{"resourceId":"colorado-ag-admt-rules-redline-human-review-authority-20261006","versions":[{"version":"external-2dc4b45219b5dca82d7c9bea78f120fed44d2fa0e372ab506d30eb5fc5355ae1","resource":{"id":"colorado-ag-admt-rules-redline-human-review-authority-20261006","title":"Colorado AG Oct 6 redline of ADMT and Chatbot Safety Act rules adds a 'materially influence' presumption and defines human reviewers by override authority","organization":"Colorado Department of Law (Attorney General)","sector":"State regulatory oversight of automated decision-making","geography":"Colorado","publishedAt":"2026-10-09","publicationDate":"2026-10-09","eventDate":"2026-10-06","sourceName":"Orrick InfoBytes","sourceLabel":"Colorado releases revised proposed automated decision-making rules ahead of hearing (Oct 9, 2026)","sourceUrl":"https://infobytes.orrick.com/2026-10-09/colorado-releases-revised-proposed-automated-decision-making-rules-ahead-of-hearing/","evidenceClass":"independent-reporting","outcomeClass":"emerging","topics":["governance-procurement","operating-model"],"finding":"On Oct 6, the Colorado AG released an interim redline of proposed rules for the ADMT Act (SB 26-189) and Chatbot Safety Act (HB 26-1263), ahead of an Oct 26 hearing; comments accepted through the hearing; laws take effect Jan 1, 2027. The draft adds a presumption that an output 'materially influences' a consequential decision when the decision-maker reviews it and it matches the outcome, rebuttable as a 'de minimis factor'. It drops the requirement to state principal reasons for adverse outcomes, replacing it with a specific description of the technology's role, removes the stay of adverse outcomes pending correction or human review, and lets human reviewers be internal or external if they have actual authority to override.","sledRelevance":"A state AG acting as AI regulator; the human-review and adverse-outcome definitions are transferable benchmarks for state agencies writing rights-affecting human-in-the-loop rules (e.g., Utah EO 2026-08). Whether Colorado agencies themselves are covered deployers is not addressed in the source.","evidence":"Opened the Orrick InfoBytes summary (Oct 9) via curl; the AG redline itself was not opened this run.","architectureImplications":"Systems producing scores, rankings or recommendations reviewed by decision-makers fall under the presumption; summarization-only tools are treated differently.","governanceImplications":"Defines meaningful human review by override authority rather than review existence, and loosens disclosure from reasons to role description.","securityPrivacyImplications":"Correction rights narrowed to instructions for correcting personal data, excluding scores and predictions.","caveats":"Law-firm secondary summary of an interim draft; rules not final and may change after Oct 26 hearing. Primary redline not inspected. Applicability to state agencies unclear; primarily private-sector deployer obligations.","streamIds":["state-government"],"roles":{"sales":"Colorado's AG is setting a concrete test for when AI materially influences a consequential decision and who counts as a human reviewer: someone with real authority to override. For state-government buyers this is a usable benchmark for their own human-in-the-loop rules. Offer decision-support mapping against that standard. Do not claim compliance outcomes; rules are an interim draft from a secondary summary, and agency applicability is unclear.","engineering":"Systems that emit scores, rankings or recommendations reviewed by staff would fall under the presumption, so log the output, the reviewer, their authority and the final decision to support rebuttal as de minimis. Generate role-of-technology disclosures from metadata. Summarization-only tools are treated differently, so classify each integration. Validate against the primary redline before design, since only a summary was inspected.","delivery":"Delivery work is an inventory of decision workflows where AI outputs reach reviewers, with reviewer authority documented in delegations. Build a disclosure and request-handling process meeting a 15-day response window. Track the Oct 26 hearing and Jan 1, 2027 effective date. Acceptance criteria are proposals pending final rules; agencies outside Colorado should treat this as a reference model only."},"roleDetails":{"sales":{"customerProblem":"Agencies need a defensible definition of meaningful human review for AI-influenced decisions.","stakeholders":["Agency general counsel","Program directors for benefits/licensing decisions","State CIO/AI office","Attorney general staff"],"discoveryQuestions":["Which decisions use AI scores or recommendations?","Do reviewers have documented override authority?","Can systems describe the technology's role in an adverse outcome?","Are agencies covered deployers under state law?"],"valueHypothesis":"Mapping workflows to an override-authority standard reduces ambiguity in rights-affecting AI use.","potentialEngagement":"Workflow and reviewer-authority assessment for a few high-impact decision processes.","unsupportedClaims":["That Colorado agencies are covered by these rules","Final rule content","Reduced legal risk from adopting the draft standard"]},"engineering":{"fit":"Relevant to decision-support systems producing scores or recommendations.","architectureIntegration":"Capture output, reviewer identity, authority and final decision in audit logs; template role-of-technology disclosures.","prerequisites":["Decision-workflow inventory","Reviewer delegation records","Primary redline review"],"constraints":["Interim draft subject to change","Colorado-specific law","Agency coverage unclear"],"security":"Protect audit logs containing personal data and scores; restrict access to reviewers and auditors.","proofOfValue":["Sample decision trace showing reviewer override capability","Generated disclosure matched to a test adverse outcome","Classification of each tool as decision-influencing or summarization-only"]},"delivery":{"work":"Inventory AI-influenced decisions, document reviewer authority, stand up disclosure handling.","dependencies":["Final rules after Oct 26 hearing","Counsel interpretation of coverage","Program staffing"],"ownership":"Agency counsel with program and AI governance leads.","skillsAdoption":"Reviewers trained on override authority and documentation.","governanceCheckpoints":["Coverage determination","Reviewer delegation sign-off","Pre-effective-date readiness review"],"acceptanceCriteria":["Proposed: 100% of in-scope workflows list a reviewer with override authority","Proposed: information requests answered within 15 days","Proposed: disclosures describe the technology's role for each adverse outcome"],"risks":["Final rules differ from redline","Rubber-stamp review despite authority","Over-reliance on secondary summary"]}},"retrievedAt":"2026-10-09T22:22:35-05:00","enrichedAt":"2026-10-09T22:22:35-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Human reviewers must hold real override authority, a staffing and delegation question.","procurementImplications":"Agencies buying decision-support tools may need vendors to support role-of-technology disclosures.","operatingModelImplications":"15-day response window for information requests implies a staffed disclosure process.","sourceVerification":{"responseId":"curl-orrick-co-admt-20261009","openedUrl":"https://infobytes.orrick.com/2026-10-09/colorado-releases-revised-proposed-automated-decision-making-rules-ahead-of-hearing/","referenceExcerpt":"Human reviewers may be internal or external if they have actual authority to override the decision.","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}