The doctor will polygraph you now.

Journal: npj health systems
Published Date: Dec 5, 2024

Abstract

Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors that could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for "fact-checking", particularly in cases where the data/models may contradict the patient. Additionally, this report simulated the misuse of a verification system using patient voice samples and identified a potential LLM bias against patient-reported information in favor of multi-dimensional data and the outputs of other AI methods (i.e., "AI self-trust"). Finally, recommendations were presented for mitigating the risk that AI verification methods will cause harm to patients or undermine the purpose of the healthcare system.

Authors

  • James Anibal
    Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, Bethesda, MD, United States.
  • Jasmine Gunkel
    Department of Bioethics, National Institutes of Health (NIH), Bethesda, MD USA.
  • Shaheen Awan
    Department of Communication Sciences & Disorders, University of Central Florida, Orlando, FL USA.
  • Hannah Huth
    Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, Bethesda, MD, United States.
  • Hang Nguyen
    Social Science and Implementation Research Team, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.
  • Tram Le
    College of Engineering, University of South Florida, Tampa, FL USA.
  • Jean-Christophe Bélisle-Pipon
    Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada.
  • Micah Boyer
    USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida, Tampa, FL USA.
  • Lindsey Hazen
    Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, Bethesda, MD, United States.
  • Yael Bensoussan
    Morsani College of Medicine, University of South Florida, Tampa, FL, United States.
  • David Clifton
    Computational Health Informatics Lab, Oxford Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.
  • Bradford Wood
    Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, Bethesda, MD, United States.

Keywords

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