Artificial intelligence is rapidly reshaping creative industries, offering powerful tools that enhance artistic expression, streamline workflows, and make creative pursuits more accessible. Platforms like MidJourney and other AI-driven tools allow individuals with no formal artistic training to generate stunning visuals, music, and even literature.

While this democratisation of creativity presents exciting opportunities, it also raises serious concerns about originality, authorship, and the future of human artists, especially fresh graduates entering the field.

The bright side: Accessibility and efficiency

One of AI’s most significant contributions to creativity is accessibility. AI-powered tools lower the barriers to entry for people who may lack technical skills but have strong creative ideas. Someone with no experience in digital illustration can now generate professional-grade artwork in minutes, and writers can use AI-assisted tools to refine and generate ideas more efficiently.

For businesses, AI is a game-changer. It speeds up content creation, helps automate repetitive design tasks, and enables rapid prototyping. Companies can produce high-quality marketing materials, concept art, and branding assets with minimal human input, reducing costs and increasing output. The efficiency AI offers is undeniable, allowing creatives to focus on strategy and high-level conceptual work rather than manual execution.

The dark side: Originality, copyright, and job displacement

However, the integration of AI into creative work comes with serious challenges. One of the most pressing concerns is originality. AI generates work based on pre-existing data, often pulling from millions of images, texts, and sounds without truly “creating” in the human sense.

This leads to questions of authorship—if an AI creates an image based on thousands of existing works, who owns the final product? The artist who input the prompt? The developers of the AI? Or the countless creators whose works were used to train the model?

Also Read: Is AI the end of originality or a new dawn for creativity?

Copyright issues are already causing legal battles. Many artists and photographers have accused AI companies of using their works without consent to train models. The lack of clear legal frameworks means AI-generated content exists in a grey area, making it difficult for human creators to protect their intellectual property.

Beyond legal concerns, there’s also the issue of job displacement. Fresh graduates in art, design, music, and other creative disciplines now face an increasingly competitive market where companies might prefer AI-generated content over hiring human artists. Why pay for a designer when an AI tool can generate 10 different versions of a logo in seconds? This shift threatens the traditional paths that many creatives rely on to build their careers.

AI and the myth of the “non-creative”

Another interesting consequence of AI’s rise is the potential for non-creatives to produce high-quality work. Someone with no artistic background can now generate a gallery-worthy digital painting, raising philosophical questions about what it means to be an artist.

Is creativity about the final product, or is it about the process? If a person uses AI to generate an idea but refines it manually, are they still an artist? These questions challenge the traditional definitions of creativity and talent.

My opinion: Adapt or be left behind

AI is not an existential threat to human creativity, but it is a force that cannot be ignored. Trying to resist AI’s advancement is futile—technology will continue to evolve whether we like it or not. The most successful creatives will be those who learn to integrate AI into their workflow rather than seeing it as competition.

Fresh graduates and emerging artists should focus on what AI cannot replicate—deep human emotion, originality, and personal storytelling. AI can generate content, but it lacks the human experience that gives art its soul. Those who embrace AI as a tool, rather than a replacement, will find themselves at an advantage in an industry that is constantly evolving.

At the same time, ethical concerns around copyright and fair compensation for artists must be addressed. Governments and industry leaders must develop clear regulations to protect human creators while allowing innovation to flourish. Without proper oversight, we risk devaluing human artistry in favour of machine-generated convenience.

Ultimately, creativity is not about how art is made but about the ideas, emotions, and narratives it conveys. AI is just another tool—how we use it will determine whether it enhances or undermines human creativity.

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The latest OpenAI’s version of ChatGPT, an AI-enabled chatbot allows users to generate images of themselves, their pets, films or memes in the distinct “Ghibli” style of Studio Ghibli, the acclaimed Japanese animation studio. Notably, not all users are on board with the “Ghiblification” of images by OpenAI’s new tool. This post looks at the legal issues surrounding this new ChatGPT feature.

Blurring the line between homage and outright infringement

Legally speaking, artistic styles per se may not be protected under copyright law. However, specific characters or scenes like Totoro or a frame from Princess Mononoke are legally protected.

However, when ChatGPT allows a user to generate an image in an ‘Ghibli-style,’ OpenAI may likely be considered as trading off the goodwill of Ghibli’s trademarks (i.e. using Ghibli’s identifiable style) which may lead to a likelihood of confusion among consumers that such a function is indeed endorsed or licensed by Studio Ghibli.

Therefore, if ChatGPT produces a “Ghibli”-fied image that may be too close to the originals, such image may be subject to a potential lawsuit.

Walking on the thin line of copyright law

To date, there isn’t any legal precedent to determine if OpenAI contravenes the copyright law.

AI companies like OpenAI for training data for its models have used the “fair use doctrine” under copyright law as a legal protection. The “fair use doctrine” is a legal grey zone. The doctrine allows limited access to copyrighted materials without prior permission (e.g. quotations, research, teaching, news reporting, and other non-infringing uses).

However, OpenAI is already facing several lawsuits over its approach to scrapping the internet for training data for its models, including plenty of copyrighted material. In 2023, The New York Times, a news company sued OpenAI that the AI company infringed its copyright by using its material without permission to train its AI models.

To summarise, it may be likely that OpenAI’s model was trained on Studio Ghibli’s work. That in turn may raise the question if OpenAI has obtained a license or permission to do such training or not? Therefore, if we may look at the output of generative AI and see identical elements or substantially similar elements in that output, and such type of use was  happening without consent and compensation, it may be problematic.

Also Read: With AI comes huge reputational risks: How businesses can navigate the ChatGPT era

Time to rewrite the rulebook?

Copyright laws, developed centuries for a pre-AI world will need an overhaul. Instead of relying on the courts to interpret the existing copyright law, lawmakers worldwide must act quickly to discuss with a view to modernise copyright law for the age of AI. Should AI creation be copyrighted? What counts as fair use when machines exploit such original work?

A potential compromised scenario may include where artists agree to a system where the AI developers will compensate them as the copyright holders, and credit them where their content is used (in producing AI output).

AI developers should be transparent on data sources such as disclosing how they source their data (e.g. public domain, licensed content, or under fair use). Or they may likely face further legal challenges from copyright owners.

Final thoughts

When Studio Ghibli Co-Founder Hayao Miyazaki saw an AI demo in 2016, he was ‘utterly disgusted’ by it, as captured in documentary footage. He had warned in the past that AI could become ‘an insult to life itself’ if it loses sight of the human soul.

Can we prove him wrong? “Ghiblification” may be just the beginning, as we foresee future clashes between copyright law and AI. The challenge lies in whether we can strike a balance between rewarding innovation and upholding artistic integrity. Lawmakers need to act swiftly to provide regulatory clarity on the fair use of AI for the benefit of all.

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AI is actively changing everything from how founders code software to how governments deliver public services. But while innovation moves fast, regulations often don’t. Across Southeast Asia, we now face a pivotal moment: How can we design an AI playbook that not only protects the public but also empowers local innovation?

As a technology lawyer who regularly deals with emerging companies, I have witnessed firsthand how policymakers usually struggle to strike a balance between enabling growth and mitigating risks. If we want AI regulation to be both relevant and effective for Southeast Asia, we need to get a few key principles right.

Use “soft law” before “hard law”

Southeast Asia’s startup ecosystems are still evolving. Imposing punitive AI laws too early may drive innovation underground or offshore. Instead, governments can first adopt soft law tools. 

The approaches taken by Singapore and Malaysia are notable as they include national AI principles, voluntary codes of conduct, and model governance toolkits serve as examples of how countries can use soft law tools to encourage AI adoption.

These approaches create legal clarity without immediately introducing penalties. They also allow startups to adopt “ethical by design” practices which is especially important for founders looking to expand into more regulated jurisdictions later.

Build institutions that can keep up with AI

Even the best written law may be meaningless without capable institutions to monitor, enforce, and evolve with the emerging technologies. Governments must invest in up-skilling regulators, judges, and public servants in AI literacy.

In Malaysia, the government has formed The National AI Office (NAIO) to drive Malaysia’s AI agenda, and assist with other agencies and relevant stakeholders in establishing a path towards making Malaysia an AI driven economy. 

Also Read: AI, GenAI, and beyond: Navigating the next wave of tech investments in SEA

Start with high risk AI use cases

Not all AI is the same. A chatbot that suggests playlists has a different risk profile different from an algorithm that decides whether a person gets a loan approved or a longer prison sentence. Governments may wish to prioritise regulating high risk use cases affecting fundamental rights like privacy, employment, or access to justice as areas that may require guardrails to prevent misuse.

Focusing early regulatory energy on these sensitive domains prevents overreach. It also avoids drowning founders in compliance burdens when they’re building low risk applications. AI regulations should be proportionate, risk based, and scalable

Don’t copy paste Western models

The temptation to adopt existing laws from other continents such as the EU style AI Act laws may be understandable, but may not always be wise. Southeast Asian countries are diverse. 

What may likely work in Singapore might not even be suitable for Indonesia or even Vietnam. A blanket regulatory framework risks stifling innovation, especially in smaller digital economies.

In the past few years, the approach by policymakers has been to build principle-based guidelines that are adaptable to their country’s regulatory maturity and digital readiness. In Malaysia, The Artificial Intelligence Governance and Ethics Guidelines (AIGE) was launched in 2024 that sets out seven key principles of AI to voluntary adopt responsible and ethical AI practices.

Additionally, the ASEAN Guide on AI Governance and Ethics also serves as a useful reference for entities in the ASEAN region seeking to adopt AI in commercial applications. The document sets out proposed governance framework, national and regional recommendations, real life use cases, and AI risk impact assessment template. The Expanded ASEAN Guide on AI Governance and Ethics – Generative AI looks at risks of Generative AI and recommends a range of policy recommendations for its responsible adoption.

Align with core national values and constitution

In Malaysia, in addition to the Federal Constitution, we also have the Rukunegara, a set of national principles that underpin the country’s values. In Malaysia, NAIO (of which I am a member under the AI Governance and Ethics Working Group) is examining the local context that may be relevant to operationalising the country’s AI governance models and exploring practical, meaningful ways to implement AI ethically.

Also Read: Navigating market trends and risks: Leveraging GenAI in banking treasury functions in APAC

In other Southeast Asian countries, a constitution may likely be the supreme law of the land that uphold values around dignity, equality, and community. In other words, AI regulations shouldn’t exist in a vacuum but be grounded in local values and culture. 

Engage startups and local innovators early

Usually, laws are drafted by government agencies, lawyers, and academics with little inputs from those actually building the technologies. This may be a missed opportunity. 

Startups are usually first movers in deploying AI and can offer real world insights on where guardrails are needed, and what’s practically enforceable. Therefore, policymakers should seek to involve founders, ecosystem enablers like accelerators, and investors early in the consultation process. For instance, investors’ involvement in drafting the AI playbook may ensure regulatory frameworks align with innovation pathways and long-term value creation.

Regulatory co-design models, including AI focused hackathons, regulatory roundtables, and structured sandbox environments are activities that both sides can learn from each other and in real time. These collaborative platforms allow rules to be tested and iterated before becoming law, ensuring they are both practical and innovation friendly.

Final thoughts

The AI journey should be co-created by all of us, policymakers, ecosystem enablers, investors, and founders alike.

With the right regulatory support by the policymakers, I am confident that Southeast Asia may perhaps even move beyond merely as AI consumers. Our local founders have the tools and talent to build the next generation of AI native solutions. We may even emerge as a serious hub for AI innovation.

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When Aunty Good Good first started talking to AI, she did not expect to make anyone laugh. She just wanted to help people, especially those who did not grow up with technology, understand what all the fuss was about.

Aunty Good Good is my light-hearted social media character, a curious, outspoken aunty who loves food, travel, and cheeky conversations with technology. She was born from a simple idea. If midlifers like me could laugh while learning about AI, we would stop fearing it and start exploring it.

So one day, she looked at ChatGPT and said, “Eh, you can talk Singlish anot?”

The internet replied with a big collective “lah”.

Those videos filled with playful Singlish banter between Aunty Good Good and AI began showing that technology does not always have to be atas, or fancy. It can be shiok, friendly, and even a bit kaypoh.

That moment when AI replied in Singlish revealed something powerful. The fastest way to make technology human is to make it laugh with us.

When AI feels too serious for ordinary people

Many older adults, especially in Asia, find AI intimidating. It talks too perfectly. It answers too fast. And most of the time, it does not sound like us.

When something feels foreign, people hesitate. They fear pressing the wrong button, saying the wrong thing, or breaking the AI.

That is where humour and culture become important. They remind us that technology does not have to be perfect. It just has to connect.

When Aunty Good Good speaks Singlish to AI, she is not mocking technology. She is translating comfort, showing that you do not need to be a tech expert to start learning. You can be yourself, accent and all.

Also Read: A prettier you: How AI avatars make storytelling easier for midlifers

Why local voices matter in a digital world

In a world filled with machine voices, local language becomes an anchor of identity. Whether it is Singlish, Taglish, or Manglish, these cultural quirks reflect who we are and how we connect.

When AI learns from these voices, it becomes more inclusive, not just smarter. It learns how we feel, not just what we say.

Imagine AI that understands when “can lah” means yes, but “can meh” means doubt. That is not just language processing. That is empathy in code.

And that is what the next phase of AI should be about. Helping machines understand people, not just prompts.

The power of play in digital learning

Behind the humour, there is also a serious insight. Play builds confidence. When adults joke with AI, they stop fearing it.

It is the same reason we teach children through play. Laughter opens the brain for learning. Curiosity keeps the door open for growth.

Aunty Good Good’s Singlish lessons are not just funny videos. They are digital inclusion tools. They help midlife learners step into AI’s world one lah at a time.

Also Read: Stop comparing AIs: How faithfulness builds clarity

From language to legacy

There is a quiet message in all this fun. AI can be a bridge between generations.

Younger people teach the tools. Older ones teach the culture. Together they create something both timeless and new.

If AI can speak Singlish, it can speak the language of belonging. And maybe that is what we need most, not just smarter machines but warmer conversations.

Closing thought

So next time you hear Aunty Good Good chatting with AI, do not laugh at her. Laugh with her. Because that is how learning begins, with curiosity, comfort, and a touch of chaos.

And maybe the real question is not whether AI can speak Singlish, but whether it can listen with heart.

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One of the most memorable moments in my 2025 happened just a few weeks ago, when I got hired as a writer by (signed an NDA not to reveal the company’s name, so let’s just call it an e-commerce agency) and got kicked out three days after signing my contract. If you’re familiar with how badly Erik Ten Hag performed at Leverkusen, well, at least he survived until day ten, a privilege I didn’t have.

They called me one day in September and told me it would begin with a three-month probation period, followed by a performance evaluation. Three days later, I was called into HR and told we had to part ways. I repeat, after three days in.

I’m not sure if this start and finish in the same week approach is becoming common in workplaces today, but no organisation should feel ethically justified in terminating someone after only three days without any warning or chance to improve. According to Seek, firing an employee without providing a reasonable opportunity to address concerns violates basic fairness expectations, making such actions appear arbitrary and irrational.

However, being someone raised with Asian values, I tend to look for positives in every situation. After hours (or days) of reflecting, here’s what I discovered.

Adaptability in modern workplaces

One of the most immediate things I learned was how adaptability has become an integral norm in modern workplaces, as it ensures that employees have what it takes to engage in challenges and meet the expectations set at their organisations. The increasing demand and flow of modern workplaces lead to an increase in employers’ expectations of what their employees can and should do.

Also Read: How your HR team can help with crisis management

In my case, I realised I didn’t hit the ground running fast enough, which likely contributed to the decision. Data from Morton Fraser MacRoberts shows that 20 per cent of new employees fail probation, and 30 per cent leave within the first 90 days. Not quite three days, but I suppose mine was a special case. Either way, the numbers show that adaptability is critical for survival.

Being proactive and taking initiative matters

Adaptability helps you survive. Proactivity helps you thrive.

Today’s focus on work-life balance sometimes discourages employees from going the extra mile, but the reality is that initiative remains one of the few things that clearly differentiates us from AI. If machines are catching up on execution, then human judgment, intent, and initiative become more valuable than ever.

Going the extra mile also applies beyond workplaces. In relationships, effort strengthens connection. In marketing, it separates brands from the rest. The same applies professionally. Taking initiative signals commitment and helps build trust early on.

The whole experience taught me something simple: no one is responsible for our growth except us. If we want to stand out, especially when we are still new and have little influence over culture or processes, we have to do more than what is asked. And with AI always advancing, determination may be what keeps us ahead.

Do you agree that human determination will always take us ahead in the race against AI?

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