{"resourceId":"suny-systemwide-ai-policy-6904","versions":[{"version":"external-7acc9e618fd5440c779de7967b5eaff72b002ec9c38fd97e7965fbcb692e9f7f","resource":{"id":"suny-systemwide-ai-policy-6904","title":"SUNY policy sets a risk-based campus governance baseline and year-end policy deadline","organization":"State University of New York","sector":"Public higher education policy","geography":"New York, United States","publishedAt":"Effective April 30, 2026; webpage publication date not separately stated","publicationDate":null,"eventDate":"2026-04-30","sourceName":"SUNY Policy 6904","sourceLabel":"Current institutional policy; normative requirements","sourceUrl":"https://www.suny.edu/sunypp/documents.cfm?doc_id=933","evidenceClass":"standards-guidance","outcomeClass":"emerging","topics":["data-security","governance-procurement","accessibility-workforce","operating-model"],"finding":"SUNY now supplies a common AI definition and risk-proportionate governance expectations, providing essential context for the audit's earlier-period findings.","sledRelevance":"Interpretation: a public-university system offers a concrete example of common principles with local implementation. Listed applicability and community-college authority should be checked locally; this is not a national requirement.","evidence":"Policy 6904 lists April 30, 2026 as its effective date. It calls for campus policies or relevant updates by December 31, 2026, with a possible one-time extension of up to two months on approved request. It addresses accountability, procurement, training, privacy, fairness and periodic review; no implementation outcome study is supplied.","architectureImplications":"Interpretation: implement risk-tiered approval metadata in existing service-management workflows; use shared controls without forcing every low-risk tool into the same architecture.","governanceImplications":"Interpretation: make decision authority, review frequency and residual-risk acceptance explicit. Policy adoption alone does not resolve the historical audit findings.","securityPrivacyImplications":"Interpretation: require data-flow and privacy review proportional to the consequences of each application, including confidential administrative records.","caveats":"Normative policy is evidence of expectations, not compliance or effectiveness. Effective date is recorded as an event, not an inferred publication date. Scope and deadline interpretation require the institution's responsible policy office.","streamIds":["campus-operations"],"roles":{"sales":"Interpretation: discuss implementation readiness with system governance, campus leadership, procurement, HR and IT. Ask which existing policies need revision, who owns the decision, and how the institution will show that controls operate. Offer a bounded gap mapping and implementation workshop tied to the campus's actual responsibilities and timelines. The value hypothesis is a clearer, executable governance process with less duplication. The policy supports planning questions but does not demonstrate an unmet commercial opportunity, a universally applicable legal deadline or compliance achieved by buying software. Confirm applicability with the responsible campus office before scoping work.","engineering":"Interpretation: represent approved purpose, risk classification, data owners and required evidence in existing application and service records. Build a proportionate workflow that distinguishes ordinary assistance from consequential automated action, with explicit escalation paths and version-change triggers. Validate that reviewer permissions and audit history prevent unapproved promotion to production. Prerequisites are an agreed inventory scope and named decision authorities. Proposed proof should walk representative low- and higher-risk cases through approval, rejection and later change, verifying retained evidence at each step. The policy specifies governance expectations, not a certified technical architecture or a product-selection recommendation.","delivery":"Interpretation: the campus governance owner should coordinate policy revisions, operating procedures and training with departmental, procurement and privacy leads. Dependencies include shared-governance participation and a clear interpretation of the policy's institutional scope. Prepare accessible guidance and examples that staff can apply to routine administrative work. Review drafts with owners, then test actual decisions before declaring implementation complete. Proposed acceptance: each locally applicable requirement maps to an approved procedure and named owner, and representative cases demonstrate correct escalation and record retention. Risks include policy-only completion, unfunded review duties and assuming that systemwide wording automatically resolves local operational differences."},"retrievedAt":"2026-09-07T03:01:01Z","enrichedAt":"2026-09-07T03:08:55Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Interpretation: co-design training with staff, accessibility specialists and representative users; retain accountable human decisions and a route to challenge outputs.","procurementImplications":"Interpretation: translate principles into evidence requests, change notices, data-use boundaries and testable supplier commitments reviewed under applicable local authority.","operatingModelImplications":"Interpretation: central governance maintains shared criteria; campus owners implement procedures and retain evidence of operation.","updateExplanation":"New to the searched archive; included as evidence newly relevant to this first recorded campus-operations edition, not asserted to be newly published today.","sourceVerification":{"openedUrl":"https://www.suny.edu/sunypp/documents.cfm?doc_id=933","referenceExcerpt":"The ultimate accountability for work completed and actions made by, or in conjunction with, AI systems must rest with human beings.","promptVersion":"sled-research-v3.1","model":null,"basis":"agent-reported inspection"}}}]}