Over the past two months, the USPTO has issued an unusually large number of public comment requests related to various proposed rules and procedure changes. This wave of RFCs includes significant proposals aimed at adjusting patent fees for fiscal year 2025, refining terminal disclaimer practices, and addressing the impact of artificial intelligence on prior art and patentability. The agency is also seeking feedback on formalizing the Director Review process following Arthrex and various changes to IPR proceedings, including discretionary review. And there’s more… (more…)
In Bonito Boats, Inc. v. Thunder Craft Boats, Inc., the Supreme Court addressed the issue of state laws that provide additional patent-like rights. The Court held that a Florida law prohibiting the use of a direct molding process to duplicate unpatented boat hulls was preempted by federal patent law. The Court reasoned that the Florida law conflicted with the “carefully crafted” goals of the federal patent system.
The USPTO and Courts have made clear that AI-created inventions are outside of the scope of US patent law. I think the answer is probably quite clear, but do folks think that the Bonito Boats approach would also preempt the states from from creating an exclusive-right award for AI-generated innovations?
The pace of technological advancement never ceases to amaze me, and it seems like even science fiction is struggling to keep up with reality. In recent months, we’ve witnessed some truly remarkable breakthroughs in the field of artificial intelligence (AI), and this latest development is right up there.
Researchers have used GPT-style machine learning architecture to decode human thoughts by analyzing their functional MRI (fMRI) brain scans. That’s right – we’re talking mind reading. The AI was initially trained trained by exposing participants to 16 hours of narrative stories while recording their brain activity. And, once trained, the AI was able to accurately describe the content of their thoughts. Of some interest, the AI was better at identifying concepts and meaning rather than the actual words at issue.
While this technology has the potential to revolutionize communication for individuals with disabilities or neurological conditions, it also raises some privacy concerns that could involve both reading thoughts and writing them.
I imagine that all this wouldn’t require a fMRI technology and instead could rely upon much smaller safe-for-home equipment such as Functional near-infrared spectroscopy (fNIRS) devices shown in the image above or made by Artinis.
A key for me here is that this is potentially moving toward an API for the human mind and body. For those outside the software world, an API (Application Programming Interface) is a set of protocols, tools, and standards that allow different computer applications to communicate with each other. APIs provide a standardized way for software components to interact. An API for the human mind and body would create an interface that allows software systems to access and interact with the brain or and other body parts. Over the past several years, folks have been making huge advances with brain/body connection, and I’m excited about where we are headed in this expanded mind approach.
A few days ago I wrote an essay about the ongoing economic war between the leaders of the US and those of China, with a focus on the impact US attorneys representing Chinese clients. For the article, I used an AI tool to create some art for my publication. The image above shows the resulting four images. I chose the bottom right and had the AI enhance the image for publication by pushing a single button. I then did a cut and paste before publishing.
Although I didn’t contribute any of the expression seen in the work, after these actions and then publishing it, I actually feel some gut level of ownership. And, that I might be upset if someone else used _my_ image without permission.
My questions for you:
Do I deserve to “own” this image?
Should I be able to claim authorship?
Should I disclose my AI creation methodology when I use the image in published works?
I recently was thinking back to 1996 and the start of my senior year at Princeton University. Although I was a mechanical & aerospace engineering major, I had become fascinated with AI and so focused my senior thesis on developing a new AI model within the department of electrical and computer engineering. Instead of employing traditional layers, I utilized a fractal metaphor to design the neural networks. The main theoretical advantage of this approach was its potential to offer a deeper understanding of how the network operated, allowing us to peer into the brain and gain insights into its learning process based on the structure created. Furthermore, the model facilitated greater human control and direction.
This past weekend, computer law expert Van Lindberg reminded me of the Dartmouth Summer Research Project on Artificial Intelligence that had a game plan of solving AI during the summer of 1956. My senior thesis project took 8 months, and met with roughly the same (lack of) success. I’ll write more about this later, but the project was one of the first to use massive parallelism offered by human players across the internet as the learning model. That part was a big success — as well as the Applet front-end developed mostly by my partner Ryan Kotaro Akita.
I feel like things are coming full circle for me, but this time the AI model has improved exponentially. The rapid progress in human-machine interaction and generative AI is astonishing. I find myself constantly exploring new, innovative technologies poised to disrupt bloated organizations. The venture capital landscape is necessarily shifting, as small teams rapidly develop and release disruptive products and services with higher speed but lower financial requirements.
Today’s exploration for me is autoGPT that allows users to stack various traditional and AI services to create the best autonomous assistant that I have seen so far. After being provided with general instructions, autoGPT can generate a dynamic project plan that it executes through online interaction and GPT-4 training results. This technology has the potential to equalize expertise, much like what happened with chess several years ago. However, unlike chess, which relies on a fixed board and finite options, this new model addresses real-time, real-world problems. Indeed, it’s a fascinating time to be alive.
This setup is wonderful but also so scary. Awesome in all senses. The AI is ruthless and without emotion or wisdom. It empowers anarchists, terrorists, and reckless operaters to inflict significant harm. GPT layering enables more sophisticated attacks that exploit a combination of human-social and technological weaknesses in a massively parallel manner. Scams, both big and small, are becoming increasingly easier to execute. Of course, there will be those who use these tools to fight for good. As the battle of technology unfolds, life may begin to resemble a futuristic graphic novel more and more.
After coming up with a core idea for a new product, Inventor jumps on chatGPT and asks the AI to expand upon the product idea, including providing additional design elements based upon the inventor’s original description. ChatGPT comes through with flying colors and provides several detailed designs that inventor had not considered. Inventor is diligent in their disclosure docs to include the chatGPT transcript. Patent search reveals that Inventor’s original idea is not patentable by itself, but it is likely patentable when combined with the chatGPT input. The patent attorney sees value in having claims directed solely to the features provided by chatGPT.
You are the patent attorney, what do you do in this situation?
Petitioners in Thaler v. Vidal ask the Supreme Court one simple question:
Does the Patent Act categorically restrict the statutory term ‘inventor’ to human beings alone?
Thaler Petition for Writ of Certiorari. Only a court with substantial hubris would be willing to take-on this case, but I’m confident that the Supreme Court is up for the task.
The power of AI tools has become viscerally apparent over the past few months and hopefully members of the court have been shown chatGPT or some other generative AI tools that are now widely available (if still quite flawed). We are are now at a point where it is easy to see an AI tool creating inventive output. And, even if recognition of the invention is fundamental to the inventing process, the AI tools certainly provide sufficient contribution to be considered for joint inventorship.
In general, we take an objective approach to patentability focusing on whether the result is a substantial step beyond what was known before and looking for objective evidence within the patent document of sufficient disclosure. Some early 20th century courts had alluded to a potential subjective test, but Congress rejected that in the 1952 Patent Act, writing that “Patentability shall not be negatived by the manner in which the invention was made.” 35 U.S.C. 103. The basic idea here is that we have a public policy goal of encouraging innovation and invention, “promot[ing] the Progress of Science and useful Arts.” And Congress concluded that a key way to get results is to reward results.
In Thaler’s case, the PTO and courts short-circuited the patentability analysis because the purported inventor is a machine, and machines simply are not permitted to be inventors.
The pending case involves a human named Thaler (Dr. Stephen Thaler) who created an “imagination engine” named DABUS. According to thus-far undisputed allegations, DABUS created two inventions and also recognized their utility without any specific guidance from a human. In Thaler’s view, DABUS was the inventor since it was the “individual . . . who invented or discovered the subject matter of the invention.” 35 USC 100(f). But, the USPTO refused to award a patent because the listed inventor was inhuman.
On appeal, the Federal Circuit affirmed — holding that the word “individual” found in 100(f) was properly interpreted as applying only to humans. One oddity of this conclusion is that definition was added in 2011 as part of the America Invents Act, and without any suggestion on record that the amendment was intended to exclude robots or non-humans.
Thaler’s new petition asks the U.S. Supreme Court to take up the case and so some simple statutory interpretation of the word “individual” in context of Section 100(f) and (g). According to Thaler, the statute is designed to focus attention on the entity that actually does the inventing and does not limit its scope to “humans” or “natural persons,” the common mechanisms used by Congress.
Professor Ryan Abbot has been Counsel of Record for Thaler throughout the case. Thaler added Mark Davies and his Orrick team for this petition. Earlier in March, the UK Supreme Court heard oral arguments regarding the UK version of the patent, asking whether “section 13(2)(a) of the Patents Act 1977 (the “1977 Act”) require a person to be named as the inventor in all cases, including where the applicant believes the invention was created by an AI machine in the absence of a traditional human inventor?” The UKIPO Comptroller-General refused the application and that decision was affirmed on appeal. [2021] EWCA Civ 1374.
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Assuming Thaler loses here, the unsatisfying solution appears to be that the owner or user of the AI will simply be claiming rights as the constructive inventor. Thaler has a pending application in the EPO suggesting himself as the inventor as owner of DABUS. This approach substantially stretches the law of inventorship. In the U.S., limitations on challenging inventors mean that many inventive entities can de facto stretch the notion of inventorship without getting caught.
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If you are interested in supporting Thaler’s position, brief in support will be in about 30-days. (Depending upon the docket date, that has not been released yet).
Associates around the country today are drafting motions, patent applications, and other documents using some version of ChatGPT. Of course, If I were a judge or examiner, I might also be interested in using AI to help facilitate my decision-making. ChatGPT is good for that as well and can provide a reasoned structure, including identifying of prior art and obviousness standards.
If you recall your last writing course, the professor repeatedly focused attention on the audience. “Who is the audience you are looking to persuade?” Moving forward, it appears that we really do have a new audience for our writing — AI advisors. This calls to mind the great tape recorder scene from Real Genius (1985). Members of the class began just leaving tape-recorders to record the boring lecture; eventually, the professor also just brought in his own taped lecture to speak to the machines.
Automated Examination: On the patent prosecution side, we may shortly be in a situation where AI systems will be able to conduct patent examination at the same level of quality as a typical human examiner. It seems obvious that we should rely upon the AI to at least facilitate examination. The bigger question is whether to eliminate the first-level human bureaucracy all together and move to an automated examination system. The benefit of that process is that it could be done very rapidly (immediate allowance / rejection) and potentially at a much lower cost. Certainly, PCT systems could move toward substantially lowering costs with initial search reports and examination being done automatically.
