AI and Copyright: What India Can Learn from the UK and European Union

Abstract

This article compares the treatment of AI-assisted and AI-generated works in the United Kingdom and the European Union. The United Kingdom assigns authorship of a computer-generated work to the person who makes the necessary arrangements for its creation. European copyright law, by contrast, continues to require an identifiable human intellectual contribution. The comparison offers India a useful basis for reform.

The paper critically assesses whether current copyright regimes adequately address the complexities introduced by the AI driven creativity and considers the consequences of these differing approaches for artists, technology innovators and the wider cultural sector. By mapping points of convergence, divergence and emerging trends, the research evaluates the capacity of existing laws to balance technological programs with the safeguarding of intellectual property. It concludes with recommendation for the harmonized and forward-looking copyright system capable of responding to the expanding role of artificial intelligence in creative industries.

Keywords

AI-generated, authorship, copyright, computer-generated works, legal frameworks, emerging trends.

Introduction

Over the last 10 years artificial intelligence (AI) has completely changed. It moved from being a simple tool for automatic work to a real creator of Art, Music, Books. Systems like ChatGPT can now create paintings, write poems and make music that sounds just like what a person would create. This huge jump in technology has changed creative business and made the clear line between human and machine creativity harder to see. Things that once needed human imagination can now be done or even done better by computer programmes. Because of this copyright law which is built on the idea that only humans can be creative is now facing big questions it was never designed to answer.

Comparative Legal Analysis

Legal systems disagree on whether artificial intelligence can participate in authorship. The United Kingdom and India leave some room for computer-generated works within existing statutes, while the United States maintains a strict human-authorship requirement. The European Union has focused on human originality, transparency and accountability. These approaches reveal the central policy choice: how to recognise AI-assisted production without displacing human creativity and responsibility.

United Kingdom: a Pragmatic Legal Framework

The United Kingdom offers an early statutory response to computer-generated works. Section 9(3) of the Copyright, Designs and Patents Act 1988 treats the author as the person who undertakes the arrangements necessary for creation. The rule does not grant authorship to a machine; it locates authorship in the human organisation of the creative process.

This formulation is pragmatic. It acknowledges that a computer may produce the final expression while keeping legal authorship with the person who organises the creative or technical process. Depending on the facts, that person may be the developer, operator or user who exercises effective control over the work.

No United Kingdom court has yet settled authorship for a fully autonomous AI output. Existing law can nevertheless accommodate many AI-assisted works because a human still makes the arrangements that lead to creation. The UK Intellectual Property Office has favoured continued human responsibility while keeping the position under review as generative systems become more autonomous.

The strength of the UK's legal model is how balanced it is. It stops rights from being given to a mission but at the same time, it gives legal clarity to the people who use or design these AI tools in a creative way. This balanced approach could be a useful example for other countries that share a similar legal system (known as common law) including India.

European Union: Towards Harmonisation and Accountability

The European Union has no single rule dedicated to AI authorship, but its copyright law applies a demanding originality standard. Decisions of the Court of Justice require a work to reflect the author's own intellectual creation and creative freedom. That standard connects copyright to human choices rather than to autonomous machine output.

A fully autonomous output may therefore fall outside ordinary copyright because it lacks a human author. The European Union has addressed adjacent concerns through transparency, accountability and platform regulation, while policymakers continue to debate whether AI-generated outputs need a separate and narrower form of protection.

The European approach is more cautious. It refuses legal personhood for machines while recognising the economic importance of AI-assisted creativity. Protection therefore remains tied to identifiable human intellectual contribution and responsibility.

The comparative picture is clear. Existing copyright principles can protect AI-assisted work where meaningful human creativity remains visible, but they are poorly suited to wholly autonomous output. Any international approach should recognise technological change without abandoning the human foundation of authorship.

Copyright protects not only economic interests but also an author's personal connection to a work through moral rights of attribution and integrity. An AI system has no reputation, intention or emotional bond with an output. Granting it moral rights would therefore detach those rights from the human interests they were designed to protect.

AI has neither legal intention nor moral agency, which makes machine authorship a poor basis for accountability. When generated content infringes copyright or causes harm, responsibility must attach to the people and organisations that design, deploy or control the system, according to their role and knowledge.

There is also a major problem of creative authenticity. Works made by AI often copy styles and elements from the huge amount of existing human-made content they were trained with which immediately raises worries about originality and plagiarism. Many AI models are trained using copyrighted materials without getting clear permission from the original creators. This leads to big ethical and legal arguments about consent and what counts as far as. Ultimately, these practices risk lowering the value of the hard creative work done by human artists whose creations are secretly feeding the AI's learning process.

Economic Implications: Value, Competition and Market Disruption

AI also presents difficult questions for the creative economy. It lowers production costs, broadens access to sophisticated tools and allows smaller creators to experiment at scale. A designer can produce prototypes more quickly, a musician can test compositions and a filmmaker can streamline editing. These gains are real, but so is the risk that value becomes concentrated in the companies controlling models, data and distribution.

Widespread AI-generated content may weaken the bargaining position of human creators, particularly when models are trained on protected work without consent or payment. Cheap synthetic output can flood markets and reduce the visibility of original work. Competition policy and copyright reform must therefore address both creator remuneration and concentration in the AI supply chain.

Policymakers must preserve the productive benefits of AI while protecting fair competition and the livelihoods of human creators. Collective licensing, transparent training-data records and workable royalty-sharing mechanisms could allow model developers to innovate while ensuring that authors are compensated when protected works contribute to commercial systems.

The Path Forward: a Hybrid Authorship Model

In conclusion, the future of authorship depends on accepting a hybrid model-one that sees creative work as a shared process between human intelligence and artificial intelligence. This model would work on three levels:

Human Authorship when a person's creativity is the most important part, the work gets full copyright protection.

Collaborative authorship when humans and AI work together, the work gets partial copyright protection based on how much the person contributed.

Special AI authorship when the AI works completely on it gets a limited, special form of protection based on the money invested and the new technology used.

This three-tiered system protects the ethical and core of authorship while making the law fit the reality of new technology. It recognizes that in the digital age, creativity is not purely human anymore, but it is still driven by human values, ethics and goals.

By adopting this balanced approach, legal systems can encourage new ideas, protect human creators, and make sure things are fair in a world that relies on more and more automation. The goal is not to change the definition of creativity, but to reimagine copyright as a living legal system that can grow right alongside human progress and technological change.

Suggestions

India should adopt a human-centred framework. Copyright should arise only where a person exercises meaningful creative control over the conception, selection or editing of an AI-assisted work. Fully autonomous outputs could receive, if policy requires it, a narrower related right of limited duration rather than ordinary copyright. The law should also require transparency about training data and fair remuneration where protected works are used.

It should also require meaningful disclosure of training-data sources and fair remuneration when copyrighted works are used. Increased global agreement collaboration through international groups like WIPO is necessary to create shared rules on AI authorship and ethics across the world. Ethical support government should encourage research and open - licensing systems that promote AI tools that make human creativity better not replace it. Boost education lawyers, Reuters, and policy makers should be trained to understand how AI works and how to adopt copyright law to these new technologies.

Artificial intelligence has expanded the range and speed of creative production, but copyright must continue to protect the human intellectual and moral interests at its core. Authorship can evolve to recognise genuine collaboration with machines without pretending that software possesses intention, dignity or responsibility.

By adopting a balance system focused on human supervision - limited protections for fully automated AI and worldwide cooperation we can protect fairness and encourage new ideas. Ethical and intelligent adoption of copyright will ensure that creativity remains a uniquely human pursuit supporting AI but never taken over by it.

Primary materials

Key primary materials: Copyright Act, 1957; WIPO copyright resources.