The U.S. Court of Appeals for the Federal Circuit’s recent conclusion that applications of machine learning are not necessarily eligible for patenting has drawn significant notice from the AI community. In Recentive Analytics v. Fox Corp., the Federal Circuit affirmed that claims directed to using machine learning to predict TV viewership were patent-ineligible abstract ideas. While the decision grabbed attention, it was unremarkable for practitioners with deep experience in AI, given the way the patents presented their technology. The Federal Circuit’s decision instead reinforces what such experienced practitioners have long known: The challenge in obtaining strong AI patents isn’t the technology itself, but rather in crafting a specification that tells the right story about technological innovation. Best practices for protecting machine learning fundamentally follow best practices for other types of software. When protecting high-value applications of AI, it remains critical to work with counsel who understand both the technology and how to position it strategically.
LINKS
Read “The Recentive Reality Check for AI Patents,” authored by Andrew (A.J.) Tibbetts, published in The Journal of AI.