AI-Generated Works and Copyright Laws

Introduction
The rapid generation of AI-based works on a broad scale has challenged the fundamentals of copyright. At the heart of this controversy lies the question of whether a machine can be an author. This article covers the thorny legal and philosophical issues associated with original works created by AI systems either autonomously or with scant human input.

As the law itself struggles to resolve this conundrum, its ramifications echo deep into the future of the creative industries, ownership rights, and the very incentives needed to innovate.

Historical-Mapping of Copyrights and Human Authorship

In the classical viewpoint, human authors have been the only source of creativity, while copyright laws oblige that assumption. Legally, the concept of an “author” has been intertwined with human expression from the Statute of Anne (1710)[1] to the Berne Convention (1886)[2] and its progeny in tracts amending family countries.

Each time originality has been stressed by the courts, the element denoted the intellectual effort of a human.[3] This part analyzes how these old-fashioned patterns of assumptions have laid an underpinning for the presumption against machines carrying rights or being authors.

AI-Generated Systems: Works and Their Conditions

There is a wide variety of AI-generated works, from texts produced by language models to paintings created by neural networks.

• In some cases, AI-generated works are almost autonomous.
• In other cases, they are co-created.
• The uncertainty in law stems precisely from the inability to describe what is meant by creative input coming from a man as opposed to that coming from a machine.

This section endeavors to classify various outputs generated by AI and consider their consequences on copyright protection.

Comparative Legal Perspectives

A comparison shows that different nations provide varying approaches to AI authorship:

• United States: The U.S. Copyright Office holds that only those works that have been created by humans can be subject to copyright protection. Notable examples include Naruto v. Slater and other administrative principles supporting this stance.
• United Kingdom: Section 9(3) of the UK Copyright, Designs and Patents Act 1988 provides for the person who makes the arrangements necessary for the computer-generated work to be the author.
• India: Indian copyright legislation is silent on AI authorship, but courts tend to favor a human-centric interpretation of originality based on human creativity.

This section critiques these positions and examines their strengths and limitations in the context of generative AI.

Doctrinal and Philosophical Challenges

• The main sticking point in recognizing AI as an author is ontological: AI lacks consciousness, intent, or moral agency.
• These factors are fundamental to copyright law.
• Philosophically, there is concern that granting authorship to AI could undermine human creativity or create unchecked rights.
• Conversely, denying copyright to AI-generated works might hinder innovation or misattribute human collaboration.

This section discusses these doctrinal and ethical tensions.

Models for Attribution and Reform

Recognized models for resolving the authorship dilemma include:

• Human-centric model: Give copyright to the programmer or user.
• Joint authorship: Treat AI and human as co-authors, with a legal proxy managing the AI’s contribution.
• Public domain: Exclude AI-generated works from copyright and promote open access.
• New rights regime: Create a subgeneric right for AI-generated content.

This section evaluates these models in terms of practicability, fairness, and innovation.

Policy Considerations and the Way Forward

• Balanced policymaking is essential to protect human creators, support technological development, and prevent monopolies.
• Such policies must be crafted collaboratively by national lawmakers and international bodies like WIPO.

This section suggests policy recommendations that align with legal traditions while fostering innovation.

Conclusion
AI is not merely a tool; rather, an active participant in the contemporary creative process. If the concept requires outputs of a certain nature to be deemed copyrightable, then these AI-generated works necessitate a re-examination of copyright. The law has to be flexible and inclusive, able to keep pace with an ever-changing reality. Instead of forcing AI-generated content into the traditional boxes that the law already recognizes, new categories of creative expression must be legally recognized so that the fundamental principles of IPR are preserved.

End-Notes:

1. Statute of Anne, 1710, 8 Ann. c. 19 (Gr. Brit.).
2. Berne Convention for the Protection of Literary and Artistic Works, Sept. 9, 1886, as revised at Paris, July 24, 1971, 828 U.N.T.S. 221.
3. Feist Pub’s, Inc. v. Rural Tel. Serv. Co., 499 U.S. 340, 346 (1991).
4. Andres Guadamuz, Artificial Intelligence and Copyright, 39 IIC 541 (2008).
5. Naruto v. Slater, 888 F.3d 418 (9th Cir. 2018).
6. U.S. Copyright Office, Compendium of U.S. Copyright Office Practices, § 306 (3d ed. 2021).
7. Copyright, Designs and Patents Act 1988, c. 48, § 9(3) (UK).
8. Eastern Book Company v. D.B. Modak, (2008) 1 SCC 1 (India).
9. Ryan Calo, Artificial Intelligence Policy: A Primer and Roadmap, 51 U.C. Davis L. Rev. 399 (2017).
10. Pamela Samuelson, Allocating Ownership Rights in Computer-Generated Works, 47 U. Pitt. L. Rev. 1185 (1986).
11. Shlomit Yanick-Ravid & Luis Antonio Velez-Hernandez, Copyrightability of Art Works Produced by Creative Robots, 19 Vand. J. Ent. & Tech. L. 507 (2017).
12. Tanya Aplin & Lionel Bently, Global Mandatory Fair Use: The Nature and Scope of the Right to Quote Copyright Works, 68 J. Copyright Soc’y U.S.A. 1 (2021).
13. Tim W. Doris, AI and the Public Domain, 55 UC Davis L. Rev. 225 (2021).
14. World Intellectual Property Organization [WIPO], WIPO Technology Trends 2019: Artificial Intelligence (2019).
15. WIPO Conversation on Intellectual Property (IP) and Artificial Intelligence (AI), WIPO Doc. WIPO/IP/AI/1/GE/19/INF/4 (2019).