S 2676 Cloud Labs to Advance Biotechnology Act of 2025

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Proposed
• Most recent activity date: 2025-08-01

Risk subdomain coverage

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

• AI system security vulnerabilities
• Cyberattacks, weapon development or use

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

• Unequal performance across groups
• Compromise of privacy
• Increased inequality and decline in employment
• AI possessing dangerous capabilities
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal to good coverage of approximately 4-5 subdomains, with primary focus on AI system security (2.2), malicious use prevention through biosecurity measures (4.2), and addressing unequal access to research resources (1.3, 6.2). Coverage is concentrated in security, research safety, and equitable access domains rather than traditional AI safety risks.

Sector coverage

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

• Scientific Research & Development Services
• Public Administration (excl. National Security)

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

• Agriculture, Mining, Construction & Manufacturing
• Information
• Educational Services
• Health Care & Social Assistance
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This legislation primarily governs Scientific Research and Development Services, with explicit coverage of biotechnology research across multiple application sectors including Health Care (health applications), Agriculture (agricultural biotechnology), and Manufacturing (chemical production). The document establishes governance for research infrastructure that spans multiple biotechnology sectors.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding Congressional bill that, if enacted, would create legally enforceable obligations for the Director of the National Science Foundation and other federal entities. The document uses mandatory language throughout ('shall') and establishes legal requirements for federal agencies.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The bill was introduced in the U.S. Senate by Mr. Young (for himself and Mr. Kim), as indicated in the document header.

Target

• Entity Types: AI_Governance_Actor, AI_Developer, Affected_Stakeholder
• Summary: The legislation creates obligations for the NSF Director to establish and manage the cloud laboratory network. It applies to cloud laboratories receiving grants and to researchers who will use these facilities. The document explicitly mentions that the network will coordinate activities of cloud laboratories 'independently operated by other entities (such as private industry, government laboratories, and academic institutions)'.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The Director of the NSF has primary responsibility for implementing and enforcing the program requirements, including establishing the network, awarding grants, and ensuring compliance with program requirements. The advisory board provides oversight and ensures safeguards are in place.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The advisory board has explicit duties to provide ongoing guidance and produce annual reports. Congress receives regular reports on program progress. The Director monitors implementation and submits reports to Congress.

AI Lifecycle Stages

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

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Operate and Monitor

AI Lifecycle Summary

The document primarily covers the Collect and Process Data stage, with significant emphasis on data generation for AI training. It also addresses Plan and Design (through implementation planning and advisory board guidance), Build and Use Model (by explicitly mentioning AI model training), and Operate and Monitor (through ongoing reporting and oversight requirements). The focus is on creating infrastructure for biological data generation to support AI development in biotechnology.

Technical Scope

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

• AI Models
• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI models in the context of training with biological data. It refers to 'artificial intelligence models' and 'biological data analysis models' but does not discuss frontier AI, general purpose AI, foundation models, or specific AI architecture types. There is no mention of compute thresholds or open-weight models. The focus is on using AI for biological data analysis rather than detailed AI system specifications.