HR5315119th Congress

FAIR Act

Sponsored By: Representative Hageman

Introduced

Summary

This bill would set rules for how federal agencies buy large language models used in government systems. Require federal purchases of large language models to meet standards of truthfulness, accuracy, and neutrality.

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  • Agency procurement would be limited to LLMs developed under four principles: truthfulness, prioritizing historical and scientific accuracy with clear acknowledgement of uncertainty, neutrality and nonpartisanship, and a ban on encoding partisan judgments unless prompted.
  • The requirement would apply to executive departments, military departments, independent establishments, and wholly owned government corporations, and it explicitly excludes the Government Accountability Office.
  • LLM developers seeking federal contracts would need to design models that conform to those principles to be eligible for purchase by covered agencies.
  • The policy frames a federal push for “trustworthy” AI so government systems aim to provide factual, objective, and nonpartisan responses to users.

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Bill Overview

Analyzed Economic Effects

2 provisions identified: 0 benefits, 0 costs, 2 mixed.

New rules for federal AI purchases

If enacted, agencies would only be able to buy large language models that meet four rules after enactment. The models would need to give truthful answers to factual questions. They would favor historical accuracy, science, and objectivity, and admit when facts are uncertain. They would stay neutral and not steer answers toward any political or ideological view (for example, DEI). Developers could not bake in partisan judgments unless the user asks for them or can easily see them.

Which agencies and models are covered

If enacted, the bill would set who must follow these AI purchase rules and what tools are covered. "Agency" would include executive departments, military departments, independent establishments, and wholly owned government corporations. The Government Accountability Office would be excluded. A "large language model" would mean a generative AI trained on very large, diverse data that writes natural-language answers to prompts. These definitions would take effect on the date of enactment.

Sponsors & CoSponsors

Sponsor

Hageman

WY • R

Cosponsors

  • Rep. Moore, Barry [R-AL-1]

    AL • R

    Sponsored 9/11/2025

Roll Call Votes

No roll call votes available for this bill.

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