More and more people are confiding in AI. This page shows what is happening.
What follows is a set of verifiable public facts: ongoing lawsuits, the latest statistics and international documents, each with its source and date. They point to one thing: risk accumulates on the user side, and no truly effective prevention exists yet.
This page is a digest of public information, not legal or medical advice. Allegations in litigation are not court findings.
The US lawsuits are still running
Litigation over harm from AI dialogue has grown from individual cases into coordinated proceedings. All entries below are public court records.
How many people confide in AI
This is not fringe behavior. Four surveys and disclosures from 2025 to 2026 draw the same rising line.
72% of US teens aged 13 to 17 have used an AI companion at least once; 52% use one at least a few times a month. Common Sense Media, nationally representative survey of 1,060 teens, 2025-07.
Among Taiwanese secondary students with mental health struggles who sought help, 46.5% had confided in generative AI, more than the 41.1% who went to school counseling. Child Welfare League Foundation, 7,007 responses, 2025-09.
19.2% of Americans aged 12 to 21 had turned to AI chatbots when sad, angry or stressed, up from 13.1% a year earlier. RAND, in JAMA Pediatrics, 2026-06.
What changes on the human side
Model-side “AI hallucination” means wrong output. This is about something else: how memory, emotion and the authority to judge get reorganized on the human side over long-term dialogue. Media call it AI psychosis. Researchers use more careful words.
“An acceptable response on its own does not establish safety across a series of conversations. User-side risk can still form during long-term interaction.”
From the USCP paper abstract. This is exactly what user side contextual phenomena research describes: projection, attachment, authority transfer. Research basis.
Minors, and regulation catching up
Taiwan has no equivalent law yet. The Taiwanese survey above shows its teenagers are already ahead of the regulation.
Named and listed, but not yet prevented
User-side risk has entered official registers. The problem is the next step: the lists have names, and there is still no mature, verifiable prevention mechanism.
Every single response passes the test, while the risk accumulates across the conversation. That is why regulation and litigation are both playing catch-up.
What this practice does about it
Facing this gap, the response here has three layers: make the phenomena researchable, make the reading teachable, and keep the capability on the human side.
Name, classify, publish
USCP uses a 20-month, 215,949-node first-person corpus to organize user-side change into fourteen observable phenomena and three constructs, publicly released and verifiable.
Turn reading into method
The six-step reading turns “something feels off” into a nameable, trainable, deliverable reading, delivered in writing to individuals, organizations and product teams.
Teach the capability
Advocating AI literacy for citizens in Taiwan: baseline understanding, awareness and judgment, for citizens, organizations and companies alike. Not tool operation. Whether to trust, whether to use, who is responsible.
If you or someone near you is in crisis, in Taiwan call 1925 (mental health support line), 1995 (Lifeline), or 119. Crisis handling always takes priority over any delivery schedule.