Artificial intelligence (AI) is set to transform many aspects of our lives, including our home and health. AI is already widely used in internet searches, and home devices with speech recognition, but in the near future we will see AI become even more widespread. This will have significant repercussions as AI performs many tasks that until now could only be undertaken by humans. AI will remove human intervention from much of the picture. This will particularly affect intellectual property law.
Likewise, numerous questions are arising regarding the patentability of innovation in and arising from AI that have not been previously addressed. Can AI systems patent their inventions? How does the doctrine of equivalents apply to AI inventions? Will the 'person skilled in the art' change?
There is a vast array of issues related to seeking intellectual property protection for AI and machine learning systems. As French lawyers, it appears to us that the process of protecting AI is similar to making wine, since a good wine requires quality grapes and time to mature. The same requirements apply to AI protection.
Fortunately, many tools, such as patents and copyright, are available to help companies protect their intellectual property rights (IP) in France1. The French Patent and Trademark Office (INPI) has recognized the growing need to clarify the rules on how inventions related to and made by AI will be handled, and to determine what patent protection exists for this technology. The recent amendment of the Guidelines by the INPI2 is a clear sign that France does not want to lag behind in dealing with the rapid developments in AI.
Under French law, programs for computers are not regarded as inventions. Applicants will sometimes avoid mentioning AI in their patent application to avoid the exclusion of their computer programs. However, the ethos is changing and a French patent might protect innovation generated artificially by AI when the following requirements are met: A patent shall be granted for any invention in all fields of technology, on the condition that it is new, involves an inventive step, is capable of industrial application and is not subject to a prohibition of patentability. These requirements are explored in more detail below:
- The debate surrounding AI inventorship is premature until the existence of an AI truly capable of an inventive act has been proved. However, we would point out that the European Patent Office (EPO) has refused two European patent applications3, in both of which a machine was designated as inventor, on the grounds that they did not meet the requirement of the European Patent Convention that the inventor designated in the application has to be a human being, not a machine. Both patent applications indicated “DABUS” as inventor, which is described as “a type of connectionist artificial intelligence”. We can therefore imagine that the INPI will, for the time being, follow the same reasoning for Aaron, Emi and Adam4.
Nonetheless, in the future AI is likely to contribute to invention, especially by enabling more collaborative innovation, and therefore patent filing strategies should be created and implemented.
- Novelty might be an issue, since AI and machine learning will certainly use information previously obtained or disclosed to generate innovation. In other words, AI may improve but cannot change common general knowledge.
- If novelty is established, examiners will assess from April 2020 whether the claimed subject matter is inventive. To assess an inventive step, the revised guidelines by the INPI suggest that AI and machine learning inventions would be eligible for patentability if their application in a particular field contributes to the technical character of the claimed invention.
- Thus, inventions relating to AI and machine learning systems must demonstrate that the claimed subject matter serves a technical purpose. At a minimum, the claimed invention should provide a technical effect that is more than simply a way of achieving the solution to a problem more quickly. Achieving the technical effect should not be reliant solely on the AI or machine learning system; both are, arguably, well known and have expected outcomes, at least in the sense of providing improvements. Nevertheless, where AI or machine learning systems are used, the application should comprehensively describe its detailed implementation, both functionally and structurally.
- The 'person skilled in the art' will be also a huge issue. At first glance, we assume that the INPI12 will consider that the person skilled in the art of AI and machine learning systems is likely to be multidisciplinary, and will therefore include scientists, engineers and/or computer scientists. Hence, the person skilled in the art is correspondingly likely to be a similarly composed team. The common general knowledge of the person skilled in the art in this field includes pre-processing data, setting parameters (such as for training and selecting validation data) and experimentation.
- The same reasoning could be followed for the sufficiency of disclosure allowing the reproduction of the invention. For a patent to be granted, there is no need to describe how Aaron, Emi or Adam arrived at this invention, or to explain their reasoning. To meet this requirement, it is sufficient to describe how the invention was conceptualized so that the person skilled in the art can reproduce it. These solutions may appear in the medical field, e.g. identification of new molecules that may have a therapeutic effect; in the mechanical field, e.g. identification of a particular profile of an aircraft wing with a strong lift or drag coefficient; or in any other technological field.
- When it comes to enforcement, evidence of the act or acts of infringement is clearly another challenge. Due to the nature of the innovation, it is difficult to demonstrate how exactly the AI worked and how it is reproduced by a competitor.
AI is everywhere but is only at the beginning of its development. From the music industry, through medical innovation and security/defense, to aeronautics, there is a real need for building trusted AI for industry. In order to avoid a "black box" AI legal regime, the criteria for protection must be precisely defined, both for AI instruments and for AI results.
As of now, there is a legal framework under French law available to try to protect some inventions and/or creations generated by AI. It is therefore important for companies to determine the value of their IP assets. French patent and copyright law must evolve to catch up with the evolution of AI. Companies should keep in mind that technological advances are often years ahead of legislative change. As a result, when building a portfolio of AI patent assets, companies should take a strategic approach, with the assumption that the current legislation will certainly change.
Likewise, it is important to identify if the innovation relates to (i) core AI, where the challenge is that it could refer only to algorithms (mathematical methods), or (ii) AI as a tool with technical effects.
A French patent lasts 20 years from its filing date, so that substantial changes may occur during the term of its enforceability. Consequently, it is advisable that companies have a long-term AI divisional filing strategy, which focuses on protecting the implementation of the generic AI algorithm and its purpose.
- Unlike copyright or patent law, trade secrets are not real property rights.
- Patent Guidelines, INPI, October 2019, "The issue of patents and utility certificates", p.74.
- Refusal of EP 18 275 163 and EP 18 275 174 by the European Patent Office ("EPO") on the 20 December 2019 (publication of the minutes of oral proceedings on 20 December 2019): "The applications are refused in accordance with Article 90(5) EPC since the designations of inventors filed for each of the applications do not meet the requirements of Article 81 and Rule 19 EPC".
- Aaron, Emi and Adam are names of AI systems.