Recently, an Artificial Intelligence (AI) named DABUS (“Device for Autonomous Bootstrapping of Unified Sentience”) made international media buzz when it was listed as an inventor on patent applications filed in the United States Patent and Trademark Office (USPTO), United Kingdom Intellectual Property Office (UKIPO) and the European Patent Office (EPO). While there have been thousands of patent applications for various AI systems, from machine learning (ML) systems, to neural networks, generative adversarial networks (GANs) and beyond, this is at least one of the first AI systems to be listed as the inventor itself.
What is DABUS
Developed by Stephen Thaler, a well-known expert in the field of AI, DABUS is an implementation of a type of generative adversarial network (GAN), where two or more neural networks are used to play against one another in order to improve the outputs of at least one of the neural networks to create something different and new.
In the most common implementation, a GAN comprises two neural networks. The first is a generator, which is used to generate new data (e.g., images, text). The second is a discriminator, which is used to determine whether the data generated by the generator is real or fake.
In order to determine fakes, the discriminator is given a (preferably large) dataset of real data to compare the data generated by the generator against. Like a high-tech game of cops and robbers, the discriminator is trying to identify the fake data provided to it from the generator. Each time the generator fails to convince the discriminator of the validity of its generated data, it learns. This process is repeated at the incredible rate that computing does these days. The results, can be stunning. In fact, a piece of artwork generated by such GANs recently sold at Christie’s for $432,000.
DABUS operates on this same principal. Give a dataset to a discriminator as a training model and let the generator try to fool the discriminator. Now, of course, Dr. Thaler uniquely calls his generator an Imagitron, and his discriminator a Perceptron, but ultimately it is still a GAN, doing what a GAN does.
What did DABUS “Invent”
Without getting into the debate or hype over what was actually “conceived” by DABUS, the actual products that were more aptly described as “designed” by DABUS are: 1) an interlocking food container; and 2) a light that flashes in a particular way that mimics neural activity. I do not intend to go into the details of these inventions, as they have been discussed ad nauseum elsewhere.
Regardless of what DABUS designed, the inventions themselves were based on datasets and information provided to it. As was said excellently elsewhere, “[DABUS] was ‘mentored’ by Dr. Thaler over a two month period to produce increasingly complex concepts.” Put differently, DABUS did not set out on its own to solve the problem of interlocking containers or calming pulsating lights; rather, DABUS was tasked with solving these concerns.
The Patent Applications
The three patent applications were submitted by a group led by Ryan Abbott, a professor of law and health sciences at the University of Surrey in the United Kingdom. Not unsurprisingly, a novel question of law has been raised by an academic. And that is not a criticism, but rather an acknowledgement that patent law will have to address certain pressing questions about the patentability and ownership of inventions in a world that is increasingly being influenced by artificial intelligence and its effects.
The question at issue here is whether, given the “creative” output of DABUS qualifies it as an “inventor” under the laws of the patent offices the applications were filed in. For instance, in the USPTO, the Manual for Patent Examining Procedure defines an inventor as a person who contributes to the conception of the invention.
Here, Dr. Abbott and his team are suggesting that DABUS, through its processing of the data into a useful invention, contributed to its conception in such a manner that it would have to be considered an inventor under that definition. Others, such as Dr. Noam Shemtov, state that DABUS, and other AI systems are merely tools. In a 2019 report commissioned by the EPO, Dr. Shemtov writes:
When it comes to a human actor that uses an AI system, whose identity may be inconsequential to the invention process, who simply uses a machine learning technique developed by another, the inventor may be the person who “tooled” the AI system in a particular way in order to generate the inventive output. Hence, under such circumstances the person that carries out the intelligent or creative conception of the invention may be the one who geared up the AI system towards producing the inventive output, taking decisions in relation to issues such as the choice of the algorithm employed, the selection of parameters and the design and choice of input data, even if the specific output was somewhat unpredictable[i].
While I tend to agree with Dr. Shemtov’s analysis of current AI systems as tools that individuals use to provide useful output, that is not to say that it is impossible to conceive that an AI system in the future will able to identify a problem, identify available materials/components/data, and solve the problem on its own, all without human intervention or direction. And herein lies where Dr. Abbott’s filing of the patent applications with DABUS as an inventor is truly aimed at addressing – AIs as inventors.
Dr. Abbott’s true intention appears to be raising the debate over whether current statutory regimes at the various patent offices would allow for an AI to be listed as an inventor, given that even at present, it could be rationalized that the AI is part of the conception of the invention. However, in the case of DABUS, it seems that there is a strong argument that the conception was at the hands of Dr. Thaler, and DABUS merely reduced the invention to practice.
Regardless, the issues related to having an AI system as an inventor are definitely worth bringing to light. Dr. Abbott told BBC News, “These days, you commonly have AIs writing books and taking pictures – but if you don’t have a traditional author, you cannot get copyright protection in the US.” And Dr. Abbott is not incorrect. The United States Copyright Office published an opinion in 2014 stating that, “[O]nly works created by a human can be copyrighted under United States Law.”
Dr. Abbott continued, stating to BBC News, “So with patents, a patent office might say, ‘If you don’t have someone who traditionally meets human-inventorship criteria, there is nothing you can get a patent on.’ In which case, if AI is going to be how we’re inventing things in the future, the whole intellectual property system will fail to work.” And again, Dr. Abbott is not incorrect. 35 U.S.C. § 100 defines an “inventor” as the “individual” who invented or discovered the subject matter of the invention. If an AI system conceived of both the problem and the inventive solution to that problem, it becomes more difficult to say that the inventor of the AI system itself was the inventor of that invention, leaving that IP unable to be secured by patents under the current regime.
Similar inventorship issues arise in both the UK, where the UK Patents Act of 1977 requires an inventor to be a person, and the EPO, where in the EPO’s published opinion written by Dr. Shemtov states, “[I]t has been shown that is is unambiguously implicit that AI systems cannot be identified as inventors.”
All three patent offices where these DABUS patent applications have filed are aware of the issue and are reviewing options and requesting input from the community. In fact, On August 27, 2019, the USPTO just released a Request for Comments on Patenting Artificial Intelligence on the Federal Register, asking for input on whether current US patent laws need to be revised to take into account inventions where an entity or entities other than a natural person contributed to the conception of an invention.
While lofty news articles have hyped the filing of these patents in DABUS’s name, let us not fall for the smoke and mirrors associated with the current state of AI systems. At least in the vast majority of existing AI systems, they are not inventors as we define them for the purpose of patents in the US. They are advanced tools that assist in the reduction to practice of inventive concepts and inventions themselves. DABUS is not an inventor for the purpose of US patent law. However, using the leverage and momentum of a good news cycle, DABUS has been able to push forward the conversation on what will inevitably be questions about ownership and protection of all forms of Intellectual Property generated by AI systems in the future.