California SCR 82 (Relative to Artificial Intelligence in Public Higher Education 2025)

• Authority: California
• Parent authority: State governments
• Jurisdiction: United States
• Collections: U.S. state and local documents
• Most recent activity: Proposed
• Most recent activity date: 2025-09-12

Risk subdomain coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Fraud, scams, and targeted manipulation

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal risk domain coverage, focusing primarily on academic integrity concerns related to AI misuse in student work (subdomain 4.3 - Fraud and manipulation). The document does not substantially address the technical risks, safety concerns, or broader societal impacts described in most risk taxonomy subdomains.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Educational Services

All other sectors had no coverage in this document.

Sectors Summary

This resolution exclusively governs the Educational Services sector, specifically focusing on California's three public higher education systems (University of California, California State University, and California Community Colleges). No other economic sectors are addressed.

Legislative Status

Soft Law

Legislative Status Summary

This is a non-binding concurrent resolution that encourages voluntary action by California higher education institutions without enforcement mechanisms, penalties, or mandatory obligations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: California State Legislature; Senate of the State of California; California Assembly
• Summary: The resolution is proposed and passed by the California Legislature, specifically the Senate with Assembly concurrence, as indicated in the resolved clause.

Target

• Entity Types: AI_Deployer, AI_User, Affected_Stakeholder
• Entities: University of California; California State University; California Community Colleges; President of the University of California; Chancellor of the California State University; Chancellor for the California Community Colleges; faculty; staff; administrators; students; academic senates
• Summary: The resolution targets California's three public higher education systems and their leadership, encouraging them to form a workgroup. Faculty, staff, administrators, and students are identified as participants who will use and be affected by AI in educational contexts.

Enforcer

• Summary: No enforcement mechanisms, authorities, or procedures are specified in this resolution. It is purely advisory and encouraging in nature with no binding obligations.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: The workgroup (to be created); California Legislature (implicit)
• Summary: The resolution encourages the workgroup to create and publish a report on strategies and best practices, suggesting a monitoring and reporting function, though this is voluntary and no formal monitoring body is established.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document focuses primarily on the Deploy and Operate and Monitor stages of AI systems already in use within higher education. It addresses how to implement AI appropriately in academic settings and how to monitor its use by students and faculty, rather than the development or technical aspects of AI systems.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Systems

Technical Scope Summary

The document uses general references to 'artificial intelligence' without defining or distinguishing between different types of AI systems, models, or technical specifications. No technical categories such as frontier AI, general-purpose AI, foundation models, or compute thresholds are mentioned.