WHO OWNS CREATIVITY? DECODING COPYRIGHT FOR AI-GENERATED WORKS

Akhilesh Kakade, Student, Symbiosis Law School, Pune

Introduction

The rise of artificial intelligence (AI) has upended conventional wisdom about creativity and begged the basic issue: who owns the copyright for works created by AI? Historically ascribed to human inventiveness, creativity today encompasses artificial intelligence systems able to produce software, art, and poetry, all with minimal to no human involvement. Projects driven by artificial intelligence, including DeepArt algorithms and OpenAI’s GPT models, show this phenomenon by generating outputs almost exactly like those of human producers.

This change calls for a review of copyright systems, especially with relation to the eligibility and ownership of such works. Conventional copyright rules presume human authorship, thereby acknowledging those with creative judgement as the legitimate owners. But artificial intelligence systems produce creative products on their own, free from the intentionality or personal expression linked with human producers. This poses important issues: Are works produced by AI eligible for copyright protection? If so, which of the programmer, user, or entity running the artificial intelligence system should be identified as the author?

AI creativity questions the fundamental ideas of originality and authorship; hence legislators should ask themselves whether the current legal systems are adequate or if a fresh approach is required to handle the complexity of computational creativity.

Importance and Relevance to the Legal Field

Intellectual property rights and copyright law will be profoundly affected by AI’s growing involvement into creative activities. Traditionally, copyright rules have been created with a human-centric perspective on creativity, stressing the part individual inventiveness and effort play. Though generally produced with little human involvement, AI-generated works challenge this knowledge by providing content that satisfies the originality and fixation criteria but does not directly reflect human authorship.

As artificial intelligence systems develop, discussions of originality, fixation, and authorship become essential. Usually requiring human creative involvement, originality is a fundamental criteria for copyright. Given artificial intelligence creating works based on past data, one wonders if these outputs are really unique. Likewise, authoring—which has always been connected with humans—now calls for review. Should the programmer, the user, or the entity possessing the artificial intelligence have copyright?

These difficulties draw attention to the necessity of flexible legal rules that strike a compromise between protection and innovation by means of fair attribution. The legal community has to decide whether to modify current systems or design fresh ones considering the special character of works produced by artificial intelligence. Resolving these problems will help copyright law to keep promoting innovation and cultural enrichment in the era of artificial intelligence..

Objectives or Purpose of the blog:

By addressing two primary objectives, this blog intends to investigate the relationship between artificial intelligence (AI) and copyright law. First, especially in relation to creative works, it is imperative to clearly define what artificial intelligence is and the frameworks that control it. Examining how artificial intelligence questions conventional ideas of creativity and originality—which have been the pillar of copyright law safeguarding writers and artists—is the second objective.

Artificial intelligence, or AI, is the ability of computer systems or algorithms to accomplish tasks usually requiring human intellect, including learning, problem-solving, and creative production including writing, music, and art. To replicate human creativity, these systems sometimes produce works that are almost exactly like human-made outputs by depending on large datasets and sophisticated computer methods. Though technology is becoming more and more important in creative sectors, artificial intelligence works under a constrained legal framework; most copyright laws, including the U.S. Copyright Act and the Berne Convention, still presume that only humans may be creators. The absence of particular clauses for works produced by artificial intelligence begs issues regarding the suitability of current legislation for the complexity presented by AI.

Examining how artificial intelligence questions established ideas of originality and creativity is the second objective of the blog. Historically considered as a distinctively human quality, creativity consists in imagination, purpose, and personal expression. But as artificial intelligence systems create outputs based on past data, questions regarding whether these works can be really unique or are just derivative surface. For writers and artists, this generates a disturbing dynamic since AI-generated works blur the boundaries between inspiration and reproduction. Moreover, the increasing application of artificial intelligence in creative domains raises possible problems including ethical questions with the attribution of authorship to non-human entities, devaluation of human innovation, and ownership issues.

By tackling these two goals, the blog aims to clarify the transforming effect of artificial intelligence on creativity and the urgent necessity of legal systems to change so that the interests of human creators are safeguarded and innovation in the age of artificial intelligence is promoted.

Understanding Artificial Intelligence and Its Creative Capabilities

Designed to replicate cognitive tasks including learning, reasoning, and creativity, artificial intelligence (AI) is a transforming tool meant to mirror human intelligence. Within the creative sectors, artificial intelligence makes outputs like poetry, visual art, music, and even books by using machine learning models, large datasets, and sophisticated algorithms. For example, DeepArt uses neural networks to create artworks in the manner of well-known painters, whereas OpenAI’s GPT models can create human-like language by analysing linguistic patterns. These technologies blur the boundaries between human and machine innovation by showcasing AI’s capacity to produce often indistinguishable from human workmanship. The fast integration of artificial intelligence in creative spheres marks a paradigm change and questions accepted wisdom regarding the uniqueness of human originality in artistic expression. 

The painting Edmond de Belamy, auctioned for $432,500 in 2018, is among the most striking examples of artificial intelligence’s creative capacity. Designed by Paris-based team Obvious using a generative adversarial network (GAN), the artwork highlights how creatively innovative artificial intelligence can be within established frameworks. GANs run two neural networks against one another: one produces outputs while the other assesses their quality, iteratively improving the output. Though these successes show the scientific sophistication of artificial intelligence, they also show its need on human input. Humans curate the training datasets, programming, and creative aims; so, one wonders whether the artificial intelligence is an independent creator or just an advanced instrument extending human agency. For copyright law, which usually sees authorship as a human effort, this distinction is essential.

Notwithstanding these powers, AI-generated works now exist in a legal void. National frameworks like the U.S. Copyright Act and international copyright rules like the Berne Convention neglect to specifically address artificial intelligence’s influence on the creation of intellectual property. Emphasizing originality as a distinctively human quality, these rules were written with human writing in mind. Without clauses allowing AI-generated material, ownership, attribution, and protection have already started to cause conflicts. Recent scholarly debates, for example, draw attention to the requirement of legislative clarity and contend that the present systems do not sufficiently address whether programmers, consumers, or even artificial intelligence systems themselves should be acknowledged as creators. This lack of clarity not only complicates enforcement but also runs the danger of weakening the incentivizing mechanism fundamental to intellectual property law. 

Beyond legal uncertainty, philosophical arguments concerning artificial intelligence’s creative ability further complicate its fit under copyright laws. Although artificial intelligence systems can produce outputs that seem original and creative, their dependence on already-existing data implies they lack the intentionality and subjective expression connected with human invention. Legal academics and philosophers contend that creativity is about the underlying idea process and personal expression that lead to it as much as it is about creating fresh work. This begs moral issues regarding whether works created by artificial intelligence merit the same defence as those produced by humans. Generative artificial intelligence forces us to reassess fundamental ideas of originality and authorship, as Lemley (2024) points out, therefore guiding legislators to create inclusive frameworks reflecting the reality of contemporary technology.

Creativity and Originality: Cornerstones of Copyright Law

Long the pillar of copyright law, creativity and originality form the foundation for author grants of exclusive rights based on intellectual creations. Originality is a non-negotiable requirement for copyright eligibility in countries including the U.S., EU, and India; it requires not only novelty but also a “personal touch” reflecting the particular intellectual effort of the author. This idea fits the larger view held by writers that authorship is a development of human creativity and cognition. The European copyright system, for example, stresses the personal imprint of the author, therefore highlighting that originality results from human judgement and decision-making—which machines naturally lack.

AI-generated works, however, challenge these fundamental ideas. Generative artificial intelligence models—such as GPT or GANs from OpenAI—analyze enormous datasets and produce outputs by spotting trends and synthesising fresh material based on past data. Although the produced works could seem fresh and aesthetically pleasing, their reliance on already-existing works begs issues regarding originality. When an artificial intelligence educated on a collection of classical paintings generates an image like a Rembrandt, for example, is it really producing something new or is it just reassembling pre-existing components? Traditionally, legal regimes have demanded some degree of human innovation during the manufacturing process, therefore placing AI-generated works in a vulnerable state. These works question the idea that originality has to always result from human action, therefore stretching the bounds of how copyright law defines creativity.

The legal acceptance of works created by artificial intelligence is further complicated by the present human-centric view of authorship. Legal systems and courts still maintain the tenet that authorship must incorporate human involvement. In Naruto v. Slater, for instance, the court decided that since authorship demanded human input, a picture taken by a monkey could not constitute protected. Likewise, the U.S. Copyright Office clearly rejects registration for works produced just by artificial intelligence systems, claiming that copyright protection only covers works resulting from human creativity. These decisions set a legal precedent excluding non-human creators—including artificial intelligence—from enjoying copyright protection even if their products satisfy conventional standards for innovation and fixation. This leaves a legal void for AI-generated works, hence legislative involvement is needed to handle these complications.

The difficulties presented by works created by artificial intelligence call for a review of the basic ideas underlying copyright law. While present systems stress originality and human agency, the emergence of generative artificial intelligence demands complex answers that consider the cooperative character of human-machine innovation. Some academics contend that allowing hybrid authorship models or sui generis rights for works produced by artificial intelligence could strike a compromise between honouring the efforts of human creators and the AI systems they produce. Such steps would let the legal system change with the times and maintain the fundamental ideas of copyright law.

Legal Challenges and Opportunities in AI-Generated Works

Works produced by artificial intelligence reveal major flaws in copyright law, especially with regard to ownership and attribution. Often neglecting to consider the collaborative and automated character of artificial intelligence innovation, copyright systems around countries were built with human authorship in mind. Legal uncertainty resulting from this lack of clarity is particularly problematic in sectors including entertainment, publishing, and technology, where AI-generated material is proliferating. For instance, American copyright law expressly mandates human authorship. Reiterating this idea in Thaler v. Perlmutter, the court said that protection of copyright is limited to works reflecting human creativity. Unless connected to a major human contribution, this choice leaves works produced by artificial intelligence unprotected. Such decisions underline how urgently reforms are needed to handle the increasing impact of artificial intelligence in creative sectors.

Dilemmas in Ownership and Attributions

The collaborative character of works produced by artificial intelligence complicates the ownership question. Multiple stakeholders—programmers designing the algorithms, dataset providers supplying training data, and consumers guiding the output of AI systems—often participate in these systems. Determining authorship in a process this complicated is difficult since it is not clear whose contribution should be judged creative. For instance, some governments—including the EU—are investigating the concept of giving works created by artificial intelligence sui generis rights. Given their important part in the creative process, this method could let consumers or developers claim ownership of AI products. Critics counter that such policies would compromise conventional ideas of authorship and neglect ethical issues including openness in artificial intelligence training.

Anil Kapoor v. Simply Life India Case Study

The Delhi High Court examined the illegal use of Anil Kapoor’s likeness and voice via AI technology in the case Anil Kapoor v. Simply Life India (2023). The court questioned the ethical and legal limitations of artificial intelligence’s powers when it observed that Kapoor’s features were being replicated without his permission using AI technologies. Although this case mostly focused on personality rights, it highlighted the more general difficulties controlling artificial intelligence’s output of content either directly affecting intellectual property rights or emulating them. The court’s ruling to award an injunction against the defendants underlined the need of preserving individual rights and established a standard for how Indian courts might handle AI-related conflicts going forward.

Ethical Issues and Possible remedies

Furthermore posing ethical questions is the growing application of artificial intelligence in artistic domains. The possible devaluation of human creativity is a key concern since AI-generated material could flood the market and reduce the cultural and financial worth of created works. Furthermore, there are questions around the training of artificial intelligence systems, sometimes drawing on datasets containing copyrighted content without appropriate authorisation. In Andersen et al. v. Stability AI Ltd., this problem surfaced when the plaintiffs claimed that AI training datasets violated their copyrights. Cases like this show how urgently more stringent rules and openness in the usage of copyrighted content for artificial intelligence training are needed. Implementing mandated disclosures of training data sources and mandating AI developers to acquire rights for copyrighted material guarantees responsibility and fairness by means of potential solutions. 

Case Study:Arijit Singh v. Codible Ventures LLP

The Bombay High Court addressed illegal replication of the plaintiff’s voice with artificial intelligence methods in Arijit Singh v. Codible Ventures LLP (2024). Under the Copyright Act, 1957, the court decided that such acts infringed the plaintiff’s moral rights as well as her economic ones. The court specifically acknowledged the damage done by artificial intelligence systems able to replicate special qualities like voice and vocal style, which define an artist’s character. This case is important since it shows how Indian courts are starting to negotiate the complexity brought about by artificial intelligence in the creative environment. It also emphasises the need of specific legislation to handle such invasions since the current system fails to sufficiently defend artists’ rights in face of developing artificial intelligence. 

Reform Prospective Avenues

Notwithstanding the difficulties, the development of artificial intelligence offers chances to rethink copyright law and modernise its systems. The adoption of hybrid authorship models, acknowledging the cooperative character of human and machine innovation, is one possible change. For instance, depending on their involvement to the operation of the artificial intelligence, the programmer or user could be recognised as the author. Sui generis rights, on the other hand, might provide a customised approach that preserves the fundamental ideas of copyright law while giving AI-generated works limited protection. Transparency in artificial intelligence systems could potentially be mandated by policymakers, therefore compelling developers to provide their algorithms and training data. Such steps would improve responsibility, stop abuse, and support fair competition in the creative sectors.

Role of Generative AI in Shaping Legal and Policy Frameworks in India

Government Initiatives and Regulatory Changes

The Indian government has launched major projects aiming at controlling artificial intelligence and its impact on society. Approved in March 2024 with a ₹10,371.92 crore budget, the IndiaAI Mission marks a historic first towards creating a strong AI ecosystem. By encouraging research, invention, and adoption across several fields, this goal seeks to establish India as a worldwide leader in artificial intelligence. Although the goal is on artificial intelligence development, it subtly acknowledges the requirement of legal systems to handle accountability, ownership, and attribution regarding works produced by artificial intelligence. This project supports more general attempts to establish ethical AI governance guidelines interacting with intellectual property issues.

Set to replace the Information Technology Act, 2000, the planned Digital India Act marks even another important advance. Specifically including clauses for “high-risk AI systems,” this Act recognises the importance of openness and responsibility in artificial intelligence uses. Though the Act mostly targets digital governance, it is intended to affect intellectual property systems by stressing the rights of authors whose works might be utilised in artificial intelligence training datasets. The Act is probably also going to contain rules on the moral application of generative artificial intelligence, therefore establishing a standard for regulatory clarity. 

Though concentrated on protecting personal data, the Digital Personal Data Protection (DPDP) Act, 2023 has major ramifications for works produced by AI. The Act subtly addresses the training of AI systems on copyrighted datasets by requiring openness in how data is used. This emphasis on moral data consumption fits the more general objective of making sure that artists’ rights are not sacrificed in order to ensure that AI-driven innovation proceeds. These projects taken together show India’s dedication to provide a balanced regulatory framework supporting intellectual property protection as well as technical advancement.

Impact on Intellectual Property Law

For legal practitioners, legislators, and students in India especially with regard to originality of authorship, the incorporation of generative artificial intelligence into creative processes brings both great opportunities and problems. Since conventional copyright systems are based on human creativity, legal practitioners must negotiate the complexity of determining authorship and ownership of AI-generated content. Under Section 2(d)(vi), the Indian Copyright Act, 1957, defines that the creator of computer-generated works is the person causing them to be made. But this clause does not specifically handle the subtleties brought about by AI-generated content, which results in legal interpretation uncertainty. 

Indian policy makers have to modernise legal systems to handle the subtleties brought forth by artificial intelligence technologies. The changing terrain of artificial intelligence-generated content could call for future copyright law changes to meet new issues. Differentiating between human- and machine-generated works could get more difficult as AI-generated content gets more sophisticated, therefore affecting authorship and copyright ownership.

For academics and students, the changing terrain provides a rich environment for investigating the ethical and legal ramifications of artificial intelligence in creative sectors. Anil Kapoor v. Simply Life India is a relevant case where the Delhi High Court issued an injunction to safeguard the actor’s personality rights from illegal use of AI technology including face morphing and voice reproduction, therefore safeguarding his privacy. This historic ruling emphasises the urgent need of thorough legal rules to control the application of artificial intelligence in recreating personal traits, so maintaining the originality and integrity of all personas.

All things considered, the emergence of generative artificial intelligence forces a review of current Indian ethical guidelines and copyright rules. Legal practitioners have to be able to apply and understand laws in situations not expected from conventional wisdom. Policymakers are advised to create rules protecting artists’ rights without thus hindering technological development. Scholars and students have the chance to add to the conversation by investigating ideas that balance the needs of all the digital era users.

Conclusion

In the framework of AI-generated works, the ownership of creativity raises a fundamental issue that calls on fundamental copyright law principles to be questioned. Historically, with intellectual property systems meant to safeguard labour, originality, and expression of human authors, creativity has been seen as a naturally human activity. These long-standing ideas are challenged, nevertheless, by the development of generative artificial intelligence—that which can generate outputs indistinguishable from human inventions.

Fundamentally, the inquiry of “Who owns creativity?” in AI-generated works is complex. Most countries, including India, have current laws that credit authorship to people—either the person who produces the work or the entity bringing it about. For instance, the Indian Copyright Act, 1957’s Section 2(d)(vi) notes the creator of a computer-generated work that “causes.” This clause is insufficient, nevertheless, to handle the complexity of generative artificial intelligence—where little or no human interaction is needed. Determining the “causer” gets difficult when AI systems run more and more independently.

Legal systems all around have responded differently. The U.S. Copyright Office has made clear that works produced without human authorship, solely by artificial intelligence, are not eligible for copyright protection in the United States. Rather, just human contributions included into AI-generated work are safeguarded. Likewise, courts have decided—as shown by the case Naruto v. Slater, where a picture taken by a monkey was found unfit for copyright—that non-human authorship is incompatible with conventional copyright rules.

The changing character of artificial intelligence calls for novel ideas. Clear and balanced solutions such as hybrid authorship models, whereby both human and artificial intelligence contributions are acknowledged, could be found. Under such systems, users or programmers guiding the artificial intelligence system could share authorship, therefore honouring their technical and artistic roles. Sui generis rights, a customised legal framework designed especially for AI-generated works, guarantee protection while maintaining conventional ideas of human authorship and offer still another option.

India’s historic cases include Anil Kapoor v. Simply Life India and Arijit Singh v. Codible Ventures LLP underline even more the need of controlling AI’s creative capacity. In these instances, the courts safeguarded people’s moral rights and personality against illegal replicas of their voice or likeness created by artificial intelligence. These rulings highlight the need of a sophisticated legal strategy that preserves human originality while handling the ethical and pragmatic consequences of AI-generated material.

Ultimately, in the AI era, ownership of creativity is about encouraging invention while maintaining responsibility rather than only about allocating rights. Changing copyright rules to fit the complexity of computer invention calls for careful balancing protection of human inventors, promotion of technology advancement, and avoidance of abuse. Legislators, attorneys, and academics must work together to create frameworks that accurately represent the reality of modern invention as generative artificial intelligence keeps redefining the limits of creativity. By doing this, we make sure that artificial intelligence preserves creative expression integrity and improves human civilization.

BIBLIOGRAPHY

Case laws:

1. Naruto v. Slater, No. 16-15469 (9th Cir. 2018)
2. Thaler v. Perlmutter, No. 22-CV-384-1564-BAH
3. Anil Kapoor v. Simply Life India, 2023 SCC OnLine Del 6914
4. Andersen v. Stability AI (2024) United States District Court
5. Arijit Singh v. Codible Ventures LLP, 2024 SCC OnLine Bom 2445

Acts and Statutes:

1. Indian Copyright Act, 1957, Section 2(d)(vi).
2. U.S. Copyright Act, 1976.
3. Berne Convention for the Protection of Literary and Artistic Works, 1886.

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13. Andersen v. Stability AI (2024) United States District Court. Decision issued in 2024. Available at: https://www.loeb.com/en/insights/publications/2024/08/andersen-v-stability

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