Japan flag South Korea flag China flag

Special Update on Patenting AI: New European Guidelines

On 30 May, Anna Bartholomew (Senior Attorney, TLIP) attended the first conference on patenting artificial intelligence (AI) held at the European Patent Office (EPO) in Munich.     At that meeting some guidance was promised and in its forthcoming 1 November 2018 annual update of the “Guidelines for Examination”, the EPO will publish updated guidance for examiners on how they should examine computer programs and mathematical methods in addition to new guidance on AI implemented inventions.

To summarise the state of play with respect to exclusions from patentability for computer programs, the Guidelines inform us that:

Computer programs are excluded from patentability under Art. 52(2)(c) and (3) if claimed as such. However, following the generally applicable criteria for Art. 52(2) and (3), the exclusion does not apply to computer programs having a technical character (G-II, 2).

In order to have a technical character, and thus not be excluded from patentability, a computer program must produce a “further technical effect” when run on a computer. A “further technical effect” is a technical effect going beyond the “normal” physical interactions between the program (software) and the computer (hardware) on which it is run. The normal physical effects of the execution of a program, e.g. the circulation of electrical currents in the computer, are not in themselves sufficient to confer technical character to a computer program (T 1173/97 and G 3/08).

Examples of further technical effects which confer technical character to a computer program are the control of a technical process or of the internal functioning of the computer itself or its interfaces.

For example, a computer program which specifies a method of controlling an anti-lock braking system in a car, determining emissions by an X-ray device, compressing video, restoring a distorted digital image, or encrypting electronic communications brings about a further technical effect when it is run on a computer.

Furthermore, if a computer program is designed based on specific technical considerations of the internal functioning of the computer on which it is to be executed, such as by being adapted to the specific architecture of the computer, it may be considered to produce a further technical effect. For example, computer programs implementing security measures for protecting boot integrity or countermeasures against power analysis attacks have a technical character since they rely on a technical understanding of the internal functioning of the computer.

Similarly, computer programs controlling the internal functioning or operation of a computer, such as processor load balancing or memory allocation, normally produce a further technical effect.

Programs for processing code at low level, such as builders or compilers, may well have a technical character. For example, when building runtime objects from development objects, regenerating only those runtime objects resulting from modified development objects contributes to producing the further technical effect of limiting the resources needed for a particular build.

In respect of the state of play of exclusions from patentability for mathematical methods, the Guidelines state that:

Mathematical methods play an important role in the solution of technical problems in all fields of technology. However, they are excluded from patentability under Art. 52(2)(a) when claimed as such (Art. 52(3)).

The exclusion applies if a claim is directed to a purely abstract mathematical method and the claim does not require any technical means. For instance, a method for performing a Fast Fourier Transform on abstract data which does not specify the use of any technical means is a mathematical method as such. A purely abstract mathematical object or concept, e.g. a particular type of geometric object or of graph with nodes and edges, is not a method but is nevertheless not an invention in the sense of Art. 52(1) because it lacks a technical character.

If a claim is directed either to a method involving the use of technical means (e.g. a computer) or to a device, its subject-matter has a technical character as a whole and is thus not excluded from patentability under Art. 52(2) and (3).

For the assessment of inventive step, all features which contribute to the technical character of the invention must be taken into account (G-VII, 5.4). When the claimed invention is based on a mathematical method, it is assessed whether the mathematical method contributes to the technical character of the invention.

A mathematical method may contribute to the technical character of an invention, i.e. contribute to producing a technical effect that serves a technical purpose, by its application to a field of technology and/or by being adapted to a specific technical implementation.

 

Some examples are provided as follows:

Technical applications

When assessing the contribution made by a mathematical method to the technical character of an invention, it must be taken into account whether the method, in the context of the invention, serves a technical purpose (T 1227/05, T 1358/09).

Examples of technical purposes which may be served by a mathematical method are:

  • controlling a specific technical system or process, e.g. an X-ray apparatus or a steel cooling process
  • determining from measurements a required number of passes of a compaction machine to achieve a desired material density;
  • digital audio, image or video enhancement or analysis, e.g. de-noising, detecting persons in a digital image, estimating the quality of a transmitted digital audio signal;
  • separation of sources in speech signals; speech recognition, e.g. mapping a speech input to a text output;
  • encoding data for reliable and/or efficient transmission or storage (and corresponding decoding), e.g. error-correction coding of data for transmission over a noisy channel, compression of audio, image, video or sensor data;
  • encrypting/decrypting or signing electronic communications; generating keys in an RSA cryptographic system;
  • optimising load distribution in a computer network;
  • determining the energy expenditure of a subject by processing data obtained from physiological sensors; deriving the body temperature of a subject from data obtained from an ear temperature detector;
  • providing a genotype estimate based on an analysis of DNA samples, as well as providing a confidence interval for this estimate so as to quantify its reliability;
  • providing a medical diagnosis by an automated system processing physiological measurements;
  • simulating the behaviour of an adequately defined class of technical items, or specific technical processes, under technically relevant conditions (see G-II, 3.3.2).

Artificial intelligence and machine learning

AI and machine learning are based on computational models and algorithms for classification, clustering, regression and dimensionality reduction, such as neural networks, genetic algorithms, support vector machines, k-means, kernel regression and discriminant analysis. Such computational models and algorithms are per se of an abstract mathematical nature, irrespective of whether they can be “trained” based on training data.

When examining whether the claimed subject-matter has a technical character as a whole (Art. 52(1), (2) and (3)), expressions such as “support vector machine”, “reasoning engine” or “neural network” are looked at carefully, because they usually refer to abstract models devoid of technical character.

AI and machine learning find applications in various fields of technology. For example, the use of a neural network in a heart-monitoring apparatus for the purpose of identifying irregular heartbeats makes a technical contribution. The classification of digital images, videos, audio or speech signals based on low-level features (e.g. edges or pixel attributes for images) are further typical technical applications of classification algorithms. Classifying text documents solely in respect of their textual content is however not regarded to be per se a technical purpose but a linguistic one (T 1358/09). Classifying abstract data records or even “telecommunication network data records” without any indication of a technical use being made of the resulting classification is also not per se a technical purpose, even if the classification algorithm may be considered to have valuable mathematical properties such as robustness (T 1784/06).

Where a classification method serves a technical purpose, the steps of generating the training set and training the classifier may also contribute to the technical character of the invention if they support achieving that technical purpose.

Of particular use to practitioners is guidance of how to go about claiming such subject matter.  Often the above technical fields live in a distributed computing environment where an IoT device may network to a server via a cloud.  These devices may subsist in a peer-to-peer network performing file sharing, an augmented reality environment with head mounted displays, autonomous vehicles interacting over an ad hoc network or maintaining a distributed ledger using a blockchain.

The November 2018 Guidelines also provide that for such distributed environments, the claim set may comprise claims directed to each entity of the distributed system and/or to the overall system and the corresponding methods. Such a claim set may be allowable under Rule 43(2)(a) (F-IV, 3.2). Each independent claim must nevertheless fulfil the requirements for patentability, in particular the requirements of Art. 54, Art. 56 and Art. 84. For example, if the invention lies in the implementation of a computer cloud using virtual machines enabling adaptation to workload changes by allocating resources in an automatic manner, a client device accessing the resources of the cloud may already be known in the art. The claim set must also fulfil the requirements of unity.