FAIR Act
H.R. 5315119th Congress

FAIR Act

Introduced in the HouseRep. Harriet Hageman (R-WY-At Large)16 sections · 1 min read
Version: Introduced in House · Sep 11, 2025

Section 1. Short title

This Act may be cited as the Fair Artificial Intelligence Realization Act of 2025 or the FAIR Act.

(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 section 102 of title 5, United 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 section 9101 of 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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