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The Role of Artificial Intelligence and Machine Learning Amid the COVID-19 Pandemic: What Lessons Are We Learning on 4IR and the Sustainable Development Goals

Author

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  • David Mhlanga

    (Faculty of Business and Economics, University of Johannesburg, Johannesburg 2006, South Africa)

Abstract

The COVID-19 pandemic came with disruptions in every aspect of human existence, with all the sectors of the economies of the world affected greatly. In the health sector, the pandemic halted and reversed progress in health and subsequently shortened life expectancy, especially in developing and underdeveloped nations. On the other hand, machine learning and artificial intelligence contributed a great deal to the handling of the pandemic globally. Therefore, the current study aimed to assess the role played by artificial intelligence and machine learning in addressing the dangers posed by the COVID-19 pandemic, as well as extrapolate the lessons on the fourth industrial revolution and sustainable development goals. Using qualitative content analysis, the results indicated that artificial intelligence and machine learning played an important role in the response to the challenges posed by the COVID-19 pandemic. Artificial intelligence, machine learning, and various digital communication tools through telehealth performed meaningful roles in scaling customer communications, provided a platform for understanding how COVID-19 spreads, and sped up research and treatment of COVID-19, among other notable achievements. The lessons we draw from this is that, despite the disruptions and the rise in the number of unintended consequences of technology in the fourth industrial revolution, the role played by artificial intelligence and machine learning motivates us to conclude that governments must build trust in these technologies, to address health problems going forward, to ensure that the sustainable development goals related to good health and wellbeing are achieved.

Suggested Citation

  • David Mhlanga, 2022. "The Role of Artificial Intelligence and Machine Learning Amid the COVID-19 Pandemic: What Lessons Are We Learning on 4IR and the Sustainable Development Goals," IJERPH, MDPI, vol. 19(3), pages 1-22, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1879-:d:744183
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    References listed on IDEAS

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    1. DiMasi, Joseph A. & Grabowski, Henry G. & Hansen, Ronald W., 2016. "Innovation in the pharmaceutical industry: New estimates of R&D costs," Journal of Health Economics, Elsevier, vol. 47(C), pages 20-33.
    2. David Mhlanga & Rufaro Garidzirai, 2020. "The Influence of Racial Differences in the Demand for Healthcare in South Africa: A Case of Public Healthcare," IJERPH, MDPI, vol. 17(14), pages 1-10, July.
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    Cited by:

    1. M. M. Kamruzzaman & Saad Alanazi & Madallah Alruwaili & Nasser Alshammari & Said Elaiwat & Marwan Abu-Zanona & Nisreen Innab & Bassam Mohammad Elzaghmouri & Bandar Ahmed Alanazi, 2023. "AI- and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    2. Yeguan Yu, 2023. "The Impact of Financial System on Carbon Intensity: From the Perspective of Digitalization," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
    3. David Mhlanga, 2023. "Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets: A Review," Energies, MDPI, vol. 16(2), pages 1-17, January.

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