INDIA'S COPYRIGHT CROSSROADS: EMBRACING AI WHILE SAFEGUARDING CREATIVITY

 

AUTHORED BY – NIREEEKSHA NAREN

 

Abstract

The rapid advancement of Artificial Intelligence (AI) has blurred the lines of human creativity, raising complex questions about authorship and copyright ownership. This paper explores the challenges posed by AI-generated works to the current legal framework built upon the concept of human authorship. The current copyright law hinges on the notion of a human author who creates original works. However, AI can now generate creative outputs such as music, art, and literature.

 

This paper examines the arguments against AI authorship, including the lack of originality and the absence of independent creative intent.  The possibility of copyright protection for AI creations is then explored, considering the level of human involvement and the potential for co-authorship. Further, it delves into the potential for copyright infringement if copyrighted works are incorporated into the training data without permission.  International perspectives on AI and copyright are also examined, highlighting recent developments that arose globally.

 

Finally, this paper proposes solutions to address the challenges of AI authorship.  This includes the possibility of redefining authorship to encompass AI as co-author, or the creation of new copyright protection models specifically for AI-generated works. Examining the legal landscape surrounding AI authorship is crucial for ensuring the continued fostering of creativity while protecting the rights of all parties involved.

 

Key words: Copyright, Ownership and Authorship, Artificial Intelligence, Originality, Creativity, Infringement.

 

 

 

INTRODUCTION

 

1. THE RISE OF AI-GENERATED CREATIVITY

The realm of creativity is no longer solely the domain of human imagination. Artificial intelligence (AI) has undergone a revolution, pushing the boundaries of what machines can create.  AI-powered tools are no longer confined to data analysis and automation.  They are now actively generating artistic expressions, musical compositions, and even literary narratives. This surge in AI-generated creativity is fueled by advancements in machine learning, particularly deep learning techniques.  Deep learning algorithms are trained on massive datasets of creative works, allowing them to identify patterns, styles, and underlying structures.  This empowers AI to not just imitate existing works, but to generate novel and unexpected outputs that often defy human expectations. The applications of AI-generated creativity are vast and ever-expanding.  In the visual arts, AI can produce stunningly realistic paintings, sculptures, and even animation.  Musicians are utilizing AI to compose original pieces that blend seamlessly with established genres or explore entirely new sonic landscapes.  Writers are collaborating with AI to generate scripts, poems, and even entire novels, pushing the frontiers of storytelling.

 

The impact of AI on creative industries is undeniable.[1]  It offers artists and creators new tools to explore and expand their artistic vision.  AI can generate variations, suggest ideas, and even complete mundane tasks, freeing human creators to focus on higher-level aspects of their work.  For businesses, AI-generated content has the potential to streamline content creation, personalize marketing campaigns, and generate new product ideas. However, this burgeoning field also presents challenges.  Concerns exist regarding the potential for AI to replace human creativity altogether.  The question of ownership and copyright becomes murky as the lines between human and machine-generated content blur.  These issues necessitate a critical examination of the legal and ethical implications surrounding AI-generated creativity.

 

1. THE COPYRIGHT CONUNDRUM: AUTHORSHIP IN THE AGE OF AI

 

The traditional copyright framework is built upon the concept of a human author who creates original works.  However, AI throws a wrench into this well-oiled system.  Can AI-generated works be copyrighted?  If so, who owns the copyright – the programmer who created the AI, the user who prompts it, or the AI itself?  The current legal landscape regarding AI authorship is a complex and evolving one.  Many copyright offices, including the one in the United States, generally deny copyright protection for works created by machines.  The reasoning behind this lies in the requirement for originality – a concept traditionally linked to human creativity and independent thought.  Critics argue that AI outputs are simply derivative works, mimicking existing styles and lacking the spark of true originality.

 

Furthermore, the question of authorship is intertwined with the concept of intent.  Section 102 (b)[2] of the copyright Act protects the expression of an idea, not the idea itself.[3]  However, AI lacks the intentionality and conscious thought processes associated with human creation.  AI operates based on algorithms and statistical patterns, raising doubts about whether its outputs can truly be considered expressions of original ideas. However, a counterpoint emerges.  AI development requires significant human effort.  Programmers invest considerable time and creativity in designing and training AI models.  Users, too, exercise creative control by providing prompts, selecting parameters, and editing AI-generated content.  These arguments suggest that AI authorship might be best understood as a collaborative process, with both humans and machines contributing to the final creative output. The issue of training data further complicates the copyright conundrum.  AI models are trained on massive datasets, which often include copyrighted works.  This raises the question of whether the use of copyrighted material in training data constitutes copyright infringement.  Fair use doctrines may come into play, but the legal boundaries remain unclear.

The rise of AI-generated creativity necessitates a reevaluation of copyright law.  New frameworks might be needed to address the unique challenges posed by AI, potentially recognizing AI as a co-author, or establishing new copyright protection models specific to machine-generated works.  This ongoing debate is crucial for fostering innovation in the age of AI while ensuring that the rights of all creative stakeholders are protected.

 

CURRENT POSITION OF THE COPYRIGHT LAW AND AI IN INDIA

1. THE HUMAN AUTHORSHIP REQUIREMENT

The current copyright framework in India, governed by the Copyright Act, 1957, hinges on the concept of a human author. This manciple is deeply rooted in the historical development of copyright law.

 

1. Historical Basis of Copyright Law

Prior to the Renaissance, control over creative works often resided with powerful entities like guilds or patrons. The rise of printing presses in the 15th century threatened this control and created a need for a new system.

 

The Statute of Anne (1710) in England addressed this by establishing the concept of copyright. It granted authors of "printed books" a monopoly on their works for a set period. This aimed to incentivize creativity by giving authors a financial stake in their work's success.  Previously, there was little incentive to create new works if others could easily copy them and reap the benefits. The Statute of Anne marked a shift towards rewarding individual creators for their intellectual efforts. This focus on human authorship became a cornerstone of copyright law.  It ensured authors, not printers or patrons, received the economic rewards associated with their original creations. This framework encouraged a flourishing of creative output during the Enlightenment and beyond.  However, with the rise of AI-generated content in the 21st century, the definition of "author" and the applicability of this historical framework are being called into question.

 

1. Limitations of Current Framework for AI under Indian Copyright Act, 1957

The Indian Copyright Act adheres to the principle of human authorship.  Several provisions of the Act highlight this requirement vis-à-vis, under Section 13(1)(a)[4] the definition of a "literary work" as any original literary, dramatic, artistic, or musical work, or any tables, computer programmes, databases, or compilations has been provided.  The key term here is "original," which implies a work that originates from the author's mind and shows some degree of creativity. Section 17[5] lays out the ownership of copyright.  It states that the author of a work shall be the first owner of the copyright.[6]  The Act does not recognize non-humans, including AI, as authors and Section 2(d)(vi)[7] introduced in 1994, specifically addresses computer-generated works.  It states that the ownership of copyright in such works "shall vest in the person who caused the work to be created."  While this provision seems to offer some leeway, it still implies a human actor initiating the process and exerting control over the creation.

 

THE CASE AGAINST AI AUTHORSHIP

The current legal framework in India, as outlined by the Copyright Act, 1957, presents a strong case against recognizing AI as an author. Here's a closer look at the arguments against AI authorship and how they connect to specific sections of the Act:

 

1. LACK OF ORIGINALITY

 

One of the primary arguments against AI authorship centers around the concept of originality, enshrined in Section 13(1)(a) of the Copyright Act. This section defines a "literary work" as any original literary, dramatic, artistic, or musical work, or any tables, computer programmes, databases, or compilations, as aforementioned. Originality, in the Indian context, implies a work that originates from the author's mind and shows some degree of creativity.  AI-generated content, while potentially novel in its output, is often derivative.  These works are trained on massive datasets of existing creative works, raising questions about whether they meet the originality threshold.

For instance, an AI trained on a vast collection of poems might generate a new poem with a unique structure and vocabulary.  However, the poem's underlying concepts, themes, and stylistic elements might still be heavily influenced by the training data.  This derivative nature weakens the argument for originality under Section 13(1)(a).

 

2. ABSENCE OF CREATIVITY AND INTENT

Another key argument against AI authorship revolves around the concepts of creativity and intent. Critics argue that AI lacks the independent thought processes and intentional decision-making associated with human creativity. AI operates based on algorithms and statistical patterns.  It can identify trends and generate outputs that mimic existing styles.  However, the creative spark - the ability to come up with something truly new and original - is often attributed to the human mind.[8]  This lack of independent creativity weakens the claim for AI authorship.

Furthermore, copyright law traditionally recognizes authors who possess the intent to create a copyrightable work.  Section 17 of the Act reinforces this by granting copyright ownership to the "author" of the work.  AI, however, lacks the conscious intentionality associated with human creation.  Its outputs are a result of complex algorithms processing data, not a deliberate attempt to express an original idea. This absence of creative intent further diminishes the argument for recognizing AI as an author under the current copyright framework.

 

CHALLENGES AND CONSIDERATIONS IN AI COPYRIGHT

The rise of AI-generated creativity presents a unique challenge – the issue of training data and potential copyright infringement.  Massive datasets are the lifeblood of AI models, particularly those involved in creative tasks like generating music, art, or text. These datasets often contain copyrighted works, raising concerns about whether their use violates copyright law.

 

TRAINING DATA AND INFRINGEMENT

The Copyright Act, 1957, offers some guidance on copyright protection for training data sets, although the Act doesn't explicitly address this issue.

 

Section 13(1)(a) defines a "literary work" as any original literary, dramatic, artistic, or musical work.  If the training data includes excerpts from copyrighted works like poems, scripts, or musical pieces, these elements themselves might be protected under this Section.

 

Section 14[9] deals with fair dealing for purposes like research, private study, criticism, or review.  If the use of copyrighted material in the training data falls under these fair dealing exceptions, it might not constitute infringement. However, the boundaries of fair dealing remain a subject of legal interpretation.

 

Section 51[10] grants copyright owners the exclusive right to reproduce their work in any material form.  Using copyrighted material in a training data set could be considered a form of reproduction, potentially falling under this Section.

 

The current legal framework leaves some ambiguity regarding the copyright implications of using copyrighted material in training data sets.  Here are some potential approaches:

 

Obtaining Licenses:  Creators of AI models could seek explicit permission from copyright holders to include their works in the training data. This approach offers greater clarity but can be cumbersome and time-consuming.

 

Anonymization:  Training data could be anonymized to remove any identifiable copyrighted material. However, this might affect the effectiveness of the training process.

 

Fair Dealing Arguments:  Developers could rely on fair use doctrines to justify the use of copyrighted material in training data.  However, the success of this argument depends on the specific nature and quantity of the copyrighted material used.

 

FAIR DEALING AND TRANSFORMATIVE USE DOCTRINES

The debate surrounding AI-generated content and copyright ownership often intersects with the concepts of fair use and transformative use.  These doctrines, enshrined in Indian copyright law, offer some potential avenues for navigating the complexities of AI creativity.

 

1. FAIR DEALING

The Indian Copyright Act under Section 52(1)(a)[11] allows "fair dealing" of copyrighted works for certain purposes without infringing the copyright owner's rights.  These purposes include:

1. Research and private study
2. Criticism or review
3. Reporting current events
4. Teaching (including research thereof)

 

Now, whether a particular use of copyrighted material qualifies as "fair dealing" depends on a multi-factor test:

1. The purpose and character of the use: Is the use for a non-commercial or educational purpose? Does it transform the copyrighted work or simply copy it?
2. The nature of the copyrighted work: Is it a published or unpublished work? Is it factual or creative?
3. The amount and substantiality of the portion used: How much of the copyrighted work is used?[12] Is it the heart of the work or a small, inconsequential portion?
4. The effect of the use upon the potential market for or value of the copyrighted work: Does the use harm the market value of the original work? Does it create a substitute for the original?

 

TRANSFORMATIVE USE

The concept of transformative use, although not explicitly mentioned in the Act, has been recognized by Indian courts. The difference between fair use and transformative use plus how it can be applied in an Indian context has been laid down in the case of Super Cassettes Industries v. Mr. Chintamani Rao & Ors.[13]  A transformative use takes a copyrighted work and uses it for a new purpose or with a new expression, adding something new, with a different character, and serving a different function.[14]

 

In the context of AI, the question arises: can AI-generated content be considered transformative of the training data it uses? Here are some arguments to consider:

 

Significant Alteration:  If the AI output significantly alters the elements from the training data, creating something entirely new, it could be considered transformative.

 

New Purpose and Expression: If the AI-generated work serves a different purpose and expresses itself in a way fundamentally different from the training data, it might qualify as transformative.

 

Limitations and Uncertainties

While fair dealing and transformative use doctrines offer some potential for AI-generated content, uncertainties remain.  The Ambiguity in Fair Dealing is that the "fair dealing" test is open-ended and subject to judicial interpretation. The specific purposes listed in Section 52(1)(a) might not easily encompass all uses of copyrighted material in AI training data. Furthermore, since the concept of transformative use itself is evolving, and the courts haven't yet addressed it explicitly in the context of AI, there is a presence of uncertainty which we may encounter in the future.

 

THE SPECTRUM OF HUMAN INVOLVEMENT AND AI CREATIVITY IN INDIA

The Indian copyright landscape around AI-generated content is grappling with a crucial question: how much human involvement is necessary for an AI output to be considered an original work worthy of copyright protection? This question hinges on the level of human creativity and intervention throughout the AI creation process.

 

1. CHALLENGES IN DISTINGUISHING ORIGINALITY

Originality is the cornerstone of copyright protection in India, enshrined in Section 13(1)(a) of the Copyright Act, 1957. This means a work must be original i.e. it must originate from the author's mind and shows some degree of creative spark. Simply copying or imitating existing works doesn't qualify. Originality serves a crucial purpose as it incentivizes creativity by granting exclusive rights to the author for a limited period. These rights allow authors to control how their work is used and potentially profit from it. Without originality as a requirement, copyright protection would become meaningless, failing to encourage new creative expression and potentially hindering artistic and literary progress.[15] Therefore, in India, originality remains a vital principle in ensuring a robust and fair copyright landscape.

Since, the Act doesn't recognize non-human authors. While programmers invest significant effort in designing and training AI models, the creative spark often associated with human authorship is debatable in AI outputs. This absence of a demonstrably human "author" further weakens the originality claim. Even if AI could overcome the "authorship" hurdle, assessing originality remains complex. While user input can be significant, some challenges arise when attributing copyright ownership:

1. Isolating User Input:  Attributing authorship becomes difficult when user input and AI capabilities intertwine.[16]  This makes it challenging to determine if the originality stems from the human or the machine. For instance, a user might provide a broad prompt like "write a poem about nature."  The AI, drawing on its training data and algorithms, generates the poem.  While the user initiated the process, the specific elements and style of the poem might be largely determined by the AI.  Separating the user's "idea" from the AI's "execution" can be challenging.

 

1. De Minimis Principle and/or Modicum of Creativity Doctrine:  The Indian Copyright Act, 1957, doesn't explicitly address the concept of "de minimis" in the context of originality. However, the ‘principle of de minimis non curat lex’ which translates to, “the law does not concern itself with trifles”[17] can be interpreted and applied to AI-generated content, particularly when considering the level of user input required for copyright protection. Nevertheless, in the landmark case of Bell v. Wilmot Storage Services.[18], the court laid down the meaning and the applicability of the said principle as a defence under section 52[19] of the Copyright Act. The Act, under Section 17, grants copyright ownership to the "author."  However, what constitutes sufficient creative input for authorship remains unclear.  If a user's input is minimal or formulaic, it might not be enough to imbue the AI output with the necessary

 

1. THE LEVEL OF ORIGINALITY.

The Act might require a certain threshold of creative contribution from the user for the work to be considered original. For example, in some scenarios like Joint Authorship,  the user and AI might contribute in a way that's so intertwined, it becomes difficult to identify a single author.  For instance, a user might iteratively refine prompts based on the AI's initial outputs.  This back-and-forth process, where both user and AI contribute creatively, might lead to arguments for joint authorship under the Act.

 

INTERNATIONAL PERSPECTIVES

The rise of AI-generated content has thrown a curveball at copyright laws around the world. Here's a breakdown of how different regions are grappling with this challenge:

 

1. US COPYRIGHT OFFICE STANCE[20]:

The US Copyright Office currently maintains that only works created by humans can be copyrighted. This stance stems from the Copyright Act's requirement for originality, which implies a work originating from a human author's mind. However, the Office acknowledges the potential for AI to contribute meaningfully to creative processes.[21] They are exploring ways to address these complexities, potentially through new legal frameworks or interpretations.

 

2. EUROPEAN UNION CONSIDERATIONS[22]:

The EU copyright framework focuses on the concept of "right holder," which doesn't necessarily require a human author. This opens the door for potential recognition of AI as a co-author in certain circumstances. Additionally, the EU emphasizes the "sweat of the brow" doctrine, which protects the effort invested in creating a work, even if the originality bar is lower. This could be relevant for AI developers who invest significant resources in training AI models.

In the case of Stephen Thaler v. Comptroller-General of Patents[23], an attempt to register copyright for works created by an AI called DABUS was made. The UK Intellectual Property Office rejected the claim, upholding the human authorship requirement. This case underlines the challenges AI faces in securing copyright protection under current legal frameworks.

 

3. THE CHINESE CASE AND RECOGNITION OF AI AUTHORSHIP:

China seems to have adopted a more progressive approach. In a groundbreaking case of Li v Liu[24] , the court recognized an AI-generated work as copyrightable.[25] This suggests a willingness to consider AI-generated works as original and copyrightable, contrasting with regions like the US and EU.

 

These cases and ongoing discussions across the globe demonstrate the evolving nature of copyright law in the age of AI. As AI capabilities continue to advance, legal systems will need to adapt to address issues like ownership, originality, and fair use in the context of AI-generated content.

 

RECOMMENDATIONS

The rise of Artificial Intelligence (AI) has thrown a curveball at intellectual property (IP) laws, particularly copyright.  The current Indian Copyright Act, 1957, doesn't explicitly address AI-generated works, leaving a grey area regarding ownership and protection. This necessitates exploring solutions and charting a future for AI copyright within the Indian legislative landscape.

 

1. THE POSSIBILITY OF CO-AUTHORSHIP:

Since the Act turns a blind eye on considering AI as an author, one solution is to consider AI as a co-author alongside the human programmer or user who provides the underlying data, sets parameters, and curates the output. This acknowledges the human contribution while recognizing the role of AI in generating the creative work.

 

2. ALTERNATIVE COPYRIGHT PROTECTION MODELS:

The current "sweat of the brow" doctrine, which protects works with substantial effort and judgment invested, might not be sufficient for AI outputs.  Here are some alternatives:

a. Sui Generis Protection: A new legal framework specifically designed for AI-generated works could be created. This could establish a separate category with its own protection standards and duration.

b. Database Right:  If the focus is on the underlying data used by AI, database rights could be explored. This protects the selection, arrangement, and presentation of data, potentially safeguarding the investment in data collection and curation.

 

3. LEGISLATIVE AND POLICY AMENDMENTS

To address the challenges of AI copyright, legislative and policy changes are crucial:

Legislative Amendments[26]: The Copyright Act could be amended to explicitly recognize AI as a contributor or joint author in certain circumstances. This would require defining the criteria for AI's contribution to qualify for authorship.

Focus on Originality: The emphasis should be on originality in the final work, regardless of whether it's solely human-created or AI-assisted. Originality can stem from the selection of data, the choice of algorithms, or the unique way the AI processes information to create the final output.

Transparency and Disclosure: Legislation might require disclosing the use of AI in the creation process. This transparency would benefit users and potential licensees by providing information about the work's origin.

Fair Use Considerations: The concept of "fair use" needs to be re-evaluated in the context of AI-generated works. Current fair use guidelines might not adequately address situations where AI utilizes copyrighted material in its creative process.

 

THE WAY FORWARD

A well-defined AI copyright framework in India can foster creativity and innovation:

Incentivize AI Development: Clear ownership and protection will encourage investment in AI research and development. Knowing there's a way to monetize AI-generated creations will drive further innovation in the field.

Promote Collaboration: A robust legal framework can facilitate collaboration between human creators and AI tools. This can lead to the creation of novel and unique works that wouldn't have been possible with either human or AI alone.

Balance Incentives with Access: While protecting copyrighted AI outputs is crucial, it's equally important to ensure access to these works for further innovation and public benefit. Finding the right balance between these two objectives will be key.

 

CONCLUSION

The interplay between AI and copyright law in India presents a compelling challenge. While the current framework might indirectly acknowledge human input in AI-generated works, a more explicit approach is necessary.  To safeguard creators' rights and navigate the complexities of AI, data privacy, and copyright, legislative reform is crucial.  Finding the right balance between protecting intellectual property and fostering innovation will be key.

India has the opportunity to become a frontrunner in the AI era by establishing a robust legal framework. This framework should clearly define authorship and ownership in AI-created works, while ensuring fair use and access to copyrighted material for further innovation.  Transparency regarding AI use in content creation is also vital.  By fostering collaboration between policymakers, legal experts, and the technology industry, India can harness the power of AI for creative expression and progress, ensuring a fair and thriving ecosystems for all stakeholders.

 

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[1] The Impact of AI on Illustrator Jobs: Strategies for survival. (2024, March 2). https://www.toolify.ai/ai-news/the-impact-of-ai-on-illustrator-jobs-strategies-for-survival-2531795#google_vignette

 

[2] The Copyright act, Section 102 (b), No 14 of 1957

[3] Lang, C. (2024, February 5). Copyright in Journalism and news reporting. Copyright Alliance. https://copyrightalliance.org/copyright-journalism-news-reporting/

[4] The Copyright act, Section 13(1)(a), No 14 of 1957

[5] The Copyright act, Section 17, No 14 of 1957

 

[6] Copyright Act 1957, s 17; Eastern India Motion Pictures v Indian Performing Right Society (1977) 2 Supreme Court Cases 820

[7] The Copyright act, Section 2(d)(vi), No 14 of 1957

[8] Lang. C, Supra note 2

[9] The Copyright act, Section 14, No 14 of 1957

[10] The Copyright act, Section 51, No 14 of 1957

[11] The Copyright act, Section 52(1)(a), No 14 of 1957

[12] October 2023 - Volume 51, Issue 9. (2023, September 21). Issuu. https://issuu.com/knoxvillebarassociation/docs/dicta_october_2023

[13] Super Cassettes Industries Limited v. Chintamani Rao, 2012 (49) PTC 1 (Del)

[14] Stim, R. (2023b, June 30). Fair use: What is transformative? Nolo.

 https://www.nolo.com/legal-encyclopedia/fair-use-what-transformative.html

[15] Singh, R., National Law University, Delhi, Kumar, P., & National Law University, Delhi. (2021). Originality requirement in copyright law [Book-chapter]. In Y. Pai & National Law University, Delhi (Eds.), Intellectual Property. https://epgp.inflibnet.ac.in/epgpdata/uploads/epgp_content/S000020LA/P000846/M010214/ET/151375974214_Q1e-text.pdf

[16] Admin. (2023, August 10). Navigating Copyright Challenges in the Age of AI-Generated Content: An Uncharted Legal landscape. Areness - Law & Beyond. https://www.arenesslaw.com/navigating-copyright-challenges-in-the-age-of-ai-generated-content-an-uncharted-legal-landscape/

[17] Iplf. (2023, January 14). Applicability of de minimis in copyright infringement lawsuit. IPLF. https://www.ipandlegalfilings.com/de-minimis-copyright-infringement-where-to-draw-the-line/#:~:text=However%2C%20de%20minimis%20is%20sometimes,require%20judicial%20notice%20and%20scrutiny.

[18] Bell v. Wilmott Storage Services, LLC No. 19-55882 (9th 2021)

[19] The Copyright act, Section 52, No 14 of 1957

 

[20] Office, U. C. (n.d.). Copyright and Artificial intelligence | U.S. Copyright Office. https://www.copyright.gov/ai/

[21] U.S. Copyright Office, Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, (2023) 37 CFR Part 202, Vol. 88, 51

[22] EU copyright - EUR-Lex. (n.d.). https://eur-lex.europa.eu/EN/legal-content/glossary/eu-copyright.html

[23] Stephen Thaler v. Comptroller-General of Patents, Designs and Trade Marks (2023, UKSC 49) https://www.supremecourt.uk/cases/uksc-2021-0201.html

[24] Li v Liu (2022) NSWCA 67 (82), (90)

[25] Ssimon. (2024, May 8). China: A landmark court ruling on copyright protection for AI-generated works - Global Litigation News. Global Litigation News. https://globallitigationnews.bakermckenzie.com/2024/05/08/china-a-landmark-court-ruling-on-copyright-protection-for-ai-generated-works/#:~:text=Artificial%20Intelligence-,China%3A%20A%20landmark%20court%20ruling%20on,protection%20for%20AI%2Dgenerated%20works&text=Recently%2C%20a%20groundbreaking%20court%20judgment,by%20Artificial%20Intelligence%20(AI).

[26] Admin, & Admin. (2023, October 11). The Nexus between Artificial Intelligence and Copyright Act. IIPRD |https://www.iiprd.com/exploring-the-nexus-between-artificial-intelligence-and-copyright-act-1956/