Concern 369 · Working draft · editorial review in progress
Harassment content targeting individuals
AI-assisted harassment is the use of generated messages, images or impersonations to repeatedly target a person with abuse.
Understanding the concern
A harasser can use AI to produce many variations of a message, adapt it to different platforms or create convincing false material. The harm is not only in any single item. Repetition, reach and the burden of responding can make someone feel unable to participate in work or public life.
This resembles a crowd shouting at one person, even when only a few people are organising it. Automated content can make the apparent crowd larger. Effective responses need to consider the pattern and target, not just whether each message contains a prohibited word. People also need practical ways to report connected incidents.
An example
One person receives a stream of personalised abusive messages that keep changing wording after earlier posts are removed.
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 report examines technology-facilitated violence, especially against women in public life. It does not establish a universal rate for all harassment targets.
UN Women · Research report
Tipping Point: Online Violence Against Women in the Public Sphere ↗ (opens in a new tab)Survey evidence and analysis of technology-facilitated violence; not a representative rate for every woman.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Can the service recognise a coordinated pattern and reduce the burden on the person being targeted?
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.
Justice
Justice means fair treatment, fair procedures, and attention to who receives benefits and burdens. It asks whether people with less power can be heard and seek repair.
Look at outcomes across different groups and individual cases. Provide a usable way to challenge decisions and correct harm. Equal wording in a policy does not guarantee equal treatment in practice.
Ask together: Who benefits, who bears the cost, and who can challenge the decision?
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?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
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