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AI-Enabled Innovation in the Public Sector: A Framework for Digital Governance and Resilience

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12219)

Abstract

This article aims to contribute to the theoretical debate on the relationships between digital governance and social innovation, and their impact on policy making for creating and capturing value from effective solutions addressing societal challenges. In particular, we question the drivers and challenges specifically considering the growing number of national strategies for innovation driven by artificial intelligence (AI) and the consequent wave of investments. To this end, a framework is presented aiming, on the one hand, to connect key dimensions and value drivers of digital governance for social innovation and complex systems methods for policy making; on the other hand, to position AI national initiatives with regard to welfare state initiatives. The framework is then applied to the analysis of cases of AI-driven innovation initiatives in Europe to assess their impact on social innovation.

Keywords

  • Digital governance
  • Social innovation
  • Social value
  • Crowdsourcing
  • Complex systems
  • Artificial intelligence

G. Viscusi—Independent Researcher.

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Acknowledgments

Work on this paper has benefited in part of the research activities on AI for the public sector conducted within the framework of the AI Watch, a joint initiative of DG CONNECT and the European Commission’s Joint Research Centre.

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Correspondence to Gianluca Misuraca .

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The views expressed in this paper are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.

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Misuraca, G., Viscusi, G. (2020). AI-Enabled Innovation in the Public Sector: A Framework for Digital Governance and Resilience. In: , et al. Electronic Government. EGOV 2020. Lecture Notes in Computer Science(), vol 12219. Springer, Cham. https://doi.org/10.1007/978-3-030-57599-1_9

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  • DOI: https://doi.org/10.1007/978-3-030-57599-1_9

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