Upcoming event: Talk by Dr Ryan Whalen at CREATe, Wednesday 18 July

A Network Theory of Patentability: Towards an Empirical Measure of Patent Nonobviousness

Date: Wednesday 18 July, 3pm
Place: CREATe Hub, Room 404, 10 Professor Square
Booking: Email kerry.patterson@glasgow.ac.uk to reserve a place.

Book now for a talk by visiting researcher Dr Ryan Whalen from the University of Hong Kong.

Abstract

The nonobviousness inquiry is one of the most notoriously complex and contingent of all legal questions. The challenges faced by those tasked with determining an invention’s nonobviousness include understanding unfamiliar technologies and seeing the world from the perspective of an objective inventor, all while avoiding issues of hindsight bias.

This research project attempts to simplify the obviousness inquiry by proposing an empirically-grounded network theory of patentability that integrates the dominant competing theoretical approaches to obviousness. We use this network theory of patentability to motivate the definition of a “network measure of nonobviousness” and subsequently demonstrate our measure by using the prior art record to approximate “technological space.” We are then able to situate claimed inventions within technological space and measure the preceding inventive activity in the area, providing insight into how likely it is that the inventions are obvious.

Our network measure of nonobviousness offers valuable objective insight into the obviousness analysis that is based on the empirical patenting record and robust to hindsight bias. It shows promise as an aide for patent application assessment, patent portfolio management, and patent dispute resolution. From a methodological perspective, this project is the first to use network analysis to answer doctrinal questions.

Biography

Ryan Whalen’s research takes a data-driven approach to understanding the law and legal systems, with a particular focus on intellectual property law and innovation policy. This approach unites traditional doctrinal analyses with empirical techniques drawn from diverse fields including machine learning, natural language processing, network analysis, and data science.

His work has appeared in a wide variety of journals including the Northwestern University Law Review, the Yale Law Journal Forum, the Michigan State Law Review, and the Journal of the Patent and Trademark Office Society.

Ryan holds a BA(hons) from Saint Mary’s University (Canada), an MA from National Chengchi University (Taiwan), a JD from the Northwestern University Pritzker School of Law, and a PhD from Northwestern University. While at Northwestern, Ryan served as the editor-in-chief of the Northwestern University Law Review.

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