Weather Information for Agriculture 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.

• Competitive dynamics

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal risk domain coverage, with only subdomain 6.4 (Competitive dynamics) receiving a coverage score of 2. The document primarily focuses on establishing drought monitoring infrastructure and AI/ML capabilities for weather forecasting, rather than addressing AI risks and harms. Most risk subdomains are not mentioned.

Sector coverage

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

• Agriculture, Mining, Construction & Manufacturing
• Public Administration (excl. National Security)

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

• Information
• Scientific Research & Development Services

All other sectors had no coverage in this document.

Sectors Summary

This Act primarily governs AI use in Agriculture through drought forecasting and soil moisture monitoring systems. It also governs Public Administration (excluding National Security) by establishing requirements for federal agencies (NOAA) to develop and deploy AI/ML technologies for weather and drought information systems.

Legislative Status

Hard Law

Legislative Status Summary

This is a binding federal statute enacted by the United States Congress with mandatory obligations, specific appropriations, and enforcement through federal administrative mechanisms.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress; Mr. Collins; Mr. Baird; Mr. Miller of Ohio; Committee on Science, Space, and Technology
• Summary: The document was introduced in the House of Representatives by specific congressional representatives and referred to the Committee on Science, Space, and Technology, indicating Congress as the proposing body.

Target

• Entity Types: AI_Governance_Actor
• Entities: National Oceanic and Atmospheric Administration (NOAA); Under Secretary; National Integrated Drought Information System; Climate Prediction Center of the National Weather Service; National Mesonet Program
• Summary: The Act applies to and regulates federal agencies, specifically NOAA and its subordinate entities, requiring them to develop AI/ML capabilities for drought forecasting and establish monitoring networks.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress; National Oceanic and Atmospheric Administration (NOAA); Under Secretary
• Summary: Congress enforces through the appropriations process and oversight, while NOAA and the Under Secretary have administrative authority to implement and ensure compliance with the Act's requirements.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: National Oceanic and Atmospheric Administration (NOAA); Under Secretary; National Integrated Drought Information System; National Coordinated Soil Moisture Monitoring Network
• Summary: NOAA and the Under Secretary are responsible for monitoring implementation through the National Integrated Drought Information System and the National Coordinated Soil Moisture Monitoring Network.

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 primarily covers the Plan and Design stage by establishing requirements for AI/ML drought forecasting systems, and the Deploy stage through establishing monitoring networks. It also addresses Operate and Monitor through ongoing drought information systems and data collection activities.

Technical Scope

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

• AI Models
• AI Systems
• Predictive AI
• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI and machine learning technologies for drought forecasting but does not reference specific AI model types, frontier AI, general purpose AI, foundation models, or compute thresholds. The focus is on predictive AI applications for weather and drought forecasting.