The recent surge of AI-generated content mimicking the iconic style of Studio Ghibli—known popularly as “Ghibli-fication”—highlights critical discussions on digital intellectual property (IP). While images produced by platforms like Midjourney and DALL·E evoke nostalgia through pastel colors and whimsical aesthetics reminiscent of Hayao Miyazaki’s animation, this trend underscores profound legal and ethical concerns.
For example, during a livestream demo by OpenAI in March 2025, developers instantly transformed a selfie into an animated film frame in Ghibli style using GPT-4o, OpenAI’s image generation model. The results appeared strikingly authentic, complete with delicate hand-drawn lines and soft pastel colors. The demo quickly went viral, prompting thousands to replicate the trend, flooding social media with “Ghibli-style” portraits ranging from friends transformed into wide-eyed characters from My Neighbor Totoro’s lush forests to pets depicted as companions in Miyazaki-esque adventures. Even OpenAI CEO Sam Altman famously adopted a Ghibli-style illustration as his profile picture, emphasizing the trend’s popularity.
The heart of this issue lies firstly in the legality and transparency of the data used to train AI models. AI’s reliance on copyrighted materials without explicit consent raises significant concerns. Transparency regarding these datasets is essential to uphold ethical standards and mitigate the risk of intellectual property infringement. Legal frameworks across nations vary significantly—Japan and Singapore adopt permissive stances on AI training datasets, whereas the EU and the U.S. emphasize fair use but highlight transparency and ethical use.
This issue takes on additional urgency for countries in the Global South. Often, these nations serve as significant sources of data used to train AI models, yet they primarily remain consumers rather than beneficiaries of AI-driven innovation. The lack of clear IP regulations and transparency in these countries exacerbates their vulnerability to exploitation, reinforcing global digital inequities.
Secondly, recognizing and protecting digital IP rights becomes crucial as creativity increasingly blends human and machine collaboration. The core challenge is defining the extent of human involvement required for a work to be copyrightable. Current international practices indicate that purely AI-generated content does not receive copyright protection unless demonstrable human creative input is involved.
Ethics and respect for original copyrights are pivotal for broader AI adoption. Clear guidelines and respectful practices offer certainty to consumers and creators alike, facilitating greater trust and willingness to adopt AI technologies. Ultimately, developers and users of AI have shared interests in establishing robust ethical standards.
Blockchain technology presents a practical solution to these issues. Blockchain provides a secure, transparent, and tamper-proof data storage method, clearly documenting the origins of training data and the degree of human contribution in AI-generated works. This ensures fair verification of copyrights and establishes trust in digital collaborations, benefiting both original creators and end-users.
Additionally, there is a growing need for innovative platforms similar to TuneCore in the music industry, which ensure fair distribution of royalties and clear copyright management for creators involved in AI-generated content. Such platforms can play a critical role in monetizing creative works, supporting creators, and enhancing overall trust in AI collaborations. Particularly, these platforms could significantly improve the economic benefits for content creators in the Global South.
Moving forward, policymakers must establish clear guidelines reinforcing transparency in AI training data and defining human creativity within collaborative AI processes. Collaborative international frameworks will be essential, as AI development transcends national borders. Policymakers, AI developers, and creative industry stakeholders must actively engage to build globally consistent regulations.
Lastly, adaptive AI ethics and governance frameworks are crucial. Given the rapid and disruptive pace of AI innovation, ethical considerations and governance policies must continuously evolve and be regularly evaluated to ensure they remain relevant, effective, and responsive to the dynamic AI landscape. This ongoing evaluation will help protect creators, users, and societies from potential negative implications while maximizing AI’s potential for positive impact.
