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. They don't hesitate, don't hedge, and don't tell you when they're uncertain. Published research shows they accept fabricated medical claims roughly a third of 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
~32%
of fabricated medical claims accepted as true by AI
1 in 5
young adults use AI for mental health advice
0
existing programs teaching AI health literacy to students

Free resources for students, educators, and organizations.

Everything built to be used, shared, and adapted. All materials will be open-source under Creative Commons.

Four-session curriculum

Slide decks, facilitator guides, and discussion materials covering AI accuracy, real-world failures, algorithmic bias, and the VERIFY framework in practice.

VERIFY toolkit

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

Replication blueprint

A step-by-step guide for any student leader, teacher, or organization to run the program independently — no expert required.

Case study library

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