119-hr5315

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FAIR Act

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Introduced:
Sep 11, 2025
Policy Area:
Government Operations and Politics

Bill Statistics

3
Actions
1
Cosponsors
0
Summaries
1
Subjects
1
Text Versions
Yes
Full Text

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Latest Action

Sep 11, 2025
Referred to the House Committee on Oversight and Government Reform.

Actions (3)

Referred to the House Committee on Oversight and Government Reform.
Type: IntroReferral | Source: House floor actions | Code: H11100
Sep 11, 2025
Introduced in House
Type: IntroReferral | Source: Library of Congress | Code: Intro-H
Sep 11, 2025
Introduced in House
Type: IntroReferral | Source: Library of Congress | Code: 1000
Sep 11, 2025

Subjects (1)

Government Operations and Politics (Policy Area)

Cosponsors (1)

(R-AL)
Sep 11, 2025

Text Versions (1)

Introduced in House

Sep 11, 2025

Full Bill Text

Length: 3,226 characters Version: Introduced in House Version Date: Sep 11, 2025 Last Updated: Nov 13, 2025 6:32 AM
[Congressional Bills 119th Congress]
[From the U.S. Government Publishing Office]
[H.R. 5315 Introduced in House

(IH) ]

<DOC>

119th CONGRESS
1st Session
H. R. 5315

To prohibit the Federal procurement of large language models not
developed in accordance with unbiased AI principles, and for other
purposes.

_______________________________________________________________________

IN THE HOUSE OF REPRESENTATIVES

September 11, 2025

Ms. Hageman (for herself and Mr. Moore of Alabama) introduced the
following bill; which was referred to the Committee on Oversight and
Government Reform

_______________________________________________________________________

A BILL

To prohibit the Federal procurement of large language models not
developed in accordance with unbiased AI principles, and for other
purposes.

Be it enacted by the Senate and House of Representatives of the
United States of America in Congress assembled,
SECTION 1.

This Act may be cited as the ``Fair Artificial Intelligence
Realization Act of 2025'' or the ``FAIR Act''.
SEC. 2.
MODELS.

(a) Policy of the United States.--It is the policy of the United
States to promote the innovation and use of trustworthy artificial
intelligence.

(b) In General.--To advance the policy established under subsection

(a) , the head of each agency shall, procure after the date of the
enactment of this Act only those large language models developed in
accordance with the following principles:

(1) Large language models shall be truthful in responding
to user prompts seeking factual information or analysis.

(2) Large language models shall prioritize historical
accuracy, scientific inquiry, and objectivity, and shall
acknowledge uncertainty where reliable information is
incomplete or contradictory.

(3) Large language models shall be neutral, nonpartisan
tools that do not manipulate responses in favor of ideological
dogmas such as diversity, equity, and inclusion.

(4) Developers of large language models shall not
intentionally encode partisan or ideological judgments into a
large language model output unless those judgments are prompted
by or otherwise readily accessible to the end user.
(c) === Definitions. ===
-In this Act:

(1) Agency.--The term ``agency''--
(A) means--
(i) an executive department (as such term
is defined in
section 101 of title 5, United States Code); (ii) a military department (as such term is defined in
States Code);
(ii) a military department (as such term is
defined in
section 102 of title 5, United States Code); (iii) an independent establishment (as such term is defined in
States Code);
(iii) an independent establishment (as such
term is defined in
section 104 of title 5, United States Code); and (iv) a wholly owned Government corporation (as such term is defined in
United States Code); and
(iv) a wholly owned Government corporation
(as such term is defined in
section 9101 of title 31, United States Code); and (B) does not include the Government Accountability Office.
title 31, United States Code); and
(B) does not include the Government Accountability
Office.

(2) Large language model.--The term ``large language
model'' means a generative AI model trained on vast, diverse
datasets that enable the model to generate natural-language
responses to user prompts.
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