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Recent USPTO Report Suggests Greater Consistency and Predictability in Patent-Ineligible Subject Matter Rejections

Last week, the US Patent and Trademark Office (“USPTO”) released a report detailing its findings on how the U.S. Supreme Court decision in Alice Corp. v. CLS Bank International, as well as subsequent USPTO guidance on 35 U.S.C. § 101 rejections, has affected rates of, and variability between, office action rejections. This report provides a new and useful glimpse into the state of patent prosecution of Alice-affected technologies after the USPTO issued its January 2019 Revised Patent Subject Matter Eligibility Guidance (“2019 PEG”).

The report focuses its analysis on two metrics: one, the percentage of patent applications that received first office action § 101 rejections, and two, the percentage of uncertainty in the patent examination process (defined as “the variation across examiners in the proportion of rejections for patent-ineligible subject matter… [uncertainty increases as] the percentage of first office action rejections…becomes more uneven across examiners within a specific technology”). U.S. Patent and Trademark Office, Adjusting to Alice: USPTO Patent examination outcomes after Alice Corp. v. CLS Bank International, 3 IP Data Highlights 3 (April 2020). These two metrics are analyzed both within the first 18 months after Alice, as well as within the 12 months following the 2019 PEG. The USPTO’s analysis indicates that the USPTO’s 2019 guidelines have affected both the rate and variability of first office action rejections based on patent-ineligible subject matter.

The USPTO first found that both § 101 rejections and uncertainty in the patent examination process sharply increased in the 18 months immediately following the Alice decision. Specifically, for Alice-affected technologies, “the chances of receiving a first office action rejection [with a § 101 rejection] increased by 31% in the 18 months following Alice.” Id. at 4. As the report notes, there are at least two explanations for the increase: one, applying the Alice standard involved expanding patent-ineligible subject matter to other technology areas, and two, “professionally trained judges, lawyers, and examiners can apply reasonable but different interpretations of the Alice standard.” Id. at 4. Additionally, “[w]ithin Alice-affected technologies, uncertainty in the patent examination process “increased by 26% in the 18 months following Alice,” which “seems to reflect the interpretive latitude in the language of the Alice standard.” Id. at 5.

The USPTO found, however, that the 2019 PEG appeared to reverse both of these upward trends. Specifically, in the year following the issuance of the 2019 PEG, “the chances of receiving a first office action [§ 101 rejection decreased] by 25%,” and “uncertainty about patent subject matter eligibility determinations … [was reduced] by 44% for Alice-affected technologies.” Id. at 7, 8. The USPTO stated that the 2019 PEG both “clarified that abstract ideas are grouped as mathematical concepts, certain methods of organizing human activity, and mental processes … [and] explained that a claim that recites an abstract idea that is not ‘directed to’ the abstract idea if the claim as a whole integrates the abstract idea into a practical application.” Id. at 7. As a result, “the 2019 PEG provided clarity and structure to the decision-making process, thereby reducing the degree of variability observed across examiners in subject matter eligibility determinations.” Id. at 8.

These figures show a trend towards a more “consistent and predictable” approach towards § 101 rejections from the USPTO since it issued its 2019 PEG. Id. at 8. These statistics should be encouraging to any inventors in Alice-affected technologies who hesitated to seek patent protection immediately following Alice, as the report indicates that patent examiners now both issue § 101 rejections less frequently, and are more consistent when they do issue rejections for patent-ineligible subject matter.

©1994-2020 Mintz, Levin, Cohn, Ferris, Glovsky and Popeo, P.C. All Rights Reserved.National Law Review, Volume X, Number 139

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About this Author

Brad Scheller Patent Litigation Attorney Mintz Law Firm
Member

Brad Scheller is a trial attorney who focuses his patent litigation practice on representing clients in the automotive devices, thermoplastics, electronic components and consumer products industries in federal district court, before the Patent Trial and Appeal Board and at the International Trade Commission. With a background in mechanical engineering and over 14 years of experience practicing law, Brad has successfully represented patent owners in enforcing their rights against infringers and protecting those rights from challenges of invalidity, and has also successfully defended and...

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Associate

Meena focuses her practice on intellectual property litigation. She has handled all aspects of litigation, including drafting pleadings and briefs, and brings to her role prior experience drafting and prosecuting US and international patents and responding to patent office actions. Meena has experience in a broad range of technology areas, including machine learning, malware detection, cybersecurity, networking hardware and software, wireless networks, data encryption, and computer programming.

Prior to joining Mintz, Meena served as an assistant district attorney with the Kings County District Attorney’s Office in Brooklyn, New York, where she worked on misdemeanor hearings and trials as well as grand jury presentations of felony cases. Earlier, she was a patent agent in the New York office of a California-based global law firm and a technical advisor and patent agent at an international law firm based in New York.

In law school, Meena served as executive articles editor of the Brooklyn Journal of International Law as well as an intern with the Children’s Law Center in Brooklyn and the Kings County District Attorney’s Office. While earning her bachelor’s degree, Meena studied uses for auditory game cues in iPhone applications as a student researcher at the University of North Carolina through the Computing Research Association’s Distributed Research Experiences for Undergraduates program. She was also twice a summer science research fellow at Bryn Mawr College, where she studied recurrent artificial neural networks and assessed the use of a humanoid robot in a computer science course.

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