Shaping Copyrights In The Era Of Artificial Intelligence

Author: LawSphereX

Category: Technology, Cyber & Privacy

Published: 2026-08-23T21:05:03.320011+00:00

Updated: 2026-08-26T17:06:19.82+00:00

SHAPING COPYRIGHTS IN THE ERA OF ARTIFICIAL

INTELLIGENCE

Astha Gandhi, SVKM's Narsee Monjee Institute of Management Studies, NMIMS, Indore

ABSTRACT

As artificial intelligence (AI) increasingly contributes to creative fields like art, literature, music, and software, traditional copyright laws, rooted in human authorship and originality are facing serious challenges. This article explores whether AI-generated or AI-assisted works can qualify for copyright, who should be considered the legal author, and how core concepts like originality, fixation, and authorship should be redefined. It also examines broader ethical and economic concerns such as fairness in attribution, transparency, cultural bias in AI models, and the impact on human creators. Focusing on both global perspectives and India’s specific legal context, the article proposes reforms like clearer definitions for AI involvement, co-authorship rules, AI disclosure requirements, and improved licensing of training data.

It calls for balanced regulation that encourages innovation without compromising creators’ rights, and advocates for international harmonization, especially through platforms like WIPO to provide consistent legal standards for AI-generated content.

HOW AI IS CHANGING THE WAY WE THINK ABOUT COPYRIGHT

Artificial Intelligence (AI) has moved far beyond being just a technical tool used to assist human creators. Today, AI can independently generate poems, compose music, paint pictures, write news articles, and even produce complex legal or academic content. 1 As a result, AI is no longer just supporting creativity it is becoming a creative agent in its own right. This dramatic shift poses a serious challenge to the traditional structure of copyright law, which has always been centered around human imagination, effort, and intention. The core concepts of copyright originality, fixation, and authorship were designed with human creators in mind. Now, with AI capable of generating content that appears “original”, questions arise: Can a machine-made work be considered truly original? 2 Who should be named the author the person who designed the AI, the one who used it, or no one at all?

And if no human author can be identified, should the work fall into the public domain? This article takes a deep dive into these evolving questions. It begins by laying out the traditional legal foundations of copyright and exploring how AI challenges them. 3 It then examines how different countries are responding to the issue and looks at various proposals for reform. The goal is not only to clarify how the law might categorize AI-generated or AI-assisted works, but also to offer practical solutions like redefining authorship standards, requiring transparency in AIgenerated content, regulating how AI is trained on existing copyrighted works, and designing copyright policies that encourage both innovation and fairness. 4 In short, this article aims to help shape a future copyright system that respects both human creativity and technological progress.

RE-EXAMINING COPYRIGHT FUNDAMENTALS

Copyright law is built on three key pillars: originality, fixation, and authorship. Traditionally, a work must be original meaning it must reflect independent thought and some degree of creativity. It must also be fixed, meaning it exists in a tangible or readable format. Most importantly, the law has always assumed that a human being is the author entitled to protection. 1 U.S. Copyright Office, Copyright and Artificial Intelligence, Part II: Copyrightability 3–4 (2024). 2 Burrell, R., & Coleman, A., Copyright Exceptions: The Digital Impact 73–75 (Cambridge Univ. Press 2005). 3 World Intellectual Property Organization [WIPO], Revisiting the Concept of Authorship in AI Contexts (2023).

4 Yu, P.K., Ar*ficial Intelligence and the Future of Copyright, 57 Hous. L. Rev. 437, 448–52 (2020).

But the development of AI calls into question these presumptions. AI systems generate content using algorithms, data analysis, and pattern recognition without consciousness, intent, or emotion. This raises complex legal questions: Can something generated by a machine be considered “original”? Is a dynamically generated work fixed enough to be protected? And most critically, who is the author if there’s no human creator involved, does that mean no copyright protection applies, and the work defaults to the public domain? These uncertainties highlight the urgent need to re-examine the foundational principles of copyright law in the age of artificial intelligence. Artificial Intelligence is no longer limited to data analysis it now plays an active role in creative fields, generating paintings, music, stories, and even scientific articles.

This development brings new legal challenges, especially in determining who owns the rights to content made with or by AI. Broadly, AI-generated content can be grouped into three scenarios based on human involvement. First are fully AI-generated works, where the machine produces the entire output based on a simple prompt, with no meaningful human input. Since copyright law traditionally requires a human author, these works raise complex questions: Who, if anyone, owns the rights the developer, the user, or no one at all? In the absence of a clear author, some argue such works should fall into the public domain, while others push for assigning ownership to those behind the AI or using it. The second scenario involves human-AI collaboration, where a person actively interacts with the AI by giving prompts, selecting outputs, or editing and reshaping the result.

This is increasingly common, but legally complex, as it’s unclear when a person’s input becomes significant enough to claim authorship. Finally, there are AI-assisted creations, where tools like grammar checkers or style suggestions help the human creator but don’t generate full content on their own. These cases usually fit within current copyright rules, with the human recognized as the author5. However, as AI becomes more advanced and plays a greater role in content generation, even assistive tools blur the lines. Of all these scenarios, human-AI collaboration is the most difficult to regulate, requiring legal systems to carefully assess the degree of human involvement in order to determine authorship and protect both creative rights and innovation.

5 Daniel J. Gervais, The Machine as Author, 105 Iowa L. Rev. 2053, 2081–82 (2020).

JURISDICTIONAL APPROACHES: DIVERGING PATHS

Around the world, legal systems are responding differently to the challenge of copyright in the age of artificial intelligence. In the United States, the U. S. Copyright Office maintains a firm stance that only works created by humans are eligible for copyright protection6. This position was reinforced in the Zarya of the Dawn case, where a comic book containing AI-generated images was denied protection for those portions created without human input. In contrast, the United Kingdom has a unique legal approach that recognizes “computer-generated works” even without a human author. Under UK law, authorship is attributed to the person who makes the necessary arrangements for the creation of the work a solution that, while practical, invites debate over what exactly counts as a creative arrangement.

Meanwhile, the European Union largely upholds the principle of human authorship but is actively exploring AI-specific legislation, such as the proposed AI Act, to address broader concerns around transparency and accountability. In India, the Copyright Act of 1957 does not currently address AI-generated works, as it assumes that authors must be human. 7 No judicial precedent has yet clarified how Indian law should treat such content, but the growing use of AI in India's IT and creative sectors is fueling calls for reform. Other jurisdictions like Canada and Australia continue to follow the traditional human-authorship model, though some governments are beginning to consider amendments and policy updates. Overall, these varied approaches highlight a lack of global consensus, revealing how unequally copyright law is evolving to keep pace with the rapid advancement of AI technologies.

CONCEPTUAL CHALLENGES: ORIGINALITY, FIXATION, AND AUTHORSHIP

One major challenge in AI-generated content is originality. Since AI systems learn from massive datasets and generate content by identifying and recombining patterns, critics argue that such creations aren’t truly original they may even risk replicating parts of existing works. However, supporters claim that even algorithmic outputs can be novel, especially when a human provides meaningful input like crafting specific prompts, selecting from outputs, or refining the result. As AI evolves, legal systems may start assessing originality less on the 6 U.S. Copyright Office, Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, at 2–4 (Mar. 2023).

7 The Copyright Act, No. 14 of 1957, § 2(d), India Code (2021).

algorithm's creativity and more on the extent of human involvement in shaping the final product.8 Another concern is authorship and fixation. Most copyright systems require a work to be “fixed” in a tangible form, which is generally satisfied by saving or recording the AI output. But in cases where AI creates live, dynamic, or interactive works such as real-time visuals or music this becomes less clear. In a similar vein, authorship is difficult to determine: who is the owner of the work the developer, the editor, the prompt-giver, or another person? Many scholars suggest treating AI as a tool, where human guidance and decision-making determine authorship. If no meaningful human creativity is involved, such works might belong in the public domain unless new laws grant AI or its users some form of legal recognition.

ETHICAL AND ECONOMIC STAKES

Copyright law plays a vital role in supporting creativity and innovation. Human creators often rely on copyright protections to earn a living and gain recognition for their work. However, with the rapid rise of AI-generated content, there’s a real concern that human artists, writers, and musicians could be pushed out of the market. If AI-generated works flood the creative industries, it may devalue human expression. On the flip side, refusing copyright protection to AI-generated works could discourage innovation and investment in generative AI technologies. The challenge is to strike a fair balance protecting human creativity while also recognizing the contributions of AI developers and users, without allowing a handful of companies to monopolize culture. Another critical concern involves fairness and moral rights.

Human creators not only want credit for their work but also deserve the right to prevent misuse or distortion of it9. In current AIgenerated content, these moral rights are often ignored especially when AI is involved in collaboration. Many works are credited to the AI system or the platform rather than the human who shaped or edited the content. Legal reforms may need to extend moral rights to include works made with AI tools, ensuring that human input is fairly acknowledged and protected, especially in co-created content.

8 WIPO, WIPO Technology Trends 2019: Artificial Intelligence, World Intell. Prop. Org. 128–30

(2019).

9 U.S. Copyright Office, Compendium of U.S. Copyright Office Prac*ces, § 313.2 (3d ed. 2021).

Finally, there are deeper cultural and ethical questions. AI systems are often trained on datasets dominated by English-language or Western content, which can unintentionally silence minority voices and reinforce cultural biases. This could result in a homogenized creative landscape that overlooks diversity. Copyright law should help counteract this by promoting transparency in training data, encouraging the inclusion of diverse cultural materials, and requiring disclosure when AI is used. Just as consumers want to know if a product is genetically modified, they should also be informed if a work is AI-generated. People are able to make knowledgeable decisions regarding the content they consume and trust is increased as a result.

PROPOSED LEGAL REFORMS

To effectively regulate AI-generated content, copyright laws must clearly distinguish between different types of AI involvement. A fundamental first step is to define categories such as fully AIgenerated works, human-AI co-created works, and AI-assisted creations. For example, works produced solely by AI with little or no human input may not warrant copyright protection, while those involving human prompts, editing, or creative direction may still qualify. Such definitions will help lawmakers determine when and to whom copyright can be granted. The next important reform involves clarifying rules for co-authorship between humans and ai. Legal frameworks should set criteria to determine when a human’s input is significant enough to be considered authorship10.

This could include whether the person guided the creative process, made meaningful edits, or transformed the AI-generated content into a new artistic work. Establishing a clear threshold for “substantial human involvement” would not only assist in legal disputes but also help creators understand their rights. Transparency is equally critical. Mandating disclosure of AI involvement whether by creators, publishers, or platforms would protect consumer trust and assist courts in evaluating claims of originality and authorship. Just as food packaging must list ingredients, content could carry simple disclosures such as “AI-generated” or “AI-assisted,” allowing users to make informed choices and encouraging ethical content creation practices. AI’s dependence on pre-existing content raises another concern: training data. Many AI models

10 Andres Guadamuz, Artificial Intelligence and Copyright, 39 Colum. J.L. & Arts 1, 10–12 (2015).

are built on copyrighted material, often without permission. Laws should require developers to license training data or use content from public domain or Creative Commons sources. This would ensure creators are fairly compensated while maintaining innovation. At the same time, fair use doctrines must be updated to reflect the realities of AI training, balancing access with protection. The worldwide scope of artificial intelligence makes international coordination essential. At present, different countries apply varying legal standards to AI authorship and copyright, resulting in confusion and the risk of forum shopping. To address this, a unified legal framework potentially developed under the guidance of the World Intellectual Property Organization (WIPO) could establish common definitions and rules regarding AI-generated content, ownership rights, and disclosure requirements.

Such standardization would bring greater legal clarity and consistency for creators, technology developers, and users across borders.

CONCEPTUAL FRAMEWORKS: RETHINKING AUTHORSHIP AND CREATIVITY

As artificial intelligence becomes more involved in creative processes, the concept of authorship needs to be re-examined. One approach is to view the human interacting with the AI—whether by giving prompts, setting parameters, or selecting outputs as the “director” of the creative process. In this model, the human’s role in guiding style, structure, or content makes them the rightful author, while AI is treated as a tool rather than a creator. Another perspective is the joint authorship model. Here, if multiple humans collaborate like someone providing a prompt and another refining or editing the output they may share authorship. However, since AI is not a legal person, it cannot be a co-author11. This model only works when the creative input comes from humans, even if AI plays a significant role in generating the material.

Some legal thinkers argue that AI should be viewed similarly to a camera or software a technical instrument rather than a creative source. In this sense, the person using the AI is like a photographer who uses a camera to create art. The human retains authorship because they control the output, even if the tool (AI) adds complexity.

11 Andres Guadamuz, Artificial Intelligence and Copyright, 39 Colum. J.L. & Arts 1, 12–15 (2015).

Finally, some scholars suggest creating a new category of intellectual property for fully AIgenerated works. Instead of full copyright, these works could receive sui generis (unique) protection for a limited time12. This would offer some incentive to developers and investors without giving long-term monopolies over machine-made content, ensuring such works eventually enter the public domain.

INDIA’S SPECIFIC CONTEXT: IMPERATIVES FOR REFORM

India is rapidly becoming a global hub for technology and creative industries like Bollywood, digital publishing, and software development all of which are increasingly adopting AI tools. However, the current legal framework, namely the Copyright Act of 1957, is outdated in this context. It recognizes only human authorship and does not account for AI-generated or AIassisted works. This gap presents several challenges. There’s no legal definition of AI-generated content, and no clarity on when a human’s contribution in collaboration with AI qualifies for authorship. There are also no rules requiring creators to disclose whether AI was used in the creation of a work. Furthermore, since many AI systems train on existing works without proper permissions, there is a high risk of copyright infringement due to the lack of statutory safeguards.

To address these issues, India must update its copyright law to include clear definitions of computer-generated works and guidance on how much human input is needed to claim authorship. Administrative bodies should develop rules to help determine authorship in AIhuman collaborations13. Disclosure of AI usage in published or commercial content should be made mandatory. Additionally, India should create licensing frameworks for training datasets either through statutory licenses or dedicated platforms. Engaging stakeholders from creative, tech, and civil society sectors will ensure the reforms are inclusive and forward-looking. These steps could position India as a global leader in ethical and innovative AI copyright governance.

BALANCING INNOVATION, ACCESS, AND EQUITY

In the era of AI, copyright reform necessitates a careful balancing act between conflicting interests. First, it is vital to encourage innovation so that investment in AI research and creative 12 WIPO, Revised Issues Paper on Intellectual Property Policy and Artificial Intelligence 12–14 (May 2021). 13 Ministry of Electronics & Information Technology, India AI Report: National Strategy for Artificial Intelligence (2021).

platforms continues to grow. At the same time, human creators must be protected to ensure their original work can be monetized and recognized. Finally, equity must be a core principle. Legal frameworks should prevent the domination of cultural output by a few large tech companies and ensure that diverse voices can thrive. This means introducing checks on monopolistic practices, promoting fairness in AI training datasets, ensuring transparency in content creation, and eventually allowing AI-generated works to enter the public domain.14 With the right balance, copyright reforms can support both progress and fairness.

CONCLUSION

AI has disrupted the foundational assumptions of copyright law chiefly, that a human, intentional agent underlies every creative work. As AI systems evolve into independent generators, it becomes imperative to rethink authorship, originality, and ownership. A calibrated approach preserving human creativity, promoting innovation, and ensuring transparency is essential. Law should not reflexively deny protection to AI output, nor should it uncritically extend robot authorship; rather, it should carefully draw lines informed by human agency and societal values. For India, adapting the Copyright Act, establishing clear authorship thresholds, requiring disclosure, and regulating training data are urgent priorities. Globally, harmonized rules and international dialogue will mitigate fragmentation and support equitable innovation.

In shaping copyright in the era of AI, societies must choose: either legislate thoughtfully to guide this transformation, or risk being governed by default by emergent technological practices that may diminish human creativity, concentrate power, and obscure accountability. The choice lies before us. 14 European Parliament, AI Act Draft Proposal: Promoting Innovation While Safeguarding Public Interest, COM (2021) 206 final (Apr. 21, 2021).