Where We Are on AI Inventorship and Where We Should be Heading

“It is likely a matter of time until an AI will be able to simulate human thought, think creatively, and independently identify and solve problems…. If current laws remain unchanged…the owner of the AI-generated IP can and likely will attempt to protect AI-based inventions as trade secrets to the extent possible.”

AI - https://depositphotos.com/236313962/stock-photo-cyber-law-internet-law-concept.htmlThe past few years saw a meteoric rise of artificial intelligence (AI) products, services, and applications. AI has evolved from merely a buzzword or a cool new idea to a substantively used tool in a variety of applications, including autonomous driving, natural language processing, drug development, finance and cybersecurity among others. Companies, universities, and inventors world-wide noted the importance of AI and began seeking to patent various aspects of AI technology. Until 2018, these patent applications identified a human inventor who invented a particular aspect of the AI technology. Then, Dr. Stephen Thaler filed a patent application for a food container and a light emitting device that identified an AI, known as DABUS, as an inventor.

Dr. Thaler’s DABUS application became a poster child for what is now a worldwide question: can AI be an inventor, at least with respect to a patent application? The DABUS application was initially filed under the patent cooperation treaty (PCT) and is now being examined in more than a dozen countries, with divergent results. To date, only South Africa has granted a patent on the DABUS application. Australia presents some promise. There, the Australian Federal Court rejected the patent office’s initial denial and ordered the office to examine the DABUS application on its merits. On the other hand, in the United States, United Kingdom, Germany and European Union, the courts have rejected the DABUS application, holding that AI cannot be an inventor. Most recently, the England and Wales Court of Appeal upheld lower rulings that the DABUS applications were deemed to be withdrawn, but the three judges were split, with the two patent specialists on the panel taking different views.

Defining an Inventor

A basic reason for these disparate decisions is how the term “inventor” is defined by statute. South Africa and Australia reached a result favorable to the DABUS application because their laws do not exclude a non-human, e.g., AI, from being an inventor. The laws of the United States, United Kingdom, and Europe, on the other hand, require the inventor to be human. This is because the inventor engages in the mental step of conception which, according to respective patent offices or the courts, can only be performed by a human.

Proponents of IP rights in the United States believe that international consensus of strong IP protections is vital to technological growth. After all, the United States Constitution grants inventors a limited monopoly to make, use, and/or sell their inventions in exchange for disclosing these inventions, in full, to others. This limited monopoly is an impetus driving innovation.

One might ask: are there immediate ramifications to technological growth if AI cannot be named as an inventor? Unlikely.

AI is Still a Tool

Although AI has become more and more advanced over the years, AI is still far away from inventing meaningful technological improvements and itself driving innovation. AI today is incredibly good at performing tasks, computing and parsing data, finding patterns, determining trends, and identifying solutions. All these tasks, however, are based on training the AI on previous examples, datasets, and patterns to solve for like outcomes. This is true across various AI industries. Cars are capable of driving autonomously because the AI component of these cars has been trained on data recorded over millions of driven miles. By the same token, AI can use natural language processing to summarize text, translate documents, and even chit-chat because it has been trained on millions of documents, question-answering datasets and previous conversations. AI can identify protein sequences and drug formulations, identify financial fraud, or diagnose cybersecurity attacks because AI has been trained to identify those patterns. There is even research in AI writing executable programing code from a proposed business case. Notably, all these tasks require human involvement, oftentimes significant. A human being designs the AI, trains the AI, and verifies when the AI produces a result. Due to advances in computing power and available training data, the AI can perform these tasks faster, more accurately, and better than humans.

AI today excels in performing tasks, yet it is still deficient in creative thinking, abstract and original thought, and identifying problems and undefined corresponding solutions. These deficiencies are, according to some jurisdictions, the hallmarks of inventorship. Until AI can transcend these limitations, it will remain a tool, rather than an inventor.

The Law Must Think Long-Term

This begs the question: are there long-term impacts to technological growth if AI cannot be named as an inventor? Definitely.

It is likely a matter of time until an AI will be able to simulate human thought, think creatively, and independently identify and solve problems. At this point, AI is likely to satisfy the current definition of what it takes to be an inventor. If current laws remain unchanged, and the AI cannot be an inventor, the owner of the AI inventions would not qualify for IP protections. The owner would need to decide whether AI inventions are even worth the cost of investment, regardless of the potentially immense benefit they could offer. The owner of the AI-generated IP can and likely will attempt to protect AI-based inventions as trade secrets to the extent possible. Alternatively, pursuing and concentrating on innovations where AI is not an inventor is another option. This will certainly impede technological growth.

One Thing Certain: We Need Certainty

AI is still in its infancy. DABUS has brought the AI inventorship issue to the forefront worldwide, marking this a good time to ponder, debate, and reach international consensus on whether and under what circumstances an AI can be an inventor. One potential solution is to pass statutes stating that AI cannot be an inventor. Another is to treat AI inventions as legal persons, similar to how corporations are treated now. Regardless of which solution is reached, it is clear that IP owners need more certainty on the issue from the courts or governments—or both.

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David McCombs

David McCombs

is primary counsel for many leading corporations in inter partes review (IPR) and is regularly identified as one of the most active attorneys appearing before the Patent Trial and Appeal Board (PTAB). His clients benefit from his 35 years of practice, which include appellate argument, patent litigation, and portfolio development.

David McCombs

Eugene Goryunov

is a partner in the Intellectual Property Practice Group in the Chicago office of Haynes and Boone and an experienced trial lawyer that represents clients in complex patent matters involving diverse technologies. He has extensive experience and regularly serves as first-chair trial counsel in post-grant review trials (IPR, CBMR, PGR) on behalf of both Petitioners and Patent Owners at the USPTO.

David McCombs

Dina Blikshteyn

is a counsel in the Intellectual Property Practice Group in the New York office of Haynes and Boone. Dina’s practice focuses on post grant proceedings before the U.S. Patent and Trademark Office, preparing and prosecuting domestic and international patent applications, as well as handling trademark and other IP disciplines. Dina is also a co-chair of the artificial intelligence practice at Haynes and Boone.

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