Impact of Artificial Intelligence on Intellectual Property Rights – Should AI-generated Works be Patentable or Copyrightable?

Author : Tewary Aditya Uttpal

Introduction

The simulation of human intelligence processes by machines, particularly computer systems, is known as artificial intelligence (AI). Learning, thinking, and self-correction are all part of it. Natural language processing (NLP), machine vision, speech recognition, expert systems, and generative tools like ChatGPT and Perplexity are a few examples of AI applications.

AI is revolutionizing the concept of creativity by challenging the belief that it is a unique human trait. These days, creativity is being rethought as a dynamic, cooperative process in which robots actively take part. AI has shown its ability to contribute creatively in ways that were previously thought to be impossible by producing original and important outputs in the fields of music, art, and science. The range of creative possibilities is increased by this shift, which encourages a new type of collaboration in which AI and humans co-create. But there are also important moral and legal concerns with AI’s involvement. These difficulties force us to reconsider the definition of creativity and its authorship as AI develops and produces work on its own.In this changing environment, artificial intelligence (AI) is changing intellectual property and ethical norms by converting creativity from a lone human endeavor into an interdependent force.

The influence of artificial intelligence (AI) on intellectual property rights is examined in this article, along with existing international legal stances, arguments on both sides of the issue, and potential future paths for balancing legal justice with technical innovation.

Understanding Intellectual Property Rights (IPR)

Creations of the human mind, including inventions, artwork, music, designs, and logos, are referred to as intellectual property (IP). It prevents unauthorized use by granting artists the only right to utilize and profit from their creations. Despite its potential connection to a physical object, intellectual property (IP) is an intangible right that safeguards the creator’s creative work. For instance, Ms. Ankita does not own the intangible rights to the music when she purchases a CD; instead, she just owns the physical CD. The buyer does not get any of the composer Mr. Ankit’s rights, including the ability to reproduce or replicate the music.

Industrial property and copyright (literary property) are the two primary categories into which intellectual property is typically separated. Trademarks, industrial designs, layout designs, and patents (both process and product) are examples of industrial property. Literary, artistic, and musical works are all protected by copyright, as are adjacent rights like broadcasting and performers’ rights. By guaranteeing that creators can retain control over and make money from their intellectual endeavors while striking a balance between ownership and public access, these legal safeguards work together to promote creativity and innovation.

Thus, the human-centric ideas of creativity, authorship, and inventorship form the foundation of the entire intellectual property system. These fundamental ideas are being upended by AI as it starts to independently produce new kinds of expression and creation. It begs the question: is it possible for a non-human being to be creative, and should it be rewarded using the same legal procedures as humans?

Rise of AI in Creative and Inventive Processes

Artificial intelligence (AI) has evolved from basic data analysis to a transformative creative force, reshaping industries ranging from art to materials science. Rather of replacing human creativity, artificial intelligence improves it by increasing inspiration, efficiency, and collaboration. The emergence of generative AI, notably Large Language Models (LLMs), represents a significant leap, allowing machines to learn from massive datasets and generate original text, graphics, music, and code.

Generative AI has evolved through GANs, diffusion models, and multimodal systems to promote digital creativity and innovation across domains. It democratizes artistic and technological expression, automates complicated creative processes, and gives people and businesses a competitive advantage. Mastering generative AI is becoming increasingly important for being relevant, innovative, and flexible in today’s quickly changing, AI-powered environment.

AI has made great advances in creativity, producing works such as “Edmond de Belamy” composing music with AIVA, and creating literature with ChatGPT. Tools like DALL·E and MidJourney produce beautiful images. Beyond art, AI promotes innovation by uncovering new materials, technical solutions, and pharmaceuticals. The 2019 DABUS case, which involved AI-invented creations, sparked global debate about AI’s legal position as an inventor.

The distinction between AI as a tool and as an autonomous creator is critical since current intellectual property (IP) regulations are human-centered. When AI is used as a tool, humans preserve creative control by making important decisions and retaining authorship, allowing AI-assisted products to qualify for copyright and patent protection. However, when AI operates autonomously, producing works with little human intervention, it lacks legal personhood and thus cannot be recognized as an author or inventor. As a result, most governments, including the United States, United Kingdom, the European Union, and India, refuse IP protection to wholly AI-generated creations, instead considering them as public domain. This distinction is critical for establishing authorship, ownership, and accountability, creating legislative reforms, and influencing economic investments in AI-driven innovation.

Legal Challenges of AI-Generated Works.

4.1 Copyright Challenges

Copyright law has typically required a human author since uniqueness involves intellectual judgment and inventiveness, which AI lacks. When AI generates things autonomously, it becomes impossible to identify the author.

In the United States, the Copyright Office and courts, particularly Thaler v. Perlmutter (2022), have refused protection to wholly AI-generated works, confirming that human authorship is constitutionally necessary.

In contrast, Section 9(3) of the United Kingdom’s Copyright, Designs and Patents Act (CDPA) 1988 assigns authorship to the person who made the required arrangements for the creation of the work. Thus, whereas U.S. law exempts AI-generated content from protection, U.K. law provides limited recognition by attributing authorship indirectly to the human who facilitated the AI’s creative process.

4.2. Patent Challenges

Patents pose an even more complicated challenge. The inventor must be a natural person who can accept legal responsibility and ownership. AI systems such as DABUS challenge this standard by developing inventions without human intellectual input.
Most governments, notably the United States Patent and Trademark Office (USPTO), the European Patent Office (EPO), and the United Kingdom Intellectual Property Office, have rejected AI inventorship claims, arguing that only humans may be inventors. However, in 2021, South Africa became the first country to grant a patent with DABUS as the inventor, indicating a potential shift in world opinion.
The main legal quandary is that awarding patents to AI would necessitate transferring ownership and liability to entities incapable of moral judgment or legal obligation.

Comparative Legal Perspectives

Due to varying national goals and interpretations, the international legal framework governing intellectual property (IP) produced by artificial intelligence (AI) is still disjointed. While some governments maintain rigid human-centric frameworks, others take a more accommodating stance to account for the quick advancement of AI technology. Ongoing discussions concerning authorship, inventorship, and ownership of AI-generated works have been exacerbated by this lack of global consistency.

In United States, human authorship and inventorship are central to IP law. The U.S. Copyright Office emphasizes that copyright requires a human author and routinely rejects protection for works made entirely by AI, even when inspired by humans. Similarly, court decisions rejecting AI-generated ideas support the requirement under patent law that a “inventor” be a genuine person. This strategy emphasizes the philosophical and constitutional underpinnings of American intellectual property law, which place a high value on human innovation and responsibility.

In a similar vein, the European Union defines originality as human intellectual invention and individual expression. EU law associates creative authorship with free will and intentional decision-making—qualities that AI systems are fundamentally devoid of. In keeping with the fundamental customs of European legal systems, this guarantees that protection is still linked to human contribution.

The Copyright, Designs and Patents Act 1988 (Section 9(3)) in the United Kingdom, on the other hand, shows a more practical approach by designating authorship of “computer-generated works” to the individual who makes the required arrangements for creation. This temporarily clarifies ownership in AI-assisted production, even though it does not acknowledge AI as an author.

However, AI-generated works are not explicitly recognized under Indian law. Due to the assumption of human authorship in both copyright and patent laws, issues about AI inventorship remain unsolved and are susceptible to case-by-case interpretation.

International frameworks such as the TRIPS Agreement and WIPO are still focused on people, but they are changing. In order to ensure equitable, uniform, and future-ready IP governance, WIPO’s continuing discussions underscore the critical need for harmonized rules to meet AI’s expanding creative and inventive capacities.

Arguments in Favor of Granting IP Rights to AI-Generated Works

• Promotion of Innovation: The creation and application of innovative AI technologies would be encouraged by the granting of intellectual property rights for works produced by AI. Businesses that make significant investments in AI research ought to be able to safeguard and market the outcomes of their systems.

• Acknowledgment of Human Contribution: Data scientists, programmers, and investors all contribute significantly to the development and training of AI, even when it produces content on its own. These contributors are indirectly rewarded when AI-generated outputs are acknowledged.

• Adaptation to Technological Reality: IP legislation may become outdated if AI’s outputs are not protected when it becomes a dominating creator and innovator. Legal frameworks could be modified to ensure relevance in the ever changing digital economy.Economic and Competitive Advantage: Countries that acknowledge intellectual property produced by AI may draw investment motivated by innovation and promote technical leadership.

• Continuity of IP System: The exclusivity concept at the heart of IP law may be undermined if valuable AI-generated works are not acknowledged and end up in the public domain.

Arguments Against Granting IP Rights to AI-Generated Works

Human-Centric Foundation of Law: Human creativity and moral agency are the cornerstones of intellectual property law. These fundamental legal and philosophical precepts are compromised when it is extended to machines.

Accountability and Enforcement Issues: Because AI lacks legal personality, it is unable to engage into contracts, possess property, or be held accountable for violations. Thus, granting AI rights would lead to ethical and practical ambiguity.

Risk of Over-Monopolization: AI is capable of producing enormous volumes of inventions and material at previously unheard-of speeds. Permitting IP protection could result in monopolization, which would hinder market competition and human ingenuity.

Dilution of Moral Rights: Moral rights are intrinsically human, much like honesty and attribution. Since AI has neither feelings or identity to defend, applying them to AI is illogical.

Alternative Models: To minimize the complexity of extending existing IP rules, AI outputs could instead be managed by contractual agreements, database rights, or open-source frameworks.

Possible Solutions and Future Directions

Option 1: Uphold the Human Authorship/Inventorship Rule: The most straightforward strategy is to state that intellectual property protection is only applicable in cases where a human has contributed significantly in a creative or inventive way. AI would continue to be a tool, and the human programmer, user, or organization in charge of the AI’s operations would retain ownership.

Option 2: Establish a New Legal Category for Works Produced by AI: For AI-generated works, governments could establish a distinct class of protection with restricted rights and duration. This could ensure that AI’s participation is acknowledged without handing it full human-like rights by striking a balance between incentives and public access.

Option 3: Public Domain Approach: Free use and additional innovation could be encouraged by placing AI-generated outputs in the public domain. This encourages cooperation and access, but it might deter funding for AI research.

Option 4: Hybrid or Shared Ownership: Depending on their roles in the development of AI, developers, owners, and users could share rights. Benefits would be distributed under this hybrid paradigm while human accountability is upheld.

Suggestions for Policy

Legal Reform: The function of AI in authorship and inventorship should be clearly defined by legislators.
Ethical Standards: Create rules to guarantee responsibility, equity, and openness in works produced by AI.
International Coordination: Global AI-IP policy harmonization should be spearheaded by the World Intellectual Property Organization (WIPO).
Promoting Responsible Innovation: Rather than replacing AI, future legislation should encourage human ingenuity that makes use of technology.

Conclusion

Innovation and creativity are changing as a result of artificial intelligence. The controversy surrounding the patentability and copyrightability of AI-generated works reflects a larger conflict between legal tradition and technical advancement. Opponents warn that acknowledging AI-generated works compromises human authorship and accountability, while supporters contend that doing so will spur investment and innovation.

In an era where human and artificial creativity are becoming more intertwined, the ultimate objective should be to guarantee that intellectual property law continues to foster innovation, reward effort, and serve the public interest.

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