Concern 392 · Working draft · editorial review in progress

Endangered-language exclusion

Endangered-language exclusion is the risk that digital services leave little room for languages whose continued use is already under pressure.

Understanding the concern

If tools work only in dominant languages, speakers may have fewer ways to learn, create or access services in their own language. AI can reinforce that pressure when it produces poor or absent support. But technology can also help communities document and use their languages when they direct the work.

Language survival depends on people, institutions and opportunities, not a chatbot alone. It would be too strong to say AI inevitably causes a language to disappear. The important question is who controls the project and whose needs it serves. Some knowledge may be private or culturally restricted, so gathering every available text is not automatically helpful.

An example

A community wants a language-learning tool but wants control over which recordings and stories may be used.

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

UNESCO and CARE principles support inclusion and community authority. They do not establish a causal forecast of language extinction from AI.

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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 project strengthen community-led language use while respecting control over cultural knowledge?

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
Catastrophic · 5/5
Likelihood
Widely observed · 4/5
Time horizon
Long
Register risk score
20
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