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Unprecedented Allowance Rates at the USPTO?

According to the USPTO, the current allowance rates are around 76% and have been above 70% since May 2017:

https://www.uspto.gov/corda/dashboards/patents/kpis/kpiAllowed.kpixml

Historically, allowance rates are just below 70%, occasionally spiking up above 70% for a quarter or two.

https://patentlyo.com/patent/2016/11/uspto-allowance-rate-2.html

Are we in unprecedented territory for the USPTO and the U.S. patent system?

Note that, between the Alice decision in 2014 and Dec. 31, 2018, only 36% of patents granted by the USPTO had valid claims after being challenged under Section 101 at the District Courts. The high invalidity rate has been relatively constant during that time.


How high will it go? An update on the allowance rate for applications relating to artificial intelligence at the USPTO

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It has been about a year since my last post on allowance rates for applications relating to artificial intelligence at the USPTO, and it seemed like a good time for an update.

In short, the allowance rate is still around 90% for applications relating to artificial intelligence, but, notably, the allowance rate in 2019 actually surpassed 90% for this technology. This may be partially due to the updated guidelines distributed by the USPTO at the beginning of the year, which "aim to improve the clarity, consistency, and predictability of actions across the USPTO." Actions are sent out by examiners to prevent the office from granting patent rights over technologies that were already publicly accessible (described exactly or as an obvious variant) at the time of filing. The USPTO could attain perfect clarity, consistency, and predictability of actions with a 100% allowance rate, but at what cost to the public?



METHODOLOGY

In the study, to find what I consider "artificial inte…

What is patent quality?

I'd like to explore patent quality more formally rather than just posting numbers to a blog. More importantly, I'd love to hear your feedback, and, in particular, any way I can improve my understanding of patent quality. If you have a lot of feedback or interest, please stop by the Technology Patent Network conference tomorrow in San Francisco, where I'll be talking about patent quality from 4:15 to 4:45.
Patent quality has received a bit of attention recently as patent systems around the world continue to self-evaluate with respect to others, as the case law continues to clarify that not all patents are created equal, and as patent tool vendors successfully push value-added insights. Still, there seems to be quite a bit of disagreement on the subject.
In 2017, former Chief Judge Paul Michel stated: "I think at the end of the day, patents are either valid or invalid as a legal instrument and therefore it's not very helpful to talk about quality or 'good' o…

Guest Lecture on "AI Patent Quality: Avoiding Flaws Inherent In Human-Performed Work" at Stanford Law

I would like to thank Jason Du Mont and his students for inviting me to speak today at Stanford Law on "AI Patent Quality: Avoiding Flaws Inherent In Human-Performed Work," as part of the Law, Science, and Technology LLM Colloquium. I was impressed by their thoughtful and challenging questions.

To summarize the presentation, most of what patent attorneys do today can be done better by machines using existing technology as applied to patent law. Because AI can optimize strategies based on tens of thousands of data points simultaneously, I believe AI will make better decisions, on average, than the human patent attorney counterparts. The underlying algorithms and technology might be ready to take us there, but the patent-specific tools are not yet fully developed. In the meantime, we can make use of as much data and stats-based analytics as possible. Based on wisdom gained from studies outside of patent law, I think we should defer decisions to AI or stats-based analytics when…

Best Practices on IP Portfolio Management and Bulk Patent Quality Evaluation (as presented at PATINEX in Korea and IP Business Journal Conference in Japan, Sept. 2018)

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I am honored to be a guest at PATINEX in Korea and IP Business Journal Conference in Japan this week, where I am presenting the slides below entitled, "Best Practices on IP Portfolio Management and Bulk Patent Quality Evaluation." I wanted to provide an introduction to data-driven patent prosecution in the software realm, particularly for companies that do not yet understand the variance between art units and examiners at the U.S. Patent and Trademark Office (USPTO).
To introduce the topic, I defined a set of "software patent applications," and analyzed what happened to those applications as they transitioned through the USPTO. Not surprisingly in light of my prior studies, the allowance rates are high for software patent applications filed in 2015 with priority in 2015. There are, of course, limitations in this dataset. That said, the data is in line with the all-time high 76% allowance rate at the USPTO. 
Also not surprisingly, the odds in some art units are sig…