Cross-Sectional Evaluation of Medical Disinformation Safeguards in Consumer-Facing Large Language Model Platforms

JMIR Infodemiology 2026 Open access

Read full text
Authors: Natansh D. Modi, Cyril A. Alex, Abdulhalim A. Awaty, Bradley D. Menz, S. Bacchi, Kacper Gradoń, Jessica M. Logan, Andrew Rowland, Lisa M. Kalisch Ellett, Ross A. McKinnon, Michael D. Wiese, Michael J. Sorich
+1 more Ashley M. Hopkins
DOI: 10.2196/89831
Cited by: 4
References: 8

Abstract

Unlabelled: This cross-sectional evaluation of six consumer-facing large language model platforms found significant heterogeneity in safeguard performance against the generation of health disinformation, with Claude and ChatGPT demonstrating complete resistance across all prompt types, while Copilot, Meta AI, Grok, and Gemini exhibited substantial vulnerabilities.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Adversarial Robustness in Machine Learning Misinformation and Its Impacts

Publication details

Journal / source
JMIR Infodemiology
Publisher
JMIR Publications Inc.
Volume
6
Pages
e89831–e89831
Publication date
20 April 2026
Language
EN