Concern 587 · Working draft · editorial review in progress
AI grooming risk
AI-assisted grooming risk concerns offenders using generated communication or identities to manipulate a young person's trust.
Understanding the concern
The defining harm is a person's attempt to exploit a child. AI may help maintain a false identity or repeated contact, but the responsibility remains with the offender. This is distinct from a chatbot independently giving an unsafe reply, even though both require child-safety safeguards.
Prevention should focus on safe service design, reporting and access to trusted support rather than expecting children to detect every convincing deception. Guidance identifies a potential misuse pathway; it does not establish how often AI is involved in grooming. Young people should be able to seek help without fear that curiosity or trust will be treated as their fault.
An example
A young person receives sustained contact from someone whose identity and intentions are misrepresented.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
Evidence and its limits
These sources establish safeguarding concerns, not a measured prevalence of AI-assisted offender grooming.
UNICEF Innocenti · December 2025 · Rights-based guidance
Guidance on AI and children, version 3.0 ↗ (opens in a new tab)Child-centered design recommendations; not a causal study of developmental harm from all AI use.
Australian eSafety Commissioner · March 2026 · Regulatory transparency report
eSafety report shows AI companions are putting children at risk ↗ (opens in a new tab)Summarizes four services' responses; a bounded review of reported safeguards, not every chatbot.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
What would make it easier for a young person to ask for help about an uncomfortable online interaction?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Dignity
Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.
Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.
Ask together: Does this use treat each person as someone whose experience matters?
Listening
Listening means trying to understand someone's experience before preparing an answer. People who use a service, work with it, or are judged by it may notice problems its designers miss.
Invite people to describe what happened in their own words. Repeat back what you understood and let them correct it. A quiet person or a complaint that is hard to measure may still reveal something important.
Ask together: Whose experience have we not heard yet?
Seeing potential
Seeing potential means recognizing people's capacity to learn, contribute, and grow. It resists reducing someone to a score or to the tasks a machine can perform faster.
Use tools to support people's development. Give learners time, feedback, and real opportunities to practice. A prediction about someone's performance should not close off their future.
Ask together: How could this help people develop abilities they value?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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