Sec. 2. Findings

218 words·~1 min read·/bill/118/hr/6881/ih/section-2

A research copy — for the controlling text, always check the official state or federal source. Not legal advice.

Congress finds the following: With the increase in public access to artificial intelligence, there has been an increase in lawsuits and public concerns about copyright infringement, including in court cases such as the following: Doe 1 v. GitHub, Inc., No. 22–cv–06823, 2023 WL 3449131, at *1 (N.D. Cal. May 11, 2023). Amended Complaint, Getty Images, Inc. v. Stability AI, Ltd., No. 23–cv–00135 (D. Del. Mar. 29, 2023). Andersen v. Stability AI Ltd., No. 23–cv–00201, 2023 WL 7132064, at *1 (N.D.

Cal. Oct. 30, 2023). Public use of foundation models has led to countless instances of the public being presented with inaccurate, imprecise, or biased information during inference, based on limited training data, limited model training mechanisms, or a lack of disclosures about the training data composition or foundation model training procedures, including in facial recognition technology usage, artificial intelligence inferences relating to health, artificial intelligence inferences relating to loan granting and housing approval, and more.

Transparency with respect to high-impact foundation models has become increasingly necessary, including to assist copyright owners with enforcing their copyright protections and to promote consumer protection. While not compromising the intellectual property rights of those who develop and deploy foundation models, users should be equipped with the information necessary to enforce their copyright protections and to make informed decisions about such foundation models.