integrated artificial intelligence framework for public management

Author

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  • Bernd W. Wirtz
  • Wilhelm M. Müller

Abstract

Artificial intelligence (AI) extends the limits of current performance in data processing and analysis many times over. Since this states a great improvement in managing public data, this conceptual study discusses the use of AI in public management structures in connection with their risks and side effects. The exercise of state power and public influence through intelligent machines make ethical and political guidelines essential for their operation, constituting the cornerstones of the AI framework model developed here. The organizational structure and technical specification are additional aspects of the AI that determine design and functionality of the framework model in practical application.

Suggested Citation

  • Bernd W. Wirtz & Wilhelm M. Müller, 2019. "An integrated artificial intelligence framework for public management," Public Management Review, Taylor & Francis Journals, vol. 21(7), pages 1076-1100, July.
    • Handle: RePEc:taf:rpxmxx:v:21:y:2019:i:7:p:1076-1100
    DOI: 10.1080/14719037.2018.1549268
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    Cited by:

    1. Petra Vujković & Dejan Ravšelj & Lan Umek & Aleksander Aristovnik, 2022. "Bibliometric Analysis of Smart Public Governance Research: Smart City and Smart Government in Comparative Perspective," Social Sciences, MDPI, vol. 11(7), pages 1-22, July.
    2. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    3. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(3), pages 217-230, December.
    4. David, Sofia & Zinica, Daniel & Bărbuță-Mișu, Nicoleta & Savga, Larisa & Virlanuta, Florina-Oana, 2024. "Public administration managers' and employees' perceptions of adaptability to change under “the future of work” paradigm," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    5. Di Vaio, Assunta & Hassan, Rohail & Alavoine, Claude, 2022. "Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    6. Yu Zhang, 2022. "The construction of college students' sports health management service platform based on artificial intelligence," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1102-1110, December.
    7. Noha Diab & Nicoleta Isac & Cosmin Dobrin, 2022. "Artificial Intelligence (AI) and Jobs: The Impact of Pandemic on Governmental Organizations in Istanbul - Turkey," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 23(1), pages 46-64, March.

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