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Artificial Intelligence against COVID-19: An Early Review

Author

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  • Naudé, Wim

    (RWTH Aachen University)

Abstract

Artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID- 19 pandemic. Since the outbreak of the pandemic, there has been a scramble to use AI. This article provides an early, and necessarily selective review, discussing the contribution of AI to the fight against COVID-19, as well as the current constraints on these contributions. Six areas where AI can contribute to the fight against COVID-19 are discussed, namely i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments and cures, and vi) social control. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages.

Suggested Citation

  • Naudé, Wim, 2020. "Artificial Intelligence against COVID-19: An Early Review," IZA Discussion Papers 13110, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp13110
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    File URL: https://docs.iza.org/dp13110.pdf
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    References listed on IDEAS

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    1. Marwin H. S. Segler & Mike Preuss & Mark P. Waller, 2018. "Planning chemical syntheses with deep neural networks and symbolic AI," Nature, Nature, vol. 555(7698), pages 604-610, March.
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    Cited by:

    1. Fontes, Catarina & Corrigan, Caitlin & Lütge, Christoph, 2023. "Governing AI during a pandemic crisis: Initiatives at the EU level," Technology in Society, Elsevier, vol. 72(C).
    2. Mihaela Cazacu & Emilia Ţiţan & Daniela-Ioana Manea & Mihaela Mihai, 2021. "The Impact of Digitalization in Mitigating the Effects of the COVID-19 Pandemic for Silver Population," Romanian Journal of Economics, Institute of National Economy, vol. 52(1(61)), pages 50-57, June.
    3. Beatriz González-Pérez & Concepción Núñez & José L. Sánchez & Gabriel Valverde & José Manuel Velasco, 2021. "Expert System to Model and Forecast Time Series of Epidemiological Counts with Applications to COVID-19," Mathematics, MDPI, vol. 9(13), pages 1-34, June.
    4. Antonio Sandu, 2020. "Pandemic - Catalyst of the Virtualization of the Social Space," Postmodern Openings, Editura Lumen, Department of Economics, vol. 11(1Sup2), pages 115-140, May.
    5. Oliver Thomas & Simon Hagen & Ulrich Frank & Jan Recker & Lauri Wessel & Friedemann Kammler & Novica Zarvic & Ingo Timm, 2020. "Global Crises and the Role of BISE," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 385-396, August.

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    More about this item

    Keywords

    data science; health; Coronavirus; COVID-19; artificial intelligence; development; technology; innovation;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O39 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Other
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • O20 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - General

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