Overview
Title
To mandate the use of artificial intelligence by Federal agencies to adapt to extreme weather, and for other purposes.
ELI5 AI
This bill wants to use smart computer programs to help the government get ready for really bad weather, like storms and fires, by making better predictions and keeping things safe. It also wants to share these weather-predicting tools with others, unless it would make things unsafe to do so.
Summary AI
S. 3888, titled the “Transformational Artificial intelligence to Modernize the Economy against Extreme Weather Act” or the “TAME Extreme Weather Act,” proposes using artificial intelligence by federal agencies to adapt to extreme weather. The bill outlines the development of AI systems to improve weather forecasts, manage electrical grids, and support wildfire detection and emissions monitoring. It also encourages partnerships with private and academic entities for innovative weather forecasting, addresses national security considerations, and mandates public access to AI models and datasets unless restricted for security reasons. Furthermore, it authorizes necessary funds to implement these initiatives.
Published
Keywords AI
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Bill Statistics
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AnalysisAI
General Summary of the Bill
The proposed legislation, titled the "Transformational Artificial intelligence to Modernize the Economy against Extreme Weather Act" or the "TAME Extreme Weather Act," seeks to mandate the use of artificial intelligence (AI) by Federal agencies. The primary objective is to harness AI technologies to adapt to extreme weather and address related challenges. The bill emphasizes enhancing weather forecasting, improving electrical grid resilience, and strengthening analytic capabilities to allocate resources more efficiently in response to extreme weather events.
The bill comprises various titles that focus on specific agencies and sectors, such as the National Oceanic and Atmospheric Administration (NOAA), the Department of Agriculture, and the Department of Energy. Each section details initiatives for leveraging AI in these domains, such as improving weather models, monitoring emissions, optimizing energy grids, and tackling illegal deforestation and wood trade.
Summary of Significant Issues
Several issues arise from the bill's current drafting:
Budgetary Concerns: The bill lacks clear budget allocations in multiple sections, leading to potential overspending or inadequate funding. The absence of specific financial limits or guidelines could result in unchecked spending.
Definition of Artificial Intelligence: The bill defines AI but explicitly mentions certain technologies like machine learning and neural networks, which may inadvertently exclude other relevant technologies. This could limit innovation and adaptability in AI applications.
Transparency and Security: Provisions allowing the withholding of data on national security grounds are vague. The lack of specific criteria for such decisions could undermine transparency and public trust.
Accountability and Metrics: There is a lack of defined criteria for measuring the success of AI applications in areas like weather forecasting and emissions monitoring. This absence of metrics poses risks to the accountability and effectiveness of the initiatives.
Partnership and Implementation Ambiguities: Terms like "novel structures" and "co-investment strategies" are not clearly defined, which could result in ambiguity in forming partnerships and potentially favor specific entities.
Privacy and Ethical Considerations: The bill does not address privacy or data protection in the gathering and use of data, raising ethical concerns, especially when handling sensitive information.
Impact on the Public
The bill is likely to have a broad impact on the public by improving the accuracy and reliability of weather forecasts, which could enhance disaster preparedness and reduce harm from extreme weather events. By potentially stabilizing energy grids and increasing efficiency, the bill may lead to more reliable energy services for consumers.
There are also positive implications for environmental protection, as the use of AI in monitoring emissions and deforestation could help combat climate change. However, the lack of specific budgetary constraints and transparency measures might lead to inefficient use of public funds and reduce trust in government initiatives.
Impact on Specific Stakeholders
Federal Agencies: Agencies such as NOAA and the Department of Energy would be at the forefront of implementing the bill's provisions. They may benefit from advanced tools and resources but will also face the challenge of effectively integrating AI technologies.
Private Sector and Academic Institutions: The promotion of public-private partnerships and co-investment strategies could benefit stakeholders in these sectors by providing new opportunities for research and development. However, unclear partnership criteria could lead to favoritism or inconsistent collaboration.
Environmental Groups and Local Communities: These stakeholders could see positive impacts through improved environmental monitoring and data transparency. Efforts to combat illegal deforestation and trade in wood products align with environmental conservation goals, although the lack of privacy safeguards poses concerns about data use.
Energy Consumers: Consumers could benefit from increased energy grid stability and efficiency, resulting in more reliable electricity services. However, without specific guidelines on protecting sensitive data, consumers may have concerns about how their information is used.
In summary, while the TAME Extreme Weather Act has the potential to leverage AI for significant public benefit, its success will largely depend on addressing the highlighted issues, ensuring transparent, accountable, and ethical implementation of its provisions.
Issues
The bill lacks specific budgetary details in various sections including sections 3, 104, 105, 106, and 401. Without clear budget allocations or cost estimates, there is a risk of overspending or insufficient funding for implementing artificial intelligence solutions across multiple federal programs.
Section 2's definition of 'artificial intelligence' includes specific technologies such as 'machine learning, neural networks, and natural language processing' but may inadvertently exclude other relevant technologies or interpret technologies not mentioned as excluded, which can limit adaptability and innovation.
Section 109 and Section 302(e) grant broad authority to withhold data, model, or code from public disclosure if deemed necessary to protect national security. The lack of specific criteria or guidelines for these decisions could lead to misuse or inconsistent practices concerning transparency and public trust.
The bill, particularly in Sections 102, 103, and 106, does not establish clear criteria or metrics for assessing the success of artificial intelligence applications in weather forecasting or emissions monitoring, which can lead to ineffective application and lack of accountability.
Section 107 discusses 'novel structures' and 'novel co-investment strategies' for partnerships without clear definitions, which could lead to ambiguity in implementation and concerns about favoritism or lack of transparency in partnering with private and academic entities.
Many sections of the bill, including Sections 201 and 303, do not address privacy concerns or data protection measures related to the collection and use of data, which raises ethical issues, especially regarding sensitive or personal information.
The bill, specifically in Section 104, relies heavily on discretionary terms such as 'may' regarding public availability and best practices, leading to potential inconsistencies in implementation and a lack of commitment to transparency or standardization.
Section 3's description of public-private partnerships lacks specificity and leaves room for broad interpretations that may preferentially benefit particular organizations without clear oversight or accountability mechanisms.
Some definitions in Sections 2 and 101, such as 'curate' and 'observational data', are imprecise, which can lead to variability in implementation and interpretation, potentially affecting data quality and reliability.
The absence of oversight or accountability measures throughout various sections (e.g., Sections 3, 107) raises concerns about ensuring the ethical and effective usage of artificial intelligence in federal agencies.
Sections
Sections are presented as they are annotated in the original legislative text. Any missing headers, numbers, or non-consecutive order is due to the original text.
1. Short title; table of contents Read Opens in new tab
Summary AI
The bill titled “Transformational Artificial intelligence to Modernize the Economy against Extreme Weather Act” or “TAME Extreme Weather Act” outlines various sections and chapters aimed at using advanced technology to improve weather prediction and response. It mentions specific programs and collaborations related to the National Oceanic and Atmospheric Administration, Department of Agriculture, and Department of Energy, all focused on employing artificial intelligence and other innovations to address challenges like extreme weather, deforestation, and energy optimization.
2. Definitions Read Opens in new tab
Summary AI
The section provides definitions for key terms related to artificial intelligence in the Act. It explains that "artificial intelligence" refers to machine systems that can make decisions or predictions, including technologies like machine learning, neural networks, and natural language processing. Additionally, "curate" means to gather and update data while ensuring its quality, and "training dataset" refers to a set of data used to teach artificial intelligence. An "open license" is defined elsewhere in U.S. law.
3. Purpose Read Opens in new tab
Summary AI
The purpose of this Act is to require Federal agencies to use artificial intelligence to better forecast weather, make electrical grids more resilient, improve decision-making on resource deployment, and foster partnerships in technical fields to respond effectively to extreme weather conditions.
101. Definitions Read Opens in new tab
Summary AI
The section provides definitions for terms related to weather forecasting, including Administrator, artificial intelligence weather model, Earth system reanalysis dataset, Environmental Information Services Working Group, numerical weather model, observational data, reforecast analysis, and synthetic data. These definitions help clarify roles, models, and data types used in the context of weather predictions.
102. Earth system reanalysis Read Opens in new tab
Summary AI
The bill requires the development of a comprehensive Earth system reanalysis dataset to improve weather understanding and forecasting technologies, including artificial intelligence, with input from various federal agencies and experts. It mandates public access to this data and any developed AI models, while also ensuring continued support for research and minimizing environmental impacts.
103. Advanced artificial intelligence applications for weather Read Opens in new tab
Summary AI
The section describes how the Administrator is tasked with exploring the use of advanced artificial intelligence to enhance weather forecasts. This involves improving data assimilation, considering Earth system processes like cloud cover and photosynthesis, and using AI models to emulate and enhance the confidence and reliability of traditional weather models.
104. Technical assistance on use of artificial intelligence weather models Read Opens in new tab
Summary AI
The bill section requires the Administrator to inventory and assess artificial intelligence weather models, offer technical support, establish best practices, and support emergency decision-making. It also includes developing a framework for model assessment, possibly sharing datasets publicly, reporting on improving models, and potentially studying the effects of AI weather models in collaboration with the National Academy of Sciences.
105. Fire combustion modeling program Read Opens in new tab
Summary AI
The bill proposes a program that uses artificial intelligence to analyze data about the environment in order to detect wildfires early, warn communities and firefighters, and predict wildfire spreading. The program will collect and use data from the federal government, integrate weather information, ensure minimal environmental impact, and provide public access to the AI code and data for free under an open license.
106. Emissions monitoring and analysis program Read Opens in new tab
Summary AI
The section outlines a program to be developed by the Administrator, using artificial intelligence to analyze global atmospheric data. This program aims to improve models, detect leaks and emissions, identify greenhouse gas changes, and support law enforcement, while also providing public access to the AI code and training data.
107. Partnerships for transformational innovation Read Opens in new tab
Summary AI
The Administrator is encouraged to form innovative partnerships with private and academic groups to enhance weather forecasting through improved understanding, advancement in forecast science, and development of AI applications. Part of this initiative includes exploring co-investment with these sectors to support high-risk research, share intellectual property, and collaboratively share resources and outcomes.
108. Retention of Federal Government expertise Read Opens in new tab
Summary AI
The section instructs the Administrator to explore ways to hire and keep expert staff, ensuring they have competitive salaries similar to those offered outside of the Federal Government, while adhering to relevant laws.
109. National security Read Opens in new tab
Summary AI
The section allows the Administrator, in consultation with the Secretary of Defense, to withhold certain models, codes, or data developed or used under the title if doing so is necessary to protect national security. It also clarifies that nothing in the title overrides other laws related to protecting the United States' national security interests.
201. Deforestation and illegal wood products Read Opens in new tab
Summary AI
The section outlines the creation of a program by the Secretary of Agriculture to use artificial intelligence to monitor global deforestation and illegal wood trade. This program aims to collect data, predict illegal wood movements, and collaborate with foreign governments to enforce laws against illegal wood trading while ensuring the technology minimizes environmental impact.
301. Secretary defined Read Opens in new tab
Summary AI
In this section, the term "Secretary" is defined as referring to the Secretary of Energy.
302. Grid and transmission optimization Read Opens in new tab
Summary AI
The section establishes a program led by the Secretary, in collaboration with the Federal Energy Regulatory Commission, to use artificial intelligence for optimizing energy grids and transmissions by reducing energy loss and stabilizing power flows. The program, to be set up within a year of certain events, involves collecting data for AI training, with public access to the developed AI code and data unless withholding is necessary for national security.
303. Preparation of environmental review documents Read Opens in new tab
Summary AI
The section establishes a program to use artificial intelligence to help create environmental review documents required by NEPA, ensuring that it complies with environmental laws and including practices to reduce the environmental impact of AI. It mandates public access to AI tools and training data, involves the National Academies in evaluating the program's effectiveness and fairness, and ensures the initiative respects all environmental laws and permits.
401. Authorization of appropriations Read Opens in new tab
Summary AI
The section authorizes the allocation of funds as needed to implement the purposes of the Act.