AI-Generated Works And Copyright Ownership - The Indian Perspective
Author: LawSphereX
Category: Intellectual Property
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AI-GENERATED WORKS AND COPYRIGHT OWNERSHIP:
THE INDIAN PERSPECTIVE Pranay Sundriyal, BBA LLB, Gitarattan International Business School, Guru Gobind Singh Indraprastha University (GGSIPU)
ABSTRACT
In an era of rapidly advancing generative artificial intelligence (AI) technologies, the question of copyright ownership for AI-generated creative works has come to the fore of legal discourse worldwide. Indian copyright law – rooted in a statute drafted in 1957 – makes no explicit provision for content autonomously produced by machines, leaving uncertainty as to who (if anyone) can claim authorship or ownership of such works. Recent government statements in India have suggested that existing intellectual property laws are sufficient: for example, the Commerce Ministry has declared the current regime “well-equipped to protect AI-generated works” and indicated no plan to create a separate category of rights. This study provides a comprehensive examination of AI-generated works and copyright ownership from the Indian perspective.
It begins with a review of relevant scholarship and policy commentary and sets out the doctrinal foundations of authorship and originality – noting that copyright traditionally hinges on a human author’s “intellectual creation” or individual imprint. The core analysis then surveys India’s legal framework, including the key statutory definitions of “author” and “computer-generated work” and the judicial treatment of originality and authorship. It highlights that although Section 2(d)(vi) defines the author of a computer-generated work as “the person who causes the work to be created”, Indian courts have interpreted “person” to mean a natural human being, generating tension with AI outputs. A comparative section examines approaches in the UK, US, and EU – for example, the UK’s CDPA s.
9(3) rule for computer-generated works, and the US Copyright Office’s strict human-authorship requirement – to show that jurisdictions vary from denying copyright to purely AI works to allowing conditional human-centric attribution. Finally, the paper discusses policy considerations (balancing innovation incentives, fairness to human creators, and data access for AI training) and offers reform proposals. For instance, legislative amendments could clarify that only works with meaningful human creative input qualify for protection or expressly attribute authorship to the human instigator of the AI process, while ensuring appropriate exceptions for AI training. These proposals aim to reconcile encouragement of innovation with safeguarding the rights of human authors.
Introduction
Generative artificial intelligence (AI) has dramatically expanded machines’ ability to produce literary and artistic works with minimal human input. Modern AI models like OpenAI’s ChatGPT or image generators such as DALL·E and Midjourney can create outputs that closely mimic human-made content. This technological advance raises fundamental copyright questions: are such outputs protectable at all, and if so, who can claim authorship? Under traditional copyright theory, protection attaches only to “original” works reflecting an author’s personal creative contribution or “intellectual creation”. In practice, jurisdictions have insisted that originality implies a human origin; for example, the EU’s highest courts state that a work must embody the author’s “own intellectual creation” for copyright to subsist. Non-human outputs thus strain copyright’s human-centric assumptions.
India’s Copyright Act, 1957 predates these developments and contains no explicit provision for autonomous machine authorship. Notably, the Act was amended in 1994 to address “computer-generated works” (see infra), but even then, defines the author as “the person who causes the work to be created” – language broad enough to include an AI user or programmer. In practice, however, Indian courts have consistently required an author to be a natural human being. For example, in Rupendra Kashyap v. Jiwan Publishing House (Delhi HC 1997) the court held that the Central Board of Secondary Education (a corporate entity) could not claim copyright in exam question papers unless human authors were identified; it emphasized that “only a natural person can claim authorship”. The same principle was reaffirmed in Tech Plus Media v. Jyoti Janda (Delhi HC 2013).
These precedents suggest that purely AI-generated works (with no meaningful human input) would likely fall outside copyright’s protection under current law. These issues are not merely theoretical. Litigation has already begun in India. In late 2024 the Delhi High Court admitted ANI Media Ltd. v. OpenAI, a suit by a major news agency alleging that ChatGPT’s use of its copyrighted news articles for training infringes the Act. The case will test whether India’s existing exception for “fair dealing” (s. 52) can accommodate large-scale AI training or whether unlicensed copying occurs. Meanwhile, the policy debate has gained momentum. In Parliament, the Commerce Ministry stated that the current law “is wellequipped to protect AI-generated works” and that no new class of rights is planned.
In April 2025, recognizing global urgency, the government convened an eight-member expert panel to review whether the Copyright Act should be updated for the AI era. These developments underscore the need for legal clarity. Against this backdrop, this paper asks: what does Indian law currently imply about AIgenerated works, and how should it adapt? Part I reviews existing scholarship and commentary on AI and copyright. Part II sets out doctrinal principles of authorship and originality. Part III examines India’s statutory framework and case law on authorship and computer-generated works. Part IV compares approaches in the UK, US, and EU. Part V considers policy tradeoffs (creativity incentives, technology use, data training), and Part VI proposes reforms to balance the interests of human creators and AI-driven innovation.
Literature Review Scholars and practitioners have begun to examine AI’s implications for copyright in India. A common theme is that current law contains a lacuna regarding autonomous AI output. As one analysis observes, the Act’s language “grants protection to original works that are created by humans”, leaving a grey area for outputs generated solely by algorithms. In the same vein, Maheshwari & Co (reported on Lexology) warns that Indian law “presently does not recognize AI-generated content as copyrightable unless a human can be identified as its author or controller”. Lexology notes that unless the AI output is traceably programmed or controlled by a person, there is “no clear statutory backing” for claiming rights in it.
SpicyIP, an Indian IP blog, similarly points out that since an AI outcome is not itself listed as a “work” under the Act’s definitions, it arguably falls outside the statutory scope. In short, commentators highlight that under the current text, purely machine-generated works lack an obvious author and are in a legal gray zone. On the question of authorship, multiple commentators conclude that AI cannot itself be an author. Chakraborty (2019) argues that an AI system cannot hold legal responsibility and thus cannot meet the definition of “author” under Indian law. This mirrors views in other jurisdictions: for example, in the US Naruto v. Slater case the courts held that only a human can be an author. Similarly, an Indian analysis reasons that the Act’s notion of “person” contemplates only natural persons, so without a human “imprint” the work lacks requisite originality.
A consequence noted in the literature is that any copyrightable work must have meaningful human contribution. The Atlantic Council blog on global AI and copyright cites an Indian law report observing that under India’s originality standard, which looks for something beyond mere compilation, AI outputs (being algorithmic compilations) “may not satisfy the required creativity” to qualify as original works. There is also attention to how other countries are handling the issue. UK commentators note that the UK Copyright Act’s Section 9(3) treats the programmer or user as author of certain computer-generated works, but only where no human author is available. US commentators emphasize the U. S. Copyright Office’s policy (2023) that works without any human author are ineligible for protection.
Indian literature refers to these international models, but stresses that India has not explicitly adopted any such approach and must interpret its older law. In sum, existing writings underscore uncertainty: while government officials assure that “current framework” suffices, legal scholars see a mismatch between that stance and the Act’s text as interpreted by courts. This paper builds on those analyses by delving into the statutory provisions, recent court cases, and international comparisons to form a coherent picture. Theoretical and Doctrinal Framework To evaluate AI-generated works under copyright, it is useful to recall the foundational concepts of authorship and originality. Copyright doctrine has historically assumed that an author is a sentient creator – often invoking labor or personality theories.
Under the labor theory (classically Locke’s idea), copyright protects the products of an author’s intellectual labor; the personality theory (e. g. Hegel) views a work as an extension of the creator’s individual personality. Both theories presuppose human agency and intent. From a utilitarian or incentive perspective, copyright rewards creative effort by human authors to encourage future works. Crucially, these theories offer little reason to grant protection when no human mind was involved in the creation of work. In practice, legal tests reflect these human-centric notions. For originality, many systems have adopted either a “modicum of creativity” standard (as in Feist Publications v. Rural Telephone Service in the U. S. ) or a “skill and labour” or “sweat of the brow” test (used in older Indian and Commonwealth cases). The Indian Supreme Court in Eastern Book Co. v. D. B.
Modak (2008) clarified that India’s originality test requires a “modicum of skill, labour or judgment”, but emphasized that mere mechanical compilation of data is insufficient. Even this low threshold, however, assumes some human imprint on the work. By contrast, output wholly generated by AI is produced by algorithms that mimic creativity but do so through statistical processing rather than human insight. Critics therefore note that AI lacks an “imprint of personality”; its outputs, no matter how complex, are not the product of a conscious creative process. As one commentator summarizes for the EU: a work is original only if it emanates from the author’s own intellectual creation and bears the author’s personal stamp. Purely AI-originated works have none of these hallmarks.
Moreover, doctrines like the idea-expression divide and fair use have been developed with human authors in mind, and their application to AI remains speculative. Until copyright law explicitly addresses AI, courts will likely apply existing principles: requiring some human creative contribution. Any doctrinal analysis must then grapple with how much and what kind of human intervention is needed. Some suggest treating AI as a tool (like a camera or computer program) so that a human “operator” is deemed the author, while others propose a sui generis approach. These issues frame our subsequent examination of the statutes and cases. Indian Legal Framework: Statutory and Case Law Analysis Statutory Definitions and Provisions. The Indian Copyright Act 1957 does not use the term “AI” but was amended to cover certain computer-generated works.
Section 2(d) defines “author” for various categories; crucially, s. 2(d)(vi) (as added in 1994) provides that for a computer-generated literary, dramatic, musical or artistic work, the author is “the person who causes the work to be created”. In parallel, Section 2(ff) (as amended) defines a “computergenerated work” to mean a work “generated by a computer in which there is no human intervention”. These provisions were evidently drafted with conventional software in mind: e. g. a computer program or typescript prepared by machine, with humans overseeing the process. The key term in s. 2(d)(vi) is thus “person”. Under s. 2(m), “person” includes individuals, companies, and even government, but excludes the State. Indian courts have read this in context to require a natural (human) person as the author. Beyond definitions, the Act lays down other rules.
Section 13 limits copyright to “original literary, dramatic, musical and artistic works”. Section 14 leaves “original” undefined, so courts have filled the gap. As noted, Eastern Book Co. v. Modak held that originality means the work is not a copy of another and that it embodies the author’s skill and labour beyond mere routine. Section 17 then governs first ownership, usually vesting copyright in the author, but with exceptions (e. g. works of hire, commissioned works, government works). Significantly, there is no special regime in the Act assigning authorship or ownership for AI beyond the computer-generated clause. If an AI tool creates a painting, it is neither a computer program nor a mere publication – so which category applies? Under current text, one must shoehorn it into existing definitions (e. g.
treat it as a literary/artistic work “by computer”) or else conclude no copyright subsists. Case Law on Authorship and Originality. Indian courts have yet to squarely address AI, but their general rulings on authorship set the tone. The key cases are Rupendra Kashyap v. Jiwan Publishing and Tech Plus Media v. Jyoti Janda (both Delhi HCs). In Rupendra Kashyap, the issue was whether the CBSE (as first owner of exam papers) could be the author; the court held no – it was an “artificial person” and could not claim authorship unless human exam-writers were identified. It stated emphatically that “only a natural person can claim authorship”. Tech Plus Media likewise rejected a claim that copyright resided in a corporate publisher, reaffirming that authorship requires an actual human creator. More recently, in Navigators Logistics Ltd. v.
Kashif Qureshi (Delhi HC, 2018) the court refused copyright in a list generated by a computer, explicitly citing lack of human intervention. These decisions have been interpreted (by commentators) as implicitly holding that an AI or computer alone cannot be an author – the output must be ultimately attributable to a human. No reported judgment in India has yet dealt with a purely AI-generated work. The ANI Media v. OpenAI case (ongoing) does not yet address authorship, focusing on data copying. Other decisions on related issues are also instructive: for example, the Delhi High Court in Eastern Book Co. v. D. B. Modak (2008) emphasized the low originality threshold (skill, judgment) but did not confront a machine-author scenario. Lower courts have maintained that juristic entities cannot be authors, and indeed the Copyright Act’s moral rights provisions (s. 57) presuppose a living author.
In sum, while Indian courts value protection for creative labour, they have uniformly tied authorship to a human source. Under current law, the only “author” of a computer-generated work is thus likely the human who initiated or controlled the process – whether that be the programmer, the user entering a prompt, or another person – but not the AI system itself. In practical terms, this means an AI-generated artwork would need a human claimant. Some have suggested treating the AI’s developer or the person who deployed the AI as the author. However, without clear legislative guidance, these attributions would rest on analogies (e. g. to photographic authorship or film producers) rather than on explicit text. Until the law is clarified, the safest view under existing case law and statutes is that no copyright subsists in an output created entirely without human creative input.
This leaves a policy gap that the expert panel and Parliament will need to address. Comparative Analysis (UK, US, EU) Examining other jurisdictions provides useful contrasts. In the United Kingdom, the Copyright, Designs and Patents Act 1988 (CDPA) contains a special rule: section 9(3) states that for “computer-generated” works with no human author, the author is “the person by whom the arrangements necessary for the creation of the work are undertaken”. In practice, this has been interpreted to mean the programmer or person commissioning the work can be deemed author of, say, a computer-generated image or text. Thus, UK law effectively backfills an author for certain AI-like outputs, ensuring copyright subsists and vests in a human (or legal) person. Case law is limited, but the Naruto v. Slater principle also applies: purely non-human authors (like animals or AI) are excluded.
The UK intellectual property office’s recent guidance (2023) similarly expects some human creative input for protection. In the United States, the approach is stricter: copyright subsists only in works of human authorship. The U. S. Copyright Office’s policy guidance (Mar 2023) explicitly excludes works created by AI without any human contribution. Courts have enforced this: for instance, Naruto v. Slater (2018) held that a monkey’s selfie was not protected because no human created it; by analogy, many commentators conclude that an AI autonomously generating content cannot be an author. The AIPPI report notes that U. S. judges and the Copyright Office have repeatedly denied protection to works lacking a human element. Some U. S. suits (e. g. the Zarya of the Dawn appeal) and proposed regulations (2024) reinforce that “the selection and arrangement must be done by a human” for copyright.
In the European Union, the situation is in flux. EU copyright law (the InfoSoc Directive 2001/29/EC and its successors) requires human intellectual creation for originality – as affirmed by the Court of Justice of the EU. Accordingly, fully AI-generated works with no human author are generally considered unprotectable in the EU (they effectively fall into the public domain). However, the EU has explicitly addressed AI in its recent Digital Markets Act (AI Act, 2023). Article 53 of the AI Act mandates that providers of generative AI comply with copyright laws and (crucially) disclose their training data or ensure licenses for copyrighted material used. This institutional approach emphasizes licensing and liability rather than new categories of copyright.
Some EU member states (through national law or forthcoming proposals) may move towards hybrid solutions (for example, requiring a threshold of human creativity for AI art) but no unified change has been made yet. To sum up, the UK provides copyright to AI outputs by attributing authorship to a human “arranger”; the US and EU (so far) refuse protection absent human involvement. India’s stance – anchored in its older statute and case law – aligns more with the latter camps, at least in terms of its underlying principles. However, India must decide whether to follow the UK model of annexing a human author (and if so, which person qualifies), or to stick with the traditional human-only rule. Policy Considerations Any legal response must balance competing policy goals. On one side is the desire to incentivize creation and maintain a robust body of creative works.
If AI-generated content were automatically granted perpetual copyright (say, in the AI itself), this could stall the entry of those works into the public domain and limit reuse. It could also create “zombie copyrights” if the AI has no lifespan – a concern noted by analysts (who observed that an AI author could never die, making the 60-year term potentially perpetual). Conversely, depriving all AI outputs of protection might discourage investment in AI-generated creativity (films, games, research) and could be unfair to human creators whose contributions underpin the AI’s output. Another key consideration is creativity policy vs. technological innovation. The government has signaled that it seeks to “achieve a balance between innovation, scientific progress and the rights of authors and performers” (India’s National IP Policy 2016; cf. Garcia and others).
AI holds enormous economic and social promise in India (for education, art, industry). Overly rigid copyright rules could push AI development offshore or leave creators with little recourse when their works are ingested. Indeed, the ANI v. OpenAI case highlights concerns about fair use: India’s current Section 52 exceptions (for private study, reporting, etc. ) may be inadequate to permit machine learning without explicit licences. The Commerce Ministry has hinted at this gap, stating that use of copyrighted works to train AI may still require permission. Reforms could address this – for example by carving out a research exception for AI training (as the EU and some US proposals do) – but that is a separate policy debate. Human creativity and moral rights also matter. Even if an AI tool produces a painting, there is typically a human user giving prompts.
Recognizing some human involvement helps protect human authors’ economic and moral rights. On the moral rights front, Indian law (s. 57) grants author the right to attribution and integrity. Extending similar recognition to human “prompters” could preserve the concept that art is ultimately human culture. Finally, international obligations (Berne Convention, TRIPS) must be considered. India must comply with minimum standards (e. g. protection of works against unauthorized copying), but conventions do not expressly forbid requiring a human author. India also participates in WIPO discussions on AI and IP. The 2023 WIPO SCCR draft of an “instrument” on AI noted a range of options (from sui generis AI rights to clarifying existing law) but has not mandated a particular path. In sum, policy considerations cut both ways.
The government’s interim view – that no new category of right is needed – reflects caution against legal fragmentation. But many commentators argue that clarification is needed, if not via new rights, then at least by amending definitions to reflect AI’s role. The expert panel will have to weigh these factors: fostering AI innovation and complying with international norms, while ensuring human creators are not unfairly displaced or left with inadequate protection. Reform Proposals Given the uncertainties identified, several reform paths are under discussion: • Statutory definitions. Amend Section 2 to define terms like “AI-generated work” or “AI-assisted work”. For example, a work could be declared AI-generated if it is produced by an algorithm without substantive human creative input.
The law could then specify that copyright subsists only if a human author can be identified – similar to the UK’s approach but with clarity. For instance, Parliament might explicitly state that in a computer-generated (or AI-generated) work, the “author” is the human who provided the creative input (prompted or directed the AI). This would codify that the AI itself is not an author. Conversely, if one wished to allow some AI works to be protected, one could define “AI-assisted works” (like computer graphics or film editing aided by AI) and treat them like joint authorship between human and computer. • Ownership rules. Section 17 could be amended to treat AI-generated works analogously to “works made for hire”. For example, if an AI tool generates an output under a service contract, the hiring party (not the tool’s developer) could be the first owner.
Alternatively, a new subsection could assign initial ownership of purely AI works to the human “causing” the creation (the programmer or the user). This would mirror UK s. 9(3) logic within Indian law. • Exception for training data. Parallel reforms could address training data. The government (DPIIT) has already warned that existing exceptions (s. 52) do not generally cover data mining or model training. To avoid legal uncertainty, India could introduce a specific exception for non-commercial text and data mining for AI research (as in EU Directive 2019/790). This would make it easier to use copyrighted corpora for developing AI models without infringing. Such an exception should, however, be carefully scoped to encourage research while still protecting rights-holders. • Human-authorship threshold. Law could explicitly require a “meaningful human authorship” threshold.
For example, Australia’s current approach (distinguishing full AI vs AI-assisted by human creative direction) or some South American proposals split by level of human input. India could stipulate that protection only exists if human creative choices are integral (e. g. selecting or arranging input prompts in a creative way). This would at least align with the constitutional goal to stimulate knowledge creation by humans. • Limited term or special registry. Some have floated that if AI-generated works are protected, they could have shorter terms or require registration, to prevent perpetual rights. For instance, the law could say that an AI-generated work’s term runs from the date of creation and expires after X years, with no moral rights. This would mitigate the “immortal AI” issue noted by commentators.
Alternatively, require a special registration marking works as AI-derived, to ensure transparency. • Sui generis rights (less likely). A more radical option is to create a new kind of related right for AI outputs (as exists in some proposals for data or broadcast rights), but this seems at odds with the government’s stated preference and could conflict with Berne/ TRIPS. Most current proposals favor clarifying copyright rather than creating new exclusive rights for machines. Any reforms should explicitly tie the right to a human element. For example, one could amend Section 2(d)(vi) to read: “in relation to any AI-generated literary, dramatic, musical or artistic work, the author shall be the person who contributed creative input to the generation of the work. ” Such amendments would give clarity that the law protects human creativity, whether expressed directly or via an AI tool.
Throughout, India should consider global harmonization: e. g. its expert panel is reportedly analyzing the UK model. Aligning with international norms (so that Indian creators have similar protections abroad) will be important as AI and digital markets are global. In short, reform should aim for a balanced approach – granting rights in AI outputs only to human creators in a transparent way, while keeping sufficient works in the public domain and allowing technology development. Conclusion The rapid rise of AI-generated creative works poses a challenge for copyright law. India’s existing statute (and case law) implicitly assumes human authors, so purely machine-made works currently occupy a legal grey zone. Official statements suggest no immediate need for new rights, but commentators warn this ignores the Act’s human-centric language.
This paper has surveyed the academic debate, the underlying doctrines of authorship, and the Indian legal framework in detail. It finds that without legislative action, copyright in India will continue to attach only to works with significant human creative input. Comparative analysis shows India could either follow the UK’s “arranger-as-author” model or maintain a strict human-authorship rule like the US/EU. Policy considerations favor a middle path: clarifying ownership for AI outputs in a way that protects human creators while encouraging AI innovation and research. Specifically, amendments are needed to define AI-generated works and to ascribe authorship explicitly to humans behind them. This will avoid confusion (and paradoxical results) under the current law. Given the stakes for India’s creative industries and tech sector, timely reform is advisable.
Whether by amendment of the Copyright Act or new rules by the panel, the law must recognize the novel reality of AI co-creators. Carefully calibrated changes – possibly following the expert panel’s recommendations – can ensure that copyright continues to serve its constitutional purpose (promoting the progress of science and useful arts) in the AI era, balancing incentives for innovation with the protection of human authorship.
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