In a new world of AI, and in light of AI policy being developed in a myriad of areas, we must not forget to determine how to reward and encourage innovation that derives from AI sources….
The first patent in human history was awarded in England in 1331, and in the 15th Century, many European nations began to use them, such as Florence who granted a patent for a marble carrying barge. The inventor of this vehicle was the first owner of an idea. In the 18th Century led by the United Kingdom and soon others such as the United States what we now understand as the patent system formed, and gave inventors incentives to disclose to the world their inventions in return for a monopoly period.
The ever-evolving legal framework governing the protection of inventions has played a crucial role in developing medicines and novel technologies across sectors. Modern patent law permits software to be patented. This has led to a revolution in innovation and catapulted humanity into the age of the knowledge society. The next frontier is to determine whether the owner of software or author of an algorithm can own the inventions by those electronic products.
Machine learning and the broader term artificial intelligence (AI) are the hopefuls of tech companies striving for more automation, tailored solutions, and faster research. While companies invest nearly 50 billion US Dollars on AI, there’s still a lack of clarity on how to protect the fruits of their inventions. Current patent law states fairly straightforward that inventions can only be made by humans. Bruce Love of the Financial Times describes this as ‘Things cannot invent things.’
Current patent law does not allow corporations to be the inventors of things but allows them to own patents. The challenge of AI inventing new ideas, technologies, and even drugs is that international patent law did not foresee that anyone but humans would have the actual cognitive capacity to create something inventive, and only humans would need recognition in a system designed to reward such ingenuity.
Recently, this focus on the human inventor has been tested: In 2018, several patent applications were filed in the name of Dr. Stephen Thaler for inventions purportedly invented by an artificial intelligence (AI) named DABUS (Device for the Autonomous Bootstrapping of Unified Sentience). On the grounds that DABUS independently conceived of the inventions, and that no human inventor could be identified, the applications list DABUS as the sole inventor.
Formal inventorship requirements vary across different jurisdictions, but the USPTO, the EPO and the UK IPO have all rejected the possibility that DABUS can be named as an inventor on the patent applications, reaching the common consensus that, under current legislation, an inventor must be a ‘natural person’ for the purposes of a patent application.
The question of whether an AI can be an inventor is not merely academic, but part of a broader point about AI inventions and their commercial reality. Being an inventor conveys certain legal rights, and is integral to the concept of patent ownership. Under the UK Patents Act 1977, the right to grant of a patent belongs first to the inventor. An AI has no legal personality and if it invents then no one has a right to the invention as a patent.
Whether the law requires an update is a question that has garnered increasing attention in with the UK government opening a consultation on the matter in September 2020, and a third WIPO session on Intellectual Property and AI scheduled for November 2020. The level of interest is understandable when we consider the history of patents, the public policy rationale and the ‘patent bargain,’ which grants a 20-year patent monopoly to an inventor for two reasons: (i) To have inventors share what they learn, so others coming after them can build on their ideas; and (ii) to reward investment in research. As we have seen, the starting place for the grant of a patent has so far been the human inventor, the ‘natural person,’ albeit a company can then own and exploit the patent. However, as the DABUS cases show, the questions we need to be asking now are: Does it matter if there is no human inventor? What does it mean for investment and transparent sharing of learning, if a company cannot obtain a patent because the inventor was an AI?
These questions may not seem that pressing at the moment, so far there has been no outcry that businesses are failing to obtain patents because of arguments concerning AI inventors. However, an inability for a company to see a return on its investment in research is likely to change the business interest in these questions quickly. If this happens, policy makers will have to consider the patent bargain, and grapple with questions such as: If patents for AI inventions generated by AI are not available, will businesses stop publicly sharing their knowledge and/or struggle to obtain investment, and is that a problem? Does the cost of development of using AI warrant patent protection, or are inventions generated by is AI based on a comparatively cheap form of research that shouldn’t be afforded the same protection as other inventions? Is financial investment in research worthy of policy protection at all, or is it the human endeavour which we seek to reward? In particular, policy makers will have to decide what the purpose of the patent system is and whether, on balance, there is a sufficient policy reason to change it.
With humanity being at the brink of a new age and about to unleash a massive acceleration in our innovative potential thanks to artificial intelligence development, we must ask if it is time to update our patent laws. Without reflecting the fact that machines and algorithms have inventive capabilities we might miss out on investments and innovations that can elevate all of mankind. Think of algorithms that might only need days to find a vaccine for a new virus, smarter law enforcement methods, or programs that help us understand interstellar travel better than we could have ever imagined.
In a new world of AI, and in light of AI policy being developed in a myriad of areas, we must not forget to determine how to reward and encourage innovation that derives from AI sources.
Originally published here.
