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Artificial Intelligence and Public Health: An Exploratory Study

Author

Listed:
  • David Jungwirth

    (Department of Environmental Health, Center for Public Health, Medical University of Vienna, 1090 Vienna, Austria
    These authors contributed equally to this work.)

  • Daniela Haluza

    (Department of Environmental Health, Center for Public Health, Medical University of Vienna, 1090 Vienna, Austria
    These authors contributed equally to this work.)

Abstract

Artificial intelligence (AI) has the potential to revolutionize research by automating data analysis, generating new insights, and supporting the discovery of new knowledge. The top 10 contribution areas of AI towards public health were gathered in this exploratory study. We utilized the “text-davinci-003” model of GPT-3, using OpenAI playground default parameters. The model was trained with the largest training dataset any AI had, limited to a cut-off date in 2021. This study aimed to test the ability of GPT-3 to advance public health and to explore the feasibility of using AI as a scientific co-author. We asked the AI asked for structured input, including scientific quotations, and reviewed responses for plausibility. We found that GPT-3 was able to assemble, summarize, and generate plausible text blocks relevant for public health concerns, elucidating valuable areas of application for itself. However, most quotations were purely invented by GPT-3 and thus invalid. Our research showed that AI can contribute to public health research as a team member. According to authorship guidelines, the AI was ultimately not listed as a co-author, as it would be done with a human researcher. We conclude that good scientific practice also needs to be followed for AI contributions, and a broad scientific discourse on AI contributions is needed.

Suggested Citation

  • David Jungwirth & Daniela Haluza, 2023. "Artificial Intelligence and Public Health: An Exploratory Study," IJERPH, MDPI, vol. 20(5), pages 1-12, March.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4541-:d:1087259
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    References listed on IDEAS

    as
    1. Benjamin Chaix & Benjamin Chaix & Benjamin Chaix & Arthur Guillemassé & Pierre Nectoux & Guillaume Delamon & Benoît Brouard & Jean Emmanuel Bibault, 2020. "Vik- A Chatbot to Support Patients with Chronic Diseases," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 27(1), pages 20501-20504, April.
    2. Daniele Giansanti, 2022. "Artificial Intelligence in Public Health: Current Trends and Future Possibilities," IJERPH, MDPI, vol. 19(19), pages 1-4, September.
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