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Artificial intelligence

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51 records in US

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Bill· HRH.R. 10315 (119th)referred

AI LABS Act

United States · United States Congress · 8 September 2026

Bill· HRH.R. 9985 (119th)referred

AI Ads Act

United States · United States Congress · 30 July 2026

Bill· SS. 5135 (119th)referred

AI Ads Act

United States · United States Congress · 27 July 2026

Bill· HRH.R. 9907 (119th)referred

LEARN AI Act

United States · United States Congress · 23 July 2026

Bill· HRH.R. 9917 (119th)referred

AI Kill Switch Act

United States · United States Congress · 23 July 2026

Bill· SS. 5051 (119th)referred

AI AGENT Act of 2026

United States · United States Congress · 21 July 2026

Bill· HRH.R. 9686 (119th)referred

FARM AI Act of 2026

United States · United States Congress · 14 July 2026

Bill· HRH.R. 9501 (119th)reported

AI Tax Integrity Act of 2026

United States · United States Congress · 29 June 2026

AI Tax Integrity Act of 2026 This bill requires the Internal Revenue Service to establish a pilot program to use artificial intelligence to identify inaccurate federal tax returns. Upon completion of the pilot program, the Government Accountability Office must submit a report to Congress describing the aggregate amount of improper tax refunds or reduced tax liability attributable to fraud detected by the pilot program, aggregate amount recovered as a result of the pilot program, and accuracy of the artificial intelligence tools used in the pilot program in identifying fraudulent federal tax returns.

Bill· SJRESS.J.Res. 198 (119th)failed

A joint resolution providing for congressional disapproval under chapter 8 of title 5, United States Code, of the rule submitted by the Centers for Medicare & Medicaid Services of the Department of Health and Human Services relating to "Medicare Program; Implementation of Prior Authorization for Select Services for the Wasteful and Inappropriate Services Reduction (WISeR) Model".

United States · United States Congress · 24 June 2026

This joint resolution prohibits the Centers for Medicare & Medicaid Services (CMS) from testing a new Medicare payment model in certain states that involves a prior authorization process and the use of enhanced technology by third-party contractors to determine whether certain claims should be paid. Specifically, the joint resolution nullifies a notice issued by the CMS on July 1, 2025, titled Medicare Program; Implementation of Prior Authorization for Select Services for the Wasteful and Inappropriate Services Reduction (WISeR) Model . (On May 12, 2026, the Government Accountability Office issued a letter of opinion stating that this notice constituted an agency rule and is therefore subject to the Congressional Review Act.) The CMS selected six states to participate in this model over a six-year period: New Jersey, Ohio, Oklahoma, Texas, Arizona, and Washington. Under the model, contracted companies must process prior authorization requests (i.e., requests for coverage determinations before a service is furnished) for certain services using enhanced technology (e.g., artificial intelligence). Contracted companies are paid based on the share of resulting savings. The CMS aims to test the model's ability to produce accurate results while streamlining the prior authorization process for Medicare claims. The model is based in part on similar processes used for Medicare Advantage claims.  CMS began implementing the model on January 1, 2026. This joint resolution prohibits the CMS from continuing to do so.

Bill· HRH.R. 9333 (119th)reported

AI Flaw Reporting and Security Enhancement Act

United States · United States Congress · 18 June 2026

AI Flaw Reporting and Security Enhancement Act This bill establishes a program to facilitate the voluntary reporting and tracking of artificial intelligence (AI) flaws, to be administered by the National Institute of Standards and Technology (NIST). In carrying out this program, NIST must seek to convene various stakeholders to establish common definitions for terms related to AI flaws and criteria for the classification of AI flaws (e.g., security-related flaws and safety-related flaws). The group must also support the development of technical standards and guidance related to detecting, managing, and disclosing AI flaws and prioritizing the remediation of such flaws. Further, NIST must develop, or enter into cooperative agreements with institutions of higher education or research institutions to develop, infrastructure for the voluntary reporting, collection, and tracking of AI flaws. This must include a national database of AI flaws or the modification of an existing national database to account for AI flaws. (NIST currently administers a national database of cybersecurity vulnerabilities.) NIST must consider certain topics when developing this infrastructure, including the interoperability of the infrastructure with relevant existing systems, standards, and best practices. Within three years of the bill’s enactment, NIST must report to Congress on the implementation of these provisions. Under the bill, an AI flaw is a set of conditions or behaviors that allow for the violation of certain policies (e.g., safety or security policies) and is not necessarily associated with malicious intent.

Bill· HRH.R. 9334 (119th)reported

Workforce for AI Trust Act

United States · United States Congress · 18 June 2026

Workforce for AI Trust Act This bill provides for various workforce development and research programs related to artificial intelligence (AI). For example, the bill authorizes the National Institute of Standards and Technology (NIST) to support education and workforce development activities to expand careers in the AI workforce. Further, the bill requires NIST to develop a common system for describing and classifying AI-related tasks, knowledge, and skills that can be used to develop job descriptions or competency areas (an AI workforce framework ). NIST must develop guidelines for using the framework and take other steps to support external use (e.g., through outreach and dissemination to AI education programs). Separately, the National Science Foundation (NSF) may make awards through eligible institutions of higher education to support graduate and postdoctoral research fellowships across disciplines (including in social science and humanities) related to trustworthy AI. NSF may also make awards to support institutional workshops to advance the development and training of trustworthy AI systems. NSF must encourage the use of AI to accelerate work across NSF-supported fields, including by supporting (1) training for undergraduate and graduate students and postdoctoral researchers, (2) workshops on the application of trustworthy AI to new uses, and (3) supplements to existing research awards for applying AI to ongoing research. Further, NSF must generally ensure that merit review panels convened to evaluate AI-related proposals incorporate perspectives from diverse research disciplines (e.g., social science, ethics, and linguistics).

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