TAME Extreme Weather Act

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Defunct
• Most recent activity date: 2025-01-03

Risk subdomain coverage

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

• AI system security vulnerabilities
• Governance failure
• Environmental harm
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

The document has minimal coverage of AI risk domains, with brief mentions of approximately 3-4 subdomains. Primary focus is on environmental impact (6.6), with implicit coverage of system robustness (7.3) through testing requirements, and minimal coverage of governance failure (6.5) through oversight mechanisms. The document is primarily focused on mandating AI use for weather forecasting rather than addressing AI risks.

Sector coverage

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

• Trade, Transportation & Utilities
• Information
• 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
• Professional & Technical Services
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This Act primarily governs AI use within federal government agencies (Public Administration) for environmental monitoring, weather forecasting, and resource management. It also has significant implications for the Information sector through AI model development, and the Trade, Transportation and Utilities sector through grid optimization requirements. Agriculture and forestry applications are addressed through deforestation monitoring.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by the United States Congress with mandatory obligations on federal agencies, using mandatory language throughout ('shall') and establishing legal requirements for AI implementation in weather forecasting and related applications.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress
• Summary: The document is an Act of Congress, as indicated by the legislative format, section structure, and references to Congressional committees. It was proposed and enacted by the legislative branch of the U.S. federal government.

Target

• Entity Types: AI_Governance_Actor, AI_Developer
• Entities: National Oceanic and Atmospheric Administration (NOAA); Department of Energy; Department of Agriculture; Animal and Plant Health Inspection Service; Federal Energy Regulatory Commission; National Aeronautics and Space Administration; National Science Foundation; National Center for Atmospheric Research; Environmental Protection Agency
• Summary: The Act mandates federal agencies to develop and deploy AI systems for weather forecasting, grid optimization, and environmental monitoring. These agencies are required to develop AI models, curate datasets, and implement AI applications. Private entities and academic institutions are also indirectly targeted through partnership provisions.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Administrator of the National Oceanic and Atmospheric Administration; Secretary of Energy; Secretary of Agriculture; Committee on Commerce, Science, and Transportation of the Senate; Committee on Science, Space, and Technology of the House of Representatives; Secretary of Defense
• Summary: The Act designates specific federal agency heads (Administrator of NOAA, Secretary of Energy, Secretary of Agriculture) as responsible for implementing and enforcing the requirements. Congressional committees provide oversight through reporting requirements. The Secretary of Defense has consultation authority on national security matters.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Committee on Commerce, Science, and Transportation of the Senate; Committee on Science, Space, and Technology of the House of Representatives; National Academy of Sciences; National Academies of Sciences, Engineering, and Medicine
• Summary: Congressional committees monitor implementation through mandatory annual reporting requirements. The National Academies are contracted to conduct independent assessments of AI programs, particularly for NEPA compliance and weather model impacts.

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
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document comprehensively covers multiple AI lifecycle stages with primary focus on Build and Use Model, Deploy, and Operate and Monitor stages. It mandates development of AI weather models, datasets, and applications, along with deployment requirements and ongoing monitoring frameworks. Plan and Design is covered through program establishment requirements, while Verify and Validate is addressed through testing and assessment provisions.

Technical Scope

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

• AI Models
• AI Systems
• Generative AI
• Open Weight / Open Source
• Predictive AI
• Task-specific AI

Technical Scope Summary

The document explicitly focuses on AI models and AI systems for weather forecasting and environmental applications. It does not use terminology like frontier AI, general purpose AI, or foundation models. The focus is on task-specific AI applications (weather forecasting, fire modeling, emissions monitoring, grid optimization). There are no compute thresholds mentioned, and the document mandates open-source release of AI code and datasets.