Creativity In the Age of the Copy-Paste Machine: AI, Art, and Authorship

When Machines Learn to Imagine

Have you ever wondered who the real creator is behind those imaginative AI memes like Ballerina Cappuccina or Tung Tung Tung Sahur? Or if they’re even considered original in the eyes of the law?
AI tools have completely hooked us with their creativity in art, writing, and design. From Gemini’s nostalgic “meet your past” trend to those orange cat meme videos that fill our brainrot. But these examples make us stop and think that can such works actually be protected by copyright? And if they can, who really owns them? Is that the person, the programmer, or the machine?
In a world where creativity can be copied and generated in seconds, the idea of what it means to be truly original is changing faster than ever.

AI tools like ChatGPT, DALL·E, and Midjourney have transformed creation. A simple prompt now produces fully formed ideas. Shows like Mahabharat: Ek Dharmayudh on JioHotstar and the AI-altered ending of Raanjhanaa illustrate how easily content can be generated. As AI starts to resemble a co-author, contributing to the final output, the boundary between tool and collaborator blurs. Yet AI lacks intention, emotion, and legal status. The question remains, when AI creates, who is the author?

The Legal Battle Over AI-Generated Works

When you think about originality, you probably imagine a person sitting with a notebook, a paintbrush, or a guitar, creating something new. But what does originality even mean when an AI model can generate content using sources from thousands of human creations? Courts have long held that originality is not about effort alone but about a minimum spark of creativity. The Supreme Court said this clearly in EBC v. D.B. Modak, rejecting the “sweat of the brow” theory and requiring at least some intellectual creativity for a work to qualify as original. But when an AI rearranges existing data, is that creativity? Or is it just remixing what humans already made? For instance, an AI can generate a “new” painting in the style of Van Gogh or compose a poem mimicking Shakespeare. This process is a masterful algorithmic recombination, which raises the question: can something trained on millions of human works ever truly possess that “minimum spark of creativity”? Even international frameworks like the Berne Convention and TRIPS recognizes works born from human intellectual creation, not machine-generated outputs.

If originality is already confusing, authorship takes the debate to another level. Copyright law assumes a human creator, someone with intentions, skill, and judgment. But AI flips this idea completely. Under the Copyright Act of India, Section 2(d) says that for computer-generated works, the “author” is the person who causes the work to be created. It sounds simple, until you ask the obvious question: who actually causes an AI-generated output? The developer? The user who typed the prompt?The WCT protects computer programs as literary works but remains silent on works created by those programs. This leaves a major gap that laws needed to be updated, if AI cannot be a legal author, and its human contributors each play different roles, who actually gets to claim ownership?

The UK’s CDPA, 1988, explains this more clearly. Section 9(3) treats the programmer, as the author. It is a practical approach that India could take inspiration from while deciding how to handle AI authorship.

However, currently as per the Indian Copyright laws, AI cannot be an author and computer-generated works are recognized only when there’s a human input behind them.

Ethical and Cultural Crossroads: Creativity Without Conscience?

When AI is used to copy and mimic art that have cultural symbol or genesis it does so without fulling understanding the cultural significance and spiritual weight those symbols carry. This raises uncomfortable questions about cultural appropriation in the digital age. AI tools can be used to produce art that are similar in style with indigenous or minority art style but the inherently lack the cultural context and the sacred meaning that indigenous art carries, they are essentially just commercialising art without consent. Studies reveal that AI-generated art frequently eternalizes gender, racial, and cultural stereotypes embedded in training data. Algorithmic bias doesn’t just replicate human prejudice; it amplifies it at scale. And here lies the paradox: while AI has democratized art creation by putting powerful tools in the hands of amateurs, it simultaneously threatens to devalue human craftsmanship. If anyone can create a Van Gogh-style masterpiece with a simple prompt, does the decade of struggle, the paint-stained studio, the emotional investment mean anything anymore?

Economic and Professional Fallout: Artists vs Algorithms

The data presents a sobering picture. Goldman Sachs research indicates that generative AI could automate 26 percent of tasks performed by professional artists and designers. Illustrators, graphic designers, and writers are already reporting lost contracts as clients opt for AI-generated content that is faster and cheaper. The economic shift is substantial: what once required weeks now takes minutes, what once cost thousands now costs just one prompt. Yet this comes at a cost, the superficiality of AI generated art cannot be compared to an art that carries the depth of human emotional investment. There is a twist in this story, a new creative economy is rising. “Prompt engineering” has emerged as a legitimate skill, blending creativity with technical know-how. Companies are hiring “AI Content Architects” and “Conversational UX Writers” who understand that the quality of the prompt determines the quality of output. Is AI, then, a threat to artists or a catalyst forcing creative rebirth?

Creative Practice in an Augmented World: Collaboration, Not Competition

Perhaps the answer lies not in choosing sides, but in hybrid authorship. Musicians like Jean-Michel Jarre and Nile Rodgers have embraced AI as a creative collaborator using it for chord progressions, melodic experimentation, and breaking through creative blocks. The Beatles’ AI-enhanced release of ‘Now and Then’ (2023) demonstrated how technology can restore and complete unfinished art. In filmmaking, AI handles VFX, generates storyboards, and even suggests narrative alternatives, while humans remain the “conductors” who infuse the final product with emotional intent. The key finding? AI can inspire, suggest, and accelerate, but human creation remains irreplaceable. What AI generates, the artist evaluates, selects, and refines. Tools like Adobe’s AI-powered Fresco assist with textures and palettes, but composition and meaning still require a human eye.

The Way Forward: Redefining Authorship and Responsibility

 Government is catching up. The Generative AI Copyright Disclosure Act (2024) in the US now requires developers to disclose copyrighted material in training datasets. India’s AI Governance Guidelines (2025) recommend transparency norms, labelling AI-generated content clearly, and revisiting fair dealing exceptions under Section 52 of the Copyright Act. Across jurisdictions, a consensus is forming: AI cannot be an author, but humans who meaningfully shape outputs can retain copyright. The call now is for ethical frameworks that protect original creators. Yet perhaps the most profound insight isn’t legal, but philosophical. In an age where machines can replicate styles, generate infinite variations, and flood the market with synthetic creativity, human art will not be distinguished by perfection but by imperfection. The emotional depth, the lived experience, the unique creative voice that AI cannot possess. No algorithm can replace the authenticity of human work.

References

1. Eastern Book Company v. D.B. Modak, (2004) 10 SCC 521.
2. Copyright Act, 1957 (India), Section 2(d).
3. Copyright, Designs and Patents Act, 1988 (UK), Section 9(3).
4. Berne Convention for the Protection of Literary and Artistic Works, WIPO.
5. Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), WTO.
6. WIPO Copyright Treaty (WCT), 1996.
7. Copyright Act, 1957 (India), Section 52 (Fair Dealing Exceptions).
8. The Legal School. “Section 52 of Copyright Act, 1957: Exceptions to Infringement.” (2025).
9. Bar and Bench. “Intersection of Intellectual Property Rights and AI-Generated Works (Part I).” (2024). 
10. The Marshall Malone. “The Democratization of Art: Digital Technology & AI.” (2024)
11. Nature. “How Stereotypes Shape AI – And What That Means For Everyone.” (2025).
12. Creative Boom. “Is AI Really Coming For Your Illustration Career? An Industry Perspective.”
13. International Journal of Music and Collaborative AI. “Collaborative AI in Music Composition: Human-AI Symbiosis in Creative Industries.” (2025).
14. Reset Media. “AI in Filmmaking: Human Creativity Meets Technology.” (2025).
15. Forbes. “How To Be Authentic In The Age Of AI.” (2025)