Patenting Algorithms in an Internet of Things (‘IoT’) and ArtificialIntelligence (‘AI’) World: Pathways to Harmonizing the Patentable
Subject Matters and Evaluation of the Novelty Requirement *Invited Researcher: Sabine JACQUES * *Constituting a disruptive technology, Artificial Intelligence (‘AI’) is impacting allindustries. However, there are rising concerns that the patent system may not be fit
for the future of innovation that is increasingly AI-related and intangible. Indeed, theexecution of AI-related inventions requires some kind of computer implementation,
thereby potentially reviving patentability issues related to computer-implementedinventions. Whilst patent offices around the world have found ways to adapt theirpatent systems to grant protection to software, difficulties remain in relation toalgorithm-based inventions though they form a significant part of today’s innovation.
Currently, algorithms themselves do not qualify as patentable inventions. Even if
algorithms overcome this first hurdle, concerns arise in relation to the application ofpatentability requirements such as novelty where national differences remain. This
research evaluates the adequacy of the novelty requirement in relation to AIinventions where many of the underlying concepts and technologies are not novel. The
ultimate aim is to evaluate the adequacy of the patent system by looking at inventions
that utilize AI, with a particular focus on the excluded subject matters and the novelty
requirement. To this end, the research adopts a comparative analysis of these concepts
in Europe (EPC countries), Japan and the United States.

*

This is a summary of the report published under the 2019 Collaborative Research Project on
Harmonization of Industrial Property Right Systems under a commission from the Japan Patent Office.

**Associate Professor of University of East Anglia, UK.

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The current patent systems have mostly focused on protecting the physicalstructures and the configuration of physical systems. As the future of innovation isincreasingly intangible, one of the main problems concerns the economics ofalgorithmic innovation. Constituting a giant network of connected devices, objects
and people through the interplay of sensors, IoT relies on powerful and complex
algorithms to collect and analyze data from different devices, and to then share theresulting information with applications built to address specific needs in real time. 1All IoT projects will include an AI component. 2 Indeed, if IoT devices andcomponents generate vast amounts of data, the analysis element can be substantiallyenhanced through AI. Where traditional data analysis techniques were not designedwith the vast amount of real-time data in mind, AI can mitigate this problem throughthe interplay of machine learning algorithms. By simulating human behavior, AI
creates actionable insights based on identified patterns from the connected devices
without, in some cases, the need for any human intervention. Additionally, AI canhelp solve some of the interoperability issues between devices where operational
technology systems have not been designed to allow devices to communicate witheach other, or through the interplay of a central platform. However, AI algorithms
also have the ability to produce a multiplicity of results to a given problem.
Consequently, the functional description given to the machine may lead to a broadclass of inventions without describing every single instance of the classindividually. Should the patentee be given a monopoly over all the class ofinventions including unpredictable ones or should it be more limited?
Currently, algorithms are excluded from the scope of patent protection because
these are not considered to be ‘inventions’ for being too abstract of non-technical. 3Committee to Discuss a Next-generation Intellectual Property System, Verification, Evaluation andPlanning Committee, Intellectual Property Strategy Headquarters, Report of the Committee to Discuss a
Next-generation Intellectual Property System—Toward the Construction of a Next-generation
Intellectual Property System Adapted to the Rise of Digital Networks, (April 2016), 4.
2 And whilst this discussion is attracting more and more academic attention in Japan, authorities tend tofocus on the implication of AI for creative endeavors rather than the effect for the patent system. DataRelated Assets Report, supra n. 2; Secretariat of Intellectual Property Strategy Headquarters, Treatmentof works created by AI (for discussion)), (January 2016); Committee to Discuss a Next-generation
Intellectual Property System, Verification, Evaluation and Planning Committee, Intellectual Property
Strategy Headquarters, Toward the Construction of a Next-generation Intellectual Property System
Adapted to the Rise of Digital Networks, (April 2016), 4-7; Similarly, in Europe, E. Fraser, ‘Computers
as inventors – legal and policy implications of artificial intelligence on patent law’ (2016) 13(3)SCRIPTed, 307.
3 The US members of congress consider a draft bill to eliminate the judicially created exclusions frompatent-eligibility; see Chris Coons, Sens. Coons and Tillis and Reps. Collins, Johnson, and Stivers
release draft bill text to reform Section 101 of the Patent Act (May 22nd, 2019) available athttps://www.coons.senate.gov/news/press-releases/sens-coons-and-tillis-and-reps-collins-johnson-andstivers-release-draft-bill-text-to-reform-section-101-of-the-patent-act.
1iiProponents for broadening the patent system to cover algorithms within its scope
tend to argue that allowing algorithms to be patented would encourage innovationin the AI industry, enable the realization of the promises of the IoT, contribute toconsumer welfare, and benefit society as a whole through the increase of trade andeconomic wealth. Opponents, on the other hand, argue that patenting algorithms
would lead to the granting of monopolies over abstract ideas, stifle innovation, andlead to the exclusion of some players, which goes against the ethos theinteroperability of devices and therefore, the potential of IoT.
Concerning the eligibility of AI algorithms, there are inherent difficulties linked to
the fact that these complex algorithms are attempting to mirror human ingenuity,which is likely to trigger one of the subject-matter exclusions. Nevertheless,wanting to seize the opportunities of this technological field, the three jurisdictions(Europe, Japan and the US) have been very active in finding ways to find somealgorithmic inventions eligible for protection. Assessing this type of inventions asother computer programs or computer-implemented inventions, all three systems
allocate crucial importance to the reliance on hardware for eligibility purposes. Yet,differences exist in terms of the type of inventions eligible deriving from thedifferences in methods of assessment. Whilst the two-tier approach prevailing inJapan appears more favorable to inventors, the technical merit doctrine currently
applied in Europe and the US is creating difficulties for the protection of AI
algorithms. However, despite the innovation-friendly Japanese approach, there arealso concerns that this flexible approach might be too laxed to efficiently
differentiate between inventions using the laws of nature and the ones that do not.
Turning to novelty, first patentability requirement applicable in all three
jurisdictions, appears rather unambiguous at first glance. Aiming to prevent doublepatenting, differences exist in terms of legislation as well as practices from patentoffices, likely to gain importance in the future, especially in relation to AI
algorithms. For example, the way in which the state of the art is conceived varies
from a jurisdiction to another. If secret prior art is novelty-destroying in Europe,
this is not always the case in the US or Japan where secret prior art will only bejeopardizing novelty in relation to third parties’ secret prior art, creating a risk of
double-patenting and rise of patent thickets. But equally, the novelty thresholds
differ. In Japan, where an ‘enlarged’ novelty concept prevails, inventors must be
vigilant that obvious variants will be included, thereby heightening the noveltyiiithreshold compared to other jurisdictions like Europe and the US. These differencesreflect existing conflicting policy objectives which need to be addressed forfurthering harmonization. It is therefore important for policy-makers to reflect onwhether the patent system should focus primarily on rewarding the initial inventor
or whether it should encourage applicants applying for protection for smallerimprovements.
As patent systems are developing ways to adapt their systems to AI innovation andremain competitive on the international scene, there is a growing need to iron out
national differences and further harmonize patentability requirements of nationalsystems. Without this, current problems are likely to escalate. Bearing these issues
in mind, this report examines the fundamental question of whether or not protecting
AI algorithms by patent is necessary and desirable in light of the future ofinnovation and current developments. To achieve this, this research focusses on thesubject-matters of patent protection and discusses the need to harmonize the novelty
requirement for the purposes of IoT and AI.
This research report adopts a comparative approach looking at the practices of threeof the five biggest patent offices in the world, namely the European Patent Office(EPO), the United States Patent and Trademark Office (USPTO) and the Japanese
Patent Office (JPO). It will first analyze the justifications underlying the patentsystem (Section II) before turning to defining algorithmic innovation for thepurpose of AI and IoT (Section III). This section outlines the features of thedevelopment of algorithms to highlight the characteristics of modern algorithmic
inventions, providing the essential premise for the evaluation of the current patent
systems. When addressing the issue of opening the patent system to algorithms, thesocial need to grant such protection (section IV) and the scope of patent protection
for this technological field must be established. Consequently, Section V deals withthe first hurdle for patenting algorithms. Reviewing legislation and cases, thissection examines the excluded patentable subject-matters and emphasizes thedifficulties in constructing algorithms as inventions. Section VI then considers theneed to harmonize the novelty requirement further. Finally, Section VII concludes
and makes a series of modest recommendations as outlined below.

ivRecommendations:
1 – Limit the ineligibility of algorithms from patentability by changing theinterpretation of relevant excluded subject-matters. Only Europe has a statutory
exclusion for mathematical formula. It could be envisaged that this exclusion limits
itself to simple algorithmic problems that can be achieved easily by the humanmind. Once there is an invention in a field of technology then this one should bepatentable regardless of any further requirements linked to technicality.
2 – Countries should harmonize their approach to novelty: Jurisdictions shouldreflect on whether a whole-contents approach or a claims-based approach isdesirable in light of the current innovation trends. Here, a whole-contents
approach should be preferred. Furthermore, self-collision should apply to bothsecret prior art originating from the applicant and third parties to ensure that
only valuable subject-matters are patented and avoid double-patenting issues.
3 – Both Europe and the US should drop the technical character doctrine: in bothjurisdictions, this doctrine has led to a series of complexities and uncertainties.
Here, focusing on the inventive concept as done in Japan contributes to thelegitimacy of the patent system in the future.
4 – Further discussions on the rationale of the disclosure requirement should takeplace. Perhaps the jurisdictions under scrutiny should consider moving away froma system where applicants are merely required to provide information how to makeand use the invention to focus on ensuring that information related to the reasons
as to why or how the invention works are specified. 4 Equally, there is a need toensure that the rules and processes included in a system are explained.
5 – Patent offices must carry on their work on the dissemination of case studies
in the area of AI and IoT-related technologies: there is no denying that these are
extremely useful for prospective applicants, patent examiners and add transparency
in the application process. Here, it would be particularly helpful to know how muchshould be disclosed to meet the novelty threshold e.g. should the topology of thenetwork be disclosed? Should the algorithms be provided? Or the parameters used?

4A s a l r e a d y s u g g e s t e d b y S . B . S e y m o r e , ' P a t e n t i n g t h e U n e x p l a i n e d ' ( 2 0 1 9 ) 9 6 ( 4 ) Wa s h U L O , 7 0 7 - 7 5 2 .

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This requires careful examination as this could have dramatic consequences on thepatentability of future inventions.
The patent system has survived three industrial revolutions without changing
drastically and has the ability to survive a fourth, but there are still elements thatcan be improved. Whilst the current position amongst patent offices seems to be toapproach the patentability of AI inventions on a case-by-case basis, current
divergences in regime are likely to be of more central importance in the future. The
current situation leads to the downplaying of the AI element in patent applications
thereby minimizing the actual disclosure. This does not seem in line with the goalsof patent law. Although the recommendations above might sound radical, eventuallythese changes are required to guarantee the societal benefits deriving from AI an d
IoT technologies. Without this, patent attorneys, patent examiners and eventuallycourts will be asked to make decisions on a case-by-case basis without fully taking
into consideration the broader policy implications of these decisions.

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