Concern 372 · Working draft · editorial review in progress

Gender-based violence content

AI-enabled gender-based abuse uses generated content or automated targeting to harm people because of gender or reinforce gendered control.

Understanding the concern

It can include sexualised fabrications, threats, impersonation and campaigns intended to silence someone. This overlaps with image-based abuse, but is broader: the goal may be to damage a woman's credibility, drive her from public life or extend an abusive relationship's control. Online and offline consequences can connect.

UN Women has examined how new tools make abusive content easier to produce and harder to contain. The impact depends on the target's circumstances and support, not simply how many posts exist. A response that removes one image while ignoring repeated intimidation may miss the larger pattern.

An example

A woman in public life faces a coordinated stream of fabricated sexual claims intended to make her withdraw from speaking.

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 document and analyse gendered technology-facilitated harm. They do not imply every woman has the same experience or that only women can be targeted.

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Broader frameworks and background

These resources provide context. They do not establish every claim in this concern.

A question to discuss

Does the response address the pattern of intimidation and the person's safety, as well as individual pieces of content?

Keep track of different views, what needs checking, and any next step in your own discussion notes.

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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.

Severity
Major · 4/5
Likelihood
Documented at scale · 5/5
Time horizon
Now
Register risk score
20
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More ways to explore

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