AI IP Year in Review: Key Takeaways from the Federal Circuit’s First Alice Analysis for Machine Learning Patents

The Federal Circuit’s decision in Recentive Analytics, Inc. v. Fox Corp., et al., 2023-2437, addressed a question of first impression: whether claims that do no more than apply established methods of machine learning to a new data environment are patent eligible under Section 101. This case involved machine learning used to optimize scheduling and geographical placement of television shows.

Applying the two-step Alice framework familiar in software patent cases, the Federal Circuit affirmed the lower court’s holding of subject matter ineligibility “because the patents are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept.”

For Alice Step 1, the court found that “[b]oth sets of patents rely on the use of generic machine learning technology in carrying out the claimed methods for generating event schedules and network maps,” and the claimed machine learning technology was “conventional.” The court rejected the argument that the claimed methods’ application of machine learning to a new field of use conferred eligibility. The greater speed and efficiency gained through machine learning could not confer patent eligibility. And the court found the claims did not delineate steps that improve the machine learning technology.

For Alice Step 2, the court found nothing in the claims, individually or in their ordered combination, that would transform the patents into something significantly more than “the abstract idea of generating event schedules and network maps through the application of machine learning.”

Takeaways

• Patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, claim patent ineligible subject matter under Section 101.
• The Federal Circuit’s Alice analysis for machine language models differs little from its applications in more traditional software contexts. The court’s prior holdings that “the application of existing technology to a novel database does not create patent eligibility” are apropos to the machine learning context. Practitioners may want to consider these prior decisions in composing their Section 101 arguments.

Read the original alert, Federal Circuit’s First Alice-Analysis for Machine Learning Patents.

This article appeared in the 2025 AI Intellectual Property: Analysis & Trends Year in Review report.