To mandate the use of artificial intelligence by Federal agencies to adapt to extreme weather, and for other purposes.
Analysis under review: This bill has generated analysis that may be too generic or incomplete. Clause-level evidence remains available below.
Summary
What This Bill Does
This bill requires federal agencies to develop artificial intelligence systems for predicting extreme weather, detecting wildfires early, monitoring greenhouse gas emissions, optimizing electrical grids, and speeding up environmental review processes. It mandates NOAA, the Department of Energy, and USDA to create AI-powered programs with public datasets and open-source code.
Who Benefits and How
Technology companies and AI developers benefit from access to free government datasets and open-source code for weather forecasting applications. Energy utilities and grid operators gain AI tools to optimize transmission and reduce outages. Emergency managers and firefighters receive better wildfire detection and weather forecasting support. Academic researchers gain access to Earth system reanalysis datasets and training data.
Who Bears the Burden and How
Federal agencies (NOAA, DOE, USDA) must allocate resources to develop new AI programs within 1-2 year deadlines. Taxpayers fund these new programs through appropriations. Foreign governments face potential pressure to share atmospheric and forestry data with US agencies.
Key Provisions
- NOAA must develop an Earth system reanalysis dataset and AI weather models within 2 years
- NOAA must create AI programs for wildfire combustion modeling and emissions monitoring within 1 year
- DOE must establish an AI program for grid and transmission optimization
- DOE must create AI tools to assist with NEPA environmental review documents
- USDA must develop AI to detect illegal wood products and deforestation
Evidence Chain:
This summary is generated from the full bill text using AI analysis. Expand "Detailed Analysis" below for identified beneficiaries/burden bearers.
At a Glance
What This Bill Does
Mandates federal agencies to develop and deploy artificial intelligence technologies for weather forecasting, wildfire detection, emissions monitoring, grid optimization, and environmental review document preparation to improve resilience against extreme weather
Key Policy Areas
Weather and Climate, Energy, Technology, Environment, Agriculture, National Security
Primary Purpose
Mandates federal agencies to develop and deploy artificial intelligence technologies for weather forecasting, wildfire detection, emissions monitoring, grid optimization, and environmental review document preparation to improve resilience against extreme weather
Policy Domains
Title I - Weather Forecasting
Identified Gains
Contextual inference, no direct clause citation- AI/Technology companies
- Weather forecasting services
- Emergency management agencies
- Energy utilities
- Academic researchers
Contextual inference, no direct clause citation
Identified Costs
Contextual inference, no direct clause citation- NOAA
- Federal budget/taxpayers
Contextual inference, no direct clause citation
Title II - Deforestation and Illegal Wood Products
Identified Gains
Contextual inference, no direct clause citation- Domestic timber industry
- Conservation groups
- Law enforcement agencies
Contextual inference, no direct clause citation
Identified Costs
Contextual inference, no direct clause citation- USDA/APHIS
- Illegal timber operators
Contextual inference, no direct clause citation
Title IV - Authorization of Appropriations
Identified Gains
Contextual inference, no direct clause citation- Federal agencies implementing the Act
Contextual inference, no direct clause citation
Identified Costs
Contextual inference, no direct clause citation- Federal budget/taxpayers
Contextual inference, no direct clause citation
Title III - Energy
Identified Gains
Contextual inference, no direct clause citation- Energy utilities
- Grid operators
- Renewable energy developers
- Project developers seeking permits
Contextual inference, no direct clause citation
Identified Costs
Contextual inference, no direct clause citation- Department of Energy
- Federal budget/taxpayers
Contextual inference, no direct clause citation
Sponsors
Legislative Progress
IntroducedMr. Schatz (for himself, Mr. Luján, Ms. Butler, and Mr. …
Stakeholder Effects
cui bono?How this legislation distributes effects. Mention counts reflect frequency, not effect magnitude.
Defense and intelligence agencies, Department of Energy, Environmental enforcement agencies
Positive-direction: Defense and intelligence agencies, Environmental enforcement agencies, Federal agencies implementing AI programs, Federal agencies implementing AI weather and energy programs (NOAA, DOE, USDA)
Negative-direction: Department of Energy, Federal agencies (NOAA, DOE, USDA), NOAA, NOAA weather forecast offices, USDA Animal and Plant Health Inspection Service
AI and weather technology companies, AI and weather technology startups, AI energy management software companies
Electric utilities and grid operators, Energy project developers seeking permits, Renewable energy generators
Academic research institutions, Academic weather researchers
Communities in wildfire-prone areas, Taxpayers
Positive-direction: Communities in wildfire-prone areas
Negative-direction: Taxpayers
Domestic legal timber industry, Illegal timber traffickers
Positive-direction: Domestic legal timber industry
Negative-direction: Illegal timber traffickers
Private weather forecasting services
Bill Structure & Actor Mappings
Who is "The Secretary" in each section?
- "the_administrator"
- → Administrator of NOAA (National Oceanic and Atmospheric Administration)
- "the_secretary"
- → Secretary of Agriculture
- "the_secretary"
- → Secretary of Energy
Note: The Secretary refers to Secretary of Agriculture in Title II but Secretary of Energy in Title III
Key Definitions
Terms defined in this bill
A machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments, including machine learning, neural networks, and natural language processing
To collect and maintain a dataset to ensure its quality, provide metadata on its provenance, and update the dataset periodically
Has the meaning given that term in section 3502(21) of title 44, United States Code
A dataset used to train an artificial intelligence
A weather model based primarily on artificial intelligence technology to project future Earth system conditions based on machine learning from an Earth system reanalysis dataset
A dataset that contains continuous global observational data and synthetic data for Earth system variables relevant to weather forecasting
We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.
Learn more about our methodology