To establish in the National Oceanic and Atmospheric Administration a program to improve precipitation forecasts, and for other purposes.

• 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.

• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal risk domain coverage, with only subdomain 7.3 (Lack of robustness) receiving a score of 2. The bill focuses on improving precipitation forecasting capabilities through AI/ML research and development, which implicitly addresses system reliability and performance issues. No other risk domains are substantively covered.

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.

• Information
• Educational Services

All other sectors had no coverage in this document.

Sectors Summary

This bill primarily governs the Public Administration sector by establishing requirements for NOAA, a federal agency. It also has implications for Scientific Research and Development Services through mandated research collaborations, and potentially affects Information sector activities related to data processing and high-performance computing for weather prediction.

Legislative Status

Hard Law

Legislative Status Summary

This is a Congressional bill that, if enacted, would create legally binding obligations for NOAA to establish and operate a precipitation forecasting program with specific authorized appropriations.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: Mr. Jackson of North Carolina; United States Congress; House Committee on Science, Space, and Technology
• Summary: The bill was introduced by Representative Jackson of North Carolina and referred to the House Committee on Science, Space, and Technology. Congress is the proposing authority for this federal legislation.

Target

• Entity Types: AI_Governance_Actor
• Entities: National Oceanic and Atmospheric Administration (NOAA); NOAA line offices; National Weather Service
• Summary: The bill establishes requirements and obligations for NOAA to create and operate a precipitation forecasting program. NOAA and its constituent offices are the primary targets who must implement the program.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Administrator of NOAA; United States Congress
• Summary: The NOAA Administrator is given direct authority to implement and update the program. Congress retains oversight through the authorization and appropriations process.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Administrator of NOAA; House Committee on Science, Space, and Technology
• Summary: The NOAA Administrator is required to conduct biennial reviews and updates of program goals, incorporating them into strategic implementation plans. Congressional oversight is implied through the committee referral and appropriations process.

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 covers multiple AI lifecycle stages with primary focus on Plan and Design, Build and Use Model, and Operate and Monitor stages. It addresses planning research priorities, developing AI/ML models for precipitation forecasting, and ongoing operational implementation and improvement of these systems.

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 machine learning and artificial intelligence as emerging technologies to be tested and evaluated for improving precipitation prediction. It focuses on AI/ML applications within Earth System Models but does not specify particular AI model types, compute thresholds, or distinguish between different AI categories.