[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
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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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