Artificial Intelligence Will Help to Solve the USPTO’s Patent Quality Problem

About a month ago, Steve Brachmann authored an article concerned with a brief given to Capitol Hill staff by Professors Frakes and Wasserman. The article highlighted fundamental, as well as practical, problems with Professors Frakes’ and Wasserman’s proposal (i.e. doubling the number of patent examiners as a means to reduce the number of invalid patents and thereby prevent societal harms) and how it could be detrimental to the U.S. patent system.

Frakes and Wasserman cite sources saying that the U.S. Patent and Trademark Office (USPTO) is granting too many bad patents which “unnecessarily drain consumer welfare, stunt productive research, and unreasonably extract rents from innovators.”  They trace the problem to a lack of sufficient review time available to the examiner:

“On average, a U.S. patent examiner spends only eighteen hours reviewing an application, which includes reading the application, searching for prior art, comparing the prior art with the application, writing a rejection, responding to the patent applicant’s arguments, and often conducting an interview with the applicant’s attorney. If examiners are not given enough time to evaluate applications, they may not be able to reject applications by identifying and articulating justifications with appropriate underlying legal validity.”

And since patent applications are presumed valid, the examiner must grant the patent if he or she cannot rebut the presumption within the time allotted for the examination.

According to Frakes and Wasserman, doubling the number of examiners would result in a net reduction of the costs associated with bad patents (such as future litigation expense savings per year of approximately $572 million dollars).

The IPWatchdog article points to several issues with Frakes’ and Wasserman’s proposal, but does not discuss other approaches or options, such as using artificial intelligence tools to improve the patent application review process—an option that USPTO Commissioner for Patents Drew Hirshfeld said in a recent Senate IP Subcommittee hearing that the Office is actively pursuing.

Examiners Need All Available Tools

While some, like Frakes and Wasserman, suggest that the path to better patents is through doing more of the same, i.e. doubling the number of examiners, there might be a better way.

According to PWC, 72% of executives testify that AI improves internal operations while freeing up workers to perform more creative and meaningful tasks. In fact, while some might fear that “robots” will take human jobs, technological innovation has been proven to generate more jobs than it takes, while automating tasks, like patent search.

AI can further the purposes of the patent system in two important ways. First, it can perform tedious prior art searches so that examiners put their limited time to higher and better uses. Second, AI tools promote a better and more effective use of inventors’ and other interested parties’ time and money in connection with patenting new technologies and maintaining patent portfolios.

For many years now, the USPTO has received hundreds of thousands of applications each year. That number has been over 600,000 patent applications each year for the last several years. Given the sheer volume of patent applications processed each year by the USPTO, and increases in relevant data sources, it is no wonder that examiners are crunched for time and applicants wait two years or more before receiving a final disposition on their application.

At this rate, simply increasing the number of patent examiners will not be enough, and technological solutions will become necessary.

Better, Faster Prior Art Searches

AI tools can streamline the application review process and the quality of the results by reducing the amount of time examiners spend researching prior art. Instead of two to four days of prior art research, artificial intelligence can do all that leg work in one to two hours. AI technology has advanced beyond simply comparing the words in a patent application to those in other patent records. AI can compare a whole patent’s content and ideas against millions of other patent records and database sources to find relevant prior art and return search results that meet or exceed those of human examiners.

Thus, even if examiners, on average, only spend 18 hours to search and review a patent application (as per Frakes and Wasserman), with AI tools they can perform the time-intensive prior art search much faster. Once that task is outsourced, the patent examiner will be able to allocate a greater portion of their review to understanding the applications, comparing the prior art to the applications, writing rejections, responding to applicants, etc.

Since the purpose of the Patent Act is to incentivize innovation for the short-term benefit of the inventor and the long-term benefit of society, surely tools that redirect inventors’ focus toward substantive matters are very valuable.

Weeding Out Unpatentable Inventions Up Front

Before a patent application even reaches the USPTO, artificial intelligence tools can save inventors time and money by identifying early on those inventions that will likely not be patentable. Instead of investing time and effort in such dead-end inventions, they can turn their attention to more promising work. And consider the benefit to the patent system and its goals if artificial intelligence not only makes the examiners more effective (whether we double their number or not), but also improves the overall quality of the initial applications.

Balancing Budgets

Similarly, instead of renewing all existing patents in a company’s portfolio, portfolio managers and practitioners can use AI to more effectively manage their intellectual property budgets. For example, AI can identify prior art which could provide a basis for an invalidation challenge, which in turn could impact the patent holder’s decision whether or not such patent is worth renewing.

Parsing Portfolios

In addition, other patent practitioners, such as M&A counsel and litigation counsel, can benefit from the power of AI search capabilities. Is that patent portfolio really as good as the seller advertises, or is it undermined by prior art and an easy target for an invalidation claim?  Is company X’s technology infringing on your patent? Artificial intelligence tools can save practitioners time and provide valuable insight into these issues.

Not a Silver Bullet, But a Powerful Tool

One challenge that must be addressed is that artificial intelligence can be “gamed”. AI is based on learning specific data patterns and making fast decisions based on those patterns. However, those patterns can be falsified or triggered by actors who wish to game the software. AI is not fool proof and there have been recorded cases where it failed to perform what it was designed to do.

Artificial intelligence, by itself, may not be a silver bullet to the issue of patent quality, but it is a powerful tool well-suited to promote the goals of our patent system by allocating examiners’ limited time to higher and better uses and facilitating a better and more cost-effective use of inventors’ and other interested parties time and money in connection with patenting new technologies and maintaining patent portfolios.

While it may be the case that we need to dramatically increase the number of examiners, it is my opinion that a combination of patent examiners with innovative tools that help them get their job done quickly and efficiently are the future of patent examination.

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