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A Student-Led Initiative

Before you trust AI with your health,
learn to VERIFY.

A six-step framework for evaluating health information from AI — designed for the generation that uses these tools the most.

V
Verify
Check the source
E
Evaluate
Assess confidence
R
Recognize
Know limitations
I
Investigate
Question bias
F
Flag
Spot red flags
Y
Your Call
Own the decision

Your generation is the first to use AI for health advice at scale. No one taught you how.

One in four young adults uses AI chatbots for health information monthly. These tools deliver every answer — right or wrong — with the same confidence. The tone rarely changes, and they almost never tell you which specific part of an answer might be wrong. Published research shows they accept fabricated medical claims roughly half the time.

There are governance frameworks for hospitals deploying AI. There are medical school courses for future doctors. But for the people actually using these tools every day — teens and young adults — there is no structured program teaching them how to evaluate what they're getting back. VERIFY is that program.

25%
of 18–29 year-olds use AI for health info monthly
KFF Health Misinformation Tracking Poll, Aug 2024
~50%
of fabricated medical claims accepted as true by AI (49–55% across models)
Kaur et al., ACL Findings 2024
Nearly 1 in 5
young people (ages 12–21) use AI chatbots for mental health advice
RAND / JAMA Pediatrics 2026
0
state-adopted health curricula found that teach teens to evaluate AI health advice
Our 2026 landscape review

Free curriculum for students, educators, and organizations.

Open-source teaching materials under Creative Commons. Download slides, facilitator guides, handouts, and assessments — everything you need to start teaching AI health literacy.

High school curriculum

6 sessions, 30 minutes each. Slides, facilitator guides, and student handouts for AP Biology, Health Science, or Advisory periods.

VERIFY toolkit In development

Printable poster, interactive walkthrough, wallet card, and infographic. Designed to be remembered after a single session.

Case study library In development

Real examples from published research, written for a student audience. When AI got it wrong, what happened, and what VERIFY would have caught.

Browse all resources →
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