It’s not surprising that we’ve experienced an explosion in artificial intelligence (AI) patent activity over the past several years.
As recently as 2016, the United States Patent & Trademark Office (USPTO) issued less than 1,000 AI-related patents.
[1] By 2019, that number rose to over 3,300, and we are on pace for more than 5,000 AI-related patent grants in 2020.
As this explosion has occurred, so have interesting questions concerning patentability, inventorship, ownership, and disclosure issues.
To address these (and other) concerns, the USPTO launched its Artificial Intelligence Initiative in 2019, engaging the innovation community and experts to determine whether AI required any changes to the U.
S.
Patent system.
In response to requests for public comments on these topics, the USPTO received comments from 43 organizations, ranging from domestic and international patent/IP bar associations to companies such as Ford Motor Co.
and Merck, and also from 55 individuals.
[2] Patent Protection Should Be Awarded to the Individuals and Entities Developing AI Technologies googletag.
cmd.
push(function() { googletag.
display(div-gpt-ad-1439400881943-0); }); At the highest levels, new AI technologies and technologies incorporating AI should be eligible for intellectual property protections.
The incentive system of the U.
S.
intellectual property regime rewards innovation and investment in development of new and useful technologies.
In this sense, AI is no different from many transformative technologies that came before AI.
Accordingly, there was general consensus that non-human entities—such as AI machines—should not be afforded inventorship status nor allowed to “own” patent rights.
The most common arguments include an AI machine’s lack of ability to conceive, inability to perform inventive steps independently, and the notion that AI is akin to a process or tool used to create a new product or result.
Underlying these arguments is the notion that if AI machines were allowed to be named as inventors and/or owners of patented technologies, it is possible that the entities funding that development would be denied the benefits of those investments.
Through our present system of traditional employment and IP transfer agreements entered into by natural persons, entities funding and supporting research typically obtain ownership and enforcement rights to those persons’ discoveries.
Allowing AI machines to qualify as inventors or owners of IP would turn this system on its head.
Along these lines, the USPTO—like the UK and EU Patent Offices—recently ruled in the highly anticipated “DABUS” application, identifying the inventor as an AI machine, that inventorship is limited to natural persons.
While the USPTO does not address this issue of liability for patent infringement, it seems clear that at least initially, it will similarly attach to natural persons and legal entities; entities will not be able to evade liability by suggesting “my AI machine did it.
” AI Technology Requires No Major Changes Necessary to U.
S.
Patent Laws Most comments suggested that no major changes to the patent laws are necessary to address issues raised by AI technologies.
One group of commenters espoused the view that the patent laws have accounted for major technological shifts in the past, and there’s no reason to think that AI will be any different.
These commentators likened AI inventions to software and computer inventions, commenting that the same eligibility impediments may arise and noting the USPTO has issued recent guidance to address issues such as subject-matter eligibility and functional claiming for computer-implemented inventions.
Another group of commenters took the position that AI technologies are still developing and that it’s too early—and perhaps entirely unnecessary—to modify existing statutory and regulatory regimes.
Submissions varied with respect to the USPTO’s more detailed questions regarding AI’s impact on patent disclosure requirements.
For instance, a majority of organizational submissions did not see unique enablement or written description issues arising from AI technologies.
However, the impact of AI on the “person of ordinary skill in the art” (or POSITA) raised substantial debate.
A primary concern centers on the ability of AI technologies to drastically expand the knowledge of a POSITA by identifying and reviewing vast amounts of data and information during the training/development process.
As humans rely more on AI, it is easy to see that a POSITA may have greater access to information, thereby potentially rendering more inventions unpatentable as obvious.
These are issues to watch as technology and the law evolve.
In sum, the public comments responding to the USPTO show that we are still in the infancy (or at least the toddler phase) of AI development.
As AI continues to evolve, the above discussed issues may crystallize into a need for statutory or regulatory change, but we are not at that point yet.
[1] Data provided from Advanced Search at uspto.
gov (http://patft.
uspto.
gov/netahtml/PTO/search-adv.
htm) using the following search terms: “artificial intelligence” or “machine learning” or “machine intelligence” or “neural network” or “deep learning” in either the abstract or claims.
Data was parsed for patents granted during each calendar year.
Data for 2020 covers January 1, 2020-June 30, 2020.
[2] https://www.
uspto.
gov/initiatives/artificial-intelligence/notices-artificial-intelligence About the Authors Daniel J.
Schwartz is a partner in Nixon Peabody’s Intellectual Property group, focusing his practice on patent, trade secrets, trademark, copyright, and licensing disputes.
He has litigated cases involving a wide range of technologies, including chemistry and chemical engineering technologies, 3-D vision technologies, wireless communications protocols, among others, in federal courts and before the U.
S.
Patent and Trademark Office.
Paulina M.
Starostka is an associate in Nixon Peabody’s Intellectual Property group who focuses her practice counseling clients through disputes involving patents, trademarks, copyrights, and trade secrets in federal courts and in Section 337 investigations before the United States International Trade Commission (USITC).
She also advises clients on trade-related matters before the Court of International Trade and the USITC.
Sign up for the free insideBIGDATA newsletter.
.