Patent protection for inventions in artificial intelligence (AI) and machine learning (ML) is complicated by subject matter eligibility requirements, a judicially created doctrine pertaining to 35 U.S.C. § 101. This paper provides two pieces of practical advice to those seeking patent protection of AI and ML inventions.
The USPTO July 2024 Subject Matter Eligibility Guidance provides clear and relevant guidance for preparing a patent eligible AI patent application. This guidance remains current with recent subject matter eligibility court rulings, and Examiners are following this guidance (in some cases, very strictly).
The first practical suggestion is following the July 2024 guidance in preparing any AI machine learning application
Prior to July 2024, the most recent subject matter eligibility guidance from the USPTO was published in January 2019. The USPTO will likely change its guidance on subject matter eligibility for AI again within a few years. Many patent applications at the USPTO take three years to examine. Accordingly, there is a possibility that a patent application prepared in light of July 2024 guidance, today, will be examined under different rules, in the near future. Expedited examination can be requested at the USPTO and can condense patent examination to a single year or less.
The second practical suggestion is request expedited examination for any AI patent application.
1 Follow the USPTO's July 2024 Subject Matter Eligibility Guidance
In July 2024, the USPTO issued updated guidance that clarifies the rule for incorporating an abstract idea into a "practical application," and thereby make it subject matter eligible. This guidance included examples that were specific to AI and ML.
According to the July 2024 guidance, an AI invention may be incorporated into a practical application by (1) linking any abstract idea to a "particular field of use," within the claims (e.g., "field of network intrusion detection"); (2) presenting " a technical explanation of [an] asserted [technological] improvement . . . in the specification" (e.g., "detect[ing] network intrusions and tak[ing] real-time remedial actions"); and (3) limiting the claims with non-abstract terms "to reflect the disclosed improvement" (e.g., dropping malicious packets in real-time after being identified by a neural network"). Example 47, claim 3, p. 12, USPTO, July 2024 Subject Matter Eligibility Examples (Jul. 2024).
Practically, to comply with the 2024 guidance, a patent application should include a specification that frames the AI as an improvement over presently available technology. Additionally, the claims should be limited to a technological field and use non-abstract terms to recite further limitations implementing the improvement described in the specification. Examples of non-abstract terms in a machine-learning context can include digital images, neural networks, receipt\transmission of data, computer hardware, real-time automatic performance, or anything else that cannot be accomplished within a human mind.
Explaining that an invention achieves an improvement in technology requires something to be said (or at least implied) of the current state of the technology being improved (e.g., what features does it lack, what performances are inadequate, and the like.) However, prior to the July 2024 guidance most practitioners were opining very little, in their patent applications, on technological background. Remaining purposely quiet on technological background and improvements to technology helps to avoid prior art based rejections by not admitting prior art or a rationale that the invention was obvious, under 35 U.S.C. § 103.1 For at least this reason, applications drafted before the USPTO's July 2024 guidance may not explain an AI invention as being an improvement in AI technology.
2 Request Expedited Examination
According to USPTO guidance from January 2019, training a neural network was considered subject matter eligible, because it was non-abstract. Specifically, the guidance asserted training a neural network was neither (1) a mathematical concept "because the mathematical concepts are not recited [as mathematical relationships, formulas, or calculations] in the claims [when training is recited at a high level]"; nor (2) a mental process because "the steps are not practically performed in the human mind." Example 39, p. 9, USPTO, Subject Matter Eligibility Examples: Abstract Ideas (Jan., 2019). A little over five years later, the USPTO guidance states that training a neural network, using a selected algorithm, such as "a backpropagation algorithm and a gradient descent algorithm," is ineligible as a mathematical calculation. Example 47, claims 2 and 3, p. 6, USPTO, July 2024 Subject Matter Eligibility Examples (Jul. 2024).
While the 2019 and 2024 guidance on training a neural network is not technically contradictory, the change in guidance has had large practical consequences for those who prepare and prosecute AI patent applications at the USPTO. Before the July 2024 guidance, training a neural network was generally considered non-abstract and eligible at the USPTO, and, today, after the July 2024 guidance, training a neural network is much more likely to be considered abstract and ineligible at the USPTO. Just as USPTO guidance on training a machine learning model in 2019 dramatically changed for practical purposes in 2024, USPTO guidance is likely to further change in the future.
Typically patent examination takes about three years, this timeline risks applications drafted today being impacted by future changes in USPTO policy. Expedited patent examination—such as through the Track One Program—allows applicants to have their cases examined quickly, often within one-year. By filing an AI application under expedited examination, an Applicant increases the likelihood that the patent application will be examined under current USPTO subject matter eligibility guidance.
3 Conclusion
AI and ML inventions present unique challenges in the patent system, but also great opportunities for innovators who understand how to navigate the process. AI innovators increase the likelihood of patent protection by preparing AI patent applications in light of the current USPTO guidance and expediting patent application examination.
Footnotes
1. C. Dresser, CaldwellLaw.com, The Patent – A Caricature of Invention, ("For example, where the invention represents an improvement on another invention, describing the earlier invention in the background section could help the examiner formulate an argument for why the patent application claims are obvious, and not entitled to patent protection. For this reason, Background sections in patents have been shrinking over the years, and modern patent practice is to explain little of the importance of the invention and not discuss any related publications" May 2023). https://caldwelllaw.com/news/the-patent-a-caricature-of-invention/
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
