By – Anubhi Srivastava

Abstract

The rise of AI in creative domains challenges traditional notions of authorship, originality, and cultural production. From Studio Ghibli-style animations to AI-generated music and scripts, machine learning blurs the line between imitation and innovation. This article examines the ethical, legal, and philosophical debates surrounding “AI art,” including copyright, authenticity, and cultural bias. It also highlights the role of consumers in shaping legitimacy and the risks of marginalizing non-Western traditions. Ultimately, it examines public policy concerns and advocates for frameworks that strike a balance between innovation and equity, transparency, and artistic integrity. 

Introduction:

The rise of artificial intelligence (AI) in creative spaces has sparked an ongoing debate about the boundaries of technological intervention in art. The recent emergence of AI-generated animations resembling Studio Ghibli’s distinct style raises pressing questions about authorship, originality, and the evolving definition of creativity. This article explores the ethical concerns, regulatory implications, and broader impact of AI on human creativity and cultural production.

Redefining the Narrative in Artistic Creation:

AI has rapidly embedded itself into everyday life, from the tips of our fingertips on smartphones to large-scale industrial applications. The integration is no longer superficial. AI can generate music, write scripts, produce animations, and create digital paintings, sometimes even with stunning emotional resonance and stylistic accuracy.

AI’s impact on the creative sphere now extends beyond aesthetics. The recent Ghibli-style animations generated by AI models show that machine learning systems can analyse visual and thematic patterns and produce works that echo established artistic voices. With advancements in generative models, AI can now replicate forms of creativity traditionally seen as uniquely ‘human’. This ability forces us to reconsider: Can an algorithmic process that mimics patterns be truly creative, or is creativity inherently human, requiring subjectivity, emotion, and lived experience?

With AI-generated works gaining visibility in both mainstream and underground artistic communities, the line between imitation and innovation blurs. Are we witnessing a new form of creativity, or simply an advanced form of mimicry?

The question is not just whether AI can create, but who is allowed to create through AI. What’s the narrative behind AI’s knowledge production? The phrase “Who directs the play, who writes the script, and who are the audience members giving their applause?” invites a deeper interrogation of power dynamics. Who designs the AI? Whose data is used? Whose aesthetics dominates?

AI is often framed as a democratizing tool, but in practice, it frequently reflects dominant narratives. Systems are trained on datasets curated by a narrow segment of society (primarily developers from elite institutions or corporations). This introduces biases into the model, reproducing structural inequalities and cultural blind spots. Rather than diversifying creative voices, AI may end up amplifying already dominant perspectives, marginalizing non-Western, indigenous, or subaltern forms of expression.

Therefore, allowing AI into the creative domain without critical checks risks transforming art into a reflection of pre-programmed ideologies, where the ‘tiger’ of artistic freedom is tamed by the ‘ringmasters’ of technological capital.

The Role of Consumers in AI Art:

Often overlooked in these debates is the power of the consumer. The reception of art, whether it is embraced as innovative or dismissed as derivative, largely depends on how audiences engage with and interpret creative works. Public reception can validate or challenge the narratives constructed by both human and AI creators. In many cases, consumers help drive trends and set market expectations, influencing whether AI-generated art is seen as a legitimate form of creative expression or simply a technologically driven imitation, as very clearly seen in the Studio Ghibli trend.

Ethical, Legal, and Philosophical Debates:

If AI is trained on the works of human creators, should those original artists be acknowledged and compensated? The regulatory implications are vast. In cases where AI is trained on a multitude of styles (maybe copyrighted), who owns the final product? The AI developer, the contributors of the training data, or the broader public?

Moreover, regulatory frameworks must grapple with jurisdictional ambiguity, especially since AI models are often developed in one country, trained on datasets sourced globally, and deployed across international markets. Add to that the looming concerns around data privacy and surveillance, and regulation becomes not just a matter of copyright, but of civil rights.

Ultimately, regulation must strike a balance: protecting the rights of artists and data subjects while not stifling technological innovation.

The debate around AI’s creative potential is also a philosophical one. If AI handles repetitive, technical, or time-consuming aspects of creative production, could this liberate human artists, enabling them to focus on more abstract or experimental pursuits?

Conversely, critics argue that excessive reliance on AI risks diluting the artistic process, reducing it to formulaic outputs devoid of context, intuition, and emotional depth. Furthermore, AI-generated art raises concerns about authenticity. Can art still serve as a window into the human condition if it is generated by non-human agents?

There’s also a broader moral question: Is the pursuit of AI-enhanced art aligned with our vision for a just and inclusive society? While AI might make tools more accessible (enabling individuals without formal training to produce high-quality content), this inclusivity might be illusory if underlying data and tools remain under elite control.

Public morality must guide our engagement with AI in creative domains. This includes ethical standards around consent, fairness, cultural preservation, and equitable access. The challenge lies in developing a collective framework that acknowledges technological progress while centring human dignity, agency, and expression.

Should AI be a co-creator, a tool, or merely an assistant? The answer may lie not in banning or embracing AI wholesale, but in redefining creativity in an age of collaboration between humans and machines.

Public Policy Concerns:

This fast-paced integration of AI into creative domains presents public policy challenges that extend beyond intellectual property into questions of culture, equity, and governance.

India’s Copyright Act of 1957 provides that computer-generated works are attributed to ‘the person who causes the work to be created’ (Section 2(d)(vi)), but Indian courts strictly limit authorship to human creators. AI systems lack legal personhood, and prompt-based use is generally insufficient to confer copyright. Hence, AI-generated works blur the line between creator and tool. This leaves courts and regulators unsure whether authorship lies with the human prompter, the AI developer, or no one at all. Policymakers must determine whether training on copyrighted material constitutes “fair use” or infringement and whether original artists deserve recognition and compensation when their work informs generative outputs. Policymakers must also address how to protect livelihoods without halting innovation. This can be done through fair remuneration schemes, initiatives, or new revenue models between AI developers and artists.

Public policy must also safeguard marginalized, indigenous, and non-Western traditions from being subsumed into datasets without acknowledgment or respect. Otherwise, cultural diversity may be eroded in favour of algorithmically dominated styles. 

Complicating matters further, AI development and deployment are inherently transnational, i.e, models may be trained in one country, built on data from another, and consumed worldwide. This raises questions about jurisdiction: whose laws apply when disputes arise? International dialogue and coordination, perhaps through treaties or multilateral MoUs, may be needed to avoid regulatory arbitrage.

Finally, consumers have a right to know whether what they are interacting with is AI-generated or human-made content. Transparent labelling and disclosure requirements should become necessary to maintain trust. 

Conclusion

Artificial intelligence has broadened creative possibilities in India, but it also challenges conventional understandings of authorship and originality. While NITI Aayog’s National Strategy for AI emphasises innovation and inclusivity, gaps remain in adapting Indian copyright law, which still presumes human authorship. An unchecked use in creative fields risks deepening inequalities by amplifying dominant cultural narratives at the expense of marginalised voices. Stronger regulatory clarity and ethical guidelines are essential to balance technological progress with cultural preservation. Thus, India’s policy future must carefully align AI-driven innovation with the protection of human creativity and expression.

Image Source : https://incubator.ucf.edu/what-is-artificial-intelligence-ai-and-why-people-should-learn-about-it/