Jeff O’Neill

In an ideal world, issued patents would not contain errors. In reality, patent drafting is tedious and time-consuming work and perfection is not an attainable goal. The patent industry seems to be steadily getting better, though. In a recent study, we uncovered an 11.24% decrease in errors per patent over the past four years. We observed this decrease by reviewing every patent issued by the U.S. Patent and Trademark Office (USPTO) since 2020 – nearly 1.4 million patents.

After a patent application is filed with the USPTO, it gets assigned to an art unit and a patent examiner in that art unit who is responsible for reviewing the application, doing a prior art search, and determining whether to grant a patent…. In the past, this process was manual. People would review patent applications to assign classification codes, and then other people would determine the art unit and examiner to be assigned using the classification codes. More recently, the USPTO is automating the assignment process. The assignment process is a great candidate for automation using machine learning, because large amounts of training data are available to train a machine learning model. Automating the assignment process has several advantages: lower costs, faster processing, and more consistent and likely better assignments of applications to art units and examiners.