Concern 823 · Working draft · editorial review in progress

AI Safety Institute network

International AI evaluation networks help countries compare technical evidence, but their work should not be mistaken for a worldwide regulator or universal safety approval.

Understanding the concern

Different countries can test similar capabilities using different methods. Sharing approaches can reveal gaps and reduce duplicated effort. Yet participating institutions have different mandates, resources and access to models. A joint technical statement does not settle every policy question or guarantee that a system is safe in every setting.

NIST describes the current International Network for Advanced AI Measurement, Evaluation, and Science and its work on automated evaluations. Think of laboratories agreeing on how to measure water quality: comparable measurements help, but decisions still require context and responsible authorities. Names and institutional arrangements can also change, so older labels need updating.

An example

A company points to participation in a government evaluation program as though the program approved all its products.

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.
Model
The learned part of an AI system. It uses patterns found during training to produce an answer or prediction.

Evidence and its limits

The network supports technical cooperation. It is not a global licensing agency, and participation does not imply endorsement of every member's or vendor's claims.

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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

What was actually evaluated, what uncertainties remain, and which authority is responsible for any decision to deploy?

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.

Accountability

Accountability means being answerable for decisions and taking responsibility for repair. It requires more than saying that the software made the choice.

Name the person or team responsible, keep useful records, and give them authority to correct problems. Make the route to a complaint clear to the people affected.

Ask together: Who will answer for the outcome and help put things right?

Prudence

Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.

Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.

Ask together: What is a careful next step, and when should we stop or change course?

Unity

Unity means working toward shared purposes while making room for real differences. It does not require everyone to have the same experience, beliefs, or opinion.

Look for a goal people can share, then explore disagreements about how to reach it. Make sure quieter or less powerful voices can influence the result.

Ask together: What purpose can we share while respecting our differences?

Editorial ratings

These are editorial judgments from the register, not measured probabilities or predictions about your situation.

Severity
Serious · 3/5
Likelihood
Widely observed · 4/5
Time horizon
Now
Register risk score
12
About the register and scoring →
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