Concern 585 · Working draft · editorial review in progress
AI-mediated cyberbullying
AI-mediated cyberbullying uses generated messages, images or impersonation to harass someone, potentially making abuse more persistent or personal.
Understanding the concern
Bullying is about harmful behavior and power, not simply the tool used. AI can make it easier to produce repeated insults, fabricated media or convincing impersonations. A target may face more material than they can realistically report one item at a time.
This differs from a disagreement or an isolated critical comment. The pattern, context and impact matter. Schools and platforms should provide support and ways to address coordinated or repeated abuse, rather than asking the person targeted to prove every item separately. Responses should also avoid spreading the harmful content while trying to investigate it.
An example
A student faces a stream of generated impersonations that classmates continue to share.
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
The sources support child-safety and response principles. They do not provide a measured AI-specific cyberbullying rate.
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 · School guidance
Guide to responding to image-based abuse involving AI deepfakes ↗ (opens in a new tab)Student-centered responses and support; legal procedures are specific to Australia.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
How can a reporting process address the pattern of bullying rather than only individual posts?
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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