Intellectual Property will never be the same again - thanks to Artificial Intelligence.

Hello Good People!

While the world continues to decide between whether to take AI seriously or not (they really should) and take the AI bubble as an excuse to stay in a bubble about its possibilities and potential, I am going to tell you how deeply and fundamentally AI has changed the Intellectual Property landscape and whether the creation and creative endeavors will ever be the same again.

Before we begin - Let's quickly distinguish b/w AI and AGI, because most of our readers are using those terms interchangeably and they are not alike.

See, artificial intelligence is a system's ability to perform specific tasks that require human intelligence (Image recognition, language transition, etc.), which means these models can be trained in a specific domain and they then produce outputs based on how refined our prompts or questions/statements etc. are. So, these systems essentially operate within well-defined parameters.

On the other hand, Artificial general intelligence is a system that's not only trained in a wide variety of tasks (and not one specific domain), they can also adapt to new tasks - like how a human brain would approach something it hasn't seen or heard before. Yep. So AGI remains a theoretical concept, for now.

Now, let's look at how AI is impacting the Intellectual Property landscape.

1. The Erosion of Traditional Authorship and Creativity:

Intellectual property has always hinged on a simple idea: human creativity. The law recognizes the creator’s right to control their work. But AI changes the nature of that creativity. When a machine like GPT-4 generates text or MidJourney creates an image, who owns it? Is it the programmer who built the model, the user who input the prompt, or no one at all?

Remember Thaler v. USPTO? Where Dr. Stephen Thaler filed a patent application listing an AI system, "DABUS", as the inventor? Both USPTO as well as the court rejected the application, on the ground that inventorship requires a human.

Then we have the famous Zarya of the Dawn Copyright Case in which the US Copyright Office partially denied copyright protection for "Zarya of the Dawn", a comic book created by Kristina Kashtanova using MidJourney, an AI image generator. The ruling again emphasized that only the human-created portions are eligible for copyright, challenging the notion of AI-generated authorship.

This question isn’t theoretical—it’s at the heart of current copyright disputes. Courts and legislators are now grappling with whether works created by AI should receive copyright protection at all. If they do, who should be recognized as the "author"? And while there is some clarity on the subject where the human's involvement is substantial and AI has only been used as a tool to enhance creativity, in other cases where AI is the sole creator, the issue persists. These debates force us to reconsider what authorship even means in the age of machines.

2. Blurring the Lines Between Inspiration and Infringement:

AI models learn by analyzing massive datasets—often scraping the internet and consuming vast amounts of copyrighted material. This has sparked lawsuits from artists, writers, and content creators whose works have been used to train AI without their consent.

This was the main contention in both Getty Images v. Stability AI case, as well as Sarah Anderson et al. v. Stability AI, MidJourney, and DeviantArt case. In both cases, the petitioners contend that AI models infringe their copyrighted works without consent.

And yes, the "fair use" defense has been brought up.

But then the central issue here is: Where does fair use end and infringement begin? Traditionally, fair use covers things like criticism, parody, or research. But AI’s ability to synthesize and repackage existing content in ways that feel original challenges those boundaries. The line between inspiration and copying has never been fuzzier, and current laws are ill-equipped to address this grey area.

3. Disrupting Ownership and Licensing Models:

AI is decentralizing creativity. Traditionally, creators owned and licensed their works directly. But with AI, anyone can generate high-quality content on demand, drastically lowering the barriers to entry. This creates a marketplace flooded with new works—many of which are derivative, data-driven, and difficult to trace back to any single source.

Take any of OpenAI copyright disputes. All of them use copyrighted works without permission and therefore, disrupt traditional ownership and licensing models.

For IP lawyers and policymakers, this is a nightmare scenario. How do you enforce ownership when millions of AI-generated works enter the public domain every day? And how do you value those works when traditional licensing frameworks no longer apply?

4. Emerging Questions in Patent Law:

The impact of AI extends beyond copyright. Patent law is also being upended. AI is now designing drugs, inventing technologies, and optimizing industrial processes. But if an invention is the result of an AI's analysis, who should be credited as the inventor? Should AI itself be listed as the inventor on a patent?

We’ve already seen test cases where patent applications were rejected because the inventor listed was an AI (Refer to Thaler's case above). Dr. Thaler also challenged the UK Intellectual Property Office's decision to reject his AI-invented patents. This raises deeper questions about whether the legal frameworks designed for human inventors can be applied to non-human creators.

There are also different jurisdictional approaches here. For instance, South Africa granted a patent listing AI as the inventor, back in 2021. An Australian court also recognized AI as an inventor, before reversing the decision on appeal. So, its not like there is consistency on what's what and that only increases our dilemmas.

5. Ethical and Governance Challenges:

Beyond legal complexities, AI’s rapid evolution presents ethical dilemmas. The very nature of IP law is to reward creativity and innovation. But what happens when the innovation itself starts eroding the rights it was designed to protect? Who decides the limits of AI’s role in content creation, and how do we ensure that these decisions align with broader societal values?

Clearview AI faced multiple lawsuits for scraping billions of images from the internet, including from social media, to train its facial recognition software. This is a violation of ethics and privacy both. Of course they scrambled their way through compensation.

Then in the personality rights realm, we have artists and record labels suing AI generated music platforms, that use AI to mimic famous artists' voices and styles without consent. These cases elaborate on ethical issues of using AI, in ways that exploit human talent without explicit consent, and without proper compensation.

We also have the issue of deepfakes that'll take its own article.

So, what do we do?

Governance is key here. It’s not enough to create reactive policies. We need forward-looking frameworks that balance innovation with fairness, protect creators without stifling progress, and address the potential monopolization of AI tools by tech giants.

We stand at a crossroads where technology is forcing a redefinition of intellectual property. As an IP lawyer and AI governance expert, I see both the opportunities and the perils. The challenge is not just legal—it’s philosophical. We need to rethink our understanding of creativity, ownership, and authorship in a world where human and machine contributions are increasingly intertwined.

The future of IP law will require more than just updated statutes; it will require a complete reimagining of what it means to create and own something in the digital age. AI is not just another tool; it’s a force that is fundamentally altering the intellectual property landscape. And how we navigate these changes will determine the future of innovation and creativity for generations to come.