The EPO generally likes applicants to abide by the Articles and Rules of the EPC. It is therefore not surprising that the Receiving Section of the EPO has refused the recent European patent applications designating an AI inventor for contravening the provisions on inventor designation (Article 81 and Rule 19 EP).  The refusal followed a mere 16 minutes of deliberation at an EPO hearing in Munich.

IPKat reported on the AI inventor patent applications earlier this year (IPKat: The first AI inventor - IPKat searches for the facts behind the hype). Dismissed as a publicity stunt by some, the team behind the European, UK and US applications have defended the applications as an attempt to address the moral issues arising from inventions for which no human inventor can be ascribed. However, it is clear from the Minutes of Oral Proceedings (and preliminary opinion), that the EPO was not convinced that the human applicant (Dr Thaler, inventor of the AI) had satisfactorily demonstrated how he had derived the right to the applications from the AI. Important questions also remain as to whether the AI can truly be said to have invented, and whether the whole debate is decades too premature.

Ownership is what matters in European patent law

One crucial issue of AI inventorship is how the applicant can be said to derive the right to a patent from the AI. How can an AI assign such a right? The Receiving Section stressed that the EPO does not investigate whether the designation of an inventor is correct (Rule 19(2) EPC). However, an applicant for a patent who is not the inventor is required to state how they derived the right to the invention from the inventor (Article 81 EPC). The team behind the AI inventor applications have always maintained that the applications are owned by the inventor of the AI, Dr Thaler, and not the AI itself. But how does Dr Thaler derive this right?

Dr Thaler, initially indicated that he derived the rights to the invention from the AI inventor as the AI's employer (a claim that raises certain philosophical questions in and of itself). The EPO did not accept this as a valid derivation of right, and Dr Thaler tried again by claiming that he was the successor in title of the AI as the AI's owner. However, as the Receiving Section noted in the preliminary opinion: "machines do not have legal personality and cannot own property...a machine cannot own rights to an invention and cannot transfer them within a employment relationship (as proposed by the applicant on 24.07.2019) or by succession (as suggested by the applicant on 02.08.2019)".

Chappie: Artificial General Intelligence employee (and most underrated movie of 2015)

It seems that the EPO can therefore neatly dismiss any need for detailed discussions on the morality of AI inventorship, so long as the AI inventor is not also claimed to be the owner of its creations. It has always been this Kat's view that the whole exercise of the AI inventor applications is slightly irrelevant given that what primarily matters from a legal standpoint is who owns an invention, and who should therefore be awarded the patent.
The written decision is expected early in the new year. IPKat has learned from Professor Ryan Abbott (University of Surrey and key member of the "AI inventor" team) that Dr Thaler plans on appealing the decision.

Has the AI actually invented?

As already mentioned, the EPO does not investigate whether the inventors named on a patent application really are the inventors (Rule 19(2) EPC). The question of whether the AI really did invent the fractal food container and fractal light signalling inventions that are the subject of the applications is therefore not one that the EPO will attempt to answer. However, it is worth remembering that the team's claims about the AI inventor are extraordinary.

An AI that is truly capable of inventing will be capable of reading and understanding the prior art, finding a problem to be solved, finding a novel and inventive solution to the problem and then communicating that solution in a way that is understandable to a skilled person. An AI capable of such a complex collection of tasks would have a close to a human level of intellect, i.e. an artificial general intelligence (AGI). An artificial general intelligence is a 20 year goal of companies like Google DeepMind and Google Brain. Dr Thaler has, in fact, argued that his algorithm "paves the way for sentient AI since it teaches how machines may generate the equivalent of subjective feelings...It is expected to be the successor to deep learning and the key to achieving human level machine intelligence. It will be used to build highly transparent and self-explanatory synthetic brains to achieve so-called “Artificial General Intelligence” (AGI)" [Merpel: someone needs to tell Demis Hassabis...]. A summary of the incredible abilities of Dr Thaler's AI can be read on his website.

So far, however, the precise details of how the AI performs the inventive act have not been published and remain distinctly vague. It seems likely (at least to this Kat) that Dr Thaler's AI may have more limited abilities than are enthusiastically propounded by the team. This raises the question of whether the AI is, in fact, no more than a tool whose abilities can be equated to other types of technology.

At the recent Life Science Patent Network (LSPN) London conference, this Kat had the pleasure of participating in a panel discussion with Professor Ryan Abbott on the topic of AI inventorship. Professor Ryan Abbott made a plea for the importance of the moral and social issues surrounding AI inventorship. However the Professor did not seem to address the question of how the AI could be said to be different to other types of platform technology, e.g. mouse models.

The central claim of the AI inventor team is that there was no human input in the generation of the invention: "the machine only received training in general knowledge in the field and proceeded to independently conceive of the invention and to identify it as novel and salient". However, the same could be said of a mouse model used to identify novel, inventive and useful antibody therapeutics. The human experimenter provides the antigenic challenge, and the mouse's immune system produces structurally unique, non-obvious therapeutics that are potential suitable for use in humans. The "invention" of the antibody structure could not have been derived by the human experimenter themselves. However, no one is arguing that mice should be inventors.

Are the AI's inventions even novel?

As a side issue, a perusal of the file reveals that the AI inventor may also not be as good at inventing as had been first thought. The two applications claimed a fractal food container (EP 18275163) and fractal light signals (EP 18275174). The team behind the AI have been previously eager to point out that a search by the UK IPO found the claims of the UK application to be novel and inventive. The EPO did not agree with the UK IPO. Both the Food Container and Light Signals invention, as originally claimed, were found to lack both novelty and inventive step (European search opinion). The Examiner cited, for example, US 5803301 as disclosing a beverage container having all of the features of the one allegedly invented by the AI.

Prior to the EPO's decision to refuse the applications because of the inventorship issues, the applicant had submitted amendments and arguments in response to the substantial objections. However, the issue of novelty and inventorship have become redundant in view of the formality issues with the applications.

Final thoughts

If Dr Thaler's appeal of the Receiving Office decision does indeed go ahead, IPKat will await the Statement of Grounds with interest (deadline for filing the appeal will be early 2020). Based on their submissions to the Receiving Office, it seems that the AI inventor team are lacking the legal arguments to overturn the decision. Moral and social arguments are unlikely to convince the Boards of Appeal. A request for a referral to the Enlarged Board can probably also be expected, but is similarly unlikely to be granted. None-the-less, the team have undoubtedly been successful in one goal, bringing attention to Dr Thaler and the team. Notably, we are only able to see the file history because early publication of the applications was requested. However, in this Kat's humble view, the whole argument surrounding AI inventorship is premature until the existence of an AI truly capable of a inventive act has been proved.

Kat friend Rachel Platts provides IPKat readers with a summary of the recent conference on Artificial Intelligence: Challenges for Intellectual Property Law.

On 17 and 18 October 2019, the Academy of European Law (ERA) hosted a conference in Brussels on "Artificial Intelligence: Challenges for Intellectual Property Law". The conference focused on how Artificial Intelligence is, or will impact, on various aspects of IP law.

Day 1, Session 1: Artificial Intelligence at the crossroads

The first presentation, by Robert Kroplewski (solicitor and member of a high-level group of experts on artificial intelligence), discussed the conceptual view of AI and the requirements of the inputs and outputs of such a system. The key take home point from this discussion was the need for AI to be lawful, ethical and trustworthy, all of which will largely stem from the data which are input into the AI system itself. Further discussed was whether there is IP ownership of the data used as the input.

Alain Strowel (Lawyer and Professor of IP and Media Law, Catholic University of Louvain and University Saint-Louis) further discussed the input and output of AI systems, with a focus on the output. What protection is granted to the content generated by an AI system, such as authorship and ownership?

The answer to this question was considered in relation to s178 CDPA--

‘computer generated’ in relation to a work, means that the work is generated by a computer in circumstances such that there is no human involvement’.

The effect on authorship is then considered under s9(3) CDPA--

‘the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken.’

The critical question here is, does AI have human involvement to be granted authorship under UK copyright law? After all, the data which are input into the AI system is usually done so by a human. Strowel was keen to express that he was not in favour of the extension of copyright to cover AI generated works, as it would create too many rights which would ultimately hinder human creativity and innovation.

Cornelia Kutterer (Senior Director, Legal Affairs, Microsoft) discussed AI from an industry perspective and noted some challenges that Microsoft has encountered. The main challenge appeared to be ethics, namely how to make sure that the decisions generated by AI were ethical and fair. Since AI is dependent on the data supplied, if there is discrimination or bias in the data, then AI decisions and outputs may also contain the same discrimination or bias.

Session 2: Protecting Artificial Intelligence through industrial property law

This session, presented by Doris Thums from the European Patent Office, focused on the patentability of AI inventions. Thums raised issues that pose challenges to the patentability of AI inventions, such as obviousness (it may be difficult to define the skilled person). It was suggested that the skilled person can be part of a team, so an AI program could be one of these persons. Further, when considering inventions created by AI, at present the human is not completely removed from the inventive process, such as the inputting data, setting parameters, or combining the results.

In considering whether the EPC and the EPO are equipped to handle the changes which AI and AI-generated inventions may bring, Thums was optimistic. She noted that existing legal norms and their interpretation are adaptable and case law reflects this. The results of case law has a direct impact on practice manuals and examination methods.

Also included in this session was brief input from Taliah Walklett from Nokia (who was quick to dispel common belief that Nokia were no longer around, they simply no longer make mobile phones anymore!), providing an industry perspective on patentability issues. In Walklett’s experience, since AI inventions continue to have a reasonable degree of human input, ownership issues have not arisen in practice. Further, challenges were currently being faced in searching the prior art and how to future-proof patents are being filed now.

After lunch, Vincent Cassiers (Lecturer, UC Louvain) discussed trade secrets in relation to AI under EU law. Discussion centered on the Trade Secrets Directive and how this has impacted on AI inventions, concluding that trying to control the input of AI and the algorithms seemed impractical in the face of the pace of the evolving technology. Instead, the focus should be on an obligation to explain how the processing works and how the decision is taken by the AI to allow transparency.

Session 3: Protecting Artificial Intelligence under EU copyright law

Gerald Spindler (Professor of Civil, Commercial, Business, Multimedia and Telecommunications Law, Göttingen) provided an interesting presentation on copyright law for AI generated creative works. As touched on previously, a key aspect is authorship. Whether copyright can be attributed to an AI generated work will depend on the amount of input from an author/artist in addition to the data input as AI programs are only as good as the data they are trained on.

The level of training which an AI is trained on is a legal ‘grey-zone’. For example, the Rembrandt-project (details here) where an AI program was trained on 346 Rembrandt paintings created an entirely ‘new’ Rembrandt painting. Thus, given the training data was all Rembrandt paintings, was the AI generated work authored by Rembrandt, or the AI?

Session 4: The increasing use of blockchain technologies in the intellectual property world

The last presentation of the day was given by Pascal Asselot (Co-founder and Managing Director of IPwe.com), who focused mainly on the uses of blockchain technology in various IP contexts. The speaker centered on how blockchain would be beneficial in keeping the records systems for trade marks and patents up to date, especially when there have been changes in details or ownership and the information takes a while to filter through the systems. The implication was, with blockchain, this would be automatic.

Day 2, Session 1: Algorithms, predictive decisions and intellectual property law

The second day kicked off with a thought-provoking talk from Florence G’sell (Professor of Private Law, University of Lorraine) on what kind of legal decisions should be delegated to AI; should we have "AI judges" for relatively simple matters? What safeguards should be put in place to ensure that the decisions are ethical and fair?

The concept of algocracy, where decisions are made by AI, machines and code rather than humans, was discussed and whether such decisions would impede human freedom. Algocracy is already filtering into the legal system, for example in Estonia there is a ‘robot judge’ used for small claims decisions.

The next session, by Lee Curtis (partner at HGF Limited), discussed the predictive behaviours of AI when considered in a trade mark context. The key issue raised focused on how AI can affect the purchasing decision for consumers. A brief history of how consumers have chosen products was provided, starting with the 1920’s shop assistants to current predictive shopping models, such as Amazon, which predict what items the consumer wants and provides the information upfront.

The discussion moved on to whether trade mark law was ready for the impact of AI, having regard to core concepts such as ‘imperfect recollection’, ‘phonetic, conceptual and visual comparison’ and ‘confusion’, all of which are very much human behaviours.

Session 2: The use of big data in Artificial Intelligence: between innovation, intellectual property protection and competition law

The last session of the conference was presented by Matthias Leistner (Professor for Civil Law and IP with Information and IT Law at Ludwig Maximilian University of Munich) and Virginie Fossoul (Legal and Policy Officer, European Commission), and discussed the impact of big data and improving access to the data without infringing IP rights.

Leistner commented on whether there would be sufficient creativity in data processed by algorithms (and thus AI programs), such that copyright could apply. Attention was directed to possible limitations and exceptions for copyright protection in light of the Text and Data Mining Directive.

Fossoul commented on the fact that the link between IP and data is not always clear cut or obvious, but that there is a need for IP policy and data policy which is coherent between all countries and member states. At the moment, there is no need for new IP rights specifically in relation to data.

Picture on upper left by Scientus and is licensed under BSDU.

Picture on left courtesy of Rachel Platts.

Picture on lower left by ITU Pictures and is licensed under the Creative Commons Attribution 2.0 Generic license.