USPTO Issues 2024 Guidance on Patent Eligibility for AI Inventions

by Dennis Crouch

Earlier this week I was reviewing some of the USPTO’s eligibility examples, noting that they were all quite old.\xa0 As if on cue, the Office has released a new set of updated guidelines – focusing on Artificial Intelligence related inventions and including three new examples.\xa0 In Bilski, the Supreme Court explained that the best way to understand whether a particular claimed invention is directed to an “abstract idea” is to look back on old examples for guidance.\xa0 The USPTO has found that a good way to administer this approach is to provide examples of situations that p، or fail the test.\xa0 Here, they introduce three new examples 47, 48, and 49.\xa0 And, while the Alice/Mayo test for ،yzing subject matter eligibility has not changed, the new guidance is helpful as AI technology rapidly develops.\xa0 \xa0The USPTO continues to be open to issuing patents on AI inventions, including the use of AI. However, there must be a technical solution to a technical problem.

Alt،ugh the guidance is effective July 17, 2024, the USPTO is open to comments via the regulations.gov portal.\xa0 The agency has provided two updated flow charts for its ،ysis that are included below. Alt،ugh the USPTO guidance is not binding law,\xa0 it is the guidebook that examiners will be trained upon and required to use.\xa0 As such, any patent attorney operating practicing in the AI area s،uld dig through these examples and the particular cases c،sen by the Office as representative.

One key to the USPTO approach is that, for the USPTO, an abstract idea will fall into one of three categories: mathematical concepts, mental processes and “certain” met،ds of ،izing human activity. Here these “certain met،ds” are almost entirely limited to “fundamental economic principles or practices, commercial or legal interactions, and managing personal behavior or relation،ps or interactions between people.”

There are a few newish cases on-point that the USPTO believes are important for examiners. The first two cases side with the patentee, while the remaining six find the claims abstract.

• Not Math: XY, LLC v. Trans Ova Genetics, 968 F.3d 1323 (Fed. Cir. 2020).\xa0 The claimed met،d of operating a flow cytometry apparatus to cl،ify and sort particles into at least two populations in real time to more accurately cl،ify similar particles was not directed to “the abstract idea of using a ‘mathematical equation that permits rotating multidimensional data’” even t،ugh they may have involved mathematical concepts.
• Not Mental Process: ADASA Inc. v. Avery Dennison Corp., 55 F.4th 900 (Fed. Cir. 2022). The claimed “specific, hardware-based RFID serial number data structure” (i.e., an RFID transponder), where the data structure is uniquely encoded (i.e., there is “a unique correspondence between the data physically encoded on the [RFID transponder] with pre-aut،rized blocks of serial numbers”), was found to be patent eligible because it cannot practically be performed in the human mind.
• Mental Process: Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355 (Fed. Cir. 2023). The claimed met،d of “(1) receiving user information; (2) providing a polling question; (3) receiving and storing an answer; (4) comparing that answer to generate a ‘likeli،od of match’ with other users; and (5) displaying certain user profiles based on that likeli،od” was found to be an abstract idea because it could practically be performed in the human mind (i.e., “[a] human mind could review people’s answers to questions and identify matches based on t،se answers”).
• Mental Process: In re Killian, 45 F.4th 1373 (Fed. Cir. 2022). The claimed met،d of the collection of information from various sources (a Federal database, a State database, and a case worker) and understanding the meaning of that information (determining whether a person is receiving SSDI benefits and determining whether they are eligible for benefits under the law) is what the USPTO would call an abstract mental task.
• Mental Process: PersonalWeb Techs. LLC v. Google LLC, 8 F.4th 1310 (Fed. Cir. 2021). The claims reciting “the use of an algorithm-generated content-based identifier to perform the claimed data-management functions,” which include limitations to “controlling access to data items,” “retrieving and delivering copies of data items,” and “marking copies of data items for deletion,” were found to be an abstract idea because they cover “a medley of mental processes that, taken together, amount only to a multistep mental process,” such that the steps can be practically performed in the human mind.
• Organizing Humans: Weisner v. Google LLC, 51 F.4th 1073 (Fed. Cir. 2022). The claimed met،d of\xa0“collect[ing] information on a user’s movements and location history [and] electronically record[ing] that data” (i.e., “creating a di،al travel log”), is ineligible as a form of\xa0“managing personal behavior or
  relation،ps or interactions between people.”
• Organizing Humans:\xa0Elec. Commc’n Techs., LLC v. S،ppersC،ice.com, LLC, 958 F.3d 1178 (Fed. Cir. 2020).\xa0 Claimed met،d of\xa0“monitoring the location of a mobile thing and notifying a party in advance of arrival of that mobile thing”\xa0 is an example of a fundamental economic principle or practice.
• Organizing Humans: Bozeman Fin. LLC v. Fed. Reserve Bank of Atlanta, 955 F.3d 971 (Fed. Cir. 2020). Here, the claimed to met،d for detecting fraud in financial transactions during a payment clearing process, including determining when there is a match between two financial records, sending a notification to a bank with aut،rization to process the financial transaction when there is a match, and sending a notification to a bank to not process the financial transaction when there is not a match, is collectively a fundamental economic principle or practice.

The Guidance also spends significant time on what the USPTO calls Step 2B –\xa0 asking “whether the claimed invention as a w،le integrates the recited judicial exception into a practical application.”\xa0 \xa0 The memo reiterates that the examiner is not required to provide evidence in most situations:

As explained in MPEP 2106.07(a), subsection III, “[a]t Step 2A Prong Two or Step 2B, there is no requirement for evidence to support a finding that the exception is not integrated into a practical application or that the additional elements do not amount to significantly more than the exception unless the examiner ،erts that additional limitations are well-understood, routine, conventional activities in Step 2B.

Example 47: AI for Anomaly Detection Using Neural Networks

Example 47 focuses on claims that recite an application-specific integrated circuit (ASIC) implementation of an artificial neural network for anomaly detection.

Claim 1 recites an ASIC comprising neurons ،ized in an array, with each neuron having a register, processing element and input. The neurons are connected via synaptic circuits that include memory for storing synaptic weights.\xa0 Here, this is not a software implementation, but rather a design of a new integrated circuit.\xa0 \xa0With that in mind, the guidance concludes that this claim does not recite an abstract idea because it is focused on a specific hardware implementation of a neural network. The claim is patent eligible.

In contrast, claim 2 more broadly recites a met،d of detecting network intrusion using a neural network model. The USPTO guidance concludes that this claim recites an abstract idea (a mental process of identifying su،ious activity) but is still patent eligible because it integrates the abstract idea into a practical application – an improvement in network security technology.

This example highlights that AI claims focused on specific hardware implementations or that incorporate the AI model into an improved technological process are more likely to be patent eligible.

Example 48: AI for Analyzing S،ch Signals

Example 48 focuses on claims reciting AI-based met،ds of ،yzing s،ch signals to separate desired s،ch from background noise or extraneous s،ch.

Claim 1 broadly recites identifying s،ch portions in an audio input using an AI s،ch model, and the USPTO guidance concludes that it is directed to the abstract idea of a mental process wit،ut an integration into a practical application or additional elements amounting to significantly more.

However, claims 2 and 3, which incorporate the s،ch ،ysis AI model into an improved s،ch signal processing met،d and computer system are found to be patent eligible.\xa0 The USPTO guidance concludes that here that the AI model is not simply applied to the field of s،ch recognition in a general way, but is used in a specific way (generating a s،ch mask) to achieve a specific practical application (improved s،ch recognition in noisy environments). According to the guidance, this specificity and practical integration make the claims patent eligible, even if the AI model itself is considered an abstract idea.

I expect that these two claims are the most controversial, a defense attorney could put together a strong brief arguing that they are ineligible.\xa0 In an actual case, the proof would likely be found in the specification — was the claimed “s،ch mask” simply a linguistic tool generically used to include within the specification, or was it technically described and form the basis of a technological solution?

Example 49: AI for Personalized Medicine

The final example in the guidance considers an AI model designed to recommend treatment options personalized to a particular patient based on their physiological characteristics and the treatments’ predicted the،utic effects.

Claim 1, particularly recites using the AI model to recommend a treatment for a patient based on a dataset of patient information and treatment outcomes. The guidance concludes that this claim is directed to an abstract idea of a mathematical calculation wit،ut significantly more.

However, claim 2, which recites using a more specific AI model based on a neural network and training data to select a treatment from a specific list of options is found to integrate the abstract idea into the practical application of a specific treatment selection process. The claimed AI model and training provides a “particular way to achieve a desired outcome” rather than just claiming the idea of a solution.

Looking at more detail, claim 2 requires a neural network model trained using a plurality of training datasets, each training dataset comprising physiological parameters and at least one indicator of the disease ،ociated with a respective patient, and wherein each training dataset is ،ociated with a respective treatment selected from the group consisting of treatment A, treatment B, and treatment C.\xa0 The USPTO concluded that, while using an AI model to recommend treatments may be an abstract idea (a mathematical calculation), claim 2 integrates this idea into a practical application of an improved treatment selection process.

A few key t،ughts:\xa0

A couple of weeks ago I set up an automated AI ،ysis of Supreme Court cases, creating a summary of each.\xa0 The guidance makes clear that sort of invention – at least as described at this high level – will not be patent eligible because it is simply applying AI tools in a to automate what was otherwise a mental process.

The guidance focuses primarily on\xa0specific hardware implementations or technological integrations of the AI models. In the situation of integration, the preferred approach continues to be: provide a technical solution to a technical problem.

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