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The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

Author

Listed:
  • Francesco Piccialli

    (University of Naples Federico II)

  • Vincenzo Schiano Cola

    (University of Naples Federico II)

  • Fabio Giampaolo

    (University of Naples Federico II)

  • Salvatore Cuomo

    (University of Naples Federico II)

Abstract

The first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Suggested Citation

  • Francesco Piccialli & Vincenzo Schiano Cola & Fabio Giampaolo & Salvatore Cuomo, 2021. "The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 23(6), pages 1467-1497, December.
    • Handle: RePEc:spr:infosf:v:23:y:2021:i:6:d:10.1007_s10796-021-10131-x
    DOI: 10.1007/s10796-021-10131-x
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    2. Victor Chang & Carole Goble & Muthu Ramachandran & Lazarus Jegatha Deborah & Reinhold Behringer, 2021. "Editorial on Machine Learning, AI and Big Data Methods and Findings for COVID-19," Information Systems Frontiers, Springer, vol. 23(6), pages 1363-1367, December.
    3. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).
    4. Mazen El-Masri & Karim Al-Yafi & Muhammad Mustafa Kamal, 2023. "A Task-Technology-Identity Fit Model of Smartwatch Utilisation and User Satisfaction: A Hybrid SEM-Neural Network Approach," Information Systems Frontiers, Springer, vol. 25(2), pages 835-852, April.
    5. Nick Drydakis, 2022. "Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 24(4), pages 1223-1247, August.
    6. Shahzad, Umer & Ghaemi Asl, Mahdi & Panait, Mirela & Sarker, Tapan & Apostu, Simona Andreea, 2023. "Emerging interaction of artificial intelligence with basic materials and oil & gas companies: A comparative look at the Islamic vs. conventional markets," Resources Policy, Elsevier, vol. 80(C).
    7. Dal Mas, Francesca & Massaro, Maurizio & Rippa, Pierluigi & Secundo, Giustina, 2023. "The challenges of digital transformation in healthcare: An interdisciplinary literature review, framework, and future research agenda," Technovation, Elsevier, vol. 123(C).

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