USPTO releases new Artificial Intelligence Patent Dataset

Artificial Intelligence Patent Dataset (AIPD) [Photo Provided = United States Patent and Trademark Office (USPTO)]

The United States Patent and Trademark Office’s (USPTO) Office of the Chief Economist released the Artificial Intelligence Patent Dataset (AIPD)—identifying which of the 13.2 million United States patents and pre-grant publications include artificial intelligence (AI)—to help enable researchers policymakers and the public explore the impacts of AI on invention.

The Office of the Chief Economist constructed the AIPD using machine learning models for eight AI component technologies. A new working paper highlights the machine learning approach used to generate the dataset which achieved superior performance compared to existing alternatives.

To assist researchers and policymakers focusing on the determinants and impacts of artificial intelligence (AI) invention OCE released two data files collectively called the Artificial Intelligence Patent Dataset (AIPD).

The first data file identifies United States (U.S.) patents issued between 1976 and 2020 and pre-grant publications (PGPubs) published through 2020 that contain one or more of several AI technology components (including machine learning natural language processing computer vision speech knowledge processing AI hardware evolutionary computation and planning and control).

OCE generated this data file using a machine learning (ML) approach that analyzed patent text and citations to identify AI in U.S. patent documents (Abood and Feltenberger 2018; Toole et al. 2020).

OCE’s approach is based on the methodology of Abood and Feltenberger (2018) but also includes an analysis of patent claims to better identify AI contained in the technical and legal scope of the invention. The second data file contains the patent documents used to train the ML models.

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