Artificial Intelligence And The Labour Theory Of Copyright In India - Emerging Challenges

Author: LawSphereX

Category: Technology, Cyber & Privacy

Published: 2026-08-23T18:16:10.9325+00:00

Updated: 2026-08-26T17:12:02.821+00:00

ARTIFICIAL INTELLIGENCE AND THE LABOUR THEORY

OF COPYRIGHT IN INDIA: EMERGING CHALLENGES

Pushap Deep, Junior Research Fellow, Department of Laws, Himachal Pradesh University, Summer Hill, Shimla, 171005 Dr. Geetika Sood, Assistant Professor, Department of Laws, Himachal Pradesh University, Summer Hill, Shimla, 171005

ABSTRACT

Modern copyright systems face significant doctrinal and policy issues as a result of Artificial Intelligence's (AI) explosive growth as an independent creative agent. The labor-desert argument, which is based on human intellectual effort, natural rights, and the ethical worth of creative labor, continues to support judicial reasoning on authorship and originality in India, where this tension is particularly evident. Indian copyright law has historically based protection on verifiable human talent, effort, and discernment. However, the traditional, human-centric understanding of authorship that the Copyright Act, 1957 assumes is undermined by the development of generative AI systems that may independently produce literary, artistic, musical, and digital creations.

AI-generated outputs blur the line between human-aided and machine-autonomous creativity, confuse authorship identification, and challenge accepted originality standards. These developments illustrate the lack of a coherent judicial interpretation of AI-generated works and reveal statutory uncertainties, especially in Section 2(d)(vi). Furthermore, regulatory ambiguity is exacerbated by the contradiction between Indian legal doctrine and rapidly changing international norms. Important international jurisdictions are placing more emphasis on human authorship, while policy discussions show different perspectives on how to acknowledge AI-generated originality. The compatibility of current copyright doctrine with algorithmic creativity is analysed in this work, which explores these normative and jurisprudential conflicts.

It examines unanswered problems about training datasets and derivative use, critically evaluates new foreign models, and assesses India's readiness to deal with these technological upheavals. The research comes to the conclusion that in order to keep Indian copyright law in line with changing technological realities while maintaining its fundamental humancentered principles, calibrated legislative reform—clarifying authorship, originality requirements, and liability is essential. Keywords: Artificial Intelligence; Labour Theory of Copyright; Generative Creativity; Indian Copyright Law; Authorship Doctrine.

INTRODUCTION

The emergence of artificial intelligence (AI), especially advanced generative systems like autonomous music composers, diffusion-based picture generators, large language models (LLMs), and multimodal creative engines, has drastically changed the world of creativity. Long-form prose, visual art, software code, and complex audiovisual works can all be produced by these algorithms in a way that increasingly resembles—and occasionally exceeds—human creative abilities. Long-standing copyright presumptions, particularly those pertaining to authorship and originality, which have traditionally been based on human intellectual labor, must be fundamentally reconsidered in light of this technological acceleration. 1 The labour-desert hypothesis, which is based on John Locke's natural rights theory, continues to be the foundation of Indian copyright law.

Copyright protection is justified since the author spends labor, skill, and judgment in creating a work, according to the Indian legal framework and court interpretation. Landmark rulings like Macmillan v. Cooper and Eastern Book Company v. D. B. Modak, in which judges determined that originality required at least a minimal degree of human intellectual effort, have strengthened this labor-centric foundation. Therefore, the normative and doctrinal core of Indian copyright jurisprudence is the human intellect. 2 The idea that human intellect and personality are inextricably linked to creation is prominently reflected in Indian copyright law. 3 As a result, copyright is safeguarded as an extension of the author's uniqueness and dignity as well as an economic privilege. 4 This humancentric basis is strengthened by Section 57 of the Copyright Act, 1957, which protects moral rights.

5 The theoretical link between creativity and human personality would be undermined if authorship were extended to AI systems devoid of consciousness or personal identity. 6 This fundamental premise is called into question by the emergence of autonomous generative AI. Because they lack aim, consciousness, expression, and individual creativity, machines do not "labor" in the Lockean or legal sense. The logical and legal foundation of protection—that is, human talent and intellectual labor—seems to crumble when AI systems produce material without significant human involvement. This poses a crucial question: given the growing

1 John Locke, Second Treatise of Government, 1690.

2 Macmillan v. Cooper, (1923) 50 IA 324; Eastern Book Company v. D.B. Modak, (2008) 1 SCC 1.

3 Supra note 1

4 Supra note 2

5 The Copyright Act, 1957, s. 57.

6 Lionel Bently & Brad Sherman, Intellectual Property Law (Oxford University Press, 2014).

distance between human agency and the act of production, can Indian copyright law still be based on a human-centric labor theory? Urgent intellectual and legislative attention is needed to resolve the conflict between human-based copyright doctrine and non-human creation. 7 Although Section 2(d)(vi) of the Copyright Act of 1957 designates the author of a "computergenerated work" as the person who "causes the work to be created," this statutory language originated in an era of simple automated programs rather than autonomous generative systems capable of producing independent creative expression. The judiciary has not yet addressed whether AI-generated outputs meet the originality criteria, whether prompting an AI system qualifies as adequate authorship, or whether these works automatically become public domain.

Therefore, the current legal framework is not adequate to support the creative and epistemic autonomy of contemporary AI systems. 8 The paper places AI-generated innovation in the context of Indian copyright law's larger philosophical, legal, and doctrinal framework. It questions if the labor-desert conceptual framework can continue to be useful in a time when creative activity is done by machines rather than by people. The paper makes the case that Indian copyright law is facing a revolutionary moment by looking at statutory ambiguities, judicial silences, comparative international developments, and theoretical conflicts. Fundamental doctrinal revaluation and carefully calibrated legal reform will be necessary to reconcile machine-generated innovation with traditional human-based authorship. 9

LABOUR THEORY OF COPYRIGHT IN INDIA

The Lockean philosophical tradition, which holds that property rights emerge when a person "mixes their labor" with unowned resources, has a key effect on the labor theory of copyright in India. According to this concept, creative works are seen as the logical progression of the author's personality, effort, and intellectual labor. This normative perspective has been consistently upheld by Indian copyright doctrine, which emphasizes that originality results from the demonstrable application of skill, labor, and judgment by the human author rather than only from novelty. As a result, courts view copyright as a way to acknowledge the author's 7 Andres Guadamuz, “Artificial Intelligence and Copyright,” Journal of Intellectual Property Law, 2022.

8 Copyright Act, 1957, s. 2(d)(vi).

9 WIPO, AI and IP Policy Report, 2021

moral and financial claim to the products of their labor as well as a reward for intellectual investment. 10 This labor-centric theory is still based on the Privy Council's ruling in Macmillan v. Cooper. The Court firmly established the labor-desert theory in Indian copyright doctrine by ruling that originality does not necessitate groundbreaking inventiveness but rather must demonstrate the "application of the author's skill, labor, and judgment. " In Eastern Book Company v. D. B. Modak, the Supreme Court further improved this strategy by adopting the "modicum of creativity" test, which struck a balance between labor-based protection and the need to avoid monopolization of purely clerical or mechanical work.

The Indian judiciary upholds a uniquely human-centric understanding of copyright through these rulings, which are based on intellectual endeavour rather than merely mechanical manufacturing. 11 As a result, Indian courts view authorship as a fundamentally human endeavour that calls for intellectual application, intentionality, and creative agency. An authorship framework that is incompatible with mechanical or algorithmic creation without human involvement is reinforced by this jurisprudential foundation, which places human labor as the doctrinal core of copyright protection. 12 Indian Copyright Law Application This human-centric labor history is reflected at the legislation level in the Copyright Act, 1957.

While Section 2(d) clearly defines "author" in terms that assume a human intellectual agent— such as the writer of a literary work, the composer of a musical work, or the creator of an artistic work—Section 13 protects original literary, dramatic, musical, and artistic works. The Act affirms that copyright protection results from human intent and creative effort, even while it acknowledges "computer-generated works. " It does this by anchoring authorship in the person "who causes the work to be created. " As a result, labor is still implicitly but crucially ingrained in the legal framework, connecting creativity to the author's intellectual engagement. 13 Recognizing AI as a copyright owner or even as a creative topic is severely hampered by this strong doctrinal and legal connection between human effort and authorship. AI systems cannot

10 Supra note 1.

11 Supra note 1

12 Lionel Bently & Brad Sherman, Intellectual Property Law, Oxford University Press, 2019.

13 Copyright Act, 1957, ss. 2(d), 13.

meet the labor-based originality barrier required by Indian law since they lack consciousness, intention, or moral personality. Because of this, AI-generated works fall into a conceptual gap in the existing legal framework, exposing the shortcomings of a labor-centric approach in a time when machines are increasingly performing jobs that have historically been linked with human creativity. As a result, the law is still structurally opposed to the notion of non-human authorship, which emphasizes the necessity of updating the copyright system to reflect advancements in technology.14

ARTIFICIAL INTELLIGENCE AND THE DISRUPTION OF LABOUR-BASED

COPYRIGHT

Nature of AI-Generated Works: Deep neural networks, transformer-based models, and multimodal frameworks are examples of complex machine-learning architectures used by contemporary generative AI systems. These architectures are trained on enormous text, image, audio, and video corpora. After being trained, these systems can generate outputs with uniqueness, coherence, and aesthetic value without the need for direct human participation throughout the production process. In many instances, the algorithm completes the significant creative transformation after the human user simply provides a quick command or "prompt. " Such machine-driven innovation calls into question the fundamental tenet that works protected by copyright must be the product of human talent, labor, and intellectual judgment.

It becomes challenging to assign authorship in the conventional labor-centric sense if the human contribution is restricted to starting an automated process. This raises the crucial question of whether such works satisfy the originality requirement under Indian copyright law. 15 Statutory Ambiguities: Section 2(d)(vi): A computer-generated work's "author" is defined as "who causes the work to be created" in Section 2(d)(vi) of the Copyright Act, 1957. But this clause was written in 1994, a time when basic algorithmic or rule-based outputs were more important than the autonomous creative potential of modern AI. Consequently, there is a great deal of uncertainty in the legislative language. First of all, the statement "causes the work to be created" is conceptually ambiguous. Does a person need to have substantial creative control, or does just inputting a prompt constitute causation?

Second, a minimal or passive role—like giving a prompt—might not meet the requirement of uniqueness because the labor theory

14 WIPO, Issues Paper on Intellectual Property Policy and AI, 2021.

15 Lionel Bently & Brad Sherman, Intellectual Property Law, Oxford University Press, 2019.

demands human intellectual activity. Third, the clause ignores the significant qualitative distinction between the probabilistic, generative outputs of contemporary AI models and deterministic software outputs. As a result, Section 2(d)(vi) seems to be out of date, making Indian law unprepared to handle the doctrinal challenges presented by sophisticated AI inventiveness. 16 Judicial Silence and Emerging Global Trends: There is a significant jurisprudential gap since Indian courts have not yet addressed AI-generated writing in a meaningful way. On the other hand, a number of international jurisdictions have started to express more precise stances. Asserting that copyright only exists in works reflecting human authorship, the U. S. Copyright Office has frequently refused to register works created entirely by AI.

The UK takes a practical but somewhat contentious stance when it comes to recognizing computer-generated works, but it does so with a limited originality threshold and a shorter term of protection. The necessity of human authorship and accountability in creative processes is emphasized by the European Union's developing AI governance framework, which includes the AI Act and other regulatory tools. India's labor-based originality theory, which is firmly rooted in human intellectual endeavour, is only partially compatible with these global changes, despite their powerful influence on Indian politicians. The discrepancy highlights the necessity for India to develop a cohesive framework of its own instead of merely copying examples from other countries. 17 AI-generated creativity has real-world economic ramifications as well.

In digital businesses including design, publishing, and music, machine-produced material could replace human creators if it is granted equal copyright protection. 18 According to the labor-desert justification, this compromises the incentive structure that copyright seeks to maintain. 19Indian courts have generally recognized that the purpose of copyright is to prevent undue enrichment and to reward human labour. 20

KEY CHALLENGES POSED BY AI TO THE LABOUR THEORY OF COPYRIGHT

Absence of Human Labour: The almost total lack of human intellectual labor during

16 Copyright Act, 1957, s. 2(d)(vi); WIPO, AI and IP Policy Report, 2021.

17 U.S. Copyright Office, Policy Guidance on AI-Generated Works, 2023; UK CDPA 1988, s. 9(3); European Parliament, Resolution on AI and Intellectual Property, 2020.

18 Daniel Gervais, “Authorship and AI,” (2020) 54(1) Vand. J. Transnat'l L. 143.

19 Supra note 2

20 Ibid.

the creating process is a fundamental challenge presented by AI-generated creativity. Through self-learning models, generative AI systems independently carry out creative and expressive tasks, replacing the human agency that has historically been thought of as the foundation of authorship. According to the labor theory, neither a machine nor a human who merely starts the AI process may be granted copyright as the machine is neither a legal person nor capable of moral or intellectual labor. This doctrinal gap highlights the conflict between algorithmic innovation and the labor-desert idea by creating a strong presumption that such works may automatically fall into the public domain. 21 • Ownership of Training Data: The training datasets used to create generative AI models provide a second significant obstacle.

Large amounts of copyrighted content that have been scraped from websites without permission are frequently used to train these algorithms. The intake of copyrighted works during training poses important ethical and legal questions, including whether it violates Indian copyright law and whether the original human creators, whose labor forms the basis of the training corpus, should be compensated. According to labor theory, the value of AI outputs is directly based on the collective intellectual labor of thousands of writers; hence, the inability to acknowledge or compensate that labor raises issues of doctrinal consistency and fairness. When AI-generated products effectively replace or stylistically replicate human creative labor, this problem becomes much more complicated.

22 • Originality and the Modicum of Creativity Standard: A "modicum of creativity" is required by Indian copyright law to prove uniqueness, however AI-generated works undermine this requirement in two ways. Because they don't have human authorship, which is a need of the labor theory, these works could be considered non-original. AI outputs, on the other hand, might be very creative, complex, and aesthetically coherent, meeting or beyond judicially set standards of originality. This contradiction reveals a doctrinal fault line: AI-generated works cannot be considered original if originality is dependent on human intellectual effort; but, if originality is solely assessed in terms of output quality, AI-generated works may unintentionally be protected, defying labor-

21 Lionel Bently & Brad Sherman, Intellectual Property Law, Oxford University Press, 2019.

22 Andres Guadamuz, “AI Training Data and Copyright,” Journal of Intellectual Property Law, 2022.

based reasoning. Therefore, the way originality has traditionally been conceptualized in Indian law is profoundly undermined by AI systems. 23 • Moral Rights and Human Dignity Considerations: The idea that a creative work embodies the personality, dignity, and expressive liberty of the author is the foundation for moral rights under Section 57, such as the right to integrity and the right to attribution. Since AI systems lack consciousness, intention, and moral personality, these rights cannot be rationally or legally extended to them. Therefore, acknowledging AI as a "author" would weaken the humanistic underpinnings of moral rights jurisprudence and weaken the dignitarian justification for Indian copyright law. Because human creative agency is prioritized by both labor theory and moral-rights doctrine, attributing authorship to AI is both theoretically and normatively problematic.

24 • Enforcement and Liability: Traditional legal liability frameworks are further complicated by AI-generated inventiveness. It is very challenging to assign blame when AI creates derivative, libelous, or infringing works. Since AI systems don't have mental states, the labor theory assumes a human creator whose intent, carelessness, or misconduct may be assessed. This raises the question of who should be held accountable: the developer, the deployer, or the end-user. Furthermore, it is difficult to assess whether violation was predictable or avoidable due to the opacity of machinelearning procedures (sometimes known as "black box" systems). The inadequacy of labor-based doctrine in controlling AI-driven innovation is further demonstrated by the lack of a defined liability framework.

25 • Enforcement, Accountability and Liability Gaps: Legal accountability is one of the main justifications for recognizing a human author. 26 Because generative AI lacks legal personhood and mens rea, it cannot be held accountable for infringement, defamation, or derivative misuse. 27 Autonomous algorithmic outputs cannot be governed by the Information Technology Act's current doctrine on vicarious liability and intermediary

23 Eastern Book Company v. D.B. Modak, (2008) 1 SCC 1

24Supra note 12; Mira T. Sundara Rajan, Moral Rights, OUP, 2011

25 OECD, Principles on Artificial Intelligence, 2019; WIPO, AI and IP Policy Report, 2021.

26 Lawrence Lessig, Free Culture (Penguin Press, 2004).

27 Shyam Sundar v. State of Rajasthan, (1974) 1 SCC 690

requirements.28 As a result, giving AI credit for authorship would leave a responsibility gap that is inconsistent with accepted copyright enforcement guidelines.29

RECONSIDERING LABOUR THEORY IN THE AI ERA

1. Limitations of the Labour Theory: Despite its historical foundations, the labor theory

of copyright has serious conceptual flaws when it comes to autonomous AI creativity. The theory assumes agency, intentionality, and subjective judgment and is based on the idea that authorship results from human effort, intellectual innovation, and a moral bond between the creator and the generated product. However, rather than using deliberate creative effort or expressive aim, generative AI systems rely on data-driven algorithms and stochastic modelling. Their outputs come from computational processes that lack personality, autonomy, or moral commitment, even though they can occasionally be mistaken for human inventions. Therefore, the standard theoretical framework is insufficient to handle AI-generated creativity since the labor-desert explanation breaks down when the entity producing the work lacks the capacity for human-like labour.

2. Public Domain as a Safeguard: AI-generated works that are entirely autonomous are

guaranteed to enter the public domain if they are not protected by copyright.30 This strategy supports the utilitarian role of copyright by preventing technology owners from monopolizing the market and facilitating broad cultural access. 31 It strikes a vital balance between rewarding human creators and guaranteeing that works without human authorship are nevertheless publicly available.32

3. A Hybrid Attribution Model Is Necessary: A hybrid attribution approach that

differentiates between varying degrees of human engagement in AI-mediated creativity is becoming more and more popular in contemporary studies in awareness of these flaws. Authorship may legitimately remain with the human user in situations when AI serves just as a tool and the human creator has significant skill, judgment, and expressive control. On the other hand, depending on the degree of the supervising person's creative contribution, limited credit may be given to them in situations when

28 The Information Technology Act, 2000, s. 79.

29 Mark Lemley, “Intellectual Property & Algorithms,” (2021) Stanford Law Review.

30 Rebecca Giblin, The Public Domain and Innovation, Melbourne Univ. Press (2019).

31 William Fisher, “Theories of Intellectual Property,” Harvard Law School (2001).

32 Prashant Reddy, “AI and Public Domain in India,” (2023) NUJS L. Rev.

AI creates material on its own but is supervised or guided by humans. In order to prevent the conceptual errors that result from pushing such works into human-centric copyright policy, experts suggest sui generis protection adapted to algorithmic creativity for completely autonomous AI-generated outputs. To implement such distinctions, India may need to revise Sections 2(d) and 13 of the Copyright Act, ensuring doctrinal coherence and technological relevance.33

4. Aligning Indian Law with International Practices: It is crucial to align domestic

copyright laws with new international standards as India's digital innovation ecosystem grows. While simultaneously investigating strategies for managing AI-generated material and controlling the use of training datasets, jurisdictions like the United States, the United Kingdom, and the European Union are placing an increased focus on human authorship. In order to prevent systematic exploitation of human creative labor, India must protect human writers from unfair competition resulting from machine-generated outputs, regulate the ingestion of copyrighted training data, and provide legal clarity for creators using AI technologies. India will be able to stay competitive in the digital economy while maintaining copyright law's foundation in justice, accountability, and human-centered principles with a forward-thinking, globally aware approach.34

RECOMMENDATIONS FOR INDIA

1. Amend Section 2(d)(vi): In order to clearly include the necessity of meaningful human

creative contribution in defining authorship, India should review and significantly amend Section 2(d)(vi) of the Copyright Act, 1957. The amended clause must make a clear distinction between AI-generated works, where human intellectual labor is either non-existent or very low, and AI-assisted works, where human creators continue to be the principal authors. To eliminate doctrinal ambiguity, stop authorship misattribution, and harmonize Indian law with changing international norms on human-centric copyright protection, such statutory clarification is crucial.35

2. Introduce Sui Generis Protection for AI-Generated Works: India should think about

creating a sui generis system that is especially suited to AI-generated works, since

33 WIPO, Revised Issues Paper on Intellectual Property and AI, 2020.

34 European Parliament, Resolution on AI and Intellectual Property Rights, 2020; U.S. Copyright Office, Policy on AI-Generated Works, 2023. 35 Copyright Act, 1957, s. 2(d)(vi); WIPO, Revised Issues Paper on Intellectual Property Policy and AI, 2020.

autonomous AI outputs do not meet traditional labor-based originality standards. Narrowly defined rights to regulate diffusion, short-term protection, and the explicit exclusion of moral rights—which are predicated on human personality and dignity— are some examples of this framework. A sui generis regime would prohibit the excessive expansion of copyright monopolies to non-human actors while simultaneously encouraging technical advancement.36

3. Require Training Data Transparency: Mandatory training data disclosure requirements

for AI developers should be introduced through legislative reform. The sources of training datasets, underlying licensing agreements, and payment methods for the usage of copyrighted works should all be disclosed by developers. In addition to encouraging ethical AI research and adherence to fair-use and licensing standards, such transparency is essential for protecting the rights of the original human inventors whose labor underpins the training data.37

4. A Tiered Legal Framework Is Necessary: Indian law necessitates a distinct approach to

authorship due to the differing degrees of AI engagement.38 Human inventors must maintain copyright as long as they retain a significant level of expertise, discretion, and creative intellectual effort.39 On the other hand, a sui generis right might be more effective than traditional copyright for autonomous AI outputs.40

5. Establish Safe Harbor with Responsible AI Requirements: If AI developers,

intermediates, and deployers adhere to well-defined responsible AI obligations, India should implement a calibrated safe harbour structure that shields them from undue liability. Safeguards against infringing outputs, restitution procedures, content filtering procedures, and adherence to ethical standards are a few examples of these responsibilities. While guaranteeing responsibility in the implementation of AI-driven creative systems, a well-balanced safe harbour policy would encourage innovation.41 36 European Parliament, Resolution on Intellectual Property Rights for the Development of AI Technologies, 2020.

37 Andres Guadamuz, “AI Training Data and Copyright,” Journal of Intellectual Property Law, 2022.

38 M. Sen, “Reforming Indian Copyright for Artificial Intelligence,” (2022) 64 JILI 88.

39Eastern Book Company (n 2)

40 WIPO, AI and IP Policy Report (2023).

41 OECD, Principles on Artificial Intelligence, 2019.

CONCLUSION

For Indian copyright law, artificial intelligence offers both opportunities and disruptions. Long ingrained in Indian originality philosophy, the labor hypothesis finds it difficult to account for creative products produced without human intellectual work. The conceptual underpinnings of authorship, creativity, and labor are stressed as generative AI systems become more autonomous creative agents. While Section 2(d)(vi) provides a basic foundation for computergenerated works, it is both doctrinally and technologically inadequate to handle the complexity of contemporary AI innovation. Therefore, India needs to develop a balanced legal response that protects human authors' rights and dignity while promoting an atmosphere that is conducive to technology advancement.

This calls for a cogent national policy on AI and intellectual property, as well as legislative change and moral judicial interpretation. Indian copyright law can only be reconciled with the reality of algorithmic creation while upholding its core human-centric ideals through such integrated solutions. The emergence of AI necessitates a hybrid strategy that strikes a balance between labor-based arguments and innovation-driven policy objectives. 42 Future reforms must properly regulate AI-generated expression while safeguarding human dignity and creative labor. 43 In order to avoid doctrinal obsolescence and advance a just creative economy, India's copyright laws must change proactively. 44

42 Abhilash Nair, Artificial Intelligence and the Law, Springer (2021).

43 EU AI Act, European Commission (2024) – human agency requirement.

44 Indian Parliamentary Committee on IP and Technology, Report No. 161 (2023).

REFRENCES

A. BOOKS

1. John Locke, Second Treatise of Government (1690).

2. Lionel Bently & Brad Sherman, Intellectual Property Law (Oxford University Press,

2019).

3. Mira T. Sundara Rajan, Moral Rights: Principles, Practice and New Technology

(Oxford University Press, 2011).

4. Cornish, Llewelyn & Aplin, Intellectual Property: Patents, Copyright, Trade Marks

and Allied Rights (Sweet & Maxwell, 9th ed., 2019).

B. STATUTES

5. Copyright Act, 1957, Sections 2(d), 2(d)(vi), 13, 57.

6. Copyright, Designs and Patents Act, 1988 (United Kingdom), Section 9(3).

7. EU Artificial Intelligence Act, Regulation Proposal (2021–2023).

C. JOURNAL ARTICLES

8. Andres Guadamuz, “AI Training Data and Copyright,” Journal of Intellectual Property

Law (2022).

9. Pamela Samuelson, “The Quest for Human Authorship in Copyright,” Columbia

Journal of Law & the Arts (2020).

10. Mark Lemley & Bryan Casey, “Fair Learning: Copyright Law and Artificial

Intelligence,” Stanford Technology Law Review (2019).

11. Ryan Abbott, “The Reasonable Robot: Artificial Intelligence and the Law,” Journal of

Law & Innovation (2020).

D. CASE LAW

12. Macmillan v. Cooper, (1923) 50 IA 324 (Privy Council).

13. Eastern Book Company v. D.B. Modak, (2008) 1 SCC 1.

14. University of London Press Ltd. v. University Tutorial Press Ltd., [1916] 2 Ch 601.

15. Feist Publications v. Rural Telephone Service Co., 499 U.S. 340 (1991).

E. INTERNATIONAL REPORTS / POLICY DOCUMENTS

16. WIPO (World Intellectual Property Organization), Revised Issues Paper on Intellectual

Property Policy and Artificial Intelligence (2021).

17. U.S. Copyright Office, Policy Guidance on Copyright Registration for Works

Containing AI-Generated Material (2023).

18. European Parliament, Resolution on Intellectual Property Rights for the Development

of Artificial Intelligence Technologies (2020).

19. OECD, OECD Principles on Artificial Intelligence (2019).

20. European Commission, White Paper on Artificial Intelligence – A European Approach

to Excellence and Trust (2020).