Concern 803 · Working draft · editorial review in progress

US state laws

Differences among US state and local AI rules can create uneven protections and make it harder to know which duties apply in a particular place.

Understanding the concern

Some rules focus on automated decisions, others on disclosure, employment or specific harms. The same product may therefore face different requirements depending on how and where it is used. For the public, the practical concern is whether there is a clear notice, a way to challenge a decision and an authority that can help.

Colorado revised its earlier AI framework through legislation signed in May 2026. New York City's employment-tool rules separately require audits and notices for covered tools. A city rule is not a state law, and an older bill summary may be outdated. The situation resembles different local building codes: knowing one does not establish compliance with all the others.

An example

An employer uses one hiring system in several locations but provides the same notice everywhere without checking local requirements.

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 examples illustrate variation, not a complete survey of US law. Scope, amendments and effective dates must be checked for the specific use.

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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 protections apply where this decision affects the person, and are those protections clearly explained?

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
Major · 4/5
Likelihood
Widely observed · 4/5
Time horizon
Near
Register risk score
16
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