It’s Summer, America’s Heating Up, and We’re Even More Unprepared

Summer officially kicked off this past weekend with the onset of a sweltering heat wave. As we hit publish on this piece, tens of millions of Americans across the central and eastern United States are experiencing sweltering temperatures that make it dangerous to work, play, or just hang out outdoors.

The good news is that even when the mercury climbs, heat illness, injury, and death are preventable. The bad news is that over the past five months, the Trump administration has dismantled essential preventative capabilities.

At the beginning of this year, more than 70 organizations rallied around a common-sense Heat Policy Agenda to tackle this growing whole-of-nation crisis. Since then, we’ve seen some encouraging progress. The new Congressional Extreme Heat Caucus presents an avenue for bipartisan progress on securing resources and legislative wins. Recommendations from the Heat Policy Agenda have already been echoed in multiple introduced bills. Four states, California, Arizona, New Jersey, and New York, now have whole-of-government heat action plans, and there are several States with plans in development. More locally, mayors are banding together to identify heat preparedness, management, and resilience solutions. FAS highlighted examples of how leaders and communities across the country are beating the heat in a Congressional briefing just last week.

But these steps in the right direction are being forestalled by the Trump Administration’s leap backwards on heat. The Heat Policy Agenda emphasized the importance of a clear, sustained federal governance structure for heat, named authorities and dedicated resourcing for federal agencies responsible for extreme heat management, and funding and technical assistance to subnational governments to build their heat readiness. The Trump Administration has not only failed to advance these goals – it has taken actions that clearly work against them.

The result? It’s summer, America’s heating up, and we’re deeply unprepared.

The heat wave making headlines today is just the latest example of how extreme heat is a growing problem for all 50 states. In just the past month, the Pacific Northwest smashed early-summer temperature records, there were days when parts of Texas were the hottest places on Earth, and Alaska – yes, Alaska – issued its first-ever heat advisory. Extreme heat is deadlier than hurricanes, floods, and tornadoes combined, and is exacerbating a mental-health crisis as well. By FAS’ estimates, extreme heat costs the nation more than $162 billion annually, costs that have made extreme heat a growing concern to private markets.

To build a common understanding of the state of federal heat infrastructure, we analyzed the status of heat-critical programs and agencies through public media, government reports, and conversations with stakeholders. All known impacts are confirmed via publicly available sources. We highlight five areas where federal capacity has been impacted:

This work provides answers to many of the questions our team has been asked over the last few months about what heat work continues at the federal level. With this grounding, we close with some options and opportunities for subnational governments to consider heading into Summer 2025.

What is the Current State of Federal Capacity on Extreme Heat?

Loss of leadership and governance infrastructure

At the time of publication, all but one of the co-chairs for the National Integrated Heat Health Information System’s (NIHHIS) Interagency Working Group (IWG) have either taken an early retirement offer or have been impacted by reductions in force. The co-chairs represented NIHHIS, the National Weather Service (NWS), Health and Human Services (HHS), and the Federal Emergency Management Agency (FEMA). The National Heat Strategy, a whole-of-government vision for heat governance crafted by 28 agencies through the NIHHIS IWG, was also taken offline. A set of agency-by-agency tasks for Strategy implementation (to build short-term readiness for upcoming heat seasons, as well as to strengthen long-term preparedness) was in development as of early 2025, but this work has stalled. There was also a goal to formalize NIHHIS via legislation, given that its existence is not mandated by law – relevant legislation has been introduced but its path forward is unclear. Staff remain at NIHHIS and are continuing the work to manage the heat.gov website, craft heat resources and information, and disseminate public communications like Heat Beat Newsletter and Heat Safety Week. Their positions could be eliminated if proposed budget cuts to the National Oceanic and Atmospheric Administration (NOAA) are approved by Congress.

Staffing reductions and actualized or proposed changes to FEMA and HHS, the federal disaster management agencies implicated in addressing extreme heat, are likely to be consequential in relation to extreme heat this summer. Internal reports have found that FEMA is not ready for responding to even well-recognized disasters like hurricanes, increasing the risk for a mismanaged response to an unprecedented heat disaster. The loss of key leaders at FEMA has also put a pause to efforts to integrate extreme heat within agency functions, such as efforts to make extreme heat an eligible disaster. FEMA is also proposing changes that will make it more difficult to receive federal disaster assistance. The Administration for Strategic Preparedness and Response (ASPR), HHS’ response arm, has been folded into the Centers for Disease Control and Prevention (CDC), which has been refocused to focus solely on infectious diseases. There is still little public information for what this merger means for HHS’ implementation of the Public Health Service Act, which requires an all-hazards approach to public health emergency management. Prior to January 2025, HHS was determining how it could use the Public Health Emergency authority to respond to extreme heat.

Loss of key personnel and their expertise

Many key agencies involved in NIHHIS, and extreme heat management more broadly, have been impacted by reductions in force and early retirements, including NOAA, FEMA, HHS, the Department of Housing and Urban Development (HUD), the Environmental Protection Agency (EPA), the U.S. Forest Service (USFS), and the Department of Energy (DOE). Some key agencies, like FEMA, have lost or will lose almost 2,000 staff. As more statutory responsibilities are put on fewer workers, efforts to advance “beyond scope” activities, like taking action on extreme heat, will likely be on the back burner.

Downsizing at HHS has been acutely devastating to extreme heat work. In January, the Office of Climate Change and Health Equity (OCCHE) was eliminated, putting a pause on HHS-wide coordination on extreme heat and the new Extreme Heat Working Group. In April, the entire staff of the Climate and Health program at CDC, the Low Income Home Energy Assistance Program (LIHEAP), and all of the staff at the National Institute for Occupational Safety and Health (NIOSH) working on extreme heat, received reduction in force notices. While it appears that staff are returning to the CDC’s National Center for Environmental Health, they have lost months of time that could have been spent on preparedness, tool development, and technical assistance to local and state public health departments. Sustained funding for extreme heat programs at HHS is under threat, the FY2026 budget for HHS formally eliminates the CDC’s Climate and Health Program, all NIOSH efforts on extreme heat, and LIHEAP.

Risks to data, forecasts, and information availability, though some key tools remain online

Staff reductions at NWS have compromised local forecasts and warnings, and some offices can no longer staff around-the-clock surveillance. Staff reductions have also compromised weather balloon launches, which collect key temperature data for making heat forecasts. Remaining staff at the NWS are handling an increased workload at one of the busiest times of the year for weather forecasting. Reductions in force, while now reversed, have impacted real-time heat-health surveillance at the CDC, where daily heat-related illness counts have been on pause since May 21, 2025 and the site is not currently being maintained as of the date of this publication.

Some tools remain online and available to use this summer, including NWS/CDC’s HeatRisk (a 7-day forecast of health-informed heat risks) and the National Highway Traffic Safety Administration’s Heat-Related EMS Activation Surveillance Dashboard (which shows the number of heat-related EMS activations, time to patient, percent transported to medical facilities, and deaths). Most of the staff that built HeatRisk have been impacted by reductions in force. The return of staff to the CDC’s Climate and Health program is a bright spot, and could bode well for the tool’s ongoing operations and maintenance for Summer 2025.

Proposed cuts in the FY26 budget will continue to compromise heat forecasting and data. The budget proposes cutting budgets for upkeep of NOAA satellites crucial to tracking extreme weather events like extreme heat; cutting budgets for the National Aeronautics and Space Administration’s LandSat program, which is used widely by researchers and private sector companies to analyze surface temperatures and understand heat’s risks; and fully defunding the National Environmental Public Health Tracking Network, which funds local and state public health departments to collect heat-health illness and death data and federal staff to analyze it.

Rollbacks in key funding sources and programs for preparedness, risk mitigation and resilience

As of May 2025, both NIHHIS Centers of Excellence – the Center for Heat Resilient Communities and the Center for Collaborative Heat Monitoring – received stop work orders and total pauses in federal funding. These Centers were set to work with 26 communities across the country to either collect vital data on local heat patterns and potential risks or shape local governance to comprehensively address the threat of extreme heat. These communities represented a cross-cut of the United States, from urban to coastal to rural to agricultural to tribal. Both Center’s leadership plans to continue the work with the selected communities in a reduced capacity, and continue to work towards aspirational goals like a universal heat action plan. Future research, coordination, and technical assistance at NOAA on extreme heat is under fire with the proposed total elimination of NOAA Research in the FY26 budget.

At FEMA, a key source of funding for local heat resilience projects, the Building Resilience Infrastructure and Communities (BRIC) program, has been cancelled. BRIC was the only FEMA Resilience grant that explicitly called out extreme heat in its Notice of Funding Opportunity, and funded $13 million in projects to mitigate the impacts of extreme heat. Many states have also faced difficulties in getting paid by FEMA for grants that support their emergency management divisions, and the FY26 budget proposes cuts to these grant programs. The cancellation of Americorps further reduces capacity for disaster response. FEMA is also dropping its support for improving building codes that mitigate disaster risk as well as removing requirements for subnational governments to plan for climate change. 

At HHS, a lack of staff at CDC has stalled payments from key programs to prepare communities for extreme heat, the Building Resilience Against Climate Effects (BRACE) grant program and the Public Health Preparedness and Response program. BRACE is critical federal funding for state and local climate and health offices. In states like North Carolina, the BRACE program funds live-saving efforts like heat-health alerts. Both of these programs are proposed to be totally eliminated in the FY26 budget. The Hospital Preparedness Program (HPP) is also slated for elimination, despite being the sole source of federal funding for health care system readiness. HPP funds coalitions of health systems and public health departments, which have quickly responded to heat disasters like the 2021 Pacific Northwest Heat Domes and established comprehensive plans for future emergencies. The National Institutes of Health’s Climate and Health Initiative was eliminated and multiple grants paused in March 2025. Research on extreme weather and health may proceed, according to new agency guidelines, yet overall cuts to the NIH will impact capacity to fund new studies and new research avenues. The National Institute of Environmental Health Sciences, which funds research on environmental health, faces a 36% reduction in its budget, from $994 million to $646 million.

Access to cool spaces is key to preventing heat-illness and death. Yet cuts, regulatory rollbacks, and program eliminations across the federal government are preventing progress towards ensuring every American can afford their energy bills. At DOE, rollbacks in energy efficiency standards for cooling equipment and the ending of the EnergyStar program will impact the costs of cooling for consumers. Thankfully, DOE’s Home Energy Rebates survived the initial funding freezes and the funding has been deployed to states to support home upgrades like heat pumps, insulation, air sealing, and mechanical ventilation. At HUD, the Green and Resilient Retrofits Program has been paused as of March 2025, which was set to fund important upgrades to affordable housing units that would have decreased the costs of cooling for vulnerable residents. At EPA, widespread pauses and cancellations in Inflation Reduction Act programs have put projects to provide more affordable cooling solutions on pause. At the U.S. Department of Agriculture, all grantees for the Rural Energy for America Program, which funds projects that provide reliable and affordable energy in rural communities, have been asked to resubmit their grants to receive allocated funding. These delays put rural community members at risk of extreme heat this summer, where they face particular risks due to their unique health and sociodemographic vulnerabilities. Finally, while the remaining $400 million in LIHEAP funding was released for this year, it faces elimination in FY26 appropriations. If this money is lost, people will very likely die and utilities will not be able to cover the costs of unpaid bills and delay improvements to the grid infrastructure to increase reliability.

Uncertain progress towards heat policy goals

Momentum towards establishing a federal heat stress rule as quickly as possible has stalled. The regulatory process for the Heat Injury and Illness Prevention in Outdoor and Indoor Work Settings is proceeding, with hearings that began June 16 and are scheduled to continue until July 3. It remains to be seen how the Occupational Safety and Health Administration (OSHA) will proceed with the existing rule as written. OSHA’s National Emphasis Program (NEP) for Heat will continue until April 6, 2026. This program focuses on identifying and addressing heat-related injuries and illnesses in workplaces, and educating employers on how they can reduce these impacts on the job. To date, NEP has conducted nearly 7,000 inspections connected to heat risks, which lead to 60 heat citations and nearly 1,400 “hazard alert” letters being sent to employers.

How Can Subnational Governments Ready for this Upcoming Heat Season?

Downscaled federal capacity comes at a time when many states are facing budget shortfalls compounded by federal funding cuts and rescissions. The American Rescue Plan Act, the COVID-19 stimulus package, has been a crucial source of revenue for many local and state governments that enabled expansion in services, like extreme heat response. That funding must be spent by December 2026, and many subnational governments are facing funding cliffs of millions of dollars that could result in the elimination of these programs. While there is a growing attention to heat, it is still often deprioritized in favor of work on hazards that damage property.

Even in this environment, local and state governments can still make progress on addressing extreme heat’s impacts and saving lives. Subnational governments can:

FAS stands ready to support leaders and communities in implementing smart, evidence-based strategies to build heat readiness – and to help interested parties understand more about the impacts of the Trump administration’s actions on federal heat capabilities. Contact Grace Wickerson (gwickerson@fas.org) with inquiries.

Impacts of Extreme Heat on Rural Communities

46 million rural Americans face mounting risks from temperature extremes that threaten workforce productivity, raise business operational costs, and strain critical public services. Though extreme heat is often portrayed in research and the media as an urban issue, almost every state in the contiguous U.S. has rural communities with above-average rates of vulnerability to extreme heat. To protect rural America, Congress must address extreme heat’s impacts by repairing rural health systems, strengthening the preparedness of rural businesses, and hardening rural energy infrastructure.

Extreme heat exacerbates rural communities’ unique health vulnerabilities

On average, Americans living in rural areas are twice as likely as those in urban areas to have pre-existing health conditions, like heart disease, diabetes, and asthma, that make them more sensitive to heat-related illness and death. Further compounding the risk, rural places also have larger populations of underinsured and uninsured people than urban areas, with 1 in 6 people lacking insurance. 

Limited healthcare infrastructure in rural places worsens these vulnerabilities. Rural areas have higher shortages of healthcare professionals who provide primary care, mental health, and dental services than urban areas. Over the last decade, 100 rural hospitals have closed, and hundreds more are vulnerable to closure. Finally, many rural communities do not have public health departments, and those that do are underfunded and understaffed. Because public health systems and healthcare professionals are the first responders to extreme heat, rural residents are severely underprepared. 

Congress should provide flexible resources and technical assistance to rural hospitals to prepare for emerging threats like extreme heat. Additionally, Congress should continue to enable the U.S. Department of Agriculture and the Department of Health and Human Services to provide loans or grant assistance to help rural residents retain access to health services and improve the financial position of rural hospitals and clinics. And because Medicaid expansion correlates with better rural hospital financial performance and fewer closures, Congress should invest in Medicaid to protect rural healthcare access.

Extreme heat puts rural businesses and workers at risk

Rural economic health relies on the outdoors (e.g., recreation tourism) and outdoor labor (e.g., agriculture and oil and gas extraction). Extreme heat in many of these places makes it dangerous to be outside, which impacts worker productivity and local business revenues. Indoor workers in facilities like manufacturing plants, food processing, and warehouses also face heat-related safety threats due to the presence of heat-producing machines and poorly ventilated buildings with limited cooling. These facilities are rapidly growing components of rural economies, as these sectors employ almost 1 in 5 rural workers. 

Simple protections like water, rest, shade, and cooling can improve productivity and generate returns on investments. But small-to-medium rural enterprises need support to adopt affordable cooling systems, shade and passive cooling infrastructure, and worker safety measures that reduce heat-related disruptions. Congress should help rural businesses reduce heat’s risks by appropriating funding to support workplace heat risk reduction and practical training on worker protections. Additionally, Congress should require OSHA to finalize a federal workplace heat standard.

Extreme heat threatens rural energy security

When a power outage happens during a severe extreme heat event, the chance of heat-related illness and death increases exponentially. Extreme heat strains power infrastructure, increasing the risk of power outages. This risk is particularly acute for rural communities, which have limited resources, older infrastructure, and significantly longer waits to restore power after an outage.

Weatherized housing and indoor infrastructure are one of the key protective factors against extreme heat, especially during outages. Yet rural areas often have a higher proportion of older, substandard homes. Manufactured and mobile homes, for example, compose 15% of the rural housing stock and are the one of the most at-risk housing types for extreme heat exposure. When the power is on, rural residents spend 40% more of their income on their energy bills than their urban counterparts. Rural residents in manufactured housing spend an alarming 75% more. Energy debt can force people to choose between paying for life-saving energy or food and key medications, compounding poverty and health outcomes. 

To drive the energy independence and economic resilience of rural America, Congress should support investments in energy-efficient and resilient cooling technologies, weatherized homes, localized energy solutions like microgrids, and grid-enhancing technologies.

Economic Impacts of Extreme Heat: Energy

As temperatures rise, the strain on energy infrastructure escalates, creating vulnerabilities for the efficiency of energy generation, grid transmission, and home cooling, which have significant impacts on businesses, households, and critical services. Without action, energy systems will face growing instability, infrastructure failures will persist, and utility burdens will increase. The combined effects of extreme heat cost our nation over $162 billion in 2024 – equivalent to nearly 1% of the U.S. GDP. 

The federal government needs to prepare energy systems and the built environment through strategic investments in energy infrastructure — across energy generation, transmission, and use. Doing so includes ensuring electric grids are prepared for extreme heat by establishing an interagency HeatSmart Grids Initiative to assess the risk of energy system failures during extreme heat and the necessary emergency responses. Congress should retain and expand home energy rebates, tax credits, and the Weatherization Assistance Program (WAP) to enable deep retrofits that prepare homes against power outages and cut cooling costs, along with extending the National Initiative to Advance Building Codes (NIABC) to accelerate state and local adoption of code language for extreme heat adaptation.  

Challenge & Opportunity: Grid Security

Extreme Heat Reduces Energy Generation and Transmission Efficiency

During a heatwave, the energy grid faces not only surges in demand but also decreased energy production and reduced transmission efficiency. For instance, turbines can become up to 25% less efficient in high temperatures. Other energy sources are also impacted: solar power, for example, produces less electricity as temperatures rise because high heat slows the flow of electrical current. Additionally, transmission lines lose up to 5.8% of their capacity to carry electricity as temperatures increase, resulting in reliability issues such as rolling blackouts. These combined effects slow down the entire energy cycle, making it harder for the grid to meet growing demand and causing power disruptions.

Rising Demand and Grid Load Increase the Threat of Power Outages

Electric grids are under unprecedented strain as record-high temperatures drive up air conditioning use, increasing energy demand in the summer. Power generation and transmission are impeded when demand outpaces supply, causing communities and businesses to experience blackouts. According to data from the North American Electric Reliability Corporation (NERC), between 2024 and 2028, an alarming 300 million people across the United States could face power outages. Texas, California, the Southwest, New England, and much of the Midwest are among the states and regions most at risk of energy emergencies during extreme conditions, according to 2024 NERC data. 

Data center build-out, driven by growing demand for artificial intelligence, cloud services, and big data analytics, further adds stress to the grid. Data centers are estimated to consume 9% of US annual electricity generation by 2030. With up to 40% of data centers’ total yearly energy consumption driven by cooling systems, peak demand during the hottest days of the year puts demand on the U.S. electric grid and increases power outage risk. 

Power outages bear significant economic costs and put human lives at severe risk. To put this into perspective, a concurrent heat wave and blackout event in Phoenix, Arizona, could put 1 million residents at high risk of heat-related illness, with more than 50% of the city’s population requiring medical care. As we saw with 2024’s Hurricane Beryl, more than 2 million Texans lost power during a heatwave, resulting in up to $1.3 billion in damages to the electric infrastructure in the Houston area and significant public health and business impacts.  The nation must make strategic investments to ensure energy reliability and foster the resilience of electric grids to weather hazards like extreme heat. 

Advancing Solutions for Energy Systems and Grid Security

Investments in resilience pay dividends, with every federal dollar spent on resilience returning $6 in societal benefits. For example, the DOE Grid Resilience State and Tribal Formula Grants, established by the Bipartisan Infrastructure Law (BIL), have strengthened grid infrastructure, developed innovative technologies, and improved community resilience against extreme weather. It is essential that funds for this program, as well as other BIL and Inflation Reduction Act initiatives, continue to be disbursed.  

To build heat resilience in communities across this nation, Congress must establish the HeatSmart Grids Initiative as a partnership between DOE, FEMA, HHS, the Federal Energy Regulatory Commission (FERC), NERC, and the Cybersecurity and Infrastructure Security Agency (CISA). This program should (i) perform national audits of energy security and building-stock preparedness for outages, (ii) map energy resilience assets such as long-term energy storage and microgrids, (iii) leverage technologies for minimizing grid loads such as smart grids and virtual power plants, and (iv) coordinate protocols with FEMA’s Community Lifelines and CISA’s Critical Infrastructure for emergency response. This initiative will ensure electric grids are prepared for extreme heat, including the risk of energy system failures during extreme heat and the necessary emergency and public health responses.  

Challenge & Opportunity: Increasing Household and Business Energy Costs

As temperatures rise, so do household and business energy bills to cover cooling costs. This escalation can be particularly challenging for low-income individuals, schools, and small businesses operating on thin margins. For businesses, especially small enterprises, power outages, equipment failures, and interruptions in the supply chain become more frequent and severe due to extreme weather, negatively affecting production and distribution. One in six U.S. households (21.2 million people) find themselves behind on their energy bills, which increases the risk of utility shut-offs. One in five households report reducing or forgoing food and medicine to pay their energy bills. Families, school districts, and business owners need active and passive cooling approaches to meet demands without increasing costs.

Advancing Solutions for Businesses, Households, and Vital Facilities

Affordably cooled homes, businesses, and schools are crucial to sustaining our economy. To prepare the nation’s housing and infrastructure for rising temperatures, the federal government should:

The Federation of American Scientists: Who We Are

At the Federation of American Scientists (FAS), we envision a world where the federal government deploys cutting-edge science, technology, ideas, and talent to solve and address the impacts of extreme heat. We bring expertise in embedding science, data, and technology into government decision-making and a strong network of subject matter experts in extreme heat, both inside and outside of government. Through our 2025 Heat Policy Agenda and broader policy library, FAS is positioned to help ensure that public policy meets the challenges of living with extreme heat.

Consider FAS a resource for… 

We are tackling this crisis with initiative, creativity, experimentation, and innovation, serving as a resource on environmental health policy issues. Feel free to always reach out to us:

Senior Manager, Climate and Health
Grace Wickerson
Medical Innovation,
Emerging Technologies
read more
Senior Associate, Climate, Health, and Environment
Autumn Burton
Environmental Health,
Resilient Communities,
Extreme Weather,
Inclusive Innovation & Technology
read more
Associate Director, Climate and Environment
Hannah Safford
read more

Securing American AI Leadership: A Strategic Action Plan for Innovation, Adoption, and Trust

The Federation of American Scientists (FAS) submitted the following response to the Request for Information (RFI) issued by the Office of Science and Technology Policy (OSTP) in February 2025 regarding the development of an Artificial Intelligence (AI) Action Plan.

At a time when AI is poised to transform every sector of the economy, the Trump administration has a critical opportunity to solidify America’s leadership in this pivotal technology. Building on the foundations laid during the first Trump administration, bold and targeted policies can unleash innovation, unlocking AI’s vast potential to stimulate economic growth, revolutionize industries, and strengthen national security. However, innovation alone is insufficient; without public trust, AI adoption will stall. Ensuring AI systems are transparent, reliable, and aligned with American values will accelerate responsible adoption and solidify AI as a cornerstone of America’s economic and technological leadership.

To sustain America’s leadership in AI innovation, accelerate adoption across the economy, and guarantee that AI systems remain secure and trustworthy, we offer a set of actionable policy recommendations. Developed by FAS in partnership with prominent AI experts, industry leaders, and research institutions—including contributors to the recent FAS Day One 2025 Project and the 2024 AI Legislative Sprint—these proposals are structured around four strategic pillars: 1) unleashing AI innovation, 2) accelerating AI adoption, 3) ensuring secure and trustworthy AI, and 4) strengthening existing world-class U.S. government institutions and programs. 

1) Unleashing AI Innovation. American AI leadership has been driven by bold private-sector investments and world-class academic research. However, critical high-impact areas remain underfunded. The federal government can catalyze investment and innovation by expanding access to essential data, investing strategically in overlooked areas of AI R&D, defining priority research challenges, promoting public-private partnerships, and attracting and retaining global talent.

2) Accelerating AI Adoption Across the Economy. The United States leads in AI breakthroughs, but these breakthroughs must translate into widespread adoption to maximize their economic and societal benefits. Accelerating adoption—a critical yet often overlooked driver of national competitiveness—requires addressing workforce readiness, expanding government capacity, and managing rising energy demands.

3) Ensuring Secure and Trustworthy AI. Ensuring AI systems are secure and trustworthy is essential not only for fostering public confidence and accelerating widespread adoption, but also for improving government efficiency and ensuring the responsible use of taxpayer resources when AI is deployed by public agencies. While the previous Trump administration recognized the necessity of public trust when promoting AI adoption, concerns persist about AI’s rapid evolution, unpredictable capabilities, and potential for misuse. Future AI accidents could further erode this trust, stalling AI progress. To address these risks and fully harness AI’s potential, the U.S. government must proactively monitor emerging threats, rigorously evaluate AI technologies, and encourage innovation that upholds fundamental American values such as privacy. 

4) Strengthening Existing World-Class U.S. Government AI Institutions and Programs. Realizing the Trump Administration’s goals will require building on leading government AI capabilities. Key initiatives—including the NIST AI Safety Institute (AISI), the National AI Research Resource (NAIRR) Pilot, the AI Use Case Inventory, and the Department of Energy’s Office of Critical and Emerging Technologies (CET)—advance AI innovation, security, and transparency. The AISI evaluates AI models with broad industry support, while the NAIRR Pilot expands access to AI resources beyond Big Tech. Federal AI use case inventories enhance government transparency and industry engagement, building public trust. DOE’s CET drives AI-powered advancements in science and national security. Integrating these proven initiatives into the AI Action Plan will solidify America’s AI leadership.

By acting decisively, the administration can ensure American AI remains the gold standard, drive economic competitiveness, and accelerate science and innovation.

Overview of Policy Proposals

Policy Proposals to Unleash AI Innovation

Policy Proposals to Accelerate AI Adoption Across the Economy

Policy Proposals to Ensure Secure and Trustworthy AI

Policy Proposals to Strengthen Existing World-Class U.S. Government AI Institutions and Programs that are Key to the Trump Administration’s AI Agenda

Policy Proposals to Unleash AI Innovation

As artificial intelligence continues transforming industries and reshaping global competition, the United States must take bold, coordinated action to maintain its technological leadership. A multi-agency approach could include launching a National Initiative for AI Explainability, accelerating materials science discovery through AI-powered autonomous laboratories, creating AI-ready datasets for the life sciences, establishing a NIST Foundation to enhance public-private collaboration in AI research, and creating a National Security AI Entrepreneur Visa to attract and retain top global talent. Together, these initiatives would strengthen America’s AI ecosystem by addressing critical challenges in transparency, scientific research, standards development, and talent acquisition—while ensuring the U.S. remains at the forefront of responsible AI innovation.

Recommendation 1. Promote Innovation in Trustworthy AI through a Public-Private National Initiative for AI Explainability 

Understanding the inner workings of AI systems is critical not only for reliability and risk mitigation in high-stakes areas such as defense, healthcare, and finance, but also for bolstering American technological leadership and maximizing government accountability and efficiency. However, despite promising progress in fields such as “mechanistic interpretability”, the study of explainability in AI systems is still nascent. A lack of explainability risks undermining trust and inhibiting AI adoption, particularly in safety-critical sectors.

To address the challenge of understanding and improving AI systems, we propose the launch of a Public-Private National Initiative for AI Explainability. Following in the footsteps of government-coordinated research projects like the Human Genome Project, this initiative would unite researchers, industry leaders, standards bodies, and government agencies to map the inner workings of advanced AI systems in a public-private partnership. 

Federal precedent for such work already exists: DARPA’s 2017-2021 Explainable AI (XAI) program sought to create machine learning systems capable of explaining their decisions in a way humans could understand. While the program advanced techniques for explainable models and human-friendly translations of complex AI reasoning, the rapid development and scaling of AI technologies in the past five years demand a renewed, more ambitious effort.

The objectives of the initiative would include:

Implementation Strategy:

To launch this effort, the President should issue an executive order to signal national commitment and assign leadership to key federal agencies, including:

The White House should leverage its convening power to unite leading AI companies, top academic institutions, and government agencies in formal collaborations. These partnerships could encompass co-funded research, shared datasets and computing resources, collaborative access to advanced AI models, and joint development of open-source tools. Establishing a structured public-private partnership will facilitate coordinated funding, align strategic priorities, and streamline resource sharing, ensuring that advancements in AI explainability directly support both national interests and economic competitiveness. To sustain this initiative, the administration should also secure consistent, multi-year federal funding through appropriations requests to Congress. 

DARPA’s XAI program showed that AI explainability requires interdisciplinary collaboration to align technical development with human understanding. Building on these insights, this initiative should include experts from computer science, cognitive science, ethics, law, and domain-specific fields to ensure explanations are clear, useful, and actionable for decision-makers across critical sectors. 

By implementing this National Initiative for AI Explainability, the Trump administration can significantly enhance public confidence in AI technologies, accelerate responsible adoption by both the public and private sectors, and solidify America’s global leadership in AI innovation. Critically, a modest investment of government resources in this initiative could unlock substantial private-sector investment, spurring innovation and driving economic growth. This strategic approach will also enhance government accountability, optimize the responsible use of taxpayer resources, and ensure that American industry continues to lead in AI development and deployment.

Recommendation 2. Direct the Department of Energy (DOE) to use AI to Accelerate the Discovery of New Materials (link to full memo >>>)

Innovations in AI and robotics could revolutionize materials science by automating experimental processes and dramatically accelerating the discovery of new materials. Currently, materials science research involves manually testing different combinations of elements to identify promising materials, which limits the pace of discovery. Using AI foundation models for physics and chemistry, scientists could simulate new materials, while robotic “self-driving labs” could run 24/7 to synthesize and evaluate them autonomously. This approach would enable continuous data generation, refining AI models in a feedback loop that speeds up research and lowers costs. Given its expertise in supercomputing, AI, and a vast network of national labs, the Department of Energy (DOE) could lead this transformative initiative, potentially unlocking advancements in critical materials, such as improved battery components, that could have immense economic and technological impacts.

Recommendation 3. Create AI-ready Collaborative Datasets to Accelerate Progress in the Life Sciences (link to full memo >>>)

Large, high-quality datasets could revolutionize life science research by powering AI models that unlock new discoveries in areas like drug development and diagnostics. Currently, researchers often work in silos with limited incentives to collaborate and share meticulously curated data, slowing progress. By launching a government-funded, end-to-end initiative—from identifying critical dataset needs to certifying automated collection methods and hosting robust open repositories—scientists could continuously generate and refine data, fueling AI models in a feedback loop that boosts accuracy and lowers costs. Even a relatively modest government investment could produce vital resources for researchers and startups to spark new industries. This model could also be extended to a range of other scientific fields to accelerate U.S.science and innovation.

Recommendation 4. Create a NIST Foundation to Support the Agency’s AI Mandate (link to full memo >>>)

To maintain America’s competitive edge in AI, NIST needs greater funding, specialized talent, and the flexibility to work effectively with private-sector partners. One solution is creating a “NIST Foundation,” modeled on the DOE’s Foundation for Energy Security and Innovation (FESI), which combines federal and private resources to expand capacity, streamline operations, and spur innovation. Legislation enabling such a foundation was introduced with bipartisan support in the 118th Congress, signaling broad consensus on its value. The Trump administration can direct NIST to study how a nonprofit foundation might boost its AI initiatives and broader mission—just as a similar report helped pave the way for FESI—giving Congress the evidence it needs to formally authorize a NIST Foundation. The administration can also support passage of authorizing legislation through Congress.

Recommendation 5. Attract Top Global Talent by Creating a National Security AI Entrepreneur Visa for Elite Dual-use Technology Founders (link to full memo >>>)

America’s leadership in AI has been driven by the contributions of immigrant entrepreneurs, with companies like NVIDIA, Anthropic, OpenAI, X, and HuggingFace—all of which have at least one immigrant co-founder—leading the charge. To maintain this competitive edge as global competition intensifies, the administration should champion a National Security Startup Visa specifically targeted at high-skilled founders of AI firms. These entrepreneurs are at the forefront of developing dual-use technologies critical for both America’s economic leadership and national security. Although the linked proposal above is targeted at legislative action, the administration can take immediate steps to advance this priority by publicly supporting legislation to establish such a visa, engaging with Congressional allies to underscore its strategic importance, and directing agencies like the Department of Homeland Security and the Department of Commerce to explore ways to streamline pathways for these innovators. This decisive action would send a clear signal that America remains the destination of choice for world-class talent, ensuring that the nation stays ahead in the race for AI dominance.

Policy Proposals to Accelerate AI Adoption Across the Economy

AI has transformative potential to boost economic growth and unlock new levels of prosperity for all. The Trump administration should take bold action to encourage greater adoption of AI technologies and AI expertise by leveraging government procurement, hiring, and standards-setting processes, alongside coordinated support for America’s teachers to prepare students to join the future AI workforce. In government, a coordinated set of federal initiatives is needed to modernize and streamline effective AI adoption in the public sector. These proposals include developing a national digital platform through GSA to streamline AI procurement processes, establishing a federal center of excellence to support state and local governments in AI implementation, and pursuing innovative hiring models to expand AI expertise at HHS. Additionally, NIST should develop voluntary standards for measuring AI energy and resource usage to inform infrastructure planning efforts. Finally, the President should announce a national teacher talent surge and set AI as a competitive priority in American education. 

Recommendation 1. Streamline Procurement Processes for Government Use of AI (link to full memo >>>)

The federal government has a critical role in establishing standards for AI systems to enhance public services while ensuring they are implemented ethically and transparently. To streamline this effort and support federal agencies, the administration should direct the General Services Administration (GSA) to create a user-friendly, digital platform for AI procurement. This platform would simplify the acquisition process by providing agencies with clear, up-to-date guidelines, resources, and best practices, all tailored to align with existing procurement frameworks. The platform would empower agencies to make informed decisions that prioritize safety, fairness, and effective use of AI technologies, while demonstrating the administration’s commitment to modernizing government operations and ensuring America leads the way in adopting cutting-edge AI solutions.

Recommendation 2. Establish a Federal Center of Excellence to Expand State and Local Government Capacity for AI Procurement and Use (link to full memo >>>)

State and local governments often face challenges in effectively leveraging AI to enhance their efficiency and service capabilities. To support responsible AI adoption at the state, local, tribal, and territorial (SLTT) levels, the administration should establish a federal AI Center of Excellence. This center would provide hands-on guidance from experts in government, academia, and civil society, helping SLTT agencies navigate complex challenges such as limited technical expertise, budget constraints, privacy concerns, and evolving regulations. It would also translate existing federal AI standards—including Executive Order 13960 and the NIST Risk Management Framework—into practical, actionable advice. By developing in-house procurement and deployment expertise, SLTT governments could independently and confidently implement AI solutions, promoting innovation while ensuring responsible, effective, and efficient use of taxpayer resources.

Recommendation 3. Pilot an AI Corps at HHS to Drive Government-Wide AI Adoption (link to full memo >>>) 

Federal agencies often struggle to leverage AI effectively, due to limited technical expertise and complex oversight requirements. Modeled after the Department of Homeland Security’s successful AI Corps, which has improved disaster response and cybersecurity, this pilot would embed AI and machine learning experts within the Department of Health and Human Services’s (HHS) 10 agencies, accelerating responsible AI implementation in healthcare, driving greater efficiency, and demonstrating a scalable model that could be replicated across other federal departments. HHS is uniquely suited for piloting an AI Corps because it oversees critical health infrastructure and massive, sensitive datasets—presenting significant opportunities for AI-driven improvements but also requiring careful management. If successful, this pilot could serve as a strategic blueprint to enhance AI adoption, improve government performance, and maximize the responsible use of taxpayer resources across the federal government.

Recommendation 4. Make America’s Teacher Workforce Competitive for the AI Era (link to full memo >>>) 

With America facing a significant shortage of teachers and a growing need for AI and digital skills in the workforce, the Trump administration can rebuild America’s teaching profession by launching a coordinated strategy led by the Office of Science and Technology Policy (OSTP). This initiative should begin with a national teacher talent surge to expand annual teacher graduates by 100,000, addressing both the urgent workforce gap and the imperative to equip students for an AI-driven future. The plan includes a Challenge.gov competition to attract innovative recruitment and retention models, updating Department of Education scholarship programs (like the Graduate Assistance in Areas of National Need) to include AI, data science, and machine learning, convening colleges of education to modernize training, and directing agencies to prioritize AI-focused teacher development. By leveraging existing grants (e.g., Teacher Quality Partnerships, SEED, the STEM Corps, and Robert Noyce Scholarships), the administration can ensure a robust pipeline of educators ready to guide the next generation.

Recommendation 5. Prepare U.S. Energy Infrastructure for AI Growth Through Standardized Measurement and Forecasting

As AI adoption accelerates, America’s energy infrastructure faces a critical challenge: next-generation AI systems could place unprecedented demands on the power grid, yet the lack of standardized measurements, and wide variations in forecasted demand, leaves utilities and policymakers unprepared. Without proactive planning, energy constraints could slow AI innovation and undermine U.S. competitiveness.

To address this, the Administration should direct the National Institute of Standards and Technology (NIST) and the Department of Energy (DOE) to develop a standardized framework for measuring and forecasting AI’s energy and resource demands. This framework should be paired with a voluntary reporting program for AI developers—potentially collected by the Energy Information Administration (EIA)—to provide a clearer picture of AI’s impact on energy consumption. The EIA should also be tasked with forecasting AI-driven energy demand, ensuring that utilities, public utility commissions, and state energy planners have the data needed to modernize the grid efficiently.

Greater transparency will enable both government and industry to anticipate energy needs, drive investment in grid modernization, and prevent AI-related power shortages that could hinder economic growth. The proactive integration of AI and energy planning will strengthen America’s leadership in AI innovation while safeguarding the reliability of its infrastructure. FAS is actively developing policy proposals with the science and technology community at the intersection of AI and energy. We plan to share additional recommendations on this topic in the coming months.

Policy Proposals to Ensure Secure and Trustworthy AI

Privacy

Protecting Americans’ privacy while harnessing the potential of AI requires decisive federal action that prioritizes both individual rights and technological advancement. Strengthening privacy protections while enabling responsible data sharing is crucial for ensuring that AI-driven innovations improve public services without compromising sensitive information. Key initiatives include establishing NIST-led guidelines for secure data sharing and maintaining data integrity, implementing a FedRAMP authorization framework for third-party data sources used by government agencies, and promoting the use of Privacy Enhancing Technologies (PETs). Additionally, the administration should create a “Responsible Data Sharing Corps” to provide agencies with expert guidance and build capacity in responsible data practices.

Recommendation 1. Secure Third Party Commercial Data for AI through FedRAMP Authorization (link to full memo >>>)

The U.S. government is a major customer of commercial data brokers and should require a pre-evaluation process before agencies acquire large datasets, ensuring privacy and security from the outset. Thoroughly vetting data brokers and verifying compliance standards can help avert national security risks posed by compromised or unregulated third-party vendors. To formalize these safeguards, OMB and FedRAMP should create an authorization framework for data brokers that provide commercially available information, especially with personally identifiable information. Building on its established role in securing cloud providers FedRAMP is well positioned to guide these protocols, ensuring agencies work only with trusted vendors and strengthening overall data protection.

Recommendation 2. Catalyze Federal Data Sharing through Privacy Enhancing Technologies (link to full memo >>>)

To maintain America’s leadership in AI and digital innovation, the administration must ensure that government agencies can securely leverage data while protecting privacy and maintaining public trust. The federal government can lead by example through the adoption of Privacy Enhancing Technologies (PETs)—tools that enable data analysis while minimizing exposure of sensitive information. Agencies should be encouraged to adopt PETs with support from a Responsible Data Sharing Corps, while NIST develops a decision-making framework to guide their use. OMB should require agencies to apply this framework in data-sharing initiatives and report on PET adoption, with a PET Use Case Inventory and annual reports enhancing transparency. A federal fellowship program could also bring in experts from academia and industry to drive PET innovation. These measures would strengthen privacy, security, and public trust while positioning the U.S. as a global leader in responsible data use.

Recommendation 3. Establish Data-Sharing Standards to Support AI Development in Healthcare (link to full memo >>>) 

The U.S. healthcare system generates vast amounts of data daily, yet fragmentation, privacy concerns, and lack of interoperability severely limit its use in AI development, hindering medical innovation. To address this, the AI Action Plan should direct NIST to lead an interagency coalition in developing standardized protocols for health data anonymization, secure sharing, and third-party access. By establishing clear technical and governance standards—similar to NIST’s Cryptographic and Biometric Standards Programs—this initiative would enable responsible research while ensuring compliance with privacy and security requirements. These standards would unlock AI-driven advancements in diagnostics, treatment planning, and health system efficiency. Other nations, including the U.K., Australia, and Finland, are already implementing centralized data-sharing frameworks; without federal leadership, the U.S. risks falling behind. By taking decisive action, the administration can position the U.S. as a global leader in medical AI, accelerating innovation while maintaining strong privacy protections.

Security, Safety, and Trustworthiness

AI holds immense promise for job growth, national security, and innovation, but accidents or misuse risk undermining public trust and slowing adoption—threatening the U.S.’s leadership in this critical field. The following proposals use limited, targeted government action alongside private-sector collaboration to strengthen America’s AI capabilities while upholding public confidence and protecting our national interests.

Recommendation 1. Establish an Early Warning System for AI-Powered Threats to National Security and Public Safety (link to full memo >>>) 

Emerging AI capabilities could also pose severe threats to public safety and national security. AI companies are already evaluating their most advanced models to identify dual-use capabilities, such as the capacity to conduct offensive cyber operations, enable the development of biological or chemical weapons, and autonomously replicate and spread. These capabilities can arise unpredictably and undetected during development and after deployment. To prepare for these emerging risks, the federal government should establish a coordinated “early-warning system” for novel dual-use AI capabilities to gain awareness of emerging risks before models are deployed. A government agency could serve as a central information clearinghouse—an approach adapted from the original congressional proposal linked above. Advanced AI model developers could confidentially report newly discovered or assessed dual-use capabilities, and the White House could direct relevant government agencies to form specialized working groups that engage with private sector and other non-governmental partners to rapidly mitigate risks and leverage defensive applications. This initiative would ensure that the federal government and its stakeholders have maximum lead time to prepare for emerging AI-powered threats, positioning the U.S. as a leader in safe and responsible AI innovation.

Recommendation 2. Create a Voluntary AI Incident Reporting Hub to Monitor Security Incidents from AI (link to full memo >>>)

The federal government should establish a voluntary national Artificial Intelligence Incident Reporting Hub to better track, analyze, and address incidents from increasingly complex and capable AI systems that are deployed in the real world. Such an initiative could be modeled after successful incident reporting and info-sharing systems operated by the National Cybersecurity FFRDC, the Federal Aviation Administration, and the Food and Drug Administration. By providing comprehensive yet confidential data collection under the umbrella of an agency (e.g. NIST) this initiative would bolster public trust, facilitate the sharing of critical risk information, and enable prompt government action on emerging threats, from cybersecurity vulnerabilities to potential misuse of AI in sensitive areas like chemical, biological, radiological, or nuclear contexts. This proposal builds on bipartisan legislation introduced in the last Congress, as well as the memo linked above, which was originally targeted at Congressional action.

Recommendation 3. Promote AI Trustworthiness by Providing a Safe Harbor for AI Researchers (link to full memo >>>)

Independent AI research plays a key role in ensuring safe and reliable AI systems. In 2024, over 350 researchers signed an open letter calling for “a safe harbor for independent AI evaluation”, noting that generative AI companies offer no legal protections for independent safety researchers. This situation is unlike established voluntary protections from companies for traditional software, and Department of Justice (DOJ) guidance not to prosecute good faith security research. The proposal linked above was targeted at Congressional action, however the executive branch could adapt these ideas in several ways, by, for example: 1) instructing the Office of Management and Budget (OMB) to issue guidance to all federal agencies requiring that contracting documents for generative AI systems include safe-harbor provisions for good-faith external research, consistent with longstanding federal policies that promote responsible vulnerability disclosure. 2) Coordinating with DOJ and relevant agencies to clarify that good-faith AI security and safety testing—such as red-teaming and adversarial evaluation—does not violate the Computer Fraud and Abuse Act (CFAA) or other laws when conducted according to established guidelines.

Recommendation 4. Build a National Digital Content Authentication Technologies Research Ecosystem (link to full memo >>>) 

AI generated synthetic content (such as fake videos, images, and audio) is increasingly used by malicious actors to defraud elderly Americans, spread child sexual abuse material, and impersonate political figures. To counter these threats, the United States must invest in developing technical solutions for reliable synthetic content detection. Through the National Institute of Standards and Technology (NIST), the Trump Administration can: 1) establish dedicated university-led national research centers, 2) develop a national synthetic content database, and 3) run and coordinate prize competitions to strengthen technical countermeasures.These initiatives will help build a robust research ecosystem to keep pace with the rapidly evolving synthetic content threat landscape, maintaining America’s role as a global leader in responsible and secure AI.

Recommendation 5. Strengthen National Security by Evaluating AI-Driven Biological Threats (link to full memo >>>)

Over the past two years, the rapid advance of AI in biology and large language models has highlighted an urgent need for a targeted U.S. Government program to assess and mitigate biosecurity risks. While AI-enabled tools hold immense promise for drug discovery, vaccine research, and other beneficial applications, their dual-use potential (e.g., identifying viral mutations that enhance vaccine evasion) makes them a national security priority. Building on the Department of Homeland Security’s (DHS) previous work on AI and CBRN threats, the Department of Energy (DOE),  DHS, and other relevant agencies, should now jointly launch a “Bio Capability Evaluations” program, backed by sustained funding, to develop specialized benchmarks and standards for evaluating dangerous biological capabilities in AI-based research tools. By forming public-private partnerships, creating a DOE “sandbox” for ongoing testing, and integrating results into intelligence assessments, such a program would enable more nuanced, evidence-based regulations and help the United States stay ahead of potential adversaries seeking to exploit AI’s biological capabilities.

Policy Proposals to Strengthen Existing World-Class U.S. Government AI Institutions and Programs that are Key to the Trump Administration’s AI Agenda

A robust institutional framework is essential for ensuring that the government fulfills its role in AI research, industry coordination, and ecosystem development. The previous Trump administration laid the groundwork for American AI leadership, and the institutions established since then can be leveraged to further assert U.S. dominance in this critical technological space.

Recommendation 1. Support the NIST AI Safety Institute as a Key Pillar of American AI Excellence

The NIST AI Safety Institute (AISI) has assembled a world-leading team to ensure that the U.S. leads in safe, reliable, and trustworthy AI development. As AI integrates into critical sectors like national security, healthcare, and finance, strong safety standards are essential. AISI develops rigorous benchmarks, tests model security, and collaborates with industry to set standards, mitigating risks from unreliable AI. Strengthening AISI protects U.S. consumers, businesses, and national security while boosting global trust in the U.S. AI ecosystem—enhancing international adoption of American AI models. AISI has broad support, with bipartisan legislation to codify the AISI advanced in Congress and backing from organizations across industry and academia. The AI Action Plan should prioritize AISI as a pillar of AI policy.

Recommendation 2. Expand the National Artificial Intelligence Research Resource from Pilot to Full Program

For decades, academic researchers have driven AI breakthroughs, laying the foundation for the technologies that now shape global competition. However, as AI development becomes increasingly concentrated within large technology companies, the U.S. risks losing the ecosystem that made these advances possible. The National AI Research Resource (NAIRR) Pilot is a critical initiative to keep American AI innovation competitive and accessible. By providing researchers and educators across the country access to cutting-edge AI tools, datasets, and computing power, NAIRR ensures that innovation is not confined to a handful of dominant firms but widely distributed. To keep America at the forefront of AI, the Trump Administration should expand NAIRR into a full-fledged program. Allowing the program to lapse would erode America’s leadership in AI research, forcing top talent to seek resources elsewhere. To secure its future, the White House should support bipartisan legislation to fully authorize NAIRR and include it in the President’s Budget Request, ensuring sustained investment in this vital initiative.

Recommendation 3. Enhance Transparency, Accountability, and Industry Engagement by Preserving the AI Use Case Inventory (link to letter of support >>>)

The AI Use Case Inventory, established under President Trump’s Executive Order 13960 and later codified in section 7225 of the FY23 National Defense Authorization Act, plays a crucial role in fostering public trust and innovation in government AI use. Recent OMB guidance (M-24-10) has expanded its scope, refining AI classifications and standardizing AI definitions. The inventory enhances public trust and accountability by ensuring transparency in AI deployments, tracks AI successes and risks to improve government services, and supports AI vendors by providing visibility into public-sector AI needs, thereby driving industry innovation. As the federal government considers revisions to M-24-10 and its plan for AI adoption within federal agencies, OMB should uphold the 2024 guidance on federal agency AI Use Case Inventories and ensure agencies have the necessary resources to complete it effectively.

Recommendation 4. Propel U.S. Scientific and Security AI Leadership by Supporting AI and Computing at DOE 

The Department of Energy (DOE) hosts leading research and innovation centers, particularly under the Undersecretary for Science and Innovation. The Office of Critical and Emerging Technologies (CET), for example, plays a key role in coordinating AI initiatives, including the proposed Frontiers in Artificial Intelligence for Science, Security, and Technology (FASST) program. To fully harness AI’s potential, DOE should establish a dedicated AI and Computing Laboratory under the Undersecretary, ensuring a strategic, mission-driven approach to AI development. This initiative would accelerate scientific discovery, strengthen national security, and tackle energy challenges by leveraging DOE’s advanced computational infrastructure and expertise. To ensure success, it should be supported by a multi-year funding commitment and flexible operational authorities, modeled after ARPA-E, to streamline hiring, procurement, and industry-academic partnerships.

Conclusion

These recommendations offer a roadmap for securing America’s leadership in artificial intelligence while upholding the fundamental values of innovation, competitiveness, and trustworthiness. By investing in cutting-edge research, equipping government and educators with the tools to navigate the AI era, and ensuring safety, the new administration can position America as a global standard-bearer for trustworthy and effective AI development.

Winning the Next Phase of the Chip War

Last year the Federation of American Scientists (FAS), Jordan Schneider (of ChinaTalk), Chris Miller (author of Chip War) and Noah Smith (of Noahpinion) hosted a call for ideas to address the U.S. chip shortage and Chinese competition. A handful of ideas were selected based on the feasibility of the idea and its and bipartisan nature. This memo is one of them.

Summary

  1. Danger Ahead: Until now, the U.S. semiconductor policy agenda focused on getting an edge over China in the production of advanced semiconductors. But now a potentially even more  substantial challenge looms. Possible Chinese dominance in so-called ‘legacy’ chips  essential for modern economic life could grant it unacceptable leverage over the United  States. This challenge will require tools far more disruptive than ever before considered by policymakers for the chip competition. 
  2. The Foot on America’s Economic Neck: Collecting offensive economic leverage lies at the  heart of Chinese leader Xi Jinping’s strategy. Chinese dominance in legacy chips could  enable Beijing’s bullying of the United States it has thus far reserved for U.S. allies. China’s  growing leverage over Washington may embolden Beijing to think it could attack Taiwan with  relative impunity. 
  3. Familiar Semiconductor Policy Tools Won’t Work Alone: China increasingly has access to  the tech it needs for its legacy ambitions (via stockpiling and indigenization), damaging  possible expanded export controls. And unfair Chinese trade practices could reduce the  benefits of subsidies, as it has for solar and critical minerals. 
  4. Learning to Love Trade Protection: Only when the U.S. market cannot access Chinese  chips will they have sufficient incentive to manufacture chips in third countries. Washington could either turn to tariffs or outright bans on Chinese chips. Washington has several options  to block China’s chips – AD/CVD, 337, ‘ICTS’, 5949, and 232. But the most powerful tool would be Section 301 of the Trade Act of 1974. 
  5. The Keys to Success: Trade measures will have to target Chinese chips contained within  other products, not just the chips themselves. The U.S. government’s clarity into global  supply chains will have to grow dramatically. Allied participation and knowledge-sharing  might be needed. The United States can ease enforcement of a chips trade war by  incentivizing private industry to share the burden of detecting violations of U.S. law.  

The Generational Leap in U.S. Chip Policy 

For five years, U.S. concerns over China’s semiconductor sector focused on its cutting-edge chip  production. The bipartisan instinct has been to mix restrictions on Chinese access to Western  technology and to fund manufacturing of advanced chips at home. It began with the Trump  administration’s sanctions against Chinese chip giants Fujian Jinhua, Huawei, and SMIC. The Biden administration’s October 2022 export controls on China’s advanced chipmakers and the CHIPS and Science Act crowned a new era of technology competition focused on the absolute bleeding edge.  

Fast forward to July 2024: Washington entered the next phase of the chip war.  

Biden administration concerns about legacy chips emerged subtly last summer from one-off statements from Commerce Secretary Gina Raimondo. Before long Team Biden began to formally investigate the issue in an industry survey. Then in May the administration doubled existing tariffs on Chinese-made chips from 25% to 50%. 

Congress is equally concerned. The bipartisan China Committee endorsed tariffs on Chinese legacy chips in its December 2023 economic report and in a January 2024 letter to the administration. China’s growing position in the production of mature-node chips took center stage in a Committee hearing in June 2024, where Committee Chair John Moolenaar called for “a reliable domestic supply of semiconductors outside the reach of the CCP”. 

This apparently sudden shift reflects the growth of the stakes in the U.S.-China chip competition over the past year: 

Despite the scale of the challenge, Washington has not yet decided on its strategy to take on the  problem. The best approach to the legacy challenge will be one that can prevent U.S. reliance on  Chinese-made chips to ensure China cannot capture decisive leverage over the U.S. economy.  Doing so will require using trade measures to reject Chinese chips from the U.S. altogether.  

Dominance Means Leverage 

China’s fast-rising position in the legacy chip industry threatens U.S. national security because it  would grant Beijing extraordinary strategic leverage over the United States. That would encourage Chinese economic coercion and even a war over Taiwan.  

2.1. Xi’s Plan for ‘Offensive Leverage’: Geoeconomics lies at the heart of Chinese leader Xi  Jinping’s international strategy. The strategy is to exploit foreign dependence on Chinese critical  supply chains to accomplish Beijing’s objectives abroad. 

Xi himself laid the foundation of this vision in a pair of speeches in 2020 in which he called for  economic “deterrence” over the rest of the world. He called for an economic “gravitational field”  to “benefit the formation of new advantages for participating in international competition and  cooperation”. China would achieve this by heightening “the dependent relationships of international  industrial chains on our country, to form a powerful countermeasure and deterrence capability  against external parties who artificially cut off supply”, according to Xi. 

The Chinese Communist Party’s 2021 Five-Year Plan enshrined these principles in Party jargon,  calling for a “powerful domestic market and strong-trading country” to “form a powerful gravitational  field for global production factors and resources”. This is often called the “dual circulation” strategy by outside observers. It could more usefully be  called “offensive leverage”. 

2.2. Beijing’s Bullying Could Come for Washington: Since Xi Jinping rose to power in 2012, China  has repeatedly demonstrated these geoeconomic principles by flashing its economic strength to accomplish strategic objectives. 

The list of examples of Chinese economic coercion is long. In 2010, China limited Japanese  purchases of rare-earth minerals over a Senkaku Islands dispute. Norwegian salmon rotted that  same year on Chinese docks in retaliation for dissident Liu Xiaobo winning the Nobel Peace Prize. In  2012, Philippine bananas also rotted over the Scarborough Shoal dispute. In 2016, Beijing conveyed its displeasure toward Seoul for agreeing to host U.S. missile defense systems by squeezing South  Korean auto sales in China and slashing Chinese tourism in the country. 

This bullying has not slowed since Xi unveiled his economic thinking in 2020. That year, China  embargoed Australian wine, barley, wheat, coal, fish, and other products after Canberra passed  laws to reduce foreign influence and called for an investigation into the origins of Covid-19.In 2021, China blocked imports of Lithuanian goods over the state opening a “Taiwanese Representative  Office”. In just the past month, Beijing has threatened French luxury brands, German car makers, and Spanish pork producers in retaliation for EU duties on Chinese electric vehicles. 

Washington faces less blatant coercion compared to its allies. True, China has targeted U.S. firms  such Micron over the past few years. But the scale and ambition of this bullying has never  approached what China has applied to the likes of Australia and Lithuania. This may be because  Beijing does not believe it yet maintains necessary leverage over Washington to brandish its  economic blade as it does toward smaller economies.  

China’s growing position in the legacy semiconductor market could change that. How would  Beijing’s behavior change if sales of the Ford F-150 relied on Beijing’s willingness to sell its semiconductors?  

2.3. Reliance Endangers Taiwan: Western European reliance on Russian energy was one factor (among many) that encouraged Vladimir Putin to believe he could invade Ukraine with relative impunity. Likewise, deepening U.S. dependence on China for strategic supply chains could make it  far more difficult to challenge Beijing on sensitive geopolitical issues.  

The United States already relies on China for other key inputs to its economy: generic  pharmaceuticals, critical minerals, solar panels, and printed circuit boards, among others. U.S.  reliance on Chinese-made legacy chips – the product at the heart of modern economic life – could be the crown jewel of Chinese geoeconomics. American economic reliance on China could embolden Xi Jinping to think he could attack Taiwan with tolerable penalty.  

The Case for Blocking China’s Chips 

Familiar semiconductor policy approaches – export controls and subsidies – are inadequate alone to prevent reliance on Chinese-made legacy chips. Washington and its allies will instead have to turn  to the old-fashioned, disruptive tools of trade defense in the face of a challenge of this scale.  

3.1. It’s Too Late for Export Controls: The crux of current U.S. semiconductor policy toward China  is to contain the growth of Chinese advanced chip production by limiting its access to exquisite  machine tools produced by the United States and its allies (often called the ‘restrict’ agenda). Without those tools, China will be unable to build the cutting-edge chips that enable AI and  advanced weapons.  

Why not do the same for legacy chips? Washington and its allies could grow its existing rules so that China could not purchase machines capable of manufacturing legacy chips from Western producers. 

The issue is that China increasingly already has the tools it needs for its legacy chip production, in two ways: 

Export controls may have worked for the legacy challenge five or ten years ago. It’s unlikely to work alone today. 

3.2. Chinese Trade Practices Undermine Subsidies: The second pillar of Washington  semiconductor strategy for the past couple of years has been what’s often called the ‘promote’  agenda. The United States is deploying $39 billion in subsidies through the 2022 CHIPS and Science  Act to incentivize new chip factories at home. The strategy has helped galvanize $447 billion in  private investment across 25 states, 37 new chip fabs, and expansions at 21 other fabs. The United  States is now projected to make 30% of all advanced logic chips by 2032. But the CHIPS and Science Act  focuses on advanced chips, not legacy ones. Only a quarter of CHIPS funding ($10 billion) is planned to be spent on legacy-chip production.

Why not pass a Chips Act for legacy chips? California Representative Ro Khanna has called for doing  so: “a Chips Act 2.0 and 3.0 to better focus on legacy chips for our cars, refrigerators, and dryers”.  Indeed, subsidies may be a key tool to spur additional domestic legacy chip  production.  

But subsidies alone are unlikely to rise to the challenge. China’s “brute force” economic strategy  might render a legacy ‘promote’ agenda stillborn.  Beijing’s approach is to eliminate foreign  competitors with low prices by flooding international markets with state-sponsored artificially high  supply. China could flood the market with cheap chips to deter private Western investment into new chip production despite generous subsidies. The result could be billions of taxpayer dollars spent  with insufficient new chip capacity to show for it. 

Two recent examples demonstrate how Chinese industrial policy practices can undermine  Washington ‘promote’ policy: 

One Pentagon-funded Idaho mine, the only cobalt mine in the United States, was planned to open last year. It’s instead been mothballed since over low cobalt prices – down by almost two-thirds in two years.The  owner of that mine, Australian firm Jervois, told investors in March it would lay off 30% of its senior corporate management over “adverse cobalt market conditions caused by Chinese  overproduction and its impact on pricing”.

The warning signs in the legacy chip sector are already flashing. Chinese semiconductors were “20  to more than 30%” cheaper than their international counterparts in 2022 and 2023, according to the  Silverado Policy Accelerator.This price advantage will likely only widen with time. 

3.3. Don’t Compete with China on Price: The challenge facing U.S. policymakers is that Chinese  industrial policy is designed to make it impossible for Western firms to offer prices competitive  against Chinese players. The solution is to deny Chinese chips access to Western markets.  

The logic is simple yet unfamiliar for some following semiconductor policy. Only if the U.S. market is denied to Chinese chips will those producing for the United States be forced to source chips outside  of China, and only then will the construction of scaled chipmaking capacity in third countries  become economic.  

How It Would Work 

Preventing U.S. reliance on Chinese chips would be more complicated than simply raising the tariff  on Chinese-made chips imported into the U.S. market. For it to work, Washington would need to  target goods that contain Chinese chips, not just the imports of the chips themselves. It also may need allied cooperation.  

4.1. Target Chips as Components, not the Chips Themselves: Semiconductors are  overwhelmingly an intermediate good, not a final product of the sort Washington typically tariffs or blocks at the border. U.S. policy will have to reflect that complexity.  

The Biden administration in May doubled U.S. tariffs on imported Chinese chips from 25% to 50%,  citing China’s “rapid capacity expansion that risks driving out investment by market-driven firms”. The original 25% tariff, imposed by the Trump administration in 2018, reduced direct imports of  Chinese chips by around 72%, according to the U.S. International Trade Commission. But direct  imports represent only a portion – likely a minority portion – of the Chinese-made chips that  otherwise enter the United States as components within other devices. 

The original 2018 tariffs had no effect on Chinese chips arriving as components of other goods – and  neither will the new Biden tariffs, which double the rate of the 2018 tariffs without changing their design. Closing this loophole would require the administration to do just that.  

One way of doing so would be to apply a “component tariff”, effectively increasing the import cost of  the final good (whatever it is) because it contains a chip or chips made in China. The China Committee called for this in January 2024. Another way would be to deny outright products containing Chinese chips entry into the United States. Both options could work, assuming a component tariff is  high enough to overcome any possible Chinese price advantage (e.g., 200% or higher).  

Some experts have expressed doubt that it is even possible as a policy matter to target Chinese chips  because they are intermediate goods. But this view is erroneous. In fact, various laws allow  Washington to tariff or outright exclude from the U.S. market any product made with Chinese  semiconductors. (See Section 5). 

4.2. Bring the Allies Along: A strategy to prevent U.S. reliance on Chinese chips would have higher  odds of success if U.S. allies join, most importantly Europe and Japan. The risk is that without allies,  international chip players would continue to design their microelectronics with Chinese chips, leaving the United States out of the best the market has to offer. A more optimistic assessment would be that the U.S. consumer market is so large that unilateral Washington action would be  enough to force leading market players to design their products without Chinese chips. 

Either way, allied signals are positive. The EU said about legacy chips last  April that it was “gathering  information on this issue”, and that it would coordinate with the United States to “collect and share  non-confidential information” about Chinese “non-market policies and practices”.The bloc’s new  duties on Chinese automakers indicate it could be open to similar measures toward chips. Japan  has taken fewer concrete steps than Europe, but Tokyo’s Minister for Economy, Trade and Industry Ken Saito told reporters that participants took “great interest” in legacy chips at the first Japan Korea-U.S. Commerce and Industry Ministerial Meeting on 28 June 2024. 

Washington’s Toolkit 

The United States has multiple policy tools that could be used to prevent U.S. reliance on Chinese made semiconductors. Th following summarizes these tools, in roughly ascending order of magnitude.  

5.1. Countervailing Duties: This form of tax can be placed by the Commerce Department on foreign goods that it finds to be subsidised and that the U.S. International Trade Commission (ITC) finds  materially injure a U.S. domestic industry. After an investigation prompted either by a petition from U.S. industry or initiated by Commerce itself, Commerce can impose “CVDs” on the goods in  question. 

Two challenges, however: First, it can sometimes be difficult to prove that Chinese state subsidies  have boosted specific goods. Second, chips imported as components of other goods aren’t a natural  fit for CVD investigations, so some policy creativity would likely be required. 

5.2. Anti-Dumping Duties: This alternative tax is like its sister duty in how it comes about and who  investigates it, but in this case it seeks to counter imports that have been “dumped” at artificially low prices in the U.S. market. 

As with CVDs, however, some policy creativity may be required to use anti-dumping duties for chips  imported as components of other goods. Further, it can be challenging to establish a baseline “fair”  price against which to measure the price of any Chinese goods in the U.S. market. Former senior Commerce official Nazak Nikakhtar noted: “It is nearly impossible to find a surrogate  country that has not been adversely affected by the PRC’s predatory pricing. . . . Virtually all  benchmark prices in trade cases are now understated and inadequate for measuring [dumping] by the PRC.” 

5.3. Section 337: This provision (from the Tariff Act of 1930) allows the U.S. ITC to investigate  imported goods for alleged links to intellectual-property theft and a range of other unfair trade  practices. Relief can take the form of exclusion orders, cease-and-desist orders, or sequestration of goods.  

But the 337’s bureaucratic process might be too burdensome. The ITC is an independent agency not subject to direction by the White House. In 2018, the Commission on the Theft of American  Intellectual Property, led by ex-ambassador and ex-governor Jon Huntsman, recommended speeding up the ITC’s 337 process.

5.4. Section 5949: With relatively little fanfare, Congress in late 2022 enacted a measure that will  curb some Chinese legacy-chip sales in the U.S. market – but only some, and slowly. Via Section  5949 of the annual defence bill, Congress prohibited the U.S. federal government and its contractors  from procuring semiconductors for “critical” uses from three Chinese firms (SMIC, YMTC, CXMT),  beginning in four years. This provision could be expanded in multiple ways that would block Chinese chips from large swathes of the U.S. market. Policymakers could shorten the phase-in period, blacklist additional companies (beside SMIC, YMTC and CXMT), or force U.S. government  contractors not to buy proscribed Chinese chips even for their own private use.

The federal government does not, however, have the authority to force state governments to adopt similar rules. This approach would also allow any company that does not contract with the federal  government to purchase Chinese chips.  

5.5. ‘ICTS’: The Commerce Department’s “Information and Communications Technology and  Services” (ICTS) regime is probably capable of restricting the import of goods containing Chinese made chips. The regime, first outlined in the final days of the Trump administration and embraced by  the Biden administration, has broad authorities to restrict transactions (from limits on cross-border  data flows to import bans) across theoretically the entire digital economy: critical infrastructure,  network infrastructure, data hosting, surveillance and monitoring tech, communications software, and emerging technology.The ICTS office’s current investigation on Chinese ‘Connected Vehicles’, will restrict Chinese-controlled critical components from being used in cars on U.S. roads. The  president might similarly be able to use ICTS to restrict the import of products containing Chinese made semiconductors.  

Taking on Chinese legacy chips, however, would not fit the ICTS Office neatly:

5.6. Section 232: This instrument (from the Trade Expansion Act of 1962) allows any federal  department to require a Commerce Department investigation of specified imports that may threaten  national security (defined broadly). The President may then impose tariffs or quotas as a remedy.  The Trump administration used Section 232 to tariff imports of steel and aluminum in 2018, and it  could be a viable approach to legacy chips too.  

232’s main drawback is that it does not allow import bans. An obvious workaround would be to apply a component tariff onto Chinese semiconductors so high that it works effectively as a ban (e.g., north  of 200%).  

5.7. Washington’s Most Powerful Tool – Section 301: The strongest tool for the legacy-chips  challenge might be the Section 301 of the Trade Act of 1974, which gives the Office of the U.S. Trade  Representative broad scope investigate “unreasonable”, “discriminatory”, or  “unjustifiable” actions that burden U.S. commerce.  After an investigation, USTR has sweeping  powers to impose remedies as it sees fit, e.g. with tariffs, import bans, or other sanctions. It gives a president notably broad, flexible, and discretionary powers. 

301 has become the bipartisan tool of choice to address unfair Chinese trade and industrial practices and to reshore supply chains: 

A future 301 investigation could almost certainly find a way to prohibit goods with Chinese-made semiconductors from entering the U.S. market. The United States could open a 301 investigation into  Beijing’s state-led subsidy strategy to do so, as the Biden administration considered doing in 2021. 

Some may worry that 301’s required investigation before applying remedies would slow down a  solution that would ideally begin as soon as possible. But a public investigation of China’s position in the semiconductor industry could have major benefits. It could provide the administration insight into the international microelectronics supply chain, needed to implement a legacy restriction policy. 

And it would send industry a clear message that it should begin shifting its supply chains before the new U.S. policy began.  

Some of History’s Lessons on Decoupling  

One challenge facing this strategy is if it is practically possible to stop Chinese-made chips from  entering the U.S. market, no matter U.S. law. Some have called banning Chinese chips tantamount to trying to “hold sand in your hands”. The U.S. government has limited visibility into global supply chains. How could Washington enforce the next phase of China chips containment? 

Two examples of U.S. efforts to remove goods from international supply chains point to lessons about how the United States could go about doing so successfully today: implementation of the  Uyghur Forced Labor Prevention Act (UFLPA), and the ‘Kimberley Process’ to prevent sourcing blood  diamonds from Africa. They show that Washington will need three things to enforce this strategy: supply chain clarity, active participation from private industry to detect lawbreakers, and an allied  coalition to ensure success in preventing U.S. reliance on Chinese-made chips.  

6.1. Improving on the UFLPA Enforcement: Removing Chinese-made legacy chips from the U.S.  market would not be the first time Washington moved to fundamentally change the U.S.-China  trading relationship in pursuit of excising specific Chinese goods from the United States. The Uyghur Forced Labor Prevention Act, passed by Congress in late 2021, prohibited entirely any goods from  Xinjiang – or those with supply chains stemming from there – from coming into the United States on  grounds that they were tainted with forced labor. UFLPA Republican co-author Marco Rubio vowed  in 2021 that it would “fundamentally change our relationship with Beijing”. Jim McGovern, the  Democratic congressman who authored the House version of the bill, said “No more business as  usual”. 

Yet the law has had a less significant impact on U.S.-China trade flows than initially anticipated, most importantly in the solar industry. Some half of all global polysilicon, a base material for solar panels, comes from Xinjiang. Chinese firms have nonetheless increased their market share in the  United States since the passage of the UFLPA. 

There are three lessons to take from these challenges that policymakers can apply to the coming legacy chip trade war: 

  1. Supply Chain Clarity Needed: The UFLPA granted the administration no additional funding  for enforcement, likely forcing difficult decisions across the administration of how to fund  the stiff demands for research into global forced labor supply chains. Enforcing legacy-chip  protectionism would likely require a major expansion of supply chain analytical capabilities  across the U.S. government, including in the Commerce Department and within Customs  and Border Protection. 
  2. Let Private Industry Help with Enforcement: UFLPA enforcement might have been more  successful if detecting those who violated U.S. law was the responsibility of private industry,  not that of the government. Is this even possible?  


It appears so. The False Claims Act of 1863 allows private parties to initiate a lawsuit on  behalf of the U.S. government against those who have defrauded the U.S. government. Whistleblowers receive some 15% to 30% of the government’s award if they win. This law,  originally passed in the Civil War to crack down on fraud from military contractors, has  increasingly been used against those who commit customs and tariffs fraud. The law triples damages and civil penalties for violators.  

These cases (called “qui tam” cases) have been brought against those who transshipped  Chinese goods through third countries to dodge 301 tariffs. In one case, manufacturing  tools firm King Kong Tools paid $1.9 million in November 2023 to settle allegations that the  firm dodged paying 301 tariffs by falsely claiming its goods were made in Germany. The  case began when a competitor to King Kong brought a qui tam suit alleging that King Kong  produced its products in China, shipped them to Germany, then sent them to the United  States. The whistleblower received an award of $286,000. 

Washington could similarly enlist the private sector to help detect violations of legacy-chip trade rules. At a minimum, the Justice Department could begin a public campaign to  encourage whistleblowers to bring qui tam cases against violators. (Including technology research firms. TechInsights, the company known for teardowns of Chinese  microelectronics to determine their quality, comes to mind here.) The U.S. government  could also find ways to increase the incentive for private parties to bring cases against tariff  dodgers. Congress could update the False Claims Act to boost the reward for whistleblowers,  for example.  

6.2. An Allied System for Legacy-Chip Trade Protection: The Kimberley Process is a UN-mandated  certification scheme launched in 2003 to prevent diamonds that fund conflict from entering global  markets. 85 member states, civil society groups, and industry agreed to commit to transparent  practices and share data to certify that imported diamonds are not tainted by conflict. 

Washington and its allies should agree to collectively work to restrict the import of Chinese made legacy chips. They could share best practices and supply chain intelligence. It could make it  easier for Washington to know where Chinese semiconductors are moving throughout global supply chains. Doing so would help build an allied coalition collectively more resilient against Beijing’s economic coercion. 

Public Comment on Executive Branch Agency Handling of CAI containing PII

Public comments serve the executive branch by informing more effective, efficient program design and regulation. As part of our commitment to evidence-based, science-backed policy, FAS staff leverage public comment opportunities to embed science, technology, and innovation into policy decision-making.

The Federation of American Scientists (FAS) is a non-partisan, nonprofit organization committed to using science and technology to benefit humanity by delivering on the promise of equitable and impactful policy. FAS believes that society benefits from a federal government that harnesses science, technology, and innovation to meet ambitious policy goals and deliver impactful results to the public. 

We are writing in response to your Request for Information on the Executive Branch Agency Handling of Commercially Available Information (CAI) Containing Personally Identifiable Information (PII). Specifically, we will be answering questions 2 and 5 in your request for information: 

2. What frameworks, models, or best practices should [the White House Office of Management and Budget] consider as it evaluates agency standards and procedures associated with the handling of CAI containing PII and considers potential guidance to agencies on ways to mitigate privacy risks from agencies’ handling of CAI containing PII?

5.  Agencies provide transparency into the handling of PII through various means (e.g., policies and directives, Privacy Act statements and other privacy notices at the point of collection, Privacy Act system of records notices, and privacy impact assessments). What, if any, improvements would enhance the public’s understanding of how agencies handle CAI containing PII?

Background

In the digital landscape, commercially available information (CAI) represents a vast ecosystem of personal data that can be easily obtained, sold, or licensed to various entities. The Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (EO 14110) defines CAI comprehensively as information about individuals or groups that is publicly accessible, encompassing details like device information and location data.

A 2017 report by the Georgetown Law Review found that 63% of Americans can be uniquely identified using just three basic attributes—gender, birth date, and ZIP code—with an astonishing 99.98% of individuals potentially re-identifiable from a dataset containing only 15 fundamental characteristics. This vulnerability underscores the critical challenges of data privacy in an increasingly interconnected world. 

CAI takes on heightened significance in the context of artificial intelligence (AI) deployment, as these systems enable both data collection and the use of advanced inference models to analyze datasets and produce predictions, insights, and assumptions that reveal patterns or relationships not directly evident in the data. Some AI systems can allow the intentional or unintentional reidentification of supposedly anonymized private data. These capabilities raise questions about privacy, consent, and the potential for unprecedented levels of personal information aggregation and analysis, challenging existing data protection frameworks and individual rights.

The United States federal government is one of the largest customers of commercial data brokers. Government entities increasingly use CAI to empower public programs, enabling federal agencies to augment decision-making, policy development, and resource allocation and enrich research and innovation goals with large yet granular datasets. For example, the National Institutes of Health have discussed within their data strategies how to incorporate commercially available data into research projects. The use of commercially available electronic health records is essential for understanding social inequalities within the healthcare system but includes sensitive personal data that must be protected. 

However, government agencies face significant public scrutiny over their use of CAI in areas including law enforcement, homeland security, immigration, and tax administration. This scrutiny stems from concerns about privacy violations, algorithmic bias, and the risks of invasive surveillance, profiling, and discriminatory enforcement practices that could disproportionately harm vulnerable populations.  For example, federal agencies like Immigration and Customs Enforcement (ICE) and Customs and Border Protection (CBP) have used broker-purchased location data to track individuals without warrants, raising constitutional concerns. 

In 2020, the American Civil Liberties Union filed a Freedom of Information Act lawsuit against several Department of Homeland Security (DHS) agencies, arguing that the DHS’s use of cellphone data and data from smartphone apps constitutes unreasonable searches without a warrant and violates the Fourth Amendment. A report by the Electronic Frontier Foundation found that CAI was used for mass surveillance practices, including geofence warrants that query all phones in specific locations, further challenging constitutional protections. 

While the Privacy Act of 1974 covers the use of federally collected personal information by agencies, there is no explicit guidance governing federal use of third-party data. The bipartisan Fourth Amendment is Not for Sale Act (H.R.4639) would bar certain technology providers—such as remote computing service and electronic communication service providers—from sharing the contents of stored electronic communications with anyone (including government actors) and from sharing customer records with government agencies. The bill has passed the House of Representatives in the 118th Congress but has yet to pass the Senate as of December 2024. Without protections in statute, it is imperative that the federal government crafts clear guidance on the use of CAI containing PII in AI systems. In this response to the Office of Management and Budget’s (OMB) request for information, FAS will outline three policy ideas that can improve how federal agencies navigate the use of CAI containing PII, including in AI use. 

Summary of Recommendations

The federal government is responsible for ensuring the safety and privacy of the processing of personally identifiable information within commercially available information used for the development and deployment of artificial intelligence systems. For this RFI, FAS brings three proposals to increase government capacity in ensuring transparency and risk mitigation in how CAI containing PII is used, including in agency use of AI: 

  1. Enable FedRAMP to Create an Authorization System for Third-Party Data Sources: An authorization framework for CAI containing PII would ensure a standardized approach for data collection, management, and contracting, mitigating risks, and ensuring ethical data use.
  2. Expand Existing Privacy Impact Assessments (PIA) to Incorporate Additional Requirements and Periodic Evaluations: Regular public reports on CAI sources and usage will enable stakeholders to monitor federal data practices effectively.
  3. Build Government Capacity for the Use of Privacy Enhancing Technologies to Bolster Anonymization Techniques by harnessing existing resources such as the United States Digital Service (USDS). 

Recommendation 1. Enable FedRAMP to Create an Authorization System for Third-Party Data Sources

Government agencies utilizing CAI should implement a pre-evaluation process before acquiring large datasets to ensure privacy and security. OMB, along with other agencies that are a part of the governing board of the Federal Risk and Authorization Management Program (FedRAMP), should direct FedRAMP to create an authorization framework for third-party data sources that contract with government agencies, especially data brokers that provide CAI with PII, to ensure that these vendors comply with privacy and security requirements. FedRAMP is uniquely positioned for this task because of its previous mandate to ensure the safety of cloud service providers used by the federal government and its recent expansion of this mandate to standardize AI technologies. The program could additionally harmonize its new CAI requirements with its forthcoming AI authorization framework.

When designing the content of the CAI authorization, a useful benchmark in terms of evaluation criteria is the Ag Data Transparent (ADT) certification process. Companies applying for this certification must submit contracts and respond to 11 data collection, usage, and sharing questions. Like the FedRAMP authorization process, a third-party administrator reviews these materials for consistency, granting the ADT seal only if the company’s practices align with its contracts. Any discrepancies must be corrected, promoting transparency and protecting farmers’ data rights. The ADT is a voluntary certification, and therefore does not provide a good model for enforcement. However, it does provide a framework for the kind of documentation that should be required. The CAI authorization should thus include the following information required by the ADT certification process:

Unlike the ADT, a FedRAMP authorization process can be strictly enforced. FedRAMP is mandatory for all cloud service providers working with the executive branch and follows a detailed authorization process with evaluations and third-party auditors. It would be valuable to bring that assessment rigor to federal agency use of CAI, and would help provide clarity to commercial vendors. 

The authorization framework should also document the following specific protocols for the use of CAI within AI systems:

By setting these standards, this authorization could help agencies understand privacy risks and ensure the reliability of CAI data vendors before deploying purchased datasets within AI systems or other information systems, therefore setting them up to create appropriate mitigation strategies. 

By encouraging data brokers to follow best practices, this recommendation would allow agencies to focus on authorized datasets that meet privacy and security standards. Public availability of this information could drive market-wide improvements in data governance and elevate trust in responsible data usage. This approach would support ethical data governance in AI projects and create a more transparent, publicly accountable framework for CAI use in government.  

Recommendation 2. Expand Privacy Impact Assessments (PIA) to Incorporate Additional Requirements and Periodic Evaluations 

Public transparency regarding the origins and details of government-acquired CAI containing PII is critical, especially given the largely unregulated nature of the data broker industry at the federal level. Privacy Impact Assessments (PIAs) are mandated under Section 208 of the 2002 E-Government Act and OMB Memo M-03-22, and can serve as a vital policy tool for ensuring such transparency. Agencies must complete PIAs at the outset of any new electronic information collection process that includes “information in identifiable form for ten or more persons.” Under direction from Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, OMB issued a request for information in April 2024 to explore updating PIA guidance for AI-era privacy concerns, although new guidance has not yet been issued. 

To ensure that PIAs can effectively provide transparency into government practices on CAI that contains PII, we recommend that OMB provide updated guidance requiring agencies to regularly review and update their PIAs at least every three years, and also require agencies to report more comprehensive information in PIAs. We provide more details on these recommendations below.

First, OMB should guide agencies to periodically update their PIAs to ensure evolutions in agency data practices are publicly captured, which is increasingly important as data-driven AI systems are adopted by government actors and create novel privacy concerns. Under OMB Memo M-03-22, agencies must initiate or update PIAs when new privacy risks or factors emerge that affect the collection and handling of PII, including when agencies incorporate PII obtained from commercial or public sources into existing information systems. However, a public comment submitted by the Electronic Privacy Information Center (EPIC) pointed out that many agencies fail to publish and update required PIAs in a timely manner, indicating that a stricter schedule is needed to maintain accountability for PIA reporting requirements. As data privacy risks evolve through the advancement of AI systems, increased cybersecurity risks, and new legislation, it is essential that a minimum standard schedule for updating PIAs is created to ensure agencies provide the public with an up-to-date understanding of the potential risks resulting from using CAI that includes PII. For example, the European Union’s ​​General Data Protection Regulation (Art. 35) requires PIAs to be reconducted every three years. 

Second, agency PIAs should report more detailed information on the CAI’s source, vendor information, contract agreements, and licensing arrangements. A frequent critique of existing PIAs is that they contain too little information to inform the public of relevant privacy harms. Such a lack of transparency risks damaging public trust in government. One model for expanded reporting frameworks for CAI containing PII is the May 2024 Policy Framework for CAI, established for the Intelligence Community (IC) by the Office of the Director of National Intelligence (ODNI). This framework requires the IC to document and report “the source of the Sensitive CAI and from whom the Sensitive CAI was accessed or collected” and “any licensing agreements and/or contract restrictions applicable to the Sensitive CAI”. OMB should incorporate these reporting practices into agency PIA requirements and explicitly require agencies to identify the CAI data vendor in order to provide insight into the source and quality of purchased data.

Many of these elements are also present in Recommendation 1, for a new FedRAMP authorization framework. However, that recommendation does not include existing agency projects using CAI or agencies that could contract CAI datasets outside of the FedRAMP authorization. Including this information within the PIA framework also allows for an iterative understanding of privacy risks throughout the lifecycle of a project using CAI. 

By obligating agencies to provide more frequent PIA updates and include additional details on the source, vendor, contract and licensing arrangements for CAI containing PII, the public gains valuable insight into how government agencies acquire, use, and manage sensitive data. These updates to PIAs would allow civil society groups, journalists, and other external stakeholders to track government data management practices over time during this critical juncture where federal uptake of AI systems is rapidly increasing.

Recommendation 3. Build Government Capacity for the Use of Privacy Enhancing Technologies to Bolster Anonymization Techniques

Privacy Enhancing Technologies (PETs) are a diverse set of tools that can be used throughout the data lifecycle to ensure privacy by design. They can also be powerful tools in ensuring that PII within CAI) is adequately anonymized and secure. OMB should collect information on current agency PET usage, gather best practices, and identify deployment gaps. To address these gaps, OMB should collaborate with agencies like the USDS to establish capacity-building programs, leveraging initiatives like the proposed “Responsible Data Sharing Core” to provide expert consultations and enhance responsible data-sharing practices.

Meta’s Open Loop project identified eight types of PETs that are ripe to be deployed in AI systems, categorizing them into maturity levels, context of deployment, and limitations. One type of PET is differential privacy, a mathematical framework designed to protect individuals’ privacy in datasets by introducing controlled noise to the data. This ensures that the output of data analysis or AI models does not reveal whether a specific individual’s information is included in the dataset. The noise is calibrated to balance privacy with data utility, allowing meaningful insights to be derived without compromising personal information. Differential privacy is particularly useful in AI models that rely on large-scale data for training, as it prevents the inadvertent exposure of PII during the learning process. Within the federal government, the U.S. Census Bureau is using differential privacy to anonymize data while preserving its aggregate utility, ensuring compliance with privacy regulations and reducing re-identification within datasets.

Scaling the use of PETs in other agencies has been referenced in several U.S. government strategy documents, such as the National Strategy to Advance Privacy-Preserving Data Sharing and Analytics, which encourages federal agencies to adopt and invest in the development of PETs, and the Executive Order (EO) on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, which calls for federal agencies to identify where they could use PETs. As a continuation of this EO, the National Science Foundation and the Department of Energy established a Research Coordination Network on PETs that will “address the barriers to widespread adoption of PETs, including regulatory considerations.”  

Although the ongoing research and development of PETS is vital to this growing field, there is an increasing need to ensure these technologies are implemented across the federal government. To kick this off, OMB should collect detailed information on how agencies currently use PETs, especially in projects that use CAI containing PII. This effort should include gathering best practices from agencies with successful PET implementations, such as the previous U.S. Census Bureau’s use of differential privacy. Additionally, OMB should identify gaps in PET deployment, assessing barriers such as technical capacity, funding, and awareness of relevant PETs. To address these gaps, OMB should collaborate with other federal agencies to design and implement capacity-building programs, equipping personnel with the knowledge and tools needed to integrate PETs effectively. For example, a forthcoming FAS’ Day One Project publication, “Increasing Responsible Data Sharing Capacity throughout Government,” seeks to harness existing government capabilities to build government capacity in deploying PETs. This proposal aims to enhance responsible data sharing in government by creating a capacity-building initiative called the  “Responsible Data Sharing Core” (RDSC). Managed by the USDS, the RDSC would deploy fellows and industry experts to agencies to consult on data use and sharing decisions and offer consultations on which PETs are appropriate for different contexts.   

Conclusion

The federal government’s increasing reliance on CAI containing PII presents significant privacy challenges. The current landscape of data procurement and AI deployment by agencies like ICE, CBP, and others raises critical concerns about potential Fourth Amendment violations, discriminatory profiling, and lack of transparency.

The ideas proposed in this memo—implementing FedRAMPamp authorization for data brokers, expanding privacy impact assessment requirements, and developing capacity-building programs for privacy-enhancing technologies—represent crucial first steps in addressing these systemic risks. As AI systems become increasingly integrated into government processes, maintaining a delicate balance between technological advancement and fundamental constitutional protections will be paramount to preserving individual privacy, promoting responsible adoption, and maintaining public trust.

We appreciate the opportunity to contribute to this Request for Information on Executive Branch Agency Handling of Commercially Available Information Containing Personally Identifiable Information. Please contact clangevin@fas.org if you have any questions or need additional information.

Public Comment on the U.S. Artificial Intelligence Safety Institute’s Draft Document: NIST AI 800-1, Managing Misuse Risk for Dual-Use Foundation Models

Public comments serve the executive branch by informing more effective, efficient program design and regulation. As part of our commitment to evidence-based, science-backed policy, FAS staff leverage public comment opportunities to embed science, technology, and innovation into policy decision-making.

The Federation of American Scientists (FAS) is a non-partisan organization dedicated to using science and technology to benefit humanity through equitable and impactful policy. With a strong track record in AI governance, FAS has actively contributed to the development of AI standards and frameworks, including providing feedback on NIST AI 600-1, the Generative AI Profile. Our work spans advocating for federal AI testbeds, recommending policy measures for frontier AI developers, and evaluating industry adoption of the NIST AI Risk Management Framework. We are members of the U.S. AI Safety Institute Research Consortium, and we responded to NIST’s request for information earlier this year concerning its responsibilities under sections 4.1, 4.5, and 11 of the AI Executive Order.

We commend NIST’s U.S. Artificial Intelligence Safety Institute for developing the draft guidance on “Managing Misuse Risk for Dual-Use Foundation Models.” This document represents a significant step toward establishing robust practices for mitigating catastrophic risks associated with advanced AI systems. The guidance’s emphasis on comprehensive risk assessment, transparent decision-making, and proactive safeguards aligns with FAS’s vision for responsible AI development.

In our response, we highlight several strengths of the guidance, including its focus on anticipatory risk assessment and the importance of clear documentation. We also identify areas for improvement, such as the need for harmonized language and more detailed guidance on model development safeguards. Our key suggestions include recommending a more holistic socio-technical approach to risk evaluation, strengthening language around halting development for unmanageable risks, and expanding the range of considered safeguards. We believe these adjustments will further strengthen NIST’s crucial role in shaping responsible AI development practices.

Background and Context

The rapid advancement of AI foundation models has spurred novel industry-led risk mitigation strategies. Leading AI companies have voluntarily adopted frameworks like Responsible Scaling Policies and Preparedness Frameworks, outlining risk thresholds and mitigation strategies for increasingly capable AI systems. (Our response to NIST’s February RFI was largely an exploration of these policies, their benefits and drawbacks, and how they could be strengthened.)

Managing misuse risks in foundation models is of paramount importance given their broad applicability and potential for dual use. As these models become more powerful, they may inadvertently enable malicious actors to cause significant harm, including facilitating the development of weapons, enabling sophisticated cyber attacks, or generating harmful content. The challenge lies not only in identifying current risks but also in anticipating future threats that may emerge as AI capabilities expand.

NIST’s new guidance on “Managing Misuse Risk for Dual-Use Foundation Models” builds upon these industry initiatives, providing a more standardized and comprehensive approach to risk management. By focusing on objectives such as anticipating potential misuse, establishing clear risk thresholds, and implementing robust evaluation procedures, the guidance creates a framework that can be applied across the AI development ecosystem. This approach is crucial for ensuring that as AI technology advances, appropriate safeguards are in place to protect against potential misuse while still fostering innovation.

Strengths of the guidance

1. Comprehensive Documentation and Transparency

The guidance’s emphasis on thorough documentation and transparency represents a significant advancement in AI risk management. For every practice under every objective, the guidance indicates appropriate documentation; this approach is more thorough in advancing transparency than any comparable guidance to date. The creation of a paper trail for decision-making and risk evaluation is crucial for both internal governance and potential external audits.

The push for transparency extends to collaboration with external stakeholders. For instance, practice 6.4 recommends providing “safe harbors for third-party safety research,” including publishing “a clear vulnerability disclosure policy for model safety issues.” This openness to external scrutiny and feedback is essential for building trust and fostering collaborative problem-solving in AI safety. (FAS has published a legislative proposal calling for enshrining “safe harbor” protections for AI researchers into law.)

2. Lifecycle Approach to Risk Management

The guidance excels in its holistic approach to risk management, covering the entire lifecycle of foundation models from pre-development assessment through to post-deployment monitoring. This comprehensive approach is evident in the structure of the document itself, which follows a logical progression from anticipating risks (Objective 1) through to responding to misuse after deployment (Objective 6).

The guidance demonstrates a proactive stance by recommending risk assessment before model development. Practice 1.3 suggests to “Estimate the model’s capabilities of concern before it is developed…”, which helps anticipate and mitigate potential harms before they materialize. The framework for red team evaluations (Practice 4.2) is particularly robust, recommending independent external experts and suggesting ways to compensate for gaps between red teams and real threat actors. The guidance also emphasizes the importance of ongoing risk assessment. Practice 3.2 recommends to “Periodically revisit estimates of misuse risk stemming from model theft…” This acknowledgment of the dynamic nature of AI risks encourages continuous vigilance.

3. Strong Stance on Model Security and Risk Tolerance

The guidance takes a firm stance on model security and risk tolerance, particularly in Objective 3. It unequivocally states that models relying on confidentiality for misuse risk management should only be developed when theft risk is sufficiently mitigated. This emphasizes the critical importance of security in AI development, including considerations for insider threats (Practice 3.1).

The guidance also demonstrates a realistic approach to the challenges posed by different deployment strategies. In Practice 5.1, it notes, “For example, allowing fine-tuning via API can significantly limit options to prevent jailbreaking and sharing the model’s weights can significantly limit options to monitor for misuse (Practice 6.1) and respond to instances of misuse (Practice 6.2).” This candid discussion of the limitations of safety interventions for open weight foundation models is crucial for fostering realistic risk assessments.

Additionally, the guidance promotes a conservative approach to risk management. Practice 5.3 recommends to “Consider leaving a margin of safety between the estimated level of risk at the point of deployment and the organization’s risk tolerance.” It further suggests considering “a larger margin of safety to manage risks that are more severe or less certain.” This approach provides an extra layer of protection against unforeseen risks or rapid capability advancements, which is crucial given the uncertainties inherent in AI development.

These elements collectively demonstrate NIST’s commitment to promoting realistic and robust risk management practices that prioritize safety and security in AI development and deployment. However, while the NIST guidance demonstrates several important strengths, there are areas where it could be further improved to enhance its effectiveness in managing misuse risks for dual-use foundation models.

Areas for improvement

1. Need for a More Comprehensive Socio-technical Approach to Measuring Misuse Risk

Objective 4 of the guidance demonstrates a commendable effort to incorporate elements of a socio-technical approach in measuring misuse risk. The guidance recognizes the importance of considering both technical and social factors, emphasizes the use of red teams to assess potential misuse scenarios, and acknowledges the need to consider different levels of access and various threat actors. Furthermore, it highlights the importance of avoiding harm during the measurement process, which is crucial in a socio-technical framework.

However, the guidance falls short in fully embracing a comprehensive socio-technical perspective. While it touches on the importance of external experts, it does not sufficiently emphasize the value of diverse perspectives, particularly from individuals with lived experiences relevant to specific risk scenarios. The guidance also lacks a structured approach to exploring the full range of potential misuse scenarios across different contexts and risk areas. Finally, the guidance does not mention measuring absolute versus marginal risks (ie., how much total misuse risk a model poses in a specific context versus how much marginal risk it poses compared to existing tools). These gaps limit the effectiveness of the proposed risk measurement approach in capturing the full complexity of AI system interactions with human users and broader societal contexts.

Specific recommendations for improving socio-technical approach

The NIST guidance in Practice 1.3 suggests estimating model capabilities by comparison to existing models, but provides little direction on how to conduct these comparisons effectively. To improve this, NIST could incorporate the concept of “available affordances.” This concept emphasizes that an AI system’s risk profile depends not just on its absolute capabilities, but also on the environmental resources and opportunities for affecting the world that are available to it.

Additionally, Kapoor et al. (2024) emphasize the importance of assessing the marginal risk of open foundation models compared to existing technologies or closed models. This approach aligns with a comprehensive socio-technical perspective by considering not just the absolute capabilities of AI systems, but also how they interact with existing technological and social contexts. For instance, when evaluating cybersecurity risks, they suggest considering both the potential for open models to automate vulnerability detection and the existing landscape of cybersecurity tools and practices. This marginal risk framework helps to contextualize the impact of open foundation models within broader socio-technical systems, providing a more nuanced understanding of their potential benefits and risks. 

NIST could recommend that organizations assess both the absolute capabilities of their AI systems and the affordances available to them in potential deployment contexts. This approach would provide a more comprehensive view of potential risks than simply comparing models in isolation. For instance, the guidance could suggest evaluating how a system’s capabilities might change when given access to different interfaces, actuators, or information sources.

Similarly, Weidinger et al. (2023) argue that while quantitative benchmarks are important, they are insufficient for comprehensive safety evaluation. They suggest complementing quantitative measures with qualitative assessments, particularly at the human interaction and systemic impact layers. NIST could enhance its guidance by providing more specific recommendations for integrating qualitative evaluation methods alongside quantitative benchmarks.

NIST should acknowledge potential implementation challenges with a comprehensive socio-technical approach. Organizations may struggle to create benchmarks that accurately reflect real-world misuse scenarios, particularly given the rapid evolution of AI capabilities and threat landscapes. Maintaining up-to-date benchmarks in a fast-paced field presents another ongoing challenge. Additionally, organizations may face difficulties in translating quantitative assessments into actionable risk management strategies, especially when dealing with novel or complex risks. NIST could enhance the guidance by providing strategies for navigating these challenges, such as suggesting collaborative industry efforts for benchmark development or offering frameworks for scalable testing approaches.

OpenAI‘s approach of using human participants to evaluate AI capabilities provides both a useful model for more comprehensive evaluation and an example of quantification challenges. While their evaluation attempted to quantify biological risk increase from AI access, they found that, as they put it, “Translating quantitative results into a meaningfully calibrated threshold for risk turns out to be difficult.” This underscores the need for more research on how to set meaningful thresholds and interpret quantitative results in the context of AI safety.

2. Inconsistencies in Risk Management Language

There are instances where the guidance uses varying levels of strength in its recommendations, particularly regarding when to halt or adjust development. For example, Practice 2.2 recommends to “Plan to adjust deployment or development strategies if misuse risks rise to unacceptable levels,” while Practice 3.2 uses stronger language, suggesting to “Adjust or halt further development until the risk of model theft is adequately managed.” This variation in language could lead to confusion and potentially weaker implementation of risk management strategies.

Furthermore, while the guidance emphasizes the importance of managing risks before deployment, it does not provide clear criteria for what constitutes “adequately managed” risk, particularly in the context of development rather than deployment. More consistent and specific language around these critical decision points would strengthen the guidance’s effectiveness in promoting responsible AI development.

Specific recommendations for strengthening language on halting development for unmanageable risks

To address the inconsistencies noted above, we suggest the following changes:

1. Standardize the language across the document to consistently use strong phrasing such as “Adjust or halt further development” when discussing responses to unacceptable levels of risk. 

The current guidance uses varying levels of strength in its recommendations regarding development adjustments. For instance, Recommendation 4 of Practice 2.2 uses the phrase “Plan to adjust deployment or development strategies,” while Recommendation 3 of Practice 3.2 more strongly suggests to “Adjust or halt further development.” Consistent language would emphasize the critical nature of these decisions and reduce potential confusion or weak implementation of risk management strategies. This could be accomplished by changing the language of Practice 2.2, Recommendation 4 to “Plan to adjust or halt further development or deployment if misuse risks rise to unacceptable levels before adequate security and safeguards are available to manage risk.”

The need for stronger language regarding halting development is reflected both in NIST’s other work and in commitments that many frontier AI developers have publicly agreed to. For instance, the NIST AI Risk Management Framework, section 1.2.3 (Risk Prioritization), suggests: “In some cases where an AI system presents the highest risk – where negative impacts are imminent, severe harms are actually occurring, or catastrophic risks are present – development and deployment should cease in a safe manner until risks can be sufficiently mitigated.” Further, the AI Seoul Summit frontier AI safety commitments explicitly state that organizations should “set out explicit processes they intend to follow if their model or system poses risks that meet or exceed the pre-defined thresholds.” Importantly, these commitments go on to specify that “In the extreme, organisations commit not to develop or deploy a model or system at all, if mitigations cannot be applied to keep risks below the thresholds.” 

2. Add to the list of transparency documentation for Practice 2.2 the following: “A decision-making framework for determining when risks have become truly unmanageable, considering factors like the severity of potential harm, the likelihood of the risk materializing, and the feasibility of mitigation strategies.”

While the current guidance emphasizes the importance of managing risks before deployment (e.g., in Practice 5.3), it does not provide clear criteria for what constitutes “adequately managed” risk, particularly in the context of development rather than deployment. A decision-making framework would provide clearer guidance on when to take the serious step of halting development. This addition would help prevent situations where development continues despite unacceptable risks due to a lack of clear stopping criteria. This recommendation aligns with the approach suggested by Alaga and Schuett (2023) in their paper on coordinated pausing, where they emphasize the need for clear thresholds and decision criteria to determine when AI development should be halted due to unacceptable risks. 

3. Gaps in Model Development Safeguards

The guidance’s treatment of safeguards, particularly those related to model development, lacks sufficient detail to be practically useful. This is most evident in Appendix B, which lists example safeguards. While this appendix is a valuable addition, the safeguards related to model training (“Improve the model’s training”) are notably lacking in detail compared to the safeguards around model security and detecting misuse.

While the guidance covers many aspects of risk management comprehensively, especially model security, it does not provide enough specific recommendations for technical approaches to building safer models during the development phase. This gap could limit the practical utility of the guidance for AI developers seeking to implement safety measures from the earliest stages of model creation.

Specific recommendations for additional safeguards for model development

For some safeguards, we recommend that the misuse risk guidance explicitly reference relevant sections of NIST 600-1, the Generative Artificial Intelligence Profile. Specifically, the GAI profile offers more comprehensive guidance on data-related and monitoring safeguards. For instance, the profile emphasizes documenting training data curation policies (MP-4.1-004) and establishing policies for data collection, retention, and quality (MP-4.1-005), which are crucial for managing misuse risk from the earliest stages of development. Additionally, the profile suggests implementing real-time monitoring processes for analyzing generated content performance and trustworthiness characteristics (MG-3.2-006), which could significantly enhance ongoing risk management during development. These references to the GAI Profile on model development safeguards could take the form of an additional item in Appendix B, or be incorporated into the relevant sections earlier in the guidance.

Beyond pointing to the model development safeguards included in the GAI Profile, we also recommend expanding Appendix B to include further safeguards for the model development phase. Both the GAI Profile and the current misuse risk guidance lack specific recommendations for two key model development safeguards: iterative safety testing throughout development and staged development/release processes. Below are two proposed additions to Appendix B:

SafeguardPossible Implementation Methods
Implement iterative safety testing throughout development.* Develop and continuously update a comprehensive suite of safety tests covering identified risk areas.

* Establish quantitative safety benchmarks and ensure the model meets predefined thresholds before progressing to next development stages.

* Conduct regular adversarial testing, updating the test suite based on discovered vulnerabilities or emerging threats.
Consider a staged development and release process.* Define clear safety criteria that must be met before advancing to each subsequent stage of model development or deployment.

* Implement a phased release strategy, incrementally increasing model capabilities or access only after thorough safety evaluations at each stage.

* If possible, maintain the capability to rapidly revert to previous versions or restrict access if safety issues are identified post-release.

The proposed safeguard “Implement iterative safety testing throughout development” addresses the current guidance’s limited detail on model training and development safeguards. This approach aligns with Barrett, et al.’s AI Risk-Management Standards Profile for General-Purpose AI Systems and Foundation Models (the “GPAIS Profile”)’s emphasis on proactive and ongoing risk assessment. Specifically, the Profile recommends identifying “GPAIS impacts…and risks (including potential uses, misuses, and abuses), starting from an early AI lifecycle stage and repeatedly through new lifecycle phases or as new information becomes available” (Barrett et al., 2023, p. 19). The GPAIS Profile further suggests that for larger models, developers should “analyze, customize, reanalyze, customize differently, etc., then deploy and monitor” (Barrett et al., 2023, p. 19), where “analyze” encompasses probing, stress testing, and red teaming. This iterative safety testing would integrate safety considerations throughout development, aligning with the guidance’s emphasis on proactive risk management and anticipating potential misuse risk.

Similarly, the proposed safeguard “Establish a staged development and release process” addresses a significant gap in the current guidance. While Practice 5.1 discusses pre-deployment risk assessment, it lacks a structured approach to incrementally increasing model capabilities or access. Solaiman et al. (2023) propose a “gradient of release” framework for generative AI, a phased approach to model deployment that allows for iterative risk assessment and mitigation. This aligns with the guidance’s emphasis on ongoing risk management and could enhance the ‘margin of safety’ concept in Practice 5.3. Implementing such a staged process would introduce multiple risk assessment checkpoints throughout development and deployment, potentially improving safety outcomes.

Conclusion

NIST’s guidance on “Managing Misuse Risk for Dual-Use Foundation Models” represents a significant step forward in establishing robust practices for mitigating catastrophic risks associated with advanced AI systems. The document’s emphasis on comprehensive risk assessment, transparent decision-making, and proactive safeguards demonstrates a commendable commitment to responsible AI development. However, to more robustly contribute to risk mitigation, the guidance must evolve to address key challenges, including a stronger approach to measuring misuse risk, consistent language on halting development, and more detailed model development safeguards.

As the science of AI risk assessment advances, this guidance should be recursively updated to address emerging risks and incorporate new best practices. While voluntary guidance is crucial, it is important to recognize that it cannot replace the need for robust policy and regulation. A combination of industry best practices, government oversight, and international cooperation will be necessary to ensure the responsible development of high-risk AI systems.

We appreciate the opportunity to provide input on this important document. FAS stands ready to continue assisting NIST in refining and implementing this guidance, as well as in developing further resources for responsible AI development. We believe that close collaboration between government agencies, industry leaders, and civil society organizations is key to realizing the benefits of AI while effectively mitigating its most serious risks.

The U.S. Bioeconomy needs biomass, but what is it and how do we use it?

In the quest for sustainable energy and materials, biomass emerges as a key player, bridging the gap between the energy sector and the burgeoning U.S. and regional bioeconomies (microbioeconomies). Despite often being pigeonholed as fuel for energy production, biomass holds far-reaching potential that extends beyond combustion. Identifying sustainable biomass feedstocks that are easily accessible and consistent in their makeup could be a game-changer to help regions unlock their bioeconomy potential and support scientific innovations toward more environmentally sustainable materials and chemicals.

Biomass is defined as “any organic matter that is available on a renewable or recurring basis, including agricultural crops and trees, wood and wood residues, plants, algae, grasses, animal manure, municipal residues, and other residue materials” by the Foundation for Food & Agriculture Research (FFAR). Biomass has mainly been viewed by the public as a source of energy through burning or for chemical conversion into biofuels, encouraged by federal incentive programs, including those from the United States Department of Agriculture (USDA) and the Department of Energy (DOE). However, aside from burning or conversion for biofuel, biomass can undergo a complex process of chemical or biological breakdown and be transformed into various building block components that can be used for a wide range of biotechnology applications.

Once the biomass is broken down into its functional components it can be used as a feedstock, which is a “resource used as the basis for manufacturing another product. [Often], . . . a source of carbon to produce an array of chemicals.” For example, lignocellulosic biomass, plant or plant-based materials not used for food, can be hydrolyzed into sugars, which serve as precursors for bio-based chemicals and materials. This allows for new, environmentally sustainable chemicals for use in biotechnology and biomanufacturing applications, thus positioning biomass as a cornerstone resource of the U.S. bioeconomy. In addition to biochemical production, biomass, and feedstock are used in the bioeconomy in bioplastics and biomaterials. To push the U.S. bioeconomy toward environmental sustainability, it is critical to begin building programmatic and physical infrastructure to harness biomass, which is ultimately converted into feedstock using biotechnology applications and used in the biomanufacturing process to create everyday materials for the public.

Not All Biomass is Used for Energy, or Sustainably Produced

While biomass holds promise as a renewable energy source, not all biomass is used for energy, and not all of it is sustainable. Corn is a consistent poster child of the biomass and biofuel industry as a sustainable way to power combustion engines. Yet, the growth of corn relies heavily on the extensive use of fertilizers and pesticides, which can lead to soil erosion, water pollution, and habitat degradation. Depending on how a company conducts its Life Cycle Assessment and Carbon Intensity of its supplies, corn may not truly represent an environmentally sustainable biomass solution.

However, it is tough to beat the productivity of corn and its ability to be used for various biomass and atmospheric carbon capture applications. For example, corn stover, the byproduct stalks and leaves leftover from harvest, can be broken down into biochar for reuse in soil nutrient replenishment and is excellent for carbon sequestration from the atmosphere. Carbon sequestration is the “storage of carbon dioxide (CO2) after it is captured from industrial facilities and power plants or removed directly from the atmosphere”. One California-based company, Charm, is harvesting the leftover corn leaves, husks, and stalks and breaking them down into bio-oil which is stored deep underground in EPA-regulated wells. This bio-oil now contains sequestered carbon from corn crops and locks it away for thousands of years thus allowing a simple, and effective, way to use farm waste materials as carbon sequestration machines. This corn stover may otherwise have been burned or left to rot, releasing its carbon into the atmosphere.

As the DOE Bioenergy Technology Office puts it:

“Crops can serve as a carbon sink, capturing CO2 from the atmosphere. During CO2 fermentation, some of this recycled CO2 can be harnessed for various applications, such as carbon capture and storage, where it can be compressed or stored underground. The convergence of lower input costs, improvement of ethanol production, and CO2 management showcases a sector poised to contribute to a sustainable and prosperous future.”

Read more

While corn remains the leader of the biomass pack for usage in atmospheric carbon capture, it is necessary to begin broadening the biomass portfolio into other crops, both conventional and not, that can offer similar carbon capture and biomass benefits for industrial energy and feedstock use. The introduction of more sustainable biomass inputs, like waste hulls from almond crops, winter oilseed crops, or macro/microalgae, might be the key to introducing options for industries to use for their biomanufacturing processes. To make the U.S. bioeconomy more environmentally sustainable, it will be necessary to prioritize the use of biomass that is sustainable for the creation of bio-based products. To achieve this, policymakers and industry leaders can come together to understand the physical infrastructure needed to support the processing and utilization of sustainable biomass.

Biomass in Carbon Accounting

A contentious issue in biomass utilization revolves around carbon accounting, particularly concerning the differentiation between biogenic and fossil fuel carbon. Biogenic carbon originates from recently living organisms and is part of the natural carbon cycle, while fossil fuel carbon is derived from the remains of extinct carbon-rich plants and animals that decomposed as they were compressed and heated in the ground. When burned, this fossil fuel carbon is released into the atmosphere, contributing to greenhouse gas emissions. The current carbon accounting frameworks often conflate these distinctions, leading to misconceptions and controversies surrounding biomass utilization’s carbon neutrality claims. Addressing this ambiguity is crucial for aligning policy frameworks with scientific realities and ensuring informed decision-making in biomass utilization. As microbioeconomies grow, any confusion about biogenic versus fossil fuel carbon could become another barrier to entry for burgeoning bioeconomy opportunities.

Environmental and Economic Impacts

All across rural America, local economic developers are seeing more biomass conversion projects come to their communities, which offers the chance to boost economic revenues from turning biomass into energy, fuel, or feedstock and creates a broad spectrum of jobs for the area. To capitalize on this, increased bioliteracy on how growing biomass could offer additional financial support for farmers, provide energy to heat communities, and become feedstock for the biotechnology and biomanufacturing industry is critical. The more we activate and connect parts of America that are not located in existing high-density technology hubs, the better prepared these communities will be when biomass projects look to settle in those places. For example, woody biomass was emphasized throughout the DOE 2023 Billion Ton report as an important biomass source for fuel and energy production, yet the process of getting the timber and woody biomass out of the forest and into processing facilities is slow to launch due to concerns over environmental impacts.

While environmental impacts are valid and of great concern in some ecosystems around the U.S., harvesting wood waste and timber in areas that are primed for increased forest fire risk might be a sustainable option for protecting forest ecosystems while also benefiting the community for energy and heat concerns. The USDA Wildland Fire Mitigation and Management Commission discussed the need for further research into forest biomass to understand how it can generate profit for communities with otherwise waste materials while also mitigating fire risk. One recommendation stated the need for “Increase[d] resources for programs to help private landowners dispose of woody biomass”. Although several programs assist landowners in this effort, there are still significant expenses involved. These costs may discourage landowners from conducting fuel reduction activities, leading them to either burn the material, which can harm air quality, or leave it on the land, potentially worsening wildfire severity in case of an outbreak. There’s a necessity for initiatives supporting the disposal of biomass, including wood chipping, hauling, and its utilization. These initiatives could receive support from USDA Rural Development and should explore ways to encourage landowners to sustainably harvest their woody biomass for both financial incentives and for reducing wildfire risk.

Billion Ton Report Recommendations

According to the 2023 DOE Billion-Ton Report, the U.S. used 342 million tons of biomass for energy and bio-based chemicals in 2022. The top biomass source for biofuels is corn, with the U.S. producing nearly 150 tons per year of corn that is converted to ethanol. Whereas ~140 million tons of forestry/wood and wood waste (woody biomass) are used for heat and power purposes. However, many other types of biomass exist and are used for various purposes including transportation or industrial and electrical power. Below is an abbreviated list, based on the Billion-Ton Report, of common biomass examples and some of their uses.

The recent Billion Ton report makes it clear that the U.S. has plenty of available biomass for use in the production of biofuel, heat/energy, and bio-based products, and that further utilization of biomass in these applications and in biotechnology and biomanufacturing industries could be a way forward to mitigate climate change and improve sustainability of the U.S. bioeconomy. To change the mindset of biomass as more than corn grown for biofuel, it will take a concerted effort by the federal agencies involved in funding biomass use projects, like the DOE, USDA, National Science Foundation, and the Department of Defense, to communicate to farmers that growing biomass can be profitable. It will also take a joint effort from the federal government and local governments to build pilot and commercial scale facilities to begin processing diverse biomass.

Overall, there is immense promise in connecting biomass growers, processors, and bio-powered industries. It allows the players in the U.S. bioeconomy to think critically about their waste outputs and how to harness biomass as the key to unlocking a future where all communities, be they rural or urban, benefit from our national bioeconomy. You can learn more about biomass use in biotechnology and biomanufacturing at our upcoming webinar May 1st at 10 AM ET.

Working with academics: A primer for U.S. government agencies

Collaboration between federal agencies and academic researchers is an important tool for public policy. By facilitating the exchange of knowledge, ideas, and talent, these partnerships can help address pressing societal challenges. But because it is rarely in either party’s job description to conduct outreach and build relationships with the other, many important dynamics are often hidden from view. This primer provides an initial set of questions and topics for agencies to consider when exploring academic partnership.

Why should agencies consider working with academics?

What considerations may arise when working with academics?

Table (Of Contents)
Characteristics of discussed collaborative structures
StructurePrimary needPotential mechanismsStructural complexityLevel of effort
Informal advisingKnowledge >> CapacityAd-hoc engagement; formal consulting agreementLowOccasional work, over the short- to long-term
Study groupsKnowledge > CapacityInformal working group; formal extramural awardModerateOccasional to part-time work, over the short- to medium-term
Collaborative researchCapacity ~= KnowledgeInformal research partnership, formal grant, or cooperative agreement / contractVariablePart-time work, over the medium- to long-term
Short-term placementsCapacity > KnowledgeIPA, OPM Schedule A(r), or expert contract; either ad-hoc or through a formal programModeratePart- to full-time work, over a short- to medium-term
Long-term rotationsCapacity >> KnowledgeIPA, OPM Schedule A(r), or SGE designation; typically through a formal programHighFull-time work, over a medium- to long-term
BOX 1. Key academic considerations
Academic career stages.

Academic faculty progress through different stages of professorship — typically assistant, associate, and full — that affect their research and teaching expectations and opportunities. Assistant professors are tenure-track faculty who need to secure funding, publish papers, and meet the standards for tenure. Associate professors have job security and academic freedom, but also more mentoring and leadership responsibilities; associate professors are typically tenured, though this is not always the case. Full professors are senior faculty who have a high reputation and recognition in their field, but also more demands for service and supervision. The nature of agency-academic collaboration may depend on the seniority of the academic. For example, junior faculty may be more available to work with agencies, but primarily in contexts that will lead to traditional academic outputs; while senior faculty may be more selective, but their academic freedom will allow for less formal and more impact-oriented work.

Soft vs. hard money positions.

Soft money positions are those that depend largely or entirely on external funding sources, typically research grants, to support the salary and expenses of the faculty. Hard money positions are those that are supported by the academic institution’s central funds, typically tied to more explicit (and more expansive) expectations for teaching and service than soft-money positions. Faculty in soft money positions may face more pressure to secure funding for research, while faculty in hard money positions may have more autonomy in their research agenda but more competing academic activities. Federal agencies should be aware of the funding situation of the academic faculty they collaborate with, as it may affect their incentives and expectations for agency engagement.

Sabbatical credits.

A sabbatical is a period of leave from regular academic duties, usually for one or two semesters, that allows faculty to pursue an intensive and unstructured scope of work — this can include research in their own field or others, as well as external engagements or tours of service with non-academic institutions . Faculty accrue sabbatical credits based on their length and type of service at the university, and may apply for a sabbatical once they have enough credits. The amount of salary received during a sabbatical depends on the number of credits and the duration of the leave. Federal agencies may benefit from collaborating with academic faculty who are on sabbatical, as they may have more time and interest to devote to impact-focused work.

Consulting/outside activity limits.

Consulting limits & outside activity limits are policies that regulate the amount of time that academic faculty can spend on professional activities outside their university employment. These policies are intended to prevent conflicts of commitment or interest that may interfere with the faculty’s primary obligations to the university, such as teaching, research, and service, and the specific limits vary by university. Federal agencies may need to consider these limits when engaging academic faculty in ongoing or high-commitment collaborations.

9 vs. 12 month salaries.

Some academic faculty are paid on a 9-month basis, meaning that they receive their annual salary over nine months and have the option to supplement their income with external funding or other activities during the summer months. Other faculty are paid on a 12-month basis, meaning that they receive their annual salary over twelve months and have less flexibility to pursue outside opportunities. Federal agencies may need to consider the salary structure of the academic faculty they work with, as it may affect their availability to engage on projects and the optimal timing with which they can do so.

Advisory relationships consist of an academic providing occasional or periodic guidance to a federal agency on a specific topic or issue, without being formally contracted or compensated. This type of collaboration can be useful for agencies that need access to cutting-edge expertise or perspectives, but do not have a formal deliverable in mind.

Academic considerations

Regulatory & structural considerations

Box 2. Key structural considerations
Regulatory guidance.

Federal agencies and academic institutions are subject to various laws and regulations that affect their research collaboration, and the ownership and use of the research outputs. Key legislation includes the Federal Advisory Committee Act (FACA), which governs advisory committees and ensures transparency and accountability; the Federal Acquisition Regulation (FAR), which controls the acquisition of supplies and services with appropriated funds; and the Federal Grant and Cooperative Agreement Act (FGCAA), which provides criteria for distinguishing between grants, cooperative agreements, and contracts. Agencies should ensure that collaborations are structured in accordance with these and other laws.

Contracting mechanisms.

Federal agencies may use various contracting mechanisms to engage researchers from non-federal entities in collaborative roles. These mechanisms include the IPA Mobility Program, which allows the temporary assignment of personnel between federal and non-federal organizations; the Experts & Consultants authority, which allows the appointment of qualified experts and consultants to positions that require only intermittent and/or temporary employment; and Cooperative Research and Development Agreements (CRADAs), which allow agencies to enter into collaborative agreements with non-federal partners to conduct research and development projects of mutual interest.

University Office of Sponsored Programs.

Offices of Sponsored Programs are units within universities that provide administrative support and oversight for externally funded research projects. OSPs are responsible for reviewing and approving proposals, negotiating and accepting awards, ensuring compliance with sponsor and university policies and regulations, and managing post-award activities such as reporting, invoicing, and auditing. Federal agencies typically interact with OSPs as the authorized representative of the university in matters related to sponsored research.

Non-disclosure agreements.

When engaging with academics, federal agencies may use NDAs to safeguard sensitive information. Agencies each have their own rules and procedures for using and enforcing NDAs involving their grantees and contractors. These rules and procedures vary, but generally require researchers to sign an NDA outlining rights and obligations relating to classified information, data, and research findings shared during collaborations.

A study group is a type of collaboration where an academic participates in a group of experts convened by a federal agency to conduct analysis or education on a specific topic or issue. The study group may produce a report or hold meetings to present their findings to the agency or other stakeholders. This type of collaboration can be useful for agencies that need to gather evidence or insights from multiple sources and disciplines with expertise relevant to their work.

Academic considerations

Regulatory & structural considerations

Case study

In 2022, the National Science Foundation (NSF) awarded the National Bureau of Economic Research (NBER) a grant to create the EAGER: Place-Based Innovation Policy Study Group. This group, led by two economists with expertise in entrepreneurship, innovation, and regional development — Jorge Guzman from Columbia University and Scott Stern from MIT — aimed to provide “timely insight for the NSF Regional Innovation Engines program.” During Fall 2022, the group met regularly with NSF staff to i) provide an assessment of the “state of knowledge” of place-based innovation ecosystems, ii) identify the insights of this research to inform NSF staff on design of their policies, and iii) surface potential means by which to measure and evaluate place-based innovation ecosystems on a rigorous and ongoing basis. Several of the academic leads then completed a paper synthesizing the opportunities and design considerations of the regional innovation engine model, based on the collaborative exploration and insights developed throughout the year. In this case, the study group was structured as a grant, with funding provided to the organizing institution (NBER) for personnel and convening costs. Yet other approaches are possible; for example, NSF recently launched a broader study group with the Institute for Progress, which is structured as a no-cost Other Transaction Authority contract.

Active collaboration covers scenarios in which an academic engages in joint research with a federal agency, either as a co-investigator, a subrecipient, a contractor, or a consultant. This type of collaboration can be useful for agencies that need to leverage the expertise, facilities, data, or networks of academics to conduct research that advances their mission, goals, or priorities.

Academic considerations

Regulatory & structural considerations

Case studies

External collaboration between academic researchers and government agencies has repeatedly proven fruitful for both parties. For example, in May 2020, the Rhode Island Department of Health partnered with researchers at Brown University’s Policy Lab to conduct a randomized controlled trial evaluating the effectiveness of different letter designs in encouraging COVID-19 testing. This study identified design principles that improved uptake of testing by 25–60% without increasing cost, and led to follow-on collaborations between the institutions. The North Carolina Office of Strategic Partnerships provides a prime example of how government agencies can take steps to facilitate these collaborations. The office recently launched the North Carolina Project Portal, which serves as a platform for the agency to share their research needs, and for external partners — including academics — to express interest in collaborating. Researchers are encouraged to contact the relevant project leads, who then assess interested parties on their expertise and capacity, extend an offer for a formal research partnership, and initiate the project.

Short-term placements allow for an academic researcher to work at a federal agency for a limited period of time (typically one year or less), either as a fellow, a scholar, a detailee, or a special government employee. This type of collaboration can be useful for agencies that need to fill temporary gaps in expertise, capacity, or leadership, or to foster cross-sector exchange and learning.

Academic considerations

Regulatory & structural considerations

Case studies

Various programs exist throughout government to facilitate short-term rotations of outside experts into federal agencies and offices. One of the most well-known examples is the American Association for the Advancement of Science (AAAS) Science & Technology Policy Fellowship (STPF) program, which places scientists and engineers from various disciplines and career stages in federal agencies for one year to apply their scientific knowledge and skills to inform policy making and implementation. The Schedule A(r) hiring authority tends to be well-suited for these kinds of fellowships; it is used, for example, by the Bureau of Economic Analysis to bring on early career fellows through the American Economic Association’s Summer Economics Fellows Program. In some circumstances, outside experts are brought into government “on loan” from their home institution to do a tour of service in a federal office or agency; in these cases, the IPA program can be a useful mechanism. IPAs are used by the National Science Foundation (NSF) in its Rotator Program, which brings outside scientists into the agency to serve as temporary Program Directors and bring cutting-edge knowledge to the agency’s grantmaking and priority-setting. IPA is also used for more ad-hoc talent needs; for example, the Office of Evaluation Sciences (OES) at GSA often uses it to bring in fellows and academic affiliates.

Long-term rotations allow an academic to work at a federal agency for an extended period of time (more than one year), either as a fellow, a scholar, a detailee, or a special government employee. This type of collaboration can be useful for agencies that need to recruit and retain expertise, capacity, or leadership in areas that are critical to their mission, goals, or priorities.

Academic considerations

Regulatory & structural considerations

Case study

One example of a long-term rotation that draws experts from academia into federal agency work is the Advanced Research Projects Agency (ARPA) Program Manager (PM) role. ARPA PMs — across DARPA, IARPA, ARPA-E, and now ARPA-H — are responsible for leading high-risk, high-reward research programs, and have considerable autonomy and authority in defining their research vision, selecting research performers, managing their research budget, and overseeing their research outcomes. PMs are typically recruited from academia, industry, or government for a term of three to five years, and are expected to return to their academic institutions or pursue other career opportunities after their term at the agency. PMs coming from academia or nonprofit organizations are often brought on through the IPA mobility program, and some entities also have unique term-limited, hiring authorities for this purpose. PMs can also be hired as full government employees; this mechanism is primarily used for candidates coming from the private sector.

Unlocking American Competitiveness: Understanding the Reshaped Visa Policies under the AI Executive Order

The looming competition for global talent has brought forth a necessity to evaluate and update the policies concerning international visa holders in the United States. Recognizing this, President Biden has directed various agencies to consider policy changes aimed at improving processes and conditions for legal foreign workers, students, researchers, and scholars through the upcoming AI Executive Order (EO). The EO recognizes that attracting global talent is vital for continued U.S. economic growth and enhancing competitiveness. 

Here we offer a comprehensive analysis of potential impacts and beneficiaries under several key provisions brought to attention by this EO. The provisions considered herein are categorized under six paramount categories: domestic revalidation for J-1 and F-1 Visas; modernization of H-1B Visa Rules; updates to J-1 Exchange Visitor Skills List; the introduction of Global AI Talent Attraction Program; issuing an RFI to seek updates to DOL’s Schedule A; and policy manual updates for O-1A, EB-1, EB-2 and International Entrepreneur Rule. Each policy change carries the potential to advance America’s ability to draw in international experts that hugely contribute to our innovation-driven economy.

Domestic Revalidation for J-1 and F-1 Visas

The EO directive on expanding domestic revalidation for J-1 research scholars and F-1 STEM visa students simplifies and streamlines the renewal process for a large number of visa holders. 

There are currently approximately 900,000 international students in the US, nearly half of whom are enrolled in STEM fields. This policy change has the potential to impact almost 450,000 international students, including those who partake in optional practical training (OPT). The group of affected individuals consists greatly of scholars with advanced degrees as nearly half of all STEM PhDs are awarded to international students.

One of the significant benefits offered by this EO directive is the reduction in processing times and associated costs. In addition, it improves convenience for these students and scholars. For example, many among the several hundreds of thousands of STEM students will no longer be obligated to spend excessive amounts on travel to their home country for a 10-minute interview at an Embassy.

Aside from saving costs, this directive also allows students to attend international conferences more easily and enjoy hassle-free travel without being worried about having to spend a month away from their vital research waiting for visa renewal back home.

Expanding domestic revalidation to F and J visa holders was initially suggested by the Secure Borders and Open Doors Advisory Committee in January 2008, indicating its long-standing relevance and importance. By implementing it, we not only enhance efficiency but also foster a more supportive environment for international students contributing significantly to our scientific research community.

Modernization of H-1B Visa Rules

The EO directive to update the rules surrounding H-1B visas would positively impact the over 500k H-1B visa holders. The Department of Homeland Security recently released a Notice of Proposed Rulemaking to reform the H-1B visa rules. It would allow these visa holders to easily transition into new jobs, have more predictability and certainty in the renewal process and more flexibility or better opportunities to apply their skills, and allow entrepreneurs to more effectively access the H-1B visa. Last year, 206,002 initial and continuing H-1Bs were issued. The new rules would apply to similar numbers in FY2025. But what amplifies this modification’s impact is its potential crossover with EB-1 and EB-2 petitioners waiting on green cards—currently at over 400k petitions. 

Additionally, the modernization would address the issue of multiple applications per applicant. This has been a controversial issue in the H-1B visa program as companies would often file multiple registrations for the same employee, thus increasing the exhaustion rate of yearly quotas, thereby reducing chances for others. This modernization could potentially address this problem by introducing clear rules or restrictions on the number of applications per applicant. USCIS recently launched fraud investigations into several companies engaging in this practice.

Updates to J-1 Exchange Visitor Skills List

The EO directive to revamp the skills list will synchronize with evolving global labor market needs. Nearly 37k of the J-1s issued in 2022 went to professors, research scholars and short term scholars, hailing from mainly China and India (nearly 40% of all). Therefore, this update not only expands opportunities available to these participants but also tackles critical skill gaps within fields like AI in the U.S. Once the J-1 skills list is updated to meet the realities of the global labor market today, it will allow thousands of additional high skilled J-1 visa holders to apply for other visa categories immediately, without spending 2-years in their countries of origin, as laid out in this recent brief by the Federation of American Scientists.

Global AI Talent Attraction Program

Recognizing AI talent is global, the EO directive on using the State Department’s public diplomacy function becomes strategically important. By hosting overseas events to appeal to such crucial talent bases abroad, we can effectively fuel the U.S. tech industry’s unmet demand that has seen a steep incline over recent years. While 59% of the top-tier AI researchers work in the U.S., only 20% of them received their undergraduate degree in the U.S. Only 35% of the most elite (top 0.5%) of AI researchers received their undergraduate degree in the U.S., but 65% of them work in the U.S. The establishment of a Global AI Talent Attraction program by the State Department will double down on this uniquely American advantage.

Schedule A Update & DOL’s RFI

Schedule A is a list of occupations for which the U.S. Department of Labor (DOL) has determined there are not sufficient U.S. workers who are able, willing, qualified and available. Foreign workers in these occupations can therefore have a faster process to receive a Green Card because the employer does not need to go through the Labor Certification process. Schedule A Group I was created in 1965 and has remained unchanged since 1991. If the DOL were to update Schedule A, it would impact foreign workers and employers in several ways depending on how the list changes:

Foreign workers with occupations that are on Schedule A do not have to go through the PERM (Program Electronic Review Management) labor certification process, a process that otherwise takes on average 300 days to complete. This is because Schedule A lists occupations for which the Department of Labor has already determined there are not sufficient U.S. workers who are able, willing, qualified and available. An updated Schedule A could cut PERM applications filed significantly down from current high volumes (over 86,000 already filed by the end of FY23 Q3). While the EO only calls for an RFI seeking information on the Schedule A List, this is a critical first step to an eventual update that is badly needed.

Policy Manual Updates for O-1A, EB-1, EB-2 and International Entrepreneur Rule

The EO’s directive to DHS to modernize pathways for experts in AI and other emerging technologies will have profound effects on the U.S. tech industry. Fields such as Artificial Intelligence (AI), Quantum computing, Biotechnology, etc., are increasingly crucial in defining global technology leadership and national security. As per the NSCAI report, the U.S. significantly lags behind in terms of AI expertise due to severe immigration challenges.

The modernization would likely include clarification and updates to the criteria of defining ‘extraordinary ability’ and ‘exceptional ability’ under O-1A, EB-1 and EB-2 visas, becoming more inclusive towards talents in emerging tech fields. For instance, the current ‘extraordinary ability’ category is restrictive towards researchers as it preferentially favors those who have received significant international awards or recognitions—a rarity in most early-stage research careers. Similarly, despite O-1A and EB-1 both designed for aliens with extraordinary ability, the criteria for EB-1 is more restrictive than O-1A and bringing both in line would allow a more predictable path for an O-1A holder to transition to an EB-1. Such updates also extend to the International Entrepreneur Rule, facilitating startup founders from critical technology backgrounds more straightforward access into the U.S. landscape.

Altogether, these updates could lead to a surge in visa applications under O-1A, EB-1, EB-2 categories and increase entrepreneurship within emerging tech sectors. In turn, this provision would bolster the U.S.’ competitive advantage globally by attracting top-performing individuals working on critical technologies worldwide.

Enhanced Informational Resources and Transparency

The directives in Section 4 instruct an array of senior officials to create informational resources that demystify options for experts in critical technologies intending to work in the U.S. The provision’s ramifications include:

Streamlining Visa Services 

This area of the order directly addresses immigration policy with a view to accelerating access for talented individuals in emerging tech fields. 

Using Discretionary Authorities to Support and Attract AI Talent

The EO’s directive to the Secretary of State and Secretary of Homeland Security to use discretionary authorities—consistent with applicable law and implementing regulations—to support and attract foreign nationals with special skills in AI seeking to work, study, or conduct research in the U.S. could have enormous implications. 

One way this provision could be implemented is through the use of public benefit parole. Offering parole to elite AI researchers who may otherwise be stuck in decades long backlogs (or are trying to evade authoritarian regimes) could see a significant increase in the inflow of intellectual prowess into the U.S. Public benefit parole is also the basis for the International Entrepreneur Rule. Given how other countries are actively poaching talent from the U.S. because of our decades long visa backlogs, creating a public benefit parole program for researchers in AI and other emerging technology areas could prove extremely valuable. These researchers could then be allowed to stay and work in the U.S. provided they are able to demonstrate (on an individual basis) that their stay in the U.S. would provide a significant public benefit through their AI research and development efforts.

Another potential utilization of this discretionary authority could be in the way of the Department of State issuing a memo announcing a one‐​time recapture of certain immigrant visa cap numbers to redress prior agency failures to issue visas. There is precedence for this as when the government openly acknowledged its errors that made immigrants from Western Hemisphere countries face longer wait times between 1968 and 1976 as it incorrectly charged Cuban refugees to the Western Hemisphere limitation. To remedy the situation, the government recaptured over 140,000 visas from prior fiscal years on its own authority, and issued them to other immigrants who were caught in the Western Hemisphere backlog. 

In the past, considerable quantities of green cards have gone unused due to administrative factors. Recapturing these missed opportunities could immediately benefit a sizable volume of immigrants, including those possessing AI skills and waiting for green card availability. For instance, if a hypothetical 300,000 green cards that were not allocated due to administrative failures are recaptured, it could potentially expedite the immigration process for a similar number of individuals. 

Finally, as a brief from the Federation of American Scientists stated earlier, it is essential that the Secretary of State and the Secretary of Homeland Security extend the visa interview waivers indefinitely, considering the significant backlogs faced by the State Department at several consular posts that are preventing researchers from traveling to the U.S. 

In August 2020, Secretary Pompeo announced that applicants seeking a visa in the same category they previously held would be allowed to get an interview waiver if their visa expired in the last 24 months. Before this, the expiration period for an interview waiver was only 12 months. In December 2020, just two days before this policy was set to expire, DOS extended it through the end of March 2021. In March, the expiration period was doubled again, from 24 months to 48 months and the policy extended through December 31, 2021. In September of 2021, DOS also approved waivers through the remainder of 2021 for applicants of F, M, and academic J visas from Visa Waiver Program countries who were previously issued a visa.

In December 2021, DOS extended its then-existing policies (with some minor modifications) through December 2022. Moreover, the interview waiver policy that individuals renewing a visa in the same category as a visa that expired in the preceding 48 months may be eligible for issuance without an interview was announced as a standing policy of the State Department, and added to the department’s Foreign Affairs Manual for consular officers.  In December 2022, DOS announced another extension of these policies, which are set to expire at the end of 2023. 

As the State Department recently noted: “These interview waiver authorities have reduced visa appointment wait times at many embassies and consulates by freeing up in-person interview appointments for other applicants who require an interview. Nearly half of the almost seven million nonimmigrant visas the Department issued in Fiscal Year 2022 were adjudicated without an in-person interview. We are successfully lowering visa wait times worldwide, following closures during the pandemic, and making every effort to further reduce those wait times as quickly as possible, including for first-time tourist visa applicants. Embassies and consulates may still require an in-person interview on a case-by-case basis and dependent upon local conditions.”

These changes would also benefit U.S. companies and research institutions, who often struggle to retain and attract international AI talent due to the lengthy immigration process and uncertain outcomes. In addition, exercising parole authority can open a new gateway for attracting highly skilled AI talent that might have otherwise chosen other countries due to the rigid U.S. immigration system. 

The use of such authorities can result in a transformational change for AI research and development in the U.S. However, all these outcomes entirely depend upon the actual changes made to existing policies—a task that many acknowledge will require serious thoughtfulness for walking a balance between remaining advantageously selective yet inclusive enough.

In summary, these provisions would carry massive impacts—enabling us to retain foreign talent vital across sectors including but not limited to education, technology and healthcare; all fuelling our national economic growth in turn.

Increasing Students Opportunity-to-Learn Through Better Data Systems

Research shows that giving students equitable opportunities to learn requires access to key inputs. These include, at a minimum: access to qualified, experienced, in-field, and effective teachers; a rich curriculum; adequate funding; support staff; up-to-date facilities; standards-based materials; and technology. Since the 1960s education scholars have argued that federal, state, and local policymakers should use evidence-based opportunity-to-learn (OTL) indicators to inform education improvement processes and decisions about educator recruitment and retention, targeted student-centered programming, and equitable resource allocation. The current availability of district-level relief funds, the restarting of state accountability systems, and a possible reauthorization of the federal Education Sciences Reform Act (ESRA), are unique policy openings for education leaders to innovate using OTL indicators, incorporate promising practices from existing reporting systems, and establish place-based measures that fit local needs.

Challenge and Opportunity

COVID-19 placed an enormous burden on our education system. Lost instruction, student absences, teacher shortages, school discipline, and the wavering mental health of our nation’s youth have all made headlines since the pandemic began. To address these challenges, policymakers, educators, parents, and community members need multiple data points—in addition to test scores—to both identify achievement and opportunity gaps and spotlight successful models. 

Luckily, a 2019 National Academies of Sciences study, in addition to several resources from the Department of Education and policy experts, demonstrate how OTL indicators can inform school, district, and systems-wide improvement. According to Stephen Elliot and Brendan Bartlett, OTL indicators “generally refer to inputs and processes within a school context necessary for producing student achievement of intended outcomes.” Such indicators can include those identified by the National Academies of Sciences in Table 1 and may also incorporate other indicators of school conditions and outcomes. When states, districts, and schools use various combinations of OTL indicators and disaggregate them by student subgroup, they can more accurately gauge and purposefully increase students’ opportunities to learn.

Table 1. OTL Indicators shared by the National Academies of Sciences
Academic readinessSelf-regulation skills
School engagementCourse performance
Test performanceOn-time graduation
Postsecondary readinessRacial, ethnic, and economic segregation
Access to high-quality pre-K programsEffective teaching
Rigorous courseworkCurricular breadth
Academic supportsSchool climate
Non-exlusionary discipline practicesIntegrated student support services
Source: National Academies of Sciences, Engineering, and Medicine. 2019. Monitoring Educational Equity. Washington, DC: The National Academies Press. https://doi.org/10.17226/25389.

OTL indicators can also provide information about the nature of the teaching and learning opportunities states, districts, and schools make available to students across the country. For example, if a state’s curriculum frameworks and assessments outline standards for science or career and technical education that requires laboratory work, computers, specialized courses, and teaching expertise—states and districts should know whether students have access to these resources.

Federal and Expert Support for OTL Indicators

Over the past two years the Department of Education (ED) released two key resources supporting OTL implementation:

Table 2. OTL Indicators shared by the Department of Education
Student chronic absenteeism ratesStudent discipline rates (e.g., in-and out-of-school suspensions, expulsions)
Data from student, staff and family surveysAccess to integrated support services (e.g., ratio of students to nurses, counselors, social workers)
Educator certification (e.g., National Board Certification) Educator experience
Educator effectiveness Educator chronic absenteeism and turnover rates
Educator supports (e.g., mentors, induction programs, professional development) Home and school Internet access and student device ratios (e.g., 1:1)
Quality of remote learning Educator access to PD for the effective use of technology
Advanced course participation and completion Culturally and linguistically responsive curriculum designs
Using diagnostic assessments Access to project-based, experiential learning opportunities
Source: U.S. Department of Education. (2021) ED COVID-19 Handbook Volume 2: Roadmap to Reopening Safely and Meeting All Students’ Needs.

In addition, several organizations released OTL-related resources describing different indicators and how they are being used to support student achievement. For example:

Ideas to Use Data to Increase Opportunities to Learn

Taken together, the resources above from ED and policy experts can facilitate the following local, state, and federal actions to increase the use of OTL indicators.

Supporting Student Opportunity to Learn through Local Data Systems

States and districts have broad flexibility to use American Rescue Plan Act funds to support student achievement—including “developing and implementing procedures and systems to improve the preparedness and response efforts of local educational agencies.” These systems could arguably include building data collection and reporting infrastructure to track OTL indicators, monitor student progress, and respond with evidence-based interventions. Instead of starting from scratch, states and districts can pull best practices from existing cradle-to-career models such as the Schott Foundation’s Loving Cities Index, or StriveTogether which track various forms of OTL data from a student’s early years (e.g., kindergarten readiness) through their entry into career paths (e.g., postsecondary enrollment).  School Systems can also adapt aspects of OTL indicators to show how they are meeting the needs of their students. For example, Houston Independent School District has an ESSER Spending Dashboard showing how much funding has been spent on educators, support staff, tutors, devices, programming, and physical health. 

Supporting Student Opportunity to Learn through State Accountability and Improvement and Reporting Systems  

At the state level, policymakers can help advance OTL indicators by using flexibility included in the Every Student Succeeds Act (ESSA) and further described by ED’s 2022 accountability guidance. For example, ESSA requires states to add at least one indicator of “school quality or student success” to their accountability systems. A number of states have responded by adding indicators of college and career readiness, extended-year graduation rates, suspension rates, school climate, and chronic absenteeism, which all provide information about the broader set of outcomes and opportunities that shape student achievement. For example, the District of Columbia amended its ESSA plan in 2022 to include academic growth, access to dual enrollment courses, and a five-year graduation rate. Many states also represent OTL data in accessible formats such as the school data dashboard in California, a parent dashboard in New York, School and District Profiles in Oregon, and school climate survey reports in Illinois. 

Supporting Student Opportunity to Learn through State and Federal Grant Programs

State and federal governments can also incorporate OTL indicators into reporting metrics for grantees. Specifically, state and federal government can solicit feedback on which indicators are most helpful to each program through public notices. By developing equity-centered measures with researchers, policymakers, and practitioners, federal agencies can help grantees build lasting data systems for reporting and continuous improvement. For example, the Full-Service Community School grant program went through negotiated rulemaking to reshape the program’s priorities and drew from suggestions submitted by policy experts to incorporate 13 reporting metrics for new grantees. To help make the collection less burdensome, agencies can also provide technical assistance and release guidance with existing data sources, best practices, and examples.

Supporting Student Opportunity to Learn through Education Sciences Reform Act (ESRA) Implementation and Reauthorization 

The federal government can help states and districts close opportunity gaps by assisting in the collection, reporting, validation, disaggregation, and analysis of OTL data through ESRA-funded programs. For example, states and districts can leverage technical assistance and research dissemination through the Regional Educational Laboratories (RELs), creating resources and providing further support through the Comprehensive Centers Program, and equipping the Statewide Longitudinal Data System (SLDS) program to aid in building state and local capacity in measuring students’ opportunity to learn. Officials at the Institute for Education Sciences (IES) can also point states and districts to existing models such as Kentucky’s Longitudinal Data System and Washington’s Indicators of Education System Health, which incorporate data across a student’s academic continuum to inform policy and practice. 

Conclusion

If state and local leaders are committed to supporting the “whole child,” then they need more than just outcome-based measures such as test scores or graduation rates (i.e., outputs). So much happens before students take a test or graduate. To improve outcomes, students, parents, teachers, and education stakeholders need better information about factors that contribute to student learning (i.e., inputs). For years federal, state, and local leaders have been assessing our students mainly to find the same persistent achievement gaps, which correlate heavily with race, ethnicity, and socioeconomic status. Expanding the use of OTL indicators also assess our federal, state, and local systems so they can find new opportunities for students to learn. 

Moving the Nation: The Role of Federal Policy in Promoting Physical Activity

Physical activity is one of the most powerful tools for promoting health and wellbeing. Movement is not only medicine—effective at treating a range of physical and mental health conditions—but it is also preventive medicine, because movement reduces the risk for many conditions ranging from cancer and heart disease to depression and Alzheimer’s disease. But rates of physical inactivity and sedentary behavior have remained high in the U.S. and worldwide for decades.

Engagement in physical activity is impacted by myriad factors that can be viewed from a social ecological perspective. This model views health and health behavior within the context of a complex interplay between different levels of influence, including individual, interpersonal, institutional, community, and policy levels. When it comes to healthy behavior such as physical activity, sustainable change is considered most likely when these levels of influence are aligned to support change. Every level of influence on physical activity within a social-ecological framework is directly or indirectly affected by federal policy, suggesting physical activity policy has the potential to bring about substantial changes in the physical activity habits of Americans. 

Every level of influence on physical activity within a social-ecological framework is directly or indirectly affected by federal policy, suggesting physical activity policy has the potential to bring about substantial changes in the physical activity habits of Americans.
FIGURE 1. Adapted from Heise, L., Elisberg, M., & Gottemoeller, M. (1999)

Why are federal physical activity policies needed?

Physical inactivity is recognized as a public health issue, having widespread impacts on health, longevity, and even the economy. Similar to other public health issues over past decades such as sanitation and tobacco use, federal policies may be the best way to coordinate large-scale changes involving cooperation between diverse sectors, including health care, transportation, environment, education, workplace, and urban planning. An active society requires the infrastructure, environment, and resources that promote physical activity. Federal policies can meet those needs by improving access, providing funding, establishing regulations, and developing programs to empower all Americans to move more. Policies also play an important role in removing barriers to physical activity, such as financial constraints and lack of safe spaces to move, that contribute to health disparities. With such a variety of factors impacting active lifestyles, physical activity policies must have inter-agency involvement to be effective.

What physical activity initiatives exist currently?

Analysis of publicly available information revealed that there are a variety of initiatives currently in place at the federal level, across several departments and agencies, aimed at increasing physical activity levels in the U.S. Information about each initiative was evaluated for their correspondence with levels of the social-ecological model, as summarized in the table. Note that it is possible the search that was conducted did not identify every relevant effort, thus there could be additional initiatives that are not included below.

Given the large number of groups with the shared goal of increasing physical activity in the nation, a memorandum of understanding (MOU) may help to promote coordination of goals and implementation strategies.

FIGURE 2. Agency roles
Department or AgencyExisting or Potential Role
Administration for Children and Families (ACF)ACF’s strategic goals include taking a “preventative and proactive approach to ensuring child, youth, family, and individual well-being.” Physical activity is a powerful preventative and proactive approach.
Administration for Community Living (ACL)ACL’s Health, Wellness, and Nutrition program addresses behavioral health, prevention of injuries and illness, and chronic disease self-management for aging and disability populations, all of which relate to physical activity, though physical activity is not directly addressed in the program’s goals.
Agency for Healthcare Research and Quality (AHRQ)AHRQ moves scientific evidence into practice to help healthcare systems and professionals deliver care that is high quality, safe, accessible, equitable, and affordable, and works to ensure that the scientific evidence is understood and used. AHRQ provides support to the U.S. Preventive Services Task Force (USPSTF), which makes recommendations about clinical preventive services including physical activity.
Centers for Disease Control and Prevention (CDC)The CDC conducts research and provides health information to tackle health problems causing death and disability for Americans, put science into action to prevent disease, and promote healthy and safe behaviors, communities and environment. The CDC has several programs focused on physical activity, partnering with other government agencies and departments as well as other organizations, including the Active People, Healthy Nation program and funding initiatives such as the State Physical Activity and Nutrition Program (SPAN 2023), which supports state-level programs to implement evidence-based strategies to address health disparities related to poor nutrition, physical inactivity, and/or obesity.
Centers for Medicare and Medicaid (CMS)CMS’ Behavioral Health Strategy is aimed at increasing access to equitable and high-quality behavioral health services and improving outcomes for people covered by Medicare, Medicaid and private health insurance. CMS could play an important role in providing access to gym memberships and exercise prescriptions for both intervention and prevention. Currently, gym memberships or fitness programs may be included in the extra coverage offered by Medicare Advantage Plans depending on the person’s location. Less commonly, coverage is provided by Medicare Supplement (Medigap) plans. For Medicaid, some states cover gym memberships as part of weight loss initiatives or partner with YMCAs or other community organizations to run health programs.
Council on Environmental Quality (CEQ) and Environmental Protection Agency (EPA)CEQ and EPA coordinate federal environmental activities and the development of environmental policy, which has a reciprocal beneficial relationship with physical activity. For example, to reduce emission and energy use, climate change policies have been introduced to encourage cycling, walking and other forms of sustainable, active transport. Parks and other green spaces that sequester carbon dioxide also provide space for people to be active. Policies that reduce air pollution help to reduce a barrier to exercising outside.
Department of Agriculture (USDA)The USDA’s strategic priorities include addressing climate change via climate smart agriculture, forestry, and clean energy. Climate, clean air, and spaces for outdoor recreation and camping such as forests are all related to physical activity. The USDA works with the Bureau of Land Management, National Park Service, and others to increase physical activity on federal land (hiking, rafting, biking, etc.), and also provides funding for urban forestry, which promotes physical activity in urban areas.
Department of Education (DE)The DE sets guidelines for physical education in schools and has provided funding for research on physical activity in schools, such as the Carol M. White Physical Education Program, which awarded grants from 2001-2015 to Local Education Agencies (LEAs) and community-based organizations (CBOs) to initiate, expand, or enhance physical education programs. The DE could also designate physical education as a core subject and ensure that physical activity is not assigned or withheld as punishment.
Department of Housing and Urban Development (HUD)HUD has an important role in community building and infrastructure. The built environment can support physical activity (e.g., by providing safe spaces for movement). For example, HUD’s Office of Community Planning and Development develops communities by promoting decent housing, suitable living environments, and expanded economic opportunities for low- and moderate-income people. Research shows that receiving HUD housing assistance is associated with higher physical activity levels in low-income Americans. HUD is also involved in the climate action plan.
Department of the Interior (DOI)The DOI manages public lands and minerals, national parks, and wildlife refuges. Within the DOI, the Bureau of Land Management and National Park Service maximize land use, including recreational activities that involve physical activity in outdoor spaces. The National Park Service promotes health and wellness through the Healthy Parks Healthy People initiative, which involves a collaboration with partners and interdisciplinary teams in the sectors of public health, medicine, conservation, and recreation to put a spotlight on the role of parks as social determinant of health.
Department of Transportation (DOT)The DOT promotes physical activity in the public sector through building and maintaining sidewalks or trails, as well as connecting them; reducing car dependency; provide increased opportunities for walking and bicycling; encouraging the creation and implementation of policies to support alternate modes of transportation; providing direct investments to supportive infrastructure such as bicycle lanes, greenways, multi use paths, sidewalks and trails; reducing distances between key destinations and providing and improving bicycle and pedestrian facilities; and installing streetlights. For example, the Safe Routes to School Programs, which promotes safe ways for youth to walk or bike to and from school through the funding of infrastructure (e.g., sidewalks) and educational programs, grew out of these federal funding programs. The DOT and its partner agencies also work to address air and noise pollution and reduce greenhouse gas emissions, to improve opportunities for safe, active, multimodal transportation and reduce dependence on vehicles, such as the Clean Air Act and the Congestion Mitigation and Air Quality Improvement (CMAQ) Program.
Department of Veterans Affairs (VA)The VA’s Veterans Health Administration is America’s largest integrated health care system. Their National Center for Health Promotion and Disease Prevention includes talking to one’s doctor about physical activity as one of their recommended preventive services. The integrated nature of medical care through the VA would promote the implementation of exercise prescriptions to a large and vulnerable population and could serve as a model for more widespread implementation.
Health Resources and Services Administration (HRSA)HRSA offers programs to improve access to health care for people who are uninsured, isolated, or medically vulnerable, and funds grants and cooperative agreements related to its mission. Funding related to physical activity is directly related to its strategic goal to “Take actionable steps to achieve health equity and improve public health.”
National Institutes of Health (NIH)As the federal government’s medical research agency, NIH supports physical activity related research in its intramural laboratories and through research funding to scientists at other organizations. Requests for applications (RFAs) and Notices of Special Interest (NOSIs) for exercise-focused research grants can promote continued research on the impacts of physical activity on health.
Office of Minority Health (OMH)The OMH promotes the health of racial and ethnic minority populations through the development of health policies and programs that will help eliminate health disparities. Prevention through physical activity and nutrition is one of OMH’s focus areas, as are clinical conditions including diabetes and hypertension that can be prevented or treated with physical activity.
Office of Personnel Management (OPM)One role of OPM, which oversees human resources for federal employees, is to help federal agencies integrate prevention strategies into their workplace through worksite health and wellness programs and organizational and employee benefits. Examples include encouraging employees to use flexible work schedules (non-duty time) to participate in health promotion activities, allowing employees to request annual leave, leave without pay, or sick leave (as appropriate) to participate in health promotion programs, and providing short periods of excused absence for health promotion programs and activities officially sponsored and administered by the agency.

The work of several agencies and departments within the federal government relates to physical activity promotion. Current initiatives are in place, but there are also opportunities for additional efforts that could further the goal of creating a more active nation.

FIGURE 3. Agency interactions
Department, Agency, or DivisionIndividualInterpersonalOrganizationalCommunityPolicy
Administration for Children and Families (ACF)XX
Administration for Community Living (ACL)XX
Agency for Healthcare Research and Quality (AHRQ)XXX
Centers for Disease Control and Prevention (CDC)XX
Centers for Medicare and Medicaid (CMS)XX
Council on Environmental Quality (CEQ)XX
Department of Agriculture (USDA)XX
Department of Education (DE)XX
Department of Housing and Urban Development (HUD)XX
Department of the Interior (DOI)XX
Department of Transportation (DOT)XX
Department of Veterans Affairs (VA)X
Environmental Protection Agency (EPA)XX
Health Resources and Services Administration (HRSA)XX
National Institutes of Health (NIH)XX
Office of Minority Health (OMH)XXX
Office of Personnel Management (OPM)XX

These and other federal departments and agencies can coordinate action with state and local partners, for example in healthcare, business and industry, education, mass media, and faith-based settings, to implement physical activity policies. 

The CDC’s Active People, Healthy Nation initiative provides an example of this approach. This campaign, launched in 2020, has the goal of helping 27 million Americans become more physically active by 2027. By taking action steps focused on program delivery, partnership engagement, communication, training, and continuous monitoring and evaluation, the campaign seeks to help communities implement evidence-based strategies across sectors and settings to provide equitable and inclusive access to safe spaces for physical activity. According to our analysis, the strategies of the Active People, Healthy Nation initiative are aligned with the social-ecological model. The Physical Activity Policy Research and Evaluation Network, a research partner of the Active People, Healthy Nation initiative, provides an example of coordinating with partners in other sectors to promote physical activity. Through collaboration across sectors, the network brings together diverse partners to put into practice research on environments that maximize physical activity. The network includes work groups focused on equity and inclusion, parks and green space, rural active living, school wellness, transportation policy and planning, and business/industry.

The Biden-Harris Administration National Strategy on Hunger, Nutrition, and Health, announced in September 2022, also includes strategies that are consistent with a social-ecological model. The strategy outlines steps toward the goal of ending hunger and increasing healthy eating and physical activity by 2030 so that fewer Americans will experience diet-related diseases. Pillar 4 of the strategy is to “make it easier for people to be more physically active—in part by ensuring that everyone has access to safe places to be active—increase awareness of the benefits of physical activity, and conduct research on and measure physical activity.” The strategy specifies goals such as building environments that promote physical activity (e.g., connecting people to parks; promoting active transportation and land use policies to support physical activity) and includes a call to action for a whole-of-society response involving the private sector, state, local, and territory governments, schools, and workplaces.

The Congressional Physical Activity Caucus has been active in introducing legislation that can help realize the goals of the current physical activity initiatives. For example, in February 2023, Sen. Sherrod Brown (D-OH), co-chair of the Caucus, introduced the Promoting Physical Activity for Americans Act, a bill that would require the Department of Health and Human Services to continue issuing evidence-based physical-activity guidelines and detailed reports at least every 10 years, including recommendations for population subgroups (e.g., children or individuals with disabilities). In addition, members of the Caucus, along with other members of congress, reintroduced the bipartisan, bicameral Personal Health Investment Today (PHIT) Act in March 2023. This legislation seeks to encourage physical activity by allowing Americans to use a portion of the money saved in their pre-tax health savings account (HSA) and flexible spending account (FSA) toward qualified sports and fitness purchases, such as gym memberships, fitness equipment, physical exercise or activity programs and youth sports league fees. The bill would also allow a medical care tax deduction for up to $1,000 ($2,000 for a joint return or a head of household) of qualified sports and fitness expenses per year.

What progress has been made?

There are signs that some of the national campaigns are leading to changes at other levels of society. For example, 46 cities, towns, and states have passed an Active People, Healthy Nation Proclamation as of September 2023. According to the State Routes Partnership, which develops “report cards” for states based on their policies supporting walking, bicycling, and active kids and communities, many states have shown movement in their policies between 2020 and 2022, such as implementing new policies to support walking and biking and increasing state funding for active transportation. However, more time is needed to determine the extent to which recent initiatives are helping to create a more active country, since most were initiated in the past two or three years. Predating the current initiatives, the overall physical activity level of Americans increased from 2008 to 2018, but there has been little change since that time, and only about one-quarter of adults meet the physical activity guidelines established by the CDC.

Clearly, there is a critical need for concerted effort to implement the strategies outlined in current physical activity initiatives so that national policies have the intended impacts on communities and on individuals. Leveraging provisions in existing legislation related to the social-ecological model of physical activity promotion will also help with implementation. For example, title III-D of the Older Americans Act supports healthy lifestyles and promotes healthy behaviors amongst older adults (age 60 and older), providing funding for evidence-based programs that have been proven to improve health and well-being and reduce disease and injury. Physical activity programs are prime candidates for such funding. In addition, programs under the 2021 Bipartisan Infrastructure Law and the 2022 Inflation Reduction Act are helping to change the current car-dependent transportation network, providing healthier and more sustainable transportation options, including walking, biking, and using public transportation, and are providing investments in environmental programs to improve public health and reduce pollution. For example, states can use funds from the Highway Safety Improvement Program for bicycle and pedestrian highway safety improvement projects, and funding is available through the Carbon Reduction Program for programs that help reduce dependence on single-occupancy vehicles, such as public transportation projects and the construction, planning, and design of facilities for pedestrians, bicyclists, and other non-motorized forms of transportation.

Partnering with non-governmental groups working towards common goals, such as the Physical Activity Alliance, can also help with implementation. The Alliance’s National Physical Activity Plan is based on the socio-ecological model and includes recommendations for evidence-based actions for 10 societal sectors at the national, state, local and institutional levels, with a focus on making change at the community level. The plan shares many priorities with those of the Active People, Healthy Nation initiative, while also introducing new goals, such as establishing a CDC Office of Physical Activity and Health. 

With coordinated action based on established public health models, such as the social-ecological framework, federal policies can be successfully implemented to make the systemic changes that are needed to create a more active nation.

The work for this blog was undertaken before Dr. Dotson joined the Agency for Healthcare Research and Quality (AHRQ). Dr. Dotson is solely responsible for this blog post’s contents, findings, and conclusions, which do not necessarily represent the views of AHRQ. Readers should not interpret any statement as an official position of AHRQ or of the U.S. Department of Health and Human Services.