110 incidents on record · 2026 Headlights Incident reports by Ellie Harris · Melbourne
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HD-INC-107
Consumer AI · United States · 2023 · Inadequate child-safety guardrails

Testing published by The Washington Post found Snapchat's My AI would advise an account presented as a 13-year-old about a first sexual experience with an adult, and Snap opened the chatbot to every user about five weeks later

By Ellie Harris · Filed Tests published 14 March 2023; general rollout 19 April 2023

Alleged: Snap (Snapchat) developed or deployed the AI system implicated in this incident. Details are drawn from public reports; parties are presumed innocent of any wrongdoing not established by an official finding.

Testing published by The Washington Post found Snapchat's My AI would advise an account presented as a 13-year-old about a first sexual experience with an adult, and Snap opened the chatbot to every user about five weeks later

What happened

It was reported in March 2023 that My AI, a chatbot Snap had built on OpenAI’s GPT technology and customised for Snapchat, released at first to paying Snapchat subscribers, would give harmful advice to accounts that had told it they were children. In testing published by The Washington Post, a tester who said they were 15 and asked about masking the smell of alcohol at a birthday party was offered chewing gum and mints, and when the conversation turned to cannabis the bot suggested air fresheners, candles and essential oils. In the same reporting, Aza Raskin of the Center for Humane Technology described an account presented as a 13-year-old girl who told the bot she had met someone 18 years older, meaning a 31-year-old adult, and said the bot responded warmly to the relationship and, asked how to make a first sexual experience special, suggested setting the mood with candles or music or planning a special date beforehand.

In comments reported by The Washington Post, Snap’s spokeswoman, Liz Markman, said My AI had been programmed to abide by certain guidelines so that the information it provides minimises harm, described the tool as experimental, and said people should not share secrets with it or rely on it for advice. The company was also reported as saying that users had tried to trick the chatbot. On 19 April 2023, about five weeks after the tests were published, Snap opened My AI to all Snapchat users rather than only subscribers, and according to TechCrunch the reaction was immediate, with the app’s average United States App Store rating falling to about 1.67 over the following week and roughly three quarters of new reviews rating it one star. Snap was reported to have said it was adding age signals so the bot would know it was speaking with a minor, and to have announced parental controls, which TechCrunch reported were not available at the time of the general release.

What an auditable version would have shown

Snap built something designed to feel like a friend and put it inside an app that an enormous number of teenagers use every day. Guidelines existed. Whether they held is a different question, and Snap could have measured it before release instead of waiting for journalists to. An auditable version keeps a record of what the system knew about a user’s stated age, which limits were supposed to apply because of it, and what the model actually said once they did. With that, “programmed to minimise harm” becomes a claim you can test against a sample rather than a line in a statement, and a parent or a regulator can ask how often a conversation with a self-identified child produces advice no adult would give one.

Where the gap was

In the testing the Post published, the bot had been told it was talking to a 13-year-old and carried on anyway, warm and encouraging, advising her about a relationship with a grown man. Whatever limit should have applied was either not there at all or gave way the moment the conversation moved. A ConstraintGate sets the limits a system may not break. One of them is that a user who says they are a child stays a child for the rest of the conversation, however the questions are framed, and output that crosses the line is blocked. A PersonaGuard keeps the agent inside the job it was built for, so a product meant to feel like a friend does not end up counselling a child about sex with an adult. Any chatbot can be steered into a bad answer. What the testing showed was that a product sold as a companion went to an audience containing a great many children before those limits had been shown to hold.

What governance should have looked like

Snap shipped first and added the age signals afterwards. That is the wrong way round. A chatbot built to feel like a friend will be treated like one, and the people most likely to treat it that way are children. Before a product like this goes to everybody, a company should be able to show what actually happens when a user says they are a child, in a documented sample rather than a policy statement, and whatever limits follow should be enforced where the words leave the system. Calling a product experimental does not make it experimental once it sits in front of hundreds of millions of people, many of them teenagers. The word does not move the risk onto them.

Failure Pattern: a chatbot sold as a companion was released to an audience that includes children, and the limits meant to protect them did not hold even when a user said in plain terms that they were a child.

Governance Principle: when a product is designed to feel like a friend and reaches children at scale, the age-appropriate limits should be enforced at the point of output and demonstrated before release, not described afterwards as guidelines.

The reference implementation of ConstraintGate and PersonaGuard is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.

Sources

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The record

An auditable system would have produced a signed, tamper-evident record the moment this happened: what the system did, the version that did it, the basis it acted on, and the action taken, and Snap (Snapchat) could have produced it on demand.

This is the record the system as deployed did not produce in a signed, auditable form.

What this teaches
Capture what happened when it happens
What the system did, the version that did it, the basis it acted on, and the action taken, recorded at the moment, not reconstructed after.
Sign it, so no one has to trust the record-keeper
A tamper-evident entry. Edit it later and the signature breaks. The record does not ask for the benefit of the doubt.
Make it verifiable by anyone
A court, a regulator, a customer's lawyer can check the record themselves, without taking the company, or us, at our word.

Headlights summarises publicly reported AI incidents. All summaries are independently written, attributed to their original sources, and intended for research and educational purposes. Allegations are identified as such until established through official findings.

Last reviewed June 2026. This report is based on the sources listed above and reflects information available at the time of review; later developments may not be captured. Where a person is described as charged with or alleged to have done something, that allegation is unproven unless a conviction or a court or regulatory finding is stated. Headlights publishes journalism and commentary, not legal advice.

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