The Promise and Perils of Artificial Intelligence in Advancing Participatory Science and Health Equity in Public Health.

Journal: JMIR public health and surveillance
PMID:

Abstract

Current societal trends reflect an increased mistrust in science and a lowered civic engagement that threaten to impair research that is foundational for ensuring public health and advancing health equity. One effective countermeasure to these trends lies in community-facing citizen science applications to increase public participation in scientific research, making this field an important target for artificial intelligence (AI) exploration. We highlight potentially promising citizen science AI applications that extend beyond individual use to the community level, including conversational large language models, text-to-image generative AI tools, descriptive analytics for analyzing integrated macro- and micro-level data, and predictive analytics. The novel adaptations of AI technologies for community-engaged participatory research also bring an array of potential risks. We highlight possible negative externalities and mitigations for some of the potential ethical and societal challenges in this field.

Authors

  • Abby C King
    Departments of Epidemiology & Population Health and of Medicine (Stanford Prevention Research Center), Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA, 94304-1210, United States, 1 650-497-2806.
  • Zakaria N Doueiri
    Department of Epidemiology & Population Health, Stanford University School of Medicine, Palo Alto, CA, United States.
  • Ankita Kaulberg
    Department of Epidemiology & Population Health, Stanford University School of Medicine, Palo Alto, CA, United States.
  • Lisa Goldman Rosas
    Departments of Epidemiology & Population Health and of Medicine (Division of Primary Care and Population Health), Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States.