With the ever increasing adoption of AI technology, no industry will unlikely be left untouched by Artificial Intelligence in the coming years. The worldwide spending on AI systems is estimated to increase as much as 100 billion USD by 2023 and global market size for AI is projected to reach as much as 200 billion USD by 2026. In the US, the Federal Government is seeking to double the dollar amount spent on AI R&D.
Seeking to further facilitate R&D in AI, patent offices in numerous jurisdictions have started to deliberate on the intersections between AI and patent law and policies. The World Intellectual Property Organization (WIPO), for example, initiated conversations with member states in 2018 to discuss incorporating AI into various aspects of IP administration, such as automated classification, prior art searches, and machine translation.
Other patent offices have looked into updating examination guidance for AI-related applications. Last year, the European Patent Office (EPO) added a new section to its Guidelines of Examination on AI and machine learning, stressing that such applications are to be “looked at carefully” for “technical character.” The EPO guidance distinguished between AI inventions with a “technical purpose” versus those with “linguistic one,” thereby continuing to make natural language processing (NLP) related inventions still difficult to patent.
Across the globe, the Japanese Patent Office (JPO) also issued guidelines with case examples for examining AI-related technology regarding the written description and inventive step requirement. The JPO guidelines note that if the “[o]nly evidence shown is inference by AI” in an invention of a product, then the written description requirement cannot be satisfied.
Turning to America, the USPTO has hosted its own conversation on the intersection between AI and patent law and policies. On March 20, 2020 the USPTO posted the responses from Requests for Comments regarding on Artificial Intelligence. This outreach effort came as part of a broader Federal directive titled, Artificial Intelligence for the American People aimed at developing and implementing strategies to accelerate AI innovation in the US. In concert with this directive, the USPTO was tasked with facilitating commercial AI research and development and exploring IP policy considerations.
To that end, last year the USPTO released a set of questions delving into the intersection between AI and patent law for the public to guide its policy considerations:
1. Inventions that utilize AI, as well as inventions that are developed by AI, have commonly been referred to as “AI inventions.” What are elements of an AI invention? For example: The problem to be addressed (e.g., application of AI); the structure of the database on which the AI will be trained and will act; the training of the algorithm on the data; the algorithm itself; the results of the AI invention through an automated process; the policies/weights to be applied to the data that affects the outcome of the results; and/or other elements.
2. What are the different ways that a natural person can contribute to conception of an AI invention and be eligible to be a named inventor? For example: Designing the algorithm and/or weighting adaptations; structuring the data on which the algorithm runs; running the AI algorithm on the data and obtaining the results.
3. Do current patent laws and regulations regarding inventorship need to be revised to take into account inventions where an entity or entities other than a natural person contributed to the conception of an invention?
4. Should an entity or entities other than a natural person, or company to which a natural person assigns an invention, be able to own a patent on the AI invention? For example: Should a company who trains the artificial intelligence process that creates the invention be able to be an owner?
5. Are there any patent eligibility considerations unique to AI inventions?
6. Are there any disclosure-related considerations unique to AI inventions? For example, under current practice, written description support for computer-implemented inventions generally require sufficient disclosure of an algorithm to perform a claimed function, such that a person of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention. Does there need to be a change in the level of detail an applicant must provide in order to comply with the written description requirement, particularly for deep-learning systems that may have a large number of hidden layers with weights that evolve during the learning/training process without human intervention or knowledge?
7. How can patent applications for AI inventions best comply with the enablement requirement, particularly given the degree of unpredictability of certain AI systems?
8. Does AI impact the level of a person of ordinary skill in the art? If so, how? For example: Should assessment of the level of ordinary skill in the art reflect the capability possessed by AI?
9. Are there any prior art considerations unique to AI inventions?
10. Are there any new forms of intellectual property protections that are needed for AI inventions, such as data protection?
11. Are there any other issues pertinent to patenting AI inventions that we should examine?
12. Are there any relevant policies or practices from other major patent agencies that may help inform USPTO's policies and practices regarding patenting of AI inventions?
These questions garnered great interest from the public. Over forty institutional entities –ranging from industry leaders, bar associations, and patent offices from other jurisdictions – commented. Their concerns can be broadly categorized into three categories: (1) disclosure requirements, (2) inventorship issues, and (3) forms of protection particular to AI-related inventions. Based on these questions and responses, we plan on posting a multi-part series of articles that will cover each of these questions in detail.
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