US AI rules, US AI rules
Colo. Rev. Stat. § 6-1-1701 et seq.
- What this page is
- US AI rules, US AI rules
- Checked against the official source
- 2026-08-15Changed
- Responsible publisher
- ExploreWorld Legal, editorial deskLiability position
Short answer
Does US AI rules apply to your operation, and which paragraph decides?
US AI rules rests on Colo. Rev. Stat. § 6-1-1701 et seq. and is tested here by a deterministic rule tree of 4 rules with a coverage score of 55 percent. The tree reads your facts, names the paragraph that decides the question and returns an outcome carrying citation, content hash and read date 2026-08-15. The outcome is a machine classification, not a compliance decision.
Colo. Rev. Stat. § 6-1-1701 et seq.Checked against the publisher 2026-08-15Official text
A source reference, not legal advice.
- Jurisdiction
- State CO, State IL, State UT
- Risk dimensions
- operations, employment, privacy
- Tier
- Tier 1
- Coverage
- 55 %
- Impact
- 5/5
- Read
- 2026-08-15
Source chain
Every block in the register row has its own address, so an outcome can be cited down to the paragraph. The node carries the reference, the scope, the link to the official text and the outcomes in the tree that rest on the block.
- Developer duties
Colo. Rev. Stat. § 6-1-1702
Reasonable care against algorithmic discrimination, plus documentation handed to the deployer.
- Deployer duties
Colo. Rev. Stat. § 6-1-1703
A risk management program, an impact assessment and notice to the consumer before a consequential decision.
- Impact assessment
Colo. Rev. Stat. § 6-1-1703(3)
Purpose, known risks, data categories, performance metrics and post-deployment monitoring.
- Consumer notice and appeal
Colo. Rev. Stat. § 6-1-1703(4)
Notice of an adverse consequential decision, the reason, and a route to correction and human review.
- Public statement
Colo. Rev. Stat. § 6-1-1703(5)
A public summary of the high-risk systems deployed and how risk is managed.
- Discriminatory use
775 ILCS 5/2-102(L)
Use of artificial intelligence that has a discriminatory effect on a protected class in recruitment, promotion, discipline or discharge.
- Zip code as proxy
775 ILCS 5/2-102(L)(2)
Use of zip code as a proxy for a protected class.
- No defence for the system
Utah Code § 13-72-101
A person cannot rely on generative AI as a defence for a statement that breaches consumer protection law.
- Disclosure on request
Utah Code § 13-72-201
A clear statement that the counterpart is a generative AI system when the consumer asks.
- Regulated occupations
Utah Code § 13-72-202
Prominent disclosure at the start of the interaction in occupations that require a licence.
Colo. Rev. Stat. § 6-1-1701 et seq.
Rule tree
Rules are tested top down. Conditions are statutory elements and each outcome points to the register blocks it rests on.
ai-co-deployer
Impact assessment missing for a high-risk system in Colorado
prohibited · Requirement applies · deployer, impact, notice
Colo. Rev. Stat. § 6-1-1703 requires a risk management program, an impact assessment and notice to the consumer before a consequential decision, with correction and human review.
ai-co
The Colorado AI Act applies to the system
risk · Requirement applies · developer, deployer, public
Developers must use reasonable care against algorithmic discrimination and provide documentation (§ 6-1-1702). Deployers need a risk program, impact assessment, consumer notice and a public statement (§ 6-1-1703).
ai-il
Illinois rules on AI in employment apply
risk · Requirement applies
775 ILCS 5/2-102(L) prohibits AI that discriminates in employment decisions and requires notice to the applicant. 820 ILCS 42 requires notice and consent for AI analysis of video interviews.
ai-ut
Utah requires disclosure of generative AI
risk · Requirement applies
Utah Code § 13-75-103 requires disclosure on request that the consumer is interacting with generative AI, and regulated occupations must disclose it up front.
Outcome
allowed · Outside the scope
The rule yields no requirement for the facts supplied
No high-risk decision in Colorado, hiring in Illinois or generative consumer interaction in Utah is stated.
fallback · sha256:sha256:1df9e94e0280edc362953a7bc
Monitoring
The journal shows what moved in the register row, with the hash before and after. The impact score follows a rule stated in plain words.
How impact is scored: Grund: tillagd eller borttagen uppgift ger 3, ändrad uppgift 2, omläsning utan ändring 0. Tillägg: +1 när ändringen rör status eller tillämpningsdatum. Tillägg: +1 när agenten ligger i klass 1. Siffran begränsas till 0 till 5.
2026-08-15 · 0/5 · lasning
Raden läst mot den officiella publiceringen utan ändring
2026-08-15 · 0/5 · lasning
Raden läst mot den officiella publiceringen utan ändring
2026-08-15 · 0/5 · lasning
Raden läst mot den officiella publiceringen utan ändring
2026-06-30 · 4/5 · tillampningsdatum, status
Regeln började tillämpas enligt utgivaren
2026-01-01 · 4/5 · tillampningsdatum, status
Regeln började tillämpas enligt utgivaren
2024-08-09 · 5/5 · antagande, identifierare, status
Regeln antogs enligt 775 ILCS 5/2-102
2024-05-17 · 5/5 · antagande, identifierare, status
Regeln antogs enligt Colo. Rev. Stat. § 6-1-1701 et seq.
2024-05-01 · 4/5 · tillampningsdatum, status
Regeln började tillämpas enligt utgivaren
2024-03-13 · 5/5 · antagande, identifierare, status
Regeln antogs enligt Utah Code § 13-72
Supervision
- Colorado Department of Law, Attorney General
- Illinois Department of Human Rights
- Utah Division of Consumer Protection
European counterparts
- ai-act · Båda texterna bygger på riskklasser, konsekvensbedömning och transparens. Coloradolagen är skriven kring beslut med rättslig verkan för konsumenter, inte kring att släppa ut en produkt på marknaden.
- ai-act · Anställning är ett högriskområde i bilaga III till AI-förordningen. Illinoisvägen går genom medborgarrättslagstiftning i stället för produktregler.
- ai-act · Artikel 50 i AI-förordningen bär samma tanke om transparens mot den som samspelar med systemet.
Artifacts and integrity
- https://legal.exploreworldai.com/api/public/v1/us-agents/us-ai-rules/manifest.json
- https://legal.exploreworldai.com/api/public/v1/us-agents/us-ai-rules/run
- https://legal.exploreworldai.com/api/public/v1/us-agents/us-ai-rules/monitor.json
- sha256:16018990250bcc2d3503fed2d00e7e4a9555e5f632f79d03e3bb14e560a16112
- sha256:498e73e8201acb70db77a0555cfa9d9759136c226813e51a7105a6b63545a35e
The verdict is a machine classification of the outcome, not legal advice and not a compliance decision. Responsibility position · Colo. Rev. Stat. § 6-1-1701 et seq.
Verifiable trust signals
- Six fixed blocks, one source per line
- No sentence written by a language model
- Engine version and read date on every answer
- No customer data, no documents, no advice
- Model card and audit published under the EU AI Act