Copyright, Fair Use & AI

In the rapidly evolving landscape of artificial intelligence, the intersection of copyright law and AI technology presents unique challenges and opportunities. This seminar aims to explore the complexities of copyright issues related to AI and provide a summary of the dozens of AI copyright lawsuits with a particular focus on whether training AI on copyright material is an infringement or fair use. It will also cover the DMCA implications of AI with respect to copyright management information. It will also cover what the Copyright Office has done to address AI.

Topics covered include:

Artificial Intelligence (AI) Intellectual Property

Agenda:

Introduction
- Welcome and prepare to explore the evolving intersection of AI and copyright law
- Set the stage for the critical discussions ahead
Overview of Existing AI Litigation
- Explore high-profile lawsuits that are defining the legal boundaries of AI, including the use of copyrighted materials to train AI
- Provide insights into the current trends and key rulings shaping AI-related litigation
Analysis of Whether Training AI on Copyrighted Material is Infringement or Fair Use
- Delve into the ongoing debate over whether using copyrighted works to train AI constitutes infringement or qualifies as fair use
- Analyze the legal tests and arguments at play in this contentious issue
DMCA Issues with Training AI on Copyrighted Material
- Examine how the DMCA applies to datasets used for AI training and the challenges it poses
- Highlight potential liabilities and legal uncertainties for developers and rights holders
The Copyright Office and AI
- Discover how the Copyright Office is adapting to the rise of AI-generated works and its implications for copyright registration
- Review recent guidance and policy developments shaping this evolving area of law
Questions & Answers (as time permits)

Duration of this webinar: 60 minutes

Originally broadcast: March 04, 2025 11:00 AM PT

Webinar Highlights

This webinar is divided into section summaries, which you can scan for key points and then dive into the sections that interest you the most.

00:00 Introduction and Speaker Overview

James Gatto, experienced in intellectual property and emerging technologies, will discuss copyright, fair use, and AI. James outlines the topics he will cover, including AI litigation, copyright infringement, and the role of the DMCA. He notes the evolving legal landscape of AI and the unique challenges it presents, particularly in relation to copyright.

05:08 AI and Copyright Infringement

James discusses the key issues in AI copyright lawsuits, focusing on whether training AI on copyrighted material constitutes infringement or fair use. He highlights the importance of understanding the DMCA and the obligations it imposes on maintaining copyright management information. James provides examples of lawsuits involving AI-generated work and the challenges of recognizing AI as an author or inventor. He warns companies about potential legal risks and the importance of having policies to manage AI use. James explains the complexity of determining liability for infringement, emphasizing the need to consider the specific facts of each case.

17:25 Fair Use and Legal Precedents

James explains the concept of fair use and its application in AI-related cases, emphasizing the importance of transformative purpose. He discusses several legal precedents, including the Campbell case and the Authors Guild vs. Google case, which illustrate the nuances of fair use. James highlights the significance of the four-factor test in determining fair use, particularly the purpose and market impact factors. He notes that courts have found fair use in cases where the use serves a public benefit or does not harm the market for the original work. James mentions the Thomson Reuters Ross case, where the court found no fair use due to the commercial nature and market impact of the use.

37:17 AI Output and Derivative Works

James discusses the implications of AI output and whether it constitutes a derivative work, noting the fact-specific nature of these cases. He explains that courts have dismissed cases where plaintiffs failed to show actual infringing output from AI tools. James highlights the importance of proving infringing output to establish liability, referencing cases like Getty Images and New York Times. He discusses the potential liability of tool developers and users, referencing the Sony case as a precedent for non-liability if the tool has substantial non-infringing uses. James emphasizes the need for a balanced approach to copyright enforcement, considering both the rights of copyright owners and the public benefit.

45:10 DMCA and Licensing Issues

James discusses the DMCA and licensing issues related to AI, focusing on the obligations to maintain copyright management information. He explains a case involving GitHub, where the court dismissed a DMCA claim due to lack of identical output. James notes the ongoing debate about licensing frameworks for AI training and the potential for compulsory licensing. He highlights the copyright office's initiative to address AI-related copyright issues and the public input received. James mentions the copyright office's guidance on human authorship and the protection of human-generated content in AI-assisted works.

48:21 Copyright Office Guidance on AI

James explains the copyright office's stance on AI-generated content, emphasizing the need to distinguish human-generated portions for protection. He provides examples of cases where the copyright office rejected applications for AI-generated works, such as Stephen Thaler's and Kristina Kashtanova's cases. James highlights the importance of disclosing AI involvement in copyright applications and the potential consequences of non-disclosure. He discusses the challenges of protecting AI-assisted works and the need for clear guidelines on what constitutes human authorship. James concludes by emphasizing the importance of understanding the copyright office's guidance and its implications for AI-generated content.

59:06 Q&A and Closing Remarks

James addresses questions about AI and copyright, clarifying that training AI is not necessarily equivalent to copying. He discusses the potential for defamation lawsuits due to false information generated by AI tools. James explains the implications of using AI-generated content, such as YouTube titles, and the challenges of obtaining copyright protection. He highlights the importance of company policies on AI use to mitigate legal risks and ensure compliance with copyright laws. James discusses the potential for licensing frameworks to resolve disputes over AI training and the tools available to detect AI use.

Please note this AI-generated summary provides a general overview of the webinar but may not capture all details, nuances, or the exact words of the speaker. For complete accuracy, please refer to the original webinar recording.

Continuing Legal Education (CLE) Credits

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California CLE

Status: Approved

Credits: 1.00 General

Earn Credit Until: June 30, 2026

South Carolina CLE

Status: Approved

Credits: 1.00 General

Difficulty: All Levels

Earn Credit Until: December 31, 2025

North Carolina CLE

Status: Approved

Credits: 1.00 General

Earn Credit Until: February 28, 2026

This presentation is approved for one hour of General CLE credit in California, South Carolina (all levels), and North Carolina.

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Speaker

James Gatto AI Team Leader
Sheppard Mullin

Jim Gatto is a partner in the Intellectual Property Practice Group in the firm’s Washington, D.C. office. He is Co-Leader of the Artificial Intelligence Team, the Blockchain & Fintech Team, and Leader of the Open Source Team. Read More ›

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