Carnegie Mellon University

AI & Patents Workshop @ ICAIL21

To be held online on June 25, 2021

A full-day workshop

Keynote address by Deputy Director Stewart of the US Patent & Trademark Office

Schedule coming soon

Workshop Scope

The workshop is intended to popularize two types of work:

  • new AI techniques to automate the processing of patents
  • issues at the intersection of AI technologies and the patent systems of the world

This workshop addresses the use of AI techniques for patents. This includes the use of Machine Learning and Natural Language Processing in patent examination, extracting meaning and information from the text of patents, evaluating patent portfolios, patent litigation analytics, patent citation analysis, and evaluating patent licenses.

This workshop also addresses legal issues associated with patent rights for AI-related inventions, including AI inventorship, eligibility, and challenges in satisfying statutory requirements.

Tracks

  • Track I: AI in the World's IP Offices

Analytics, Searching, Translation, Automation, and Challenges

 

  • Track II: Patenting AI Technology
    • AI inventorship / authorship
    • Patentability requirements for AI inventions

  • Track III: AI for Patent  Practice & Scholarship
    • AI for patent prosecution analytics
    • AI for patent portfolio analytics
    • Machine learning for patent / trademark text

Schedule coming soon 

Workshop Objectives

Our objectives are to build a stronger community of researchers, to find synergies among related approaches and alternatives, and to promote opportunities for collaboration.

We invite paper submissions on research and tools involving AI and patents. Student submissions are welcome.

AI & Patent Processing Motivation

The world’s patent offices must process large volumes of patent applications every day. Moreover, patents are increasingly of interest to numerous industries beyond traditional technology sectors. Many companies, universities, and government entities own portfolios of hundreds or thousands of patents. Extensive amounts of patent data must be assessed when the jurisdiction’s patent office examines pending patent applications, when judges preside over patent litigation, when companies decide what types of R&D they want to invest in, when companies decide what types of technology they want to license, when patent owners determine whether to sue competitors for patent infringement, and when companies assess how to avoid infringing patents.

There are millions of existing patents documents, and each year 300,000 new patents are granted in the U.S. alone. There are a wide variety of patent tasks that remain primarily manual, requiring patent attorneys and patent examiners to filter and analyze huge amounts of data, thereby consuming valuable time, money, and other resources. Artificial intelligence (AI) has tremendous potential to facilitate the processing of patent documents and related patent data. 

Intended Audience

Patent practitioners, legal scholars, economists, AI / NLP researchers, patent office representatives, and industry software developers

Organizers and Program Committee

  • Dean Alderucci, Carnegie Mellon University
  • Sean Tu, West Virginia University College of Law
  • Jerry Ma, United States Patent & Trademark Office
Please email your submissions and requests for further information to Dean Alderucci