How Intellectual Property Legal Advisory in Kenya Protects AI & Digital Assets

So, you asked ChatGPT to write a story – and it delivered a masterpiece. The million-dollar question now becomes: Who owns it? You, the user who prompted it? OpenAI, the minds behind ChatGPT? Or ChatGPT itself, the mysterious machine? For now, the law still sides with human creators. However, as AI capabilities continue to advance rapidly, experts in Intellectual Property legal advisory in Kenya warn that this legal stance may shift in the future..

The rise of digital assets, such as cryptocurrencies, only further shakes the pillars of intellectual property (IP) law. Suddenly, we are not asking who owns a story, but who owns a dataset? Is copyright enough to protect a virtual fashion design? Can you patent a digital contract?

The Future of Intellectual Property Legal Advisory in Kenya: Key Legal Debates

Initially designed for books and logos, IP law is now being pushed into unchartered territory. The surge of AI-generated content and digital assets has opened a Pandora’s box of questions, throwing the world into a digital Wild West and forcing the IP sheriffs to rethink the rules.  This article explores the intersection of IP and the evolving landscape of AI and digital assets, unpacking the legal grey areas and emerging debates. 

1. Intellectual Property 

According to the World Intellectual Property Organization (WIPO), intellectual property (IP) refers to creations of the mind. These creations are intangible assets that owners can protect through various IP rights, such as copyright, patents, trademarks, and industrial designs. 

• Copyright: Copyright is a form of intellectual property that gives grants legal protection to creators of original works once ideas are reduced into a medium, such as writing, images, or digital files. This protection extends to digital assets, which are stored and distributed digitally. However, there is an ongoing discussions on whether works generated by AI can qualify for copyright since traditional copyright requires a human author. In addition, there are issues surrounding the use of copyrighted works to train AI systems. 
• Patents: Patents protect new inventions that offer technical solutions to problems. They may apply to AI systems and digital assets where there are novel, inventive, and non-obvious solutions presented. Like copyright, patent laws require a human inventor. Nevertheless, the idea of recognizing AI inventors is currently a debated topic.  
• Trademarks: Trademarks protect distinctive signs, logos, words, or symbols used by creatives to distinguish their goods or services in the market. In the digital environment, trademarks apply to brand names for software, AI products, or digital services. This is important to help consumers distinguish between human-generated content and AI-generated content. 
• Industrial Designs: These protect the visual and aesthetic aspects of products, such as shape, colour and texture. For AI and digital assets, protection may apply to graphical user interfaces, icons, or digital artwork.

Kenya has a comprehensive IP legal and institutional framework:

• Copyright: The primary legislation is the Copyright Act, 2001, which is administered by the Kenya Copyright Board (KECOBO). The legal criteria for copyright protection is that the work must be original and be fixed in a tangible medium. 
• Patents: The governing law is the Industrial Property Act, 2001, which is administered by the Kenya Industrial Property Institute (KIPI). To qualify for patent protection, an invention must be novel, inventive, and industrially useful. 
• Trademarks: The primary legislation is the Trade Marks Act, which is administered by KIPI.  A trademark must be distinct to enable consumers to distinguish the goods or services of one business from those of others.
• Industrial Designs: The governing law is the Industrial Property Act, 2001, which is administered by KIPI. An industrial design must be new, meaning that it has not previously disclosed to the public anywhere in the world prior to the date of filing of the application, and it must not contrary to public order or morality. 

2. Artificial Intelligence 

Artificial intelligence (AI) is a broad term that refers to the development of machines and systems capable of accomplishing tasks that typically require human intelligence, such as reasoning, decision-making and problem-solving. 

Within AI, there are two important subfields: 

• Machine Learning (ML): This is a subset of AI that enables systems to learn patterns from data rather than being explicitly programmed. ML powers several applications used today, including fraud detection systems and recommendation engines. 
• Deep Learning: This is a subset of ML that uses deep neural networks to model complex data relationships. Deep learning is responsible for many breakthroughs in AI, such as image recognition, voice synthesis, and natural language understanding. 

AI can be categorized into three levels based on their capabilities:  

• Narrow AI (or weak AI): These are AI systems designed to carry out very specific tasks. They are limited to one single area of expertise and cannot learn or perform functions outside their intended purpose. All AI systems used today fall under this category, for instance, virtual assistants such as Siri and Alexa, self-driving cars, and facial recognition software. Since they are tools used by humans, IP rights generally lie with the human creator or programmer. 
• Artificial General Intelligence (AGI) (or strong AI):  This refers to AI systems that would have the ability to understand, learn, and apply knowledge across a wide range of tasks at the same cognitive ability level as human beings. Currently, AGI is largely theoretical and is still in the research and development phase. However, it raises pertinent concerns around authorship and originality if such systems begin to act autonomously. 
• Artificial Super Intelligence (ASI): This refers to the ultimate advancement in AI development, where AI surpasses human intelligence across virtually every field, including creativity, decision-making, emotional intelligence, and complex problem solving. Such systems are capable of self-improvement and operate at speeds and levels of comprehension far beyond human capabilities humans. While not yet a reality, ASI prompts deeper consideration around the future of IP ownership. 

3. Digital Assets 

A digital asset is a tangible or intangible item that exists in electronic form. Such assets holds value and can consequently be bought, owned, traded, and transferred. Digital assets can be classified into two categories: 

• Traditional digital assets: These refer to assets that originally existed in physical form or were created using conventional digital tools (e.g. photos, videos, audio or music files, presentations, graphics, 3D files). They predate blockchain and are typically stored and managed in centralized databases. While these assets may be subject to IP protection (e.g. copyright), enforcing ownership and controlling unauthorized copying can be challenging due to the ease of duplication and lack of transparency.
• Blockchain digital assets: These refer to digital assets that are originally built on or registered through blockchain technology, such as cryptocurrencies (e.g. Bitcoin), non-fungible tokens (e.g. NFTs), and security tokens. Unlike traditional digital assets, which can be easily copied and lack transparent ownership, blockchain assets are embedded with cryptographically secured metadata that records ownership, authorship, and transaction history on a decentralized ledge. This enables stronger assertions of IP rights and consequently introduces new paradigms for IP registration and enforcement in the digital environment.  

Digital assets are created using intellectual effort or have distinctive branding. Therefore, they may fall under various types of IP rights such as:  

• Copyright: Software, music, e-books, videos.
• Trademark: Logos, domain names, brand elements on websites
• Patent: Unique software algorithms or technical methods 

4. Role of IP in Artificial Intelligence and Digital Assets

Artificial Intelligence	Digital Assets
Protection of AI technologies themselves: IP protects the components used to build AI systems such as algorithms and source code (copyright or trade secrets), AI models and architectures (patents), and training data (copyright or trade secrets).	Protection of creativity and innovation: IP rights protect digital assets from infringement and unauthorized use by defining how others can access or use such assets. This helps combat digital piracy and exploitation.
Encouraging Innovation: IP incentivizes investment and development in AI systems by granting exclusive rights.	Legal ownership: IP ensures that creators retain ownership rights over their unique and original digital creations. These rights are enforceable in a court of law.
Commercialization: IP allows AI developers to use their AI systems for revenue generation, e.g. licensing and patents.	Commercialization: IP allows owners to license, sell, monetize or franchise their digital assets for revenue generation.

5. Emerging Challenges

AI technology raises important questions in IP, such as: 

• Authorship and Copyright: Can an autonomous AI system be considered an author? Can copyrighted works be used to train AI systems?
• Patents: Should AI-generated inventions qualify for patents? In a landmark decision in 2021, South Africa became the first country in the world to award a patent to an AI system known as the Device for the Autonomous Bootstrapping of Unified Sentience (DABUS) for two of its creations, a food container and flashing beacon. 
• Trademarks: AI systems may create derivatives that unintentionally resemble existing trademarks. In addition, these machines may be used to generate deepfakes, which are realistic but fake representations of individuals or brands. This can lead to potential trademark infringement disputes as it may dilute brand reputation or pose impersonation threats. 
• Moral and Ethical Rights: AI systems may replicate or rework human-created works, blurring the lines of originality, inventiveness, and attribution. 

Similarly, digital assets also raise unique concerns:

• Ownership and Authorship: For traditional digital assets, such as photos or music files, ownership typically rests with the creator. However, with blockchain assets, owning the token does not always mean you own the rights to the actual artwork or content it represents.  
• Authenticity: It is often hard to prove who created or owns a digital asset, especially if there is no trusted record of where it came from. While blockchain can provide a permanent and verifiable history of ownership and transactions, this is only effective if the information put into it was accurate to begin with. 
• Licensing and Usage Rights: Digital assets are often shared or sold without clear licensing terms, which can lead to misuse and ambiguity. 
• Infringement: Digital content can easily be duplicated, which raises concerns around infringement and misappropriation.
• AI-Generated Content: Digital assets may be created by AI systems, which raises the question of the protection and ownership of AI-generated works. 

6. Way Forward

As AI and digital assets transform how we create, share, and protect innovation, IP law must evolve just as boldly. The future belongs to those who understand both the technology and the rights behind it. 

At Kioi & Co. Advocates, our team of IP lawyers is uniquely positioned to help creators, innovators, and businesses navigate this rapidly changing landscape. Please feel free to contact us at info@kioi.co.ke or book a consultation with any of our Associates for this or any other related legal matters.