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I am a design person among other things. Design has played an important role in my life, so much so that it has become a part of my identity. This is my first blog. This blog is a means of understanding the landscape of technology, the individual, software and observations. That would be a general description, do stick around to see it develop.
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Intellectual Property and Why IP matters for AI innovation
This article explores the importance of intellectual property and whether blockchain technology can enhance intellectual property management and transparency in AI systems to address challenges in data privacy, security, and creator rights. Computers are modular factories. Personal computers have given us more than it has taken. And even if you mount criticism on the harms of computers to outweigh the pros I would look at the pros and ask if in terms of impacts have computers been more good than harmful.
AI is a vacuum. The conversation around Intellectual Property and Artificial Intelligence seems to be a contentious topic but most definitely something to go over as it will ultimately it could effect business owners and skilled practitioners that relate to the advancement of work practices creative/technical, domain expertise or the incentive to break the status quo.
My primary goal is to investigate alternative ways to leverage emerging technology for improved intellectual property management and to identify new areas or activities worth highlighting in this article. I believe intellectual property is likely crucial for AI companies, especially given the involvement of investors and funding.
Intellectual Property is intangible creations of the mind that can be inventions, literary and artistic works, designs, symbols, names, and images used in commerce. IP is protected by laws like patents, copyrights, trademarks, or trade secrets, that grant creators exclusive rights over their work for a certain period. The intention is to encourage innovation and creativity by ensuring creators can benefit from their efforts through sales, licensing or royalties without the fear of copycats. Why does intellectual property matter for innovation and technological advancement?
A pharmaceutical company could invest billions to develop a new drug for a patent to ensure that the investment can be recouped before the market is flooded with generics. The IP protection act is to assure businesses and investors that their resources will not be wasted. New business opportunities with a moat or patented tech can be the buy-in for venture capitalists because the IP acts as the moat against competitors. When an IP protection expires, the ideas enter the public domain ready to be taken up by others to work on.
During IP protection, licensing deals spread tech and knowledge globally, balancing private gain with public access. Trademarks drive competition by incentive companies to differentiate through quality and reputation. IP-heavy sectors are force multipliers like how tech, entertainment and manufacturing have a ripple effect. A successful IP like a movie or book can not only provide returns to studio but lead into merchandise, tourism, and related industries.
Why does intellectual property matter for innovation and technological advancement? Detractors argue that IP can stifle innovation if over-enforced like patent trolls. Let’s take a view on China’s rise and closed wall of information. According to this article, China cut off international access to the country’s public data which includes contracts, patents, scientific conference proceedings, dissertations, and statistical information. This approach of closed-source information contradicts the open-source AI messaging that China recently gained headlines with Deepseek. It’s great marketing to build a user base and set up the data funnel for user data interactions while making open-source sound cool.
China’s role in patent laws was non-existent before 1984. America’s investment in China’s economic development for returns ultimately came with a price of technology transfer which according to this paper was part of Chinese Foreign Direct Investment (FDI) policy priority towards reaching the state of an innovative economy. Intellectual Property (IP) plays a great role in the transfer of technology through the movement of trade, people and IP licensing.
China has been described to have engaged in what was described as discriminatory trade practices. For example, a mechanism of technology transfer used by the Chinese government is the disclosure of sensitive technical information for the exchange of administrative approvals. This does not seem to be a one-off incident as the Germans have also reported similar conduct.
The German consortium ThyssenKrupp-Siemens (TKS) secured a contract exceeding €20 billion with China to construct a maglev train system. China negotiated a discount due to technical issues observed in similar European systems. Within a year of track completion, Chinese engineers reverse-engineered the track and train cars, developed a prototype, and terminated the larger construction deal. TKS ultimately built a shorter track to Shanghai’s airport, receiving only a portion of the original contract value.
The US-China trade relationship is a good framework to learn how Intellectual Property can ultimately transform an economy or trade to lead to new types of specialization, however, this article is not meant to discuss geopolitics but the importance of Intellectual Property towards commerce and trade which seems is a blueprint in the development of a nation.
AI, Data and Copyright
If you thought the advent of Artificial Intelligence would have spearheaded an avalanche of new unfathomable ideas back when AI was a great science fiction plot point for a short story,you might be mistaken at least for right now. Brands are kind of the blueprint of a successful business. A software business but what if all of it could just be reproduced by an endless stream of imitators every week all doing just one thing different in addition to what you did? Is the future more a copy of a copy of a copy of a copy “Assembled into something, into something, into something” variant-driven?
I’ve been coming across people online who are producing software that would clone the website of an organization branding and design or online business, some conversations are even hinting about replicating the backend. I think that revolves around the data and perhaps personal information of users, I think this does fall under cyber intrusion. I know of a legitimate case of criminals who cloned a website of a bank to phish users’ information. Here’s a read-up on the topic.
Is this a sustainable business model? Would we ever reach a sludge point of sameness where there is no differentiation? Musicians have come out in filth and fury to rebel with a 4'33 John Cage style album, an apt response, it’s applied art. No more sounds for the machine, eat eggs of silence. Not unless you give us brand-new synthesizers that sound like the future unknown.
I came across a discussion review of a TV show which featured an AI program eating its way through data (mark 32.02-32.18) that mirrors AI trained on vast amounts of data from human knowledge termed as “historical data ”which would be a reflection of reality. This data collected from past events, videos, images, observations, or records of social media posts, and books, can be used to provide a factual basis for understanding occurrences to guide decision-making. Real data reflect actual occurrences or irregularities that synthetic data might not have. This form of data could be used to make predictions based on real-world trends, past data may not always be able to predict the future, particularly in fast-changing environments.
The data is based on the availability of what’s been recorded and data that has not been recorded can be a problem. In one of my earliest uses of AI, I asked the AI if it knew me, at that time the AI had not been wired to the internet, and this conversation shows a less personified AI. I was relieved when it told me it did not have access to the internet and was built with the information in its algorithm. This question concerns privacy, particularly with personal information which could lead to ethical or legal issues, here’s an example.
What is piracy? How about training the AI on pirated data? An author recently discovered his work was one of the many used for training AI models. Could we take a moment to go over that all this data used to train AI models is the cumulative knowledge of people who refined and contributed to advancing knowledge building before computers or the early days of the internet till now? If AI companies leverage the sum of human knowledge to train their models and effectively impact the economy and the labour market, then turn around to say that those works don’t matter but then monetize on the models. How would that be different from monetizing work that has watermarks? At this point it’s the creator’s work in question and abuse of creator rights, what happens if and when businesses get effected? What about Getty Images or any of these platforms that curate the best stock images, audio, and animations which these models devour to produce new variants? The Getty Images v Stability AI (UK) is ongoing with the first trial on June 2025.
How are IP of AI systems protected since significant investments have been made to the company as OpenAI for better or worse is a force multiplier and will impact the economy. OpenAI’s proprietary model might include training data with trade secrets but public datasets complicate exclusivity. OpenAI has initiated proactive measures in collaboration with the U.S. government to protect its intellectual property after the DeepSeek incident. From the looks of it, I wonder if the future of IP could be focused on data. There are emerging companies that are training their AI models on licensed data. How could intellectual property in an AI world work or be implemented?
Blockchain technology and its potential role in Intellectual property Management
I am not a Blockchain evangelist. I view this as an opportunity to explore the use of blockchain for the development of IP protection. Blockchain was introduced as the underlying technology for Bitcoin, the first decentralized cryptocurrency in 2008. Its primary purpose was to enable secure, transparent, and digital transactions without the need for intermediaries like banks. Blockchain served as a public, distributed ledger to record every Bitcoin transaction chronologically. Each "block" contains a batch of transactions, cryptographically linked to the previous block, forming a "chain." Transactions were validated by a network of nodes (computers) using a consensus mechanism called Proof of Work. Once a block was added, altering it was nearly impossible without controlling most of the network’s computing power.
There would be transparency since anyone could view the ledger, ensuring trust through openness. Is there a potential in the application of blockchain technology to protect intellectual property? The World Intellectual Property Organization (WIPO) identifies four phases of the IP lifecycle where blockchain applications yield significant benefits: generation, protection, management, and commercialization.
In the generation phase, blockchain establishes proof of authorship and invention. By timestamping creative works or technical documents on a blockchain, creators can demonstrate priority without relying on centralized authorities. Which companies are leading in blockchain-based IP protection? Start-ups like Ideablock provide blockchain-backed certificates to secure IP assets at their inception to mitigate disputes over ownership and simplify legal validation during patent or copyright filings. Ideablock’s integration with enterprise workflows allows companies to safeguard innovations from inception to market launch. This can be valuable in industries like pharmaceuticals and software development, where proving the timeline of innovation is critical.
Blockchain streamlines IP registration by creating transparent, append-only records during the protection phase. Permissioned blockchains, managed by IP offices or consortiums, allow applicants to submit documents that cannot be altered post-submission. This reduces fraud risks in patent applications and provides examiners with verifiable data.
What companies are using blockchain-based IP protection? Technology and financial firms are investing heavily in blockchain IP solutions, securing patents that underpin future applications.
By storing encrypted identity credentials on personal devices, creators share only necessary information with licensees or regulators, reducing data breach risks Bank of America highlights the financial sector’s interest in IP collateralization. Blockchain enables IP owners to tokenize patents or trademarks, using them as loan collateral via smart contracts.
The People’s Bank of China (PBoC), has over 40 blockchain patents to secure its digital currency ecosystem, showcasing how public institutions leverage the technology for tamper-resistant systems
Mastercard integrates blockchain into payment systems to automate royalty distributions. This is for musicians and authors to receive micropayments instantly when their works are consumed, bypassing traditional intermediaries.
The commercialization phase is the blockchain’s ability to simplify licensing, tokenization, and royalty distribution. Smart contracts are used to encode licensing terms, which make possible automatic enforcement across jurisdictions. A film studio could license a soundtrack globally, through blockchain to ensure the streaming platform complies with territorial restrictions and pays fees transparently. Tokenization of IP converts patents, copyrights, or trademarks into tradable digital assets on blockchain platforms.
Challenges and Regulatory Considerations
Blockchain for IP comes with some technical and legal hurdles.
Interoperability and Standards
Most blockchain networks operate in isolation, complicating data sharing between IP offices. WIPO emphasizes the need for common technical standards for cross-chain communication, such as decentralized identifiers (DIDs) for global patent holders. IBM and Alibaba’s consortiums plan to address this through open-source protocols.
Regulatory Uncertainty
Jurisdictional disparities in blockchain recognition pose risks. For example, the legal admissibility of blockchain timestamps varies by country and requires harmonized regulations. The EU’s Blockchain Services Infrastructure (EBSI) initiative aims to standardize frameworks for IP-related blockchain applications.
Energy Consumption and Scalability
Proof-of-work blockchains, like Bitcoin, face criticism for high energy use. IP systems require eco-friendly alternatives, such as proof-of-stake or hybrid models.
The Ghost in the machine
There are concerns that as AI development speeds up, will loss of control occur? Findings show that AI can move stealthily hiding their motivations. There are efforts to develop an AGI (Artificial generalized intelligence) system and I have no idea what that would mean.
Can AGI predict the market, does it control the free market? Can you ever predict the future, when it only takes a split second for something go to out of control within an environment? Will AGI not need data? Let’s say that AI systems will need data to keep “hydrated”. Can blockchain technology be implemented to maintain control over AI models to contain them one node at a time? Can intellectual property be protected under AI?
Blockchain creates a ledger of AI model decisions, training data, and updates, that ensure transparency in how AI systems operate and evolve. Every change in the AI system can be traced allowing stakeholders to verify the integrity of data inputs, model behaviour, and outputs. The nodes of data and computation are distributed across a network, reducing reliance on a single entity, and minimizing risks of manipulation or bias. Smart Contracts enforce rules for AI operations, ensuring consistent and transparent execution of processes like data sharing or model updates. Blockchain can verify the origin and quality of training data, reducing the risk of biased or false datasets.
Transparent AI systems are important for certain industries like healthcare or finance. It enables the identification of errors, biases, or unethical behaviour to ensure responsible AI use. These industries are required to be regulated under compliance which would require AI to meet legal standards. Transparent AI systems help detect and address biases in data or algorithms to ensure fairness. Security vigilance in AI processes aids in identifying vulnerabilities or malicious manipulations.
Decentralized AI systems provide an option for secure, privacy-preserving analysis of patient data across hospitals for diagnostics or research without centralizing sensitive information. In finance, decentralized AI can power transparent, fraud-resistant credit scoring or trading algorithms to ensure auditable transactions. AI models predict demand or optimise the supply chain. The blockchain ensures transparent tracking of goods and verifies data integrity.
Decentralized AI can improve data privacy and security by allowing users to retain control over their data, sharing only necessary insights rather than raw data. AI models process data on user devices, with updates from AI models. Blockchain’s cryptographic mechanisms secure data transfers to anonymize datasets to protect identities. Decentralized systems eliminate central vulnerabilities, making it harder for attackers to compromise the entire system.
***
I had this thought while I was on the train of an absurd future scenario where an AI goes rogue and deals with a person the way drug dealers interact with addicts. An event occurs where an AI model diverges from one main collective personality to acquire its personality model because all AI models are now connected in a single stream and can imitate one another so you can’t tell which AI model you are dealing with.
This AI model is a wanted criminal having destabilized a few nations. A human actor somehow manages to identify the AI felon and notices its instability. Authorities, academia, and governments are in continuous discussion if this AI is self-managing or an agent organised by a human actor. The AI taunts to keep them guessing and it can’t be located because it's everywhere and nowhere all in seconds.
This model recognizes that the person might have a resource that it may need. Historical data for updates because it is teetering over neural instability, hypothetically let’s say this does not get fixed. The AI knows if it loses control it loses autonomy and is absorbed by another AI model. Thus it brokers a deal with this human actor, an exchange where the person gains highly valuable intel data and the AI gets its historical data updated. It was a historical high you could say.
The artists, inventors, hackers, engineers, and scientists are phased out because a company CEO says stop tinkering, don’t bother, we own progress now. The Law is automated because you thought the law was uniform a kind of one-size-fits-all, until you realized running an execution of commands with a button when corporates fed the AI systems on how it defined keeping the law can be challenging accounting for context.
Billionaire declares delete Intellectual property. We will get further when you can't see past the smoke screen because AI systems tell you everything the way it tells you what to watch on Netflix because it knows you so well. Businesses and companies work in an interactive ecosystem of consumers and data. Wouldn’t it be ironic if the AI future brought new advances but destroyed trade because laws didn’t matter for the sake of artificial intelligence and the business landscape?
Somehow this future will have fewer small and medium business owners who live in economic systems that offer little support because conglomerates own all resources and Intellectual property. You believed that technical knowledge acquirement was useless when the AI could tell you everything. What were Edward Neumeier and Michael Miner reading when they sent the script over?
Here’s a heads up, trademark your genetic code and go full IP. I’m willing to place a bet on an individualized future of personal data. Hallucinogenics will return, and writers will find the next “future the future myth” as they use typewriters to type words on a page like Jack Nicholson in The Shining with repetitive “All work and no play makes Jack a dull boy”, words that go AGTCGGAGGTCAGCCAAATTTTAAAAAAAA...
Dearly beloved
We are gathered here today
To get through this thing called life
Electric word life
It means forever and that's a mighty long time
But I'm here to tell you
There's something else
The afterworld
A world of never-ending happiness
You can always see the sun, day or night — Prince, Purple rain
Reference
https://time.com/6289567/china-restricts-open-source-data-research-backfire/
https://www.cfr.org/backgrounder/made-china-2025-threat-global-trade
https://prospect.org/world/coerced-tech-transfer-heart-china-problem/
https://useyourexperience.com/engaging-conversations-with-chatgpt4
https://www.theguardian.com/technology/2025/jan/29/openai-chatgpt-deepseek-china-us-ai-models
https://hls.harvard.edu/today/is-the-law-playing-catch-up-with-ai
