At the end of August, PatentsView and the United States Patent and Trademark Office (USPTO) convened a group of 10 researchers, developers, and analysts to discuss the best and newest practices in identifying inventor demographics, including the use of gender and race. The event was structured as an all-day symposium with seven individual presentations and a three-person panel conversation on the social and economic implications of advancing our understanding of inventor demographics.

Recordings from each session of the symposium are now available online.

View the recordings now.

Why Study Inventor Demographics?

Quite simply, greater diversity and participation among inventors fuels more innovation and improves economic welfare. However, the current data suggest many people, particularly from diverse communities, are not represented among inventors. This means that challenges exist at various points along the pathway from inspiration, to inventor, to innovator and entrepreneur. Learning about who is and is not  participating as inventors and why is a critical step toward ensuring that all people can contribute equally to the innovation landscape and improve economic outcomes at both a personal and societal level.

Unfortunately, the research into identifying and addressing such gaps is still in its infancy. One of the largest barriers is the lack of information about the demographics of inventors who apply for and ultimately receive patents.

Disambiguation Methods and Practices

Researchers have been using several methods and practices to shed light on inventor demographics when that information is not self-reported — the main processes are disambiguation and attribution.

Each of these different processes has its own strengths and weaknesses. Speakers at the Advancing Research on Inventor Demographics Symposium, held on August 26, 2022, discussed the societal consequences of inequities in innovation. They also provided an in-depth discussion of the methods used to identify an inventor’s gender, race, ethnicity, and country of origin when that information is not reported in publicly available datasets.

Leading Experts Discuss Cutting-Edge Research

The symposium brought together economists, computer scientists, and others to discuss research methods, applied examples, and new ideas. The experts included:

• Julio Raffo, a researcher in the Economics and Statistics Division at the World Intellectual Property Organization, who discussed gender attribution and the World Gender Name Dictionary 2.0.
• Ernest Miguelez, a research fellow at the French National Centre for Scientific Research (CNRS), who discussed the PatentsView approach to inventor gender.
• Michelle Saksena, a senior research economist at USPTO, who discussed assessing approaches for identifying the gender of inventors on patents.
• Fangzhou Xie, a Ph.D. student at the Department of Economics at Rutgers University, who discussed using an R package he developed, called rethnicity, to predict ethnicity from names.
• Francesco Lissoni, a professor of economics at the Bordeaux School of Economics within the University of Bordeaux, who discussed ways to determine inventors’ foreign-origin status using name analysis.
• Jay Budzick, the CTO of Zest AI, who discussed using the Zest Race Predictor to uncover hidden disparities.
• Marc Elliot, Distinguished Chair in Statistics and senior principal researcher at the RAND Corporation, who discussed methods to estimate race and ethnicity, and associated disparities, when records do not include self-reported data.
• Trevon Logan, a Distinguished Professor of Economics at Ohio State University; Adam Gailey, a principal in the Financial Economics Practice of Charles River Associates; and Jason Dietrich, section chief for compliance and analytics policy at the Consumer Financial Protection Bureau, who participated in a panel discussion about gaps in innovation by race/ethnicity and gender.