[Federal Register Volume 90, Number 185 (Friday, September 26, 2025)]
[Notices]
[Pages 46422-46424]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2025-18737]


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OFFICE OF SCIENCE AND TECHNOLOGY POLICY


Notice of Request for Information; Regulatory Reform on 
Artificial Intelligence

AGENCY: Office of Science and Technology Policy.

ACTION: Request for information.

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SUMMARY: The Office of Science and Technology Policy (OSTP) requests 
input from all interested parties in identifying existing Federal 
statutes, regulations, agency rules, guidance, forms, and 
administrative processes that unnecessarily hinder the development, 
deployment, and adoption of artificial intelligence (AI) technologies 
within the United States. Through this Request for Information (RFI), 
OSTP is seeking input from the public, including private sector 
organizations, industry groups, academia, state, local, and tribal 
governments, and any other interested parties, on priorities for such 
regulatory reform or other agency action necessary to promote AI 
innovation and adoption.

DATES: Interested persons are invited to submit comments on or before 
11:59 p.m. (ET) October 27, 2025.

ADDRESSES: Interested individuals and organizations should submit 
comments electronically via the Federal eRulemaking Portal at http://www.regulations.gov by searching the Docket ID number OSTP-TECH-2025-
0067. Comments submitted in response to this notice should be submitted 
electronically through the Federal eRulemaking Portal at http://www.regulations.gov by selecting the Docket ID number. Information on 
how to use regulations.gov, including instructions for accessing agency 
documents, submitting comments, and viewing the docket, is available on 
the site under ``FAQ'' (https://www.regulations.gov/faq).

Instructions

    Response to this RFI is voluntary. Please note that all submissions 
received in response to this notice may be posted on https://www.regulations.gov/ or otherwise released in their entirety.
    Do not include in your submissions any copyrighted material; 
information of a confidential nature, such as personal or proprietary 
information; or any information you would not like to be made publicly 
available.
    OSTP will not respond to individual submissions. A response to this 
RFI will not be viewed as a binding commitment to develop or pursue the 
project or ideas discussed. This RFI is not accepting

[[Page 46423]]

applications for financial assistance or financial incentives.
    Responses containing references, studies, research, and other 
empirical data that are not widely published should include copies of 
or electronic links to the referenced materials. Responses from minors, 
or responses containing profanity, vulgarity, threats, or other 
inappropriate language or content will not be considered.
    Comments submitted in response to this notice are subject to the 
Freedom of Information Act (FOIA). Please note that the United States 
Government will not pay for response preparation, or for the use of any 
information contained in a response.

FOR FURTHER INFORMATION CONTACT: For additional information, please 
direct questions to Ashley Lin at [email protected] or (202) 
881-4961.

SUPPLEMENTARY INFORMATION: Artificial intelligence (AI) encompasses a 
broad range of computational techniques and systems that perform tasks 
traditionally requiring human judgment, such as perception, prediction, 
optimization, decision support, and autonomous operation. AI has 
applications across nearly every sector of the economy and public life, 
including healthcare, finance, transportation, manufacturing, 
education, agriculture, and national security. AI adoption is expected 
to yield significant benefits, including greater efficiency, improved 
safety and reliability, expanded access to services, and enhanced 
economic competitiveness. Realizing these benefits depends on continued 
AI innovation and public adoption.
    On July 23, 2025, the White House issued America's AI Action Plan 
to achieve global dominance in AI. The AI Action Plan directed OSTP to 
``launch a Request for Information [RFI] from businesses and the public 
at large about current Federal regulations that hinder AI innovation or 
adoption, and work with relevant Federal agencies to take appropriate 
action.'' This RFI advances that directive by focusing on identifying 
the regulatory and procedural barriers that unnecessarily slow safe, 
beneficial AI deployment.
    The realization of the benefits from AI applications cannot be done 
through complete de-regulation, but require policy frameworks, both 
regulatory and non-regulatory. Suitable policy frameworks enable 
innovation while safeguarding the public interest. This is critical to 
foster public trust in AI technologies, leading to broader deployment 
and faster adoption. Such policy frameworks may include statutory and 
regulatory requirements, technical standards, guidance documents, 
voluntary frameworks, and other instruments.
    Most existing Federal regulatory regimes and policy mechanisms were 
developed before the rise of modern AI technologies. As a result, they 
often rest on assumptions about human-operated systems that are not 
appropriate for AI-enabled or AI-augmented systems. These assumptions 
include, but are not limited to:
     Decision-Making and Explainability--Decisions are made, 
documented, and explained, in ways where the processes and rationale 
are traceable to a human actor.
     Liability and Accountability--Allocation of legal 
responsibility and remedial frameworks rests with human actors or 
clearly identifiable organizational decision points.
     Human Oversight and Intervention--Prescriptive 
requirements for human oversight, review, intervention, or continuous 
supervision in operational processes.
     Data Practices--Data collection, retention, provenance, 
sharing, and permitted uses cases that do not account for the scale, 
reuse, or training dynamics characteristic of AI systems.
     Testing, Validation, and Certification--Approaches to 
testing, approval, and post-market oversight designed for static 
products or human-delivered services, rather than adaptive or 
continuously learning systems.
    These assumptions manifest differently across sectors and their AI 
applications. For example, in healthcare, regulations for medical 
devices, telehealth, and patient privacy were designed around human 
clinicians and discrete medical device updates. It may create 
challenges to apply the same policy framework for overseeing 
continuously updating AI diagnostic tools and ensuring explainable 
clinical recommendations. In transportation, safety standards and 
certification processes are built for human drivers and operators. 
Similarly, this may raise questions around operational design domain 
limits and incident investigation for autonomous vehicles, unmanned 
systems, and other AI-enabled transportation technologies.
    When applied to AI-enabled or AI-augmented systems, policy 
frameworks that assume human-operated systems or fail to account for 
technological progress hinder the development, deployment, and adoption 
for AI across sectors. These barriers generally fall into five 
categories: (1) regulatory mismatch, where existing rules no longer 
aligns with AI capabilities, (2) structural incompatibility, where 
legal or operational requirements are fundamentally unsuitable for AI 
systems, (3) lack of regulatory clarity, where insufficient guidance 
and rules that plausibly cover AI systems delays adoption, increases 
compliance costs, and slows innovation, (4) direct hindrance, where 
regulations directly target AI development, deployment, and adoption, 
and (5) organizational factors, which influence how available policy 
frameworks and administrative tools are and are not used.
    1. Regulatory Mismatches--Existing requirements are based on human-
centered assumptions (e.g., mandatory human supervision or 
documentation practices) that do not align with AI capabilities or 
operational models. In many cases, the underlying goals can still be 
met if the regulations are applied flexibly. Administrative tools such 
as waivers, exemptions, pilot programs, conditional approvals, or time-
limited experimental authorities can enable lawful deployment while 
preserving regulatory objectives.
    2. Structural Incompatibility--Certain statutory or regulatory 
frameworks are not just mismatched, but structurally unable to 
accommodate particular AI applications because key legal constructs or 
procedural prerequisites assume human actors (e.g., statutory human 
decisionmakers, prohibitions on automated data practices). Where no 
administrative flexibility exists, meaningful AI adoption may require 
legislative change or comprehensive regulatory revision.
    3. Lack of Regulatory Clarity--In some circumstances, existing laws 
plausibly cover AI activities, but insufficient interpretive guidance, 
standards, or objective criteria leaves compliance, risk management, 
and enforcement uncertain. This ambiguity can delay adoption, increase 
compliance costs, and hinder innovation. Remedies may include 
authoritative guidance, interpretive rules, sector-specific standards, 
or clarity on enforcement priorities.
    4. Direct Hindrance--There are also a number of regulations that 
directly target AI and are a major hindrance to AI development, 
deployment, and adoption. For example, guidance that prevent Federal 
workers from using AI on their work computers for reasonable use cases 
fall under this category.
    5. Organizational Factors--AI adoption may also be influenced by 
organizational factors, such as gaps in workforce readiness, 
institutional capacity, or cultural acceptance. While these are not 
barriers embedded in Federal governance mechanisms, they

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nonetheless influence how available policy frameworks and 
administrative tools are (or are not) used. For example, agencies may 
have the administrative flexibilities to overcome regulatory 
mismatches, but not fully utilize them due to a lack of awareness, 
hindering the pace and scope of AI adoption.
    This RFI seeks to identify Federal regulations that hinder AI 
development, deployment, or adoption, particularly due to rules 
established before current AI capabilities were anticipated. OSTP is 
especially interested in regulations that, while serving important 
purposes, contain requirements or assumptions incompatible with how AI 
systems function or could function. Respondents are encouraged to 
identify regulations across all sectors where the underlying 
assumptions, technical requirements, or compliance frameworks may 
create unnecessary barriers to beneficial AI applications, even if the 
core policy objectives remain valid.
    Specifically, OSTP invite responses to one or more of the following 
questions:
    (i) What AI activities, innovations, or deployments are currently 
being inhibited, delayed, or otherwise constrained due to Federal 
statues, regulations, or policies? Please describe the specific barrier 
and the AI capability or application that would be enabled if it was 
addressed. The barriers may directly hinder AI development or adoption, 
or indirectly hinder through incompatible policy frameworks.
    (ii) What specific Federal statutes, regulations, or policies 
present barriers to AI development, deployment, or adoption in your 
sector? Please identify the relevant rules and authority with 
specificity, including a cite to the Code of Federal Regulations (CFR) 
or the U.S. Code (U.S.C.) where applicable.
    (iii) Where existing policy frameworks are not appropriate for AI 
applications, what administrative tools (e.g., waivers, exemptions, 
experimental authorities) are available, but underutilized? Please 
identify the administrative tools with specificity, citing the CFR or 
U.S.C. where applicable.
    (iv) Where specific statutory or regulatory regimes are 
structurally incompatible with AI applications, what modifications 
would be necessary to enable lawful deployment while preserving 
regulatory objectives?
    (v) Where barriers arise from a lack of clarity or interpretive 
guidance on how existing rules cover AI activities, what forms of 
clarification (e.g., standards, guidance documents, interpretive rules) 
would be most effective?
    (vi) Are there barriers that arise from organizational factors that 
impact how Federal statues, regulations, or policies are used or not 
used? How might Federal action appropriately address them?

    Dated: September 24, 2025.
Stacy Murphy,
Deputy Chief Operations Officer/Security Officer.
[FR Doc. 2025-18737 Filed 9-25-25; 8:45 am]
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