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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Artificial intelligence and increasing misinformation.

Scott Monteith1, Tasha Glenn2, John R Geddes3

  • 1Michigan State University College of Human Medicine, Traverse City Campus, Traverse City, Michigan, USA.

The British Journal of Psychiatry : the Journal of Mental Science
|October 26, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) advancements expose patients to medical misinformation. Generative AI, like ChatGPT, can create unreliable content, including dangerous advice about mental illness, necessitating awareness among psychiatrists.

Keywords:
Generative artificial intelligenceartificial intelligencedisinformationmisinformationtechnology

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence
  • Mental Health

Background:

  • Rapid advancements in artificial intelligence (AI) are leading to widespread public exposure to AI-generated content.
  • Generative AI models, including large language models (LLMs), are increasingly used for commercial purposes, producing text, images, audio, and video.
  • The public will frequently encounter AI-generated messages in their daily lives.

Purpose of the Study:

  • To highlight the potential risks of misinformation generated by AI, particularly in the medical and psychiatric fields.
  • To inform healthcare professionals, especially psychiatrists, about the unreliability of generative AI.
  • To emphasize the need for vigilance regarding AI-generated medical information encountered by patients.

Main Methods:

  • This is a conceptual analysis and review of the implications of generative AI in healthcare.
  • The study examines the capabilities and limitations of current generative AI models.
  • It synthesizes information on the potential for AI to generate inaccurate or harmful medical content.

Main Results:

  • Generative AI models can produce content with factual errors, nonsensical information, fabricated sources, and dangerous advice.
  • Misinformation related to mental illness is a significant concern, potentially leading to adverse patient outcomes.
  • The unreliability of AI-generated content poses a risk to public health and patient safety.

Conclusions:

  • Psychiatrists and other healthcare providers must be aware that patients may receive and act upon misinformation from generative AI.
  • Educating patients about the limitations of AI-generated medical information is crucial.
  • Healthcare systems need to develop strategies to mitigate the impact of AI-driven medical misinformation.