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Are we Nearly There Yet? A Desires & Realities Framework for Europe’s AI Strategy

Author

Listed:
  • Ariana Polyviou

    (University of Nicosia)

  • Efpraxia D. Zamani

    (The University of Sheffield)

Abstract

Of all emerging technologies, Artificial Intelligence (AI) is perhaps the most debated topic in contemporary society because it promises to redefine and disrupt several sectors. At the same time, AI poses challenges for policymakers and decision-makers, particularly regarding formulating strategies and regulations to address their stakeholders’ needs and perceptions. This paper explores stakeholder perceptions as expressed through their participation in the formulation of Europe’s AI strategy and sheds light on the challenges of AI in Europe and the expectations for the future. Our analysis reveals six dimensions towards an AI strategy; ecosystems, education, liability, data availability sufficiency & protection, governance and autonomy. It draws on these dimensions to construct a desires-realities framework for AI strategy in Europe and provide a research agenda for addressing existing realities. Our findings contribute to understanding stakeholder desires on AI and hold important implications for research, practice and policymaking.

Suggested Citation

  • Ariana Polyviou & Efpraxia D. Zamani, 2023. "Are we Nearly There Yet? A Desires & Realities Framework for Europe’s AI Strategy," Information Systems Frontiers, Springer, vol. 25(1), pages 143-159, February.
  • Handle: RePEc:spr:infosf:v:25:y:2023:i:1:d:10.1007_s10796-022-10285-2
    DOI: 10.1007/s10796-022-10285-2
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    References listed on IDEAS

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    1. Nancy Pouloudi & Wendy Currie & Edgar A. Whitley, 2016. "Entangled Stakeholder Roles and Perceptions in Health Information Systems: A Longitudinal Study of the U.K. NHS N3 Network," Post-Print hal-01282317, HAL.
    2. Benjamin Saunders & Julius Sim & Tom Kingstone & Shula Baker & Jackie Waterfield & Bernadette Bartlam & Heather Burroughs & Clare Jinks, 2018. "Saturation in qualitative research: exploring its conceptualization and operationalization," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1893-1907, July.
    3. Inga Ulnicane & William Knight & Tonii Leach & Bernd Carsten Stahl & Winter-Gladys Wanjiku, 2021. "Framing governance for a contested emerging technology:insights from AI policy [The next space race is Artificial Intelligence]," Policy and Society, Darryl S. Jarvis and M. Ramesh, vol. 40(2), pages 158-177.
    4. Alkemade, Floortje & Suurs, Roald A.A., 2012. "Patterns of expectations for emerging sustainable technologies," Technological Forecasting and Social Change, Elsevier, vol. 79(3), pages 448-456.
    5. van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
    6. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    7. Sarah Bankins & Paul Formosa & Yannick Griep & Deborah Richards, 2022. "AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context," Information Systems Frontiers, Springer, vol. 24(3), pages 857-875, June.
    8. Pouloudi, Nancy & Currie, Wendy & Whitley, Edgar A., 2016. "Entangled stakeholder roles and perceptions in health information systems: a longitudinal study of the UK NHS N3 network," LSE Research Online Documents on Economics 62275, London School of Economics and Political Science, LSE Library.
    9. Oleksandr Melnychenko, 2020. "Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?," JRFM, MDPI, vol. 13(9), pages 1-19, August.
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    Cited by:

    1. Denis Dennehy & Anastasia Griva & Nancy Pouloudi & Yogesh K. Dwivedi & Matti Mäntymäki & Ilias O. Pappas, 2023. "Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI," Information Systems Frontiers, Springer, vol. 25(1), pages 1-7, February.

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