AI IP Year in Review – Patent Law and Generative AI 101

While Artificial Intelligence (AI) solutions, such as predictive AI, have been around for decades, generative AI systems are recent innovations with far reaching implications for patent law. Generative AI, such as ChatGPT, DALL-E, and LLaMa, uses machine learning models to learn patterns from human-created content and generate new content based on those patterns.

Because generative AI focuses on creating new content, it introduces various challenges when used in the patenting process. This article addresses four points related to the utilization of generative AI in the patenting process: (i) patent inventorship; (ii) AI-generated prior art; (iii) eligibility under 35 U.S.C. § 101; and (iv) statutory and regulatory hurdles.

Patent Inventorship

First, generative AI may present unique and intriguing issues regarding patent inventorship. According to the Federal Circuit, only human beings qualify as inventors, but in many cases, it is unclear whether a human’s contribution to the inventive process in the context of generative AI systems qualifies them as an inventor of an invention. For example, a human inventor might use or rely on a generative AI system to develop an invention. These types of situations can intro-duce ambiguity about inventorship because it can be difficult to determine whether a human actually conceived of the invention. This may lead to increased litigation to determine inventorship when inventors use generative AI tools.¹

The United States Patent and Trademark Office (USPTO) has recently published regulations regarding inventorship and the use of AI tools.² The regulations suggest helpful guidance, such as applying the Pannu factors, which are currently used to determine whether an individual qualifies as an inventor when multiple individuals contributed to the patent.

The regulations also suggest helpful guiding principles such as: (1) use of an AI system doesn’t negate the ability to be an inventor; (2) conception requires more than recognizing a problem or having a plan; (3) significant contribution for inventorship requires more than reduction to practice; (4) creating “an essential building block” used to derive the invention may constitute significant contribution for inventorship; and (5) ownership of an AI system doesn’t make the owner an inventor of the AI system’s creations.³

While these principles are helpful, many questions remain unanswered and additional rulemaking is likely needed. For example, what constitutes a “significant contribution” or an “essential building block” when a generative AI tool is used by the inventor? Patent practitioners, inventors, and companies will need to carefully consider these open questions and the various potential answers they may raise.

AI-Generated Prior Art

Second, generative AI may raise significant issues when used to create prior art to reject a patent application or invalidate an existing patent.

Notably, generative AI can produce vast amounts of prior art, leading to increased costs during both patent prosecution and litigation due to the additional art that may need to be considered. Additionally, there is a risk that the generated prior art may be technically inaccurate, resulting in increased time and costs associated with evaluating these references.

Given these concerns, it’s possible that courts may introduce additional guardrails around the use of AI generated prior art. As one example, prior art publications are presumed to be enabling absent contrary evidence, and therefore places the burden on applicants, who have to prove that a reference fails to enable a person of ordinary skill in the art to practice the subject matter.⁴ However, this may not be a safe assumption with AI generated prior art, as generative AI technologies might be unable to identify a use for an invention. Consequently, such AI generated prior art may not be enabling, as it fails to instruct a person of ordinary skill in the art on how to make and use the invention. To address this concern, a possible guardrail that could be introduced is that AI generated prior art is not automatically considered enabling.

A further guardrail that could be introduced is a conception requirement for AI generated references to qualify as prior art.⁵ Conception requires recognition and appreciation of the invention.⁶ For AI generated references, conception could require: (1) human review, recognition, and appreciation of the invention; or (2) evidence that the AI system recognized and appreciated the invention.⁷ Qualifying evidence may include the AI system performing a simulation of the invention.⁸ This requirement may reduce the number of references qualifying as prior art. In turn, this would likely increase incentives for inventors to file patent applications in view of the additional requirements for AI generated references to qualify as prior art.⁹

Eligibility Under 35 U.S.C. 101

Third, generative AI may introduce unique issues regarding 35 U.S.C. § 101. Specifically, an invention that uses or relies on generative AI might be considered non-patent-eligible subject matter. This is often because AI/ML innovations are related to algorithms and computational processes, which are often viewed under the lens of abstract ideas and, therefore, not eligible for patenting.

Under current USPTO guidance, abstract ideas may be patent-eligible when integrated into practical application of the abstract idea or when the claimed invention amounts to significantly more than the abstract idea.¹⁰ This can often be demonstrated by showing that the claimed invention improves the functioning of the computer itself or improves another technological field.¹¹

Given these considerations, there may be subject matter eligibility concerns when a patent applicant merely applies an AI system to an existing problem, especially a non-technical problem. On the other hand, patent applications that involve unique data preparation for an AI model, improvements to the AI model itself, or unique environment adaptations of an AI model, may face fewer subject matter eligibility issues.

For example, the PTAB reversed a § 101 rejection of a patent for a “kernel-based machine learning classifier” because improved memory usage and classifier accuracy led to an improvement of machine learning technology, specifically improved kernel-based classifiers.¹² Therefore, the type of AI invention and how that invention is presented in the claims may affect whether that invention is patent subject matter eligible.

Statutory and Regulatory Hurdles

Lastly, generative AI may raise complex issues during patent prosecution. Generative AI tools may introduce at least three statutory and regulatory hurdles for practitioners (e.g., attorneys, agents) and inventors at the USPTO.

First, USPTO regulations require natural persons (e.g., human beings) to sign submissions.¹³ Therefore, practitioners and inventors should be aware of AI tools that automatically sign submissions.

Second, there may be confidentiality and public disclosure issues surrounding use of generative AI tools. For example, inputting patent-eligible subject matter into an online generative AI system may trigger the one-year grace period under 35 U.S.C. § 102(b)(1), and potentially implicate client confidentiality requirements.¹⁴

Finally, by presenting a submission to the USPTO, the submitting party is certifying that included statements are true and that a reasonable inquiry under the circumstances has been made.¹⁵ This requirement may be implicated by practitioners who use generative AI tools to identify prior art and case law, given practitioners who use such tools may find it challenging to verify the accuracy of the outputted results, and therefore comply with the reasonable inquiry standard.

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As AI evolves, the law and stakeholders will inevitably need to similarly evolve to address not only the issues discussed herein, but many more issues of first impression.

[1] Thaler v. Vidal, 43 F.4th 1207, 1210 (Fed. Cir. 2022).
[2] Inventorship Guidance for AI-Assisted Inventions, 89 Fed. Reg. 10043 (February 13, 2024).
[3] Id.
[4] In re Antor Media Corp., 689 F.3d 1282, 1287 (Fed. Cir. 2012).
[5] Lucar R. Yordy, The Library of Babel for Prior Art: Using Artificial Intelligence to Mass Produce Prior Art in Patent Law, 74 VANDERBILT LAW REV. 521, 554 (March 2021).
[6] Manual of Patent Examining Procedure (MPEP) § 2138.04.
[7] Id. at 555.
[8] Id. at 556.
[9] Id.
[10] MPEP § 2106.04(d).
[11] MPEP § 2106.04(d)(1).
[12] Ex Parte Holtmann-Rice (Appeal No. 2024-000046, March 27, 2024).
[13] Guidance on Use of Artificial Intelligence-Based Tools in Practice Before the United States Patent and Trademark Office, 89 Fed. Reg. 25609 (April 11, 2024).
[14] Representation Of Others Before The United States Patent And Trademark Office, 86 Fed. Reg. 28466 (May 26, 2021).
[15] 37 CFR § 11.18(b).

This article appeared in the 2024 AI Intellectual Property Year in Review: Analysis & Trends report.