Artificial Intelligence (AI) has revolutionized the healthcare and health tech industries providing unprecedented opportunities for providers, tech companies, and researchers to develop better insights, diagnose illnesses, and improve patient care.
AI has the potential to transform the way health care is delivered, making it more efficient, accurate, and accessible.
However, with the increasing reliance on AI in health care and health tech, protecting the intellectual property (IP) involved in AI products and services has become a critical consideration for businesses to maintain a competitive advantage in the market.
In this essay, we will discuss the availability of IP protection for AI-related inventions, the advantages and disadvantages of each IP strategy, and the key considerations businesses need to take into account when protecting their AI innovations.
Patenting AI Software
One of the most common strategies for protecting AI innovations is through patents. A patent is a legal monopoly that gives the patent holder the exclusive right to make, use, sell, or offer for sale the patented invention for a limited period of time.
In the case of AI-based products, there are several components that may be potentially patentable, including the AI software itself, the process by which the AI analyzes data, the data, and the overall product.
However, obtaining a patent for AI software can be challenging due to the evolving nature of patent law and the specific requirements for patentability. I
n the United States, for example, the U.S. Supreme Court’s 2014 decision in Alice Corp. v. CLS Bank held that implementing “abstract ideas” on a computer does not make it patentable, casting doubt on the patentability of software in general, including AI software.
The decision created a two-part patent eligibility test that patent examiners and courts use to determine if AI-related patent applications are eligible for patentability.
Despite these challenges, the number of patent filings for AI software has been steadily increasing.
According to the United States Patent and Trademark Office (USPTO), patent filings for AI software more than doubled from 2002 to 2018.
In 2020, USPTO reported that it had received approximately 80,000 patent applications for AI software and approved 77% of them.
However, it is worth noting that not all aspects of AI-based products may be patentable under current U.S. law.
For example, the data itself is not patentable but can be protected by other forms of IP, as we will discuss later.
Similarly, the actual code of the AI software may not be patentable, but other aspects such as how the AI functions, the method by which the AI uses or integrates the data, and the overall product may be patentable.
It is important to carefully evaluate the patentability of different aspects of AI-related inventions before filing a patent application.
One of the main disadvantages of seeking patent protection for AI innovations is the requirement for public disclosure. When a patent application is filed, it must provide enough information to describe the invention in detail, including how the product or process works.
Once the patent application is filed, it becomes public after 18 months, and anyone can access and use that information, including competitors. If the patent is not granted, the inventor may have disclosed valuable information without any recourse to stop others from using it.
Moreover, the process of obtaining a patent can be time-consuming, with the current time from filing to issuance averaging around two to three years, during which the invention remains disclosed to the public without any assurance of obtaining a patent.
Despite these challenges, patent protection can be a powerful IP right that provides a monopoly for the invention, allowing the inventor to exclude others from making, using, selling, or offering for sale the patented invention.
This can give businesses a competitive advantage by preventing competitors from using their AI innovation without permission, and potentially generating revenue through licensing or sales of the patented technology.
Another advantage of obtaining a patent for AI innovations is that it can provide a strong deterrent against potential infringement.
Once a patent is granted, the patent holder can take legal action against anyone who infringes on their patent, potentially resulting in damages, injunctions, or other remedies.
This can help protect the market share and market value of the AI product or service, as well as deter others from copying or imitating the innovation.
Furthermore, patents can also be valuable assets for businesses in the form of intellectual property portfolios.
A strong patent portfolio can enhance a business’s valuation, attract investment, and provide a competitive edge in the market.
It can also serve as a defensive strategy, as a business with a strong patent portfolio can deter potential lawsuits from competitors and protect itself from infringement claims.
Despite these advantages, there are also some disadvantages to seeking patent protection for AI innovations.
As mentioned earlier, the process of obtaining a patent can be time-consuming and costly, involving significant legal fees, filing fees, and ongoing maintenance fees.
In addition, the requirements for patentability, such as novelty, non-obviousness, and utility, can be complex and difficult to meet, especially in the rapidly evolving field of AI.
There is also a risk that a patent application may be rejected or challenged by patent examiners, competitors, or other parties, leading to costly and time-consuming legal battles.
Moreover, as AI technologies continue to evolve rapidly, the scope of patent protection may become narrow, as courts and patent offices grapple with the challenges of applying traditional patent law to emerging technologies.
The uncertain and evolving landscape of patent law for AI can make it challenging to obtain and enforce patents for AI innovations, and businesses need to carefully evaluate the risks and benefits of pursuing patent protection for their AI-related inventions.
Copyright Protection for AI Innovations
Copyright is another form of IP protection that may apply to certain aspects of AI innovations.
Copyright protects original works of authorship, such as software code, written content, images, and other creative expressions.
In the context of AI, copyright protection may apply to the underlying software code that powers the AI, as well as any creative content generated by the AI, such as art, music, or written works.
In some cases, obtaining copyright protection for AI innovations may be easier and more straightforward than obtaining patents.
Unlike patents, which require meeting specific requirements for patentability, copyright protection automatically applies to original works of authorship once they are created in a tangible form.
This means that as soon as an AI innovation is created, it is automatically protected by copyright law, without the need for registration or other formalities.
Another advantage of copyright protection is that it can last for a longer period of time compared to patents.
In most countries, including the United States, copyright protection lasts for the life of the author plus 70 years, providing a longer duration of protection for AI innovation. This can be especially valuable for AI innovations with a longer lifespan or commercial potential.
Another limitation of copyright protection is that it does not provide the same level of exclusivity as patents. Unlike patents, which give the patent holder the exclusive right to exclude others from making, using, selling, or offering for sale the patented invention, copyright only provides the right to control the copying, distribution, and public performance of the copyrighted work.
This means that others may be able to create similar AI innovations using different algorithms or methods, as long as they do not copy the specific code or content protected by copyright.
Additionally, enforcing copyright can also be challenging, as it may require proving actual copying or infringement, which can be difficult in the context of AI where the technology operates autonomously and generates output without human intervention.
This can make it challenging to detect and prove infringement and may require advanced technical expertise and evidence to establish a claim of copyright infringement in the AI field.
Trade Secret Protection for AI Innovations
A trade secret is another form of IP protection that can be used to protect AI innovations. A trade secret is a confidential and proprietary information that provides a business with a competitive advantage and is not publicly disclosed.
Examples of trade secrets in the context of AI may include algorithms, data sets, training methods, or other proprietary information that gives a business a technological advantage.
One of the main advantages of trade secret protection is that it does not require registration or formalities, unlike patents or copyrights.
As long as the information is kept confidential and not disclosed to the public, it can be protected as a trade secret. This can provide immediate protection for AI innovations without the need for lengthy and costly registration processes.
Another advantage of trade secret protection is that it can potentially last indefinitely, as long as the information remains confidential.
This can provide long-term protection for valuable AI innovations, especially in cases where the innovation may not meet the requirements for patent or copyright protection, or where the business wants to keep the information confidential for strategic reasons.
However, trade secret protection also has its limitations. One of the main challenges of trade secret protection is maintaining the confidentiality of the information.
Once the information is disclosed to the public, or if it is independently discovered or reverse-engineered by others, it may lose its trade secret status and no longer be protected.
This means that businesses need to implement strong measures to protect the confidentiality of their trade secret information, such as implementing access controls, confidentiality agreements, and other security measures.
Another challenge of trade secret protection is that it may not provide the same level of exclusivity as patents or copyrights.
While trade secret protection can prevent others from using or disclosing confidential information, it does not prevent others from independently developing similar AI innovations using their own resources and expertise.
This means that trade secret protection may not be as effective in preventing competition as patents or copyrights, which provide a more exclusive right to exclude others from using the innovation.
Conclusion
In conclusion, IP protection is an important consideration for businesses that are involved in AI innovation. Patents, copyrights, and trade secrets are three main forms of IP protection that can be used to protect AI innovations, each with its own advantages and limitations.
Patents can provide strong exclusivity and legal protection but can be time-consuming and costly to obtain. Copyrights can provide automatic protection for creative expressions but may have limitations in protecting the underlying algorithms or methods used by AI.
Trade secrets can provide immediate protection without formalities, but require strict confidentiality measures and may not provide the same level of exclusivity as patents or copyrights.
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