A quick post that checks on the state of play for computer-implemented inventions (“software patents”) at the European Patent Office. It has a quick look at some minor updates to the Guidelines for Examination and then reviews a few recent Board of Appeal cases.
Guidelines for Examination
After the overhaul of 2018, there are relatively few updates to the Guidelines for Examination for the 1 November 2019 edition. I go through those that relate to computer-implemented inventions below. I recommend viewing the links to the sections with the “Show modifications” check box ticked.
Section G-II, 3.3.1 on “Artificial intelligence and machine learning” has been tweaked to indicate that terms such as “support vector machine”, “reasoning engine” or “neural network” do not by themselves imply a technical means. They must be considered in context (i.e. make sure you describe a “hard” engineering problem and context).
Section G-II, 3.3 on “Mathematical methods” has a few minor changes.
It is stressed that special attention needs to be paid to the clarity of terms in claims that relate to mathematical methods. If terms are deemed to have “no well-recognised meaning” this may make it difficult to demonstrate a technical character (and so care should be taken to provide detailed functional definitions within the detailed description).
It is also added that mathematical methods may produce a technical effect when applied to a field of technology and/or adapted to a specific technical implementation. In this case, the “computational efficiency” of the steps of the methods may be taken into account when assessing inventive step. This is echoed in a minor update to section G-II, 3.6 on “Programs for computers”.
As also discussed below, the EPO is hinting that it might be a good idea to provide some actual experimental evidence to back up claims of increased efficiency when dealing with more abstract software-style inventions.
In this case, the Board distinguished the field of data privacy from the field of data security. It was implied that the field of data security could give rise to technical solutions that provide an inventive step under Article 56 EPC. However, the field of data privacy was felt to relate to administrative, rather than technical, endeavours. In particular, the Board held that de-identifying data, by removing individually identifiable information, and by aggregating data from a plurality of sources, was not technical. It was felt that the claims related to data processing with a legal or administrative aim, rather than a technical one.
It is noted that the specification of the patent application was relatively light on concrete technical details – this may have led the Board to a negative opinion. The generalizations to the field of data privacy are perhaps too heavy-handed; there appears to be room to argue that some data privacy systems do contain technical features. In the light of this case, those drafting applications directed towards a data privacy aim may wish to determine if the technical effects may be recast in neighbouring data security fields.
T 0817/09 – Scoring a Document
T 0817/09 related to a computer implemented method for scoring a document.
The scoring was related to history data and was generated by monitoring signatures of the document, where the signatures were provided in the form of “term vectors”. As per similar linguistic processing cases discussed before, the “term vector” was found not to be “an inherently technical object” and “semantic similarity” was deemed to be a non-technical linguistic concept. The Board considered that solutions developed by the “notional mathematician” or the “notional computer programmer” would generally not be technical, whereas solutions developed by a digital signal processing engineer could be technical.
On the facts, the claimed methods were not found to provide any resource savings that could be presented as a technical, rather than linguistic effect. This does, however, suggest that providing evidence of technical improvements, e.g. reduced server processing times and/or reduced memory usage, may help applications with algorithmic subject matter.
T 0697/17 – Database Management Systems
T 0697/17 considered the patentability of SQL extensions within a relational database.
At first instance, the Examining Division held that the claim in question “entirely described a purely abstract method”. The Board disagreed: they held that the claim related to a method performed in a relational database system, which was a known form of software system within the field of computer science and as such would involve a computer system. The claim was thus not an abstract method. The Board noted that describing a technical feature at a high level of abstraction does not necessarily take away the feature’s technical character.
In consideration of inventive step, the Board cited T 1924/17, and stated that features make a technical contribution if they result from technical considerations on how to (for instance) improve processing speed, reduce the amount of memory required, improve availability or scalability, or reduce network traffic, when compared with the prior art or once added to the other features of the invention, and contribute in combination with technical features to achieve such an effect. However, effects and the respective features are non-technical if the effects are achieved by non-technical modifications to the underlying non-technical method or scheme (for example, a change of the business model, or a “pure algorithmic scheme”, i.e. an algorithmic scheme not based on technical considerations). The Board made an interesting distinction between a “programmer as such” and a “technical programmer”, and stated it was difficult to distinguish abstract algorithmic aspects that were non-technical and arose from the “programmer as such” from “technical programming” aspects that arose from the “technical programmer”.
Returning to T 1924/17, the Board concluded that a database management system is not a computer program as such but rather a technical system. The data structures used for providing access to data and for optimising and processing queries were deemed functional data structures and were held to purposively control the operation of the database management system and of the computer system to perform those technical tasks. While a database system is used to store non-technical information and database design usually involves information-modelling aspects, which do not contribute to solving a technical problem, the implementation of a database management system involves technical considerations. In the end, the case, which had been pending for 13 years, was remitted back to the Examining Division with an informally rap over the knuckles. It provides a useful citation for those drafting and prosecuting applications relating to database management systems.
Examination practice at the European Patent Office follows a set of Guidelines. These are published online and provide guidance for European Examiners and applicants. They are updated annually.
An updated set of Guidelines came into force on 1st November 2018. The recent updates introduce major amendments to sections that cover subject matter that is excluded from patentability in European. These sections include those directed to “mathematical methods”, “schemes, rules and methods for performing mental acts, playing games or doing business” (often shortened to “business methods”), and “programs for computers”. The updates are relevant to those filing applications related to “computer-implemented inventions” (often colloquially referred to as “software patents”).
Although the amendments do not significantly change current practice at the European Patent Office, they do expand the guidance on what may and may not be protected with a European patent. They represent a significant upgrade and demonstrate the maturity of the case law with regard to computer-implemented inventions.
This post will review and highlight the updates. The post may be useful for those seeking to patent machine learning and artificial intelligence inventions. The updates cover the following areas:
claims to distributed computing systems;
inventions that use mathematical methods;
AI and machine learning inventions;
inventions that cover simulations and models; and
inventions that relate to business methods, gaming, mental acts or computer programs.
Section F-IV, 3.9.3 has been added to the section relating to claims for computer-implemented inventions. It provides expanded guidance and an example relevant to processes operating in a distributed computing environment. These processes form a basis for many real-world implementations of computer-implemented inventions. For example, a smartphone accessing a cloud computing service would implement a process operating in a distributed computing environment.
The section sets out the current practice of the European Patent Office. Claims in a claim set may be directed to each entity of the distributed system and/or the system as a whole. Such a claim set may be argued to meet the requirement for multiple independent claims set by Rule 43(2)(a) EPC, i.e. the claims may be allowed despite having multiple independent claims in the same category because the subject-matter of the claims relates to a plurality of interrelated products. However, each individual claim will need to meet the requirements of novelty, inventive step and clarity.
For example, if a cloud computing service provides a new image classification function via an application programming interface that is accessed by a smartphone, a claim set may feature apparatus claims to both a server computing device (the cloud server) and a mobile computing device (the “accessing device” or smartphone). If the smartphone is simply a generic smartphone making a network request (e.g. an “HTTPS request to a REST API endpoint”), it will likely not be new when compared to known smartphones. An objection will be raised against the smartphone claim. However, if the smartphone implements some new low-level processing, e.g. some new feature extraction process that is specific to the new image classification function (like pre-extracting cat-like facial features), it may also be new and inventive in itself and be allowed.
The updated section draws our attention to the need for clarity in claims to distributed entities. It recommends that distributed method claims specify the entity that is performing each method step.
Claiming distributed processes in a challenge. In practice, one entity often implements most of the new and inventive process (e.g. the cloud server), while other devices are relatively “thin” and generic (e.g. the smartphone). However, claims to the accessing device are often of greater commercial value (e.g. they might allow a royalty for each smartphone that is sold). This often leads to the inclusion of claims to the mobile computing device in a claim set, but a high likelihood of an objection being raised by the European Examiner.
To attempt to overcome novelty and inventive step objections to “accessing device” claims, it is common to include an indirect or implicit reference to the functions of the server computing device. This can then lead to one or more clarity, novelty or inventive step objections. For example, the indirect features may trigger a clarity objection for not clearly specifying features of the “accessing device”. Alternatively, the indirect features may be ignored for novelty and/or inventive step, as they are deemed to present no inherent structural limitations for the “accessing device”.
When drafting claims to distributed systems, it is worth questioning the inventors to determine what functions may be implemented with low-level adaptations to the accessing device. If the invention can be embodied in an “app”, it is worth looking at the architecture of the app, and the sequence of low-level system calls it may be implementing. This may not be obvious to the inventors, as commercial and engineering demands often require as much functionality as possible to be embodied on the back-end in the cloud.
The section on the examination of mathematical methods has been re-written and two sub-sections have been added. A first sub-section – 3.3.1 – now provides specific guidance for artificial intelligence and machine learning. A second sub-section – 3.3.2 – expands upon claims to simulation, design or modelling.
The updated guidance is now clearer on the importance of “technical means”, i.e. a concrete implementation in a field of technology, when an invention makes use of mathematical methods. This complements the recent changes to practice for “abstract inventions” in the United States.
I really like the updates to this section and the inclusion of helpful concrete examples. The section emphasises that a mathematical method or algorithm per se will not be enough to make a claim feature patentable, although many patentable inventions do have a mathematical or algorithmic basis.
Examples of the Fast Fourier Transform, geometric objects and graphs are provided: these features may contribute to the technical character of an invention if they contribute to producing a technical effect that serves a technical purpose. Put another way, these features need to be provided in a context that relates to an engineering problem encountered in the real-world, and the use of these features needs to result in a change in the real-world that helps solve that problem. This is further emphasised later in the guidance – the technical purpose of the mathematical features needs to be specific rather than generic, and the claim needs to be functionally limited to the technical purpose, either explicitly or implicitly.
What kind of applications are seen by the European Patent Office to be “technical”? My personal definition is: does the application relate to something in the real-world that requires knowledge that is taught in an undergraduate engineering degree? If the answer is “yes”, then the application is “technical”. If the answer is “no”, then the application may not be “technical”.
Section 3.3 now provides a useful list of purposes that are deemed “technical”. These include:
controlling a specific machine or technical process, e.g. an X-ray apparatus or steel cooling;
using measurements to control a machine or technical process, e.g. using a compaction machine to achieve a desired material density;
digital audio/visual processing, this can be relatively high-level – detecting people is a provided example (but a clear relation to captured data is recommended);
processing speech data, e.g. to generate text (but processing text per se may not be technical);
encoding data, e.g. for transmission or storage;
generating higher-level measurements by processing data from physiological sensors or other medical diagnosis;
analysing DNA samples to provide a genotype estimate; and
simulating “technical” things (this is described in more detail in new sub-section 3.3.2).
The section stresses that there must be a sufficient link between the technical purpose of the invention and the mathematical method steps, for example, by specifying how the input and the output of the sequence of mathematical steps relate to the technical purpose so that the mathematical method is causally linked to a technical effect. When drafting an application for Europe for an invention that features mathematical operations (e.g. equations and/or algorithmic designs), it is recommended to place such an explanation in the description – this can then be pointed to in examination if any objection is raised.
Similar to practice in the United Kingdom, the section ends by indicating that a feature may contribute to the technical character of an invention independently of any technical application, when the claim is directed to a specific technical implementation of a mathematical method, and the mathematical method is particularly adapted for that implementation in that its design is motivated by technical considerations of the internal functioning of the computer. Using the Fast Fourier Transform example, it may be possible to obtain protection for a new digital implementation of the Fast Fourier Transform, if you were performing specific mathematical operations that were adapted to the available computing resources of the implementation, e.g. available memory registers, processing cores, etc.
When considering inventions involving mathematical methods, one useful approach is to make an initial determination:
Does the invention relate to a specific engineering application (e.g. what branch of “applied” maths is being considered)?
Or does the invention relate to a new technical implementation of a mathematical operation (e.g. in effect a new and beneficial way of performing mathematical operations or “computing” using a device – sometimes called “core” inventions)?
A positive answer in the first case, suggests a quick check against the provided examples and the case law to determine if the specific engineering application has in the past been deemed to be “technical” under European practice.
A positive answer in the second case suggests looking carefully at the constraints imposed by the electronic hardware of the implementation. You will need to describe how the mathematical method is adapted, e.g. as compared to a “text-book” application, to provide concrete implementational improvements.
Artificial Intelligence and Machine Learning
Sub-section 3.3.1 is relatively short and seeks to summarise existing case law that applies in this area. This anticipates a large rise in patent applications over the coming years.
Machine learning inventions have been patented at the European Patent Office almost since its inception in the late 1970s. The present sub-section reminds us that despite the recent resurgence in neural networks, algorithms for approaches such as “classification, clustering, regression and dimensionality reduction” including “genetic algorithms, support vector machines, k-means, kernel regression and discriminant analysis” have been around for a number of years.
The sub-section stresses that the algorithms and approaches themselves per se of an abstract mathematical nature. The guidance from section 3.3 therefore applies: the invention either needs to relate to a specific engineering application that uses the approaches (e.g. using k-means clustering to classify packets in a network for selective filtering) or a new technical implementation of the approach that is constrained by technical factors at least the underlying computation hardware.
The sub-section hints that “technical character” often requires a clear causal link to measured data that represents physical phenomena. For example, classification of digital data such as physiological measurements, images, videos, or audio data is seen to be a common “technical application”. However, classifying text data is regarded as a “linguistic” and “non-technical” application. Likewise, general classification of “data” or “records” without a link to a specific technical problem would likely be seen as “non-technical”. Reference is made to case T 1358/09.
The sub-section ends by indicating that if a classification method is seen to serve a technical purpose then the steps of generating the training set and training the classifier may also contribute to the technical character of the invention if they support the technical purpose. This provides useful advice for drafting claims for inventions in this area: it is recommended to consider independent claims to the generation of training data and architecture training, as well as claims to an inference step. These claims may also provide a distributed processing system as discussed in section 3.3, for example inference may be performed on a smartphone, whereas data cleaning and training may be performed on a remote server. Care should be taken to cover different infringing acts.
Simulation, design or modelling
Sub-section 3.3.2 draws out material that was present in section 3.3. Discussing this material in a separate sub-section clarifies the high-level overview now present in section 3.3.
A computer-implemented simulation of a specific technical system or process may be seen to provide a technical effect and lead to a granted European patent. However, objections will be raised to computer-implemented simulations of non-technical systems or processes, such as those with an aim in the fields of finance, marketing, administration, scheduling or logistics. Care should be taken; cases such as T 531/09 indicate that the presence of technical devices (X-ray scanners in that case) is not enough to provide technical character, the technical devices need to be specific devices and the simulation needs to perform a technical purpose.
In the field of computer-aided design, the determination of a technical parameter which is intrinsically linked to the functioning of a technical object, where the determination is based on technical considerations, is a technical purpose. For example, a method of determining a particular value for a parameter of a specific technical device, in a manner that improves production or use of the device may be seen as suitably “technical”. Care should be taken if the design involves decisions to be made by a human being – e.g. the selection of an approved value – this intervention may be seen to break a causal chain that connects the design method to a technical purpose. Such decisions also risk importing factors that are outside of a narrow determination based on “technical considerations”.
Finally, this new sub-section suggests that claims that produce “models” will often lead to objections on the grounds that the models are not technical features per se; instead, they are seen as “abstract” mathematical or mental features. This again complements current practice in the United States. It is emphasised that generation of a model may be considered to lack a technical effect, even if the modelled product, system or process is technical. It this case it is important that the claim clearly indicates how the model is used, or to be used, in a technical system or process to solve a technical problem.
The previous high-level summary in section 3.5 has now been deleted, with this material being moved into separate sub-sections related to each of “performing mental acts”, “playing games” and “doing business”. Each sub-section then contains new material relating to each sub-category.
Each sub-section begins with a useful definition of each exclusion. Although this is described in the context of the exclusion being applied to the whole claim (e.g. the exclusion applying “as such” or “per se”), this often will not occur in practice, e.g. in most cases the exclusions set out in Article 52(2)(c) EPC will be avoided by having the method performed by a computing device. However, the definitions are useful as they indicate which claim features may be ignored for inventive step on the grounds that they provide no technical effect.
These are described as instructions to the human mind on how to conduct cognitive, conceptual or intellectual processes. The learning of a language is given as an example, which hints at how the European Patent Office legally support an objection to “linguistic” features (e.g. text processing) as being non-technical.
When drafting claims to computer-implemented inventions, especially method claims, care should be taken to avoid accidentally falling within the exclusion. For example, claims should be checked to ensure that the method steps therein cannot be performed entirely in the human mind; at least one step needs to be performed outside of the human mind. In practice, considering whether a method step can be performed in the human mind is useful when predicting whether inventive step objections may be issued during European examination; if the determination is positive, the method step can often be drafted or amended in a manner that avoids this interpretation, e.g. by referring to a specific technical apparatus. The sub-section indicates that a method would not be seen as performing mental acts if it requires the use of technical means or if it provides a physical entity as a resulting product.
The sub-section does not indicate that mental steps are necessarily ignored for an analysis of inventive step; however, it does emphasise that are mental steps must contribute to producing a technical effect that serves a technical process. A good example provided in the sub-section is that of affixing a driver to a Coriolis mass flowmeter: steps specifying the position of the driver may be performed mentally but by defining the position so as to maximise the performance of the flowmeter, a technical contribution is provided.
Games are defined in sub-section 3.5.2 as a conceptual framework of conventions and conditions that govern player conduct and how a game evolves in response to decisions and actions by the players. Games are governed by game rules, that are by their nature abstract, mental entities that are only meaningful within a game context. Games may be simple – matching random numbers – or complex – video games with extensive virtual game worlds.
If a claim sets out technical means for implementing the rules of a game, it is not excluded as such and analysis moves onto inventive step. To provide an inventive step, a claim feature must make a technical contribution, i.e. provide some engineering benefit beyond a mere computer-implementation of the game rules. The benefit of a claim feature is to be assessed from the point of view of an engineer or game programmer, who may be given the games rules by a game designer as a “requirements specification”.
The sub-section indicates that in many situations the burden is on the applicant to show that a gaming invention provides a real engineering benefit. It notes that abstracting non-technical game elements, relying on a complexity of a solution or indicating cognitive content will not help the applicant.
It is interesting to compare the general negativity of this sub-section with cases such as T 928/03 and T 12/08 that presented a more liberal view of the technical nature of gaming inventions. It will be seen whether they represent a narrower approach than seen in the past.
Doing business is defined in sub-section 3.5.3 as including activities which are of financial, commercial, administrative or organisational nature. The latter two areas should be noted; they are often overlooked as they do not directly relate to making a profit but are still seen to be “non-technical”.
Some useful examples of “business method” features are provided. They include:
management of rights and contractual agreements,
scheduling of tasks,
business optimisation, and
data science for the purpose of managerial decision making.
If an invention relates to any of these features, it should be assumed to relate to excluded subject matter unless there is strong evidence that a technical problem is being solved by a technical solution that involves technical considerations.
For practitioners, a disclosure document or inventor from industry will often present an invention in terms of a commercial benefit. For example, inventors often become familiar with internally promoting an invention on commercial grounds. Care should be taken to dig behind these grounds and return to the underlying engineering aspects of the idea. If no engineering aspects can be presented, the idea may not be suitable for a European patent application. Examiners and Boards of Appeal will also use an indication of a commercial benefit, or the presence of the above business features, as evidence of a lack of a technical contribution. For this reason, it is recommended to avoid discussing these when drafting the patent specification.
Programs for Computers
Section 3.6 has now been redrafted and sub-sections 3.6.1, 3.6.2, and 3.6.3 have been added to respectively cover “further technical effects”, “information modelling” and programming, and “data retrieval, formats and structures”.
Section 3.6 now begins by indicating that computer programs must produce a “further technical effect” to avoid exclusion on the grounds of being a computer program “as such”. A “further technical effect” is an effect that goes beyond the normal operation of a computer, e.g. the physical effects of executing a computer program. Controlling a technical process or the internal functioning of a computer or its interfaces are deemed to be valid “further technical effects”.
Although not explicitly indicated in section 3.6, it is relatively straightforward to demonstrate a “further technical effect” and avoid an objection to the whole claim under Articles 52(2)(c) and (3) EPC. For example, claims to a computer program may be said to provide a “further technical effect” if they include instructions to implement a technical method, e.g. if they indicate a dependency to an independent method claim that is deemed technical. In this manner, European patent applications often feature claims to a “computer program for implementing the method of claim X”.
Further technical effects that may be demonstrated by a computer program are set out in sub-section 3.6.1. These include:
controlling a technical system or process (e.g. a braking system of a car or an X-ray device);
data processing in any of the areas highlighted in section 3.3, e.g. audio/visual processing, encryption or compression;
improving the internal functioning of a computer running the program, e.g. programs that are adapted for a specific architecture or that provide benefits at the kernel or operating system level; and
providing low-level tools such as compilers, memory allocators, and builders.
This updated section and its sub-sections are more useful in indicating what kind of features may be deemed to provide a technical effect. For example, if a feature of a computer program is deemed to provide a “further technical effect” as set out in this section, the feature would be seen as “technical” and be counted in any evaluation of inventive step (e.g. for other independent system or method claims).
Information Modelling and Programming
Sub-section 3.6.2 now provides useful guidance when the invention relates to aspects of computer engineering or software in itself, e.g. as opposed to a computerised solution in another field of engineering. While software developers may assume that their solution is technical according to the normal use of that term, features may not actually be “technical” for the requirements of patentability.
Information modelling is defined here as relating to providing a formal description of a real-world system or process. It may be seen to relate to models built in graphical or textual modelling languages, such as the Unified Modelling Language (UML) or the Business Process Modelling Notation (BPMN). Information Modelling may result in data models or templates that represent an underlying process.
Programming is defined as relating to the way in which computer code is written. It can involve choosing certain options or conventions for performing a common functional operation, or defining and providing a programming language, including text-based or graphical systems.
This sub-section stresses that information modelling or programming features that improve the intellectual effort of a programmer or software developer will often be seen to lack technical character and so cannot contribute to an inventive step. Benefits such as re-usability, platform-independence, conciseness, easier code-management or convenience for documentation, are not regarded as technical effects. For a feature to provide a technical effect, it must provide an improvement from the viewpoint of the computer, as opposed to the programmer. For example, manipulating machine code to provide for greater memory efficiency is seen as providing a technical contribution.
Data retrieval, formats and structures
Computer-implemented data structures or data formats embodied on a medium or as an electromagnetic carrier wave may be claimed, as they do not fall within the exclusions of Article 52(2) EPC. This sub-section has been relocated from previous section 3.7.
This section emphasises that cognitive data, i.e. data that is only relevant to a human user, cannot normally contribute to an inventive step. However, functional data, i.e. data that controls a device processing the data and that reflects technical features of the device, can.
Some examples of functional data are provided. These include a picture encoding, an index structure for a relational database, or a header structure of an electronic message. It is emphasised that the actually data content of the picture, database record or electronic message is often seen to be cognitive content and so cannot contribute to an inventive step.
In recent years there has been a resurgence of interest in machine learning and so-called “artificial intelligence” systems. Much of this resurgence is based on advances in so-called “deep learning”, neural networks with multiple layers of connections. For example, convolutional neural networks now provide state-of-the-art performance in many image recognition tasks and recurrent neural networks have been used to increase the accuracy of many commercial machine translation systems. Machine learning may be considered a subdiscipline of “artificial intelligence” that deals with algorithms that are trained to perform tasks such as classification based on collections of data. This recent resurgence has meant that more companies wish to protect innovations in this field. This quickly brings them into the realm of computer-implemented inventions, and the nuances of protection at the European Patent Office.
“Computer-implemented invention” is the European Patent Office term for a software invention. Claims that specify machine learning and artificial intelligence systems are almost certainly to be considered “computer-implemented inventions”. The innovation in such systems occurs in the design of the algorithms and/or software architectures. Claims for new hardware to implement machine learning and artificial intelligence systems, such as new graphical processing unit configurations, would not be classed as computer-implemented inventions and would be considered in the same manner as conventional computer devices.
What Do We Have To Go On?
As key advances in the field have only been seen since 2010, there are few Board of Appeal cases that explicitly consider these inventions. It is likely we will see many Board of Appeal decisions in this field, but it is unlikely these will filter through the system much before 2020. However, applications in the field are being filed and examined. The following review is based on knowledge of these applications, evaluated in the context of existing Board of Appeal cases.
A first issue regarding machine learning and artificial intelligence systems is that many of the underlying techniques are public knowledge, given the rapid turn-over of publications and repositories of electronic pre-prints such as arXiv. Hence, many applicants may face novelty and inventive step objections if the invention involves the application of known techniques to new domains or problems. For patent attorneys who are drafting new applications, it is recommended to perform a pre-filing search of such publication sources and ensure that the inventors provide a full appraisal of what is public knowledge.
Domain of Invention
A second issue is the domain of the invention. This may be seen as the context of the invention as presented in the claims and patent description.
Inventions that apply machine learning approaches to fields in engineering are generally considered more positively by the European Patent Office. These fields will typically either operate on low-level data that represents physical properties or have some form of actuation or change in the physical world. For example, the following domains are less likely to have features excluded from an inventive step evaluation for being “non-technical”: navigating a robot within a three-dimensional space; dynamic adaptive change of a Field Programmable Gate Array; audio signal analysis in speech processing; and controlling a power supply to a data centre.
On the other hand, inventions that apply machine learning approaches within a business or “enterprise” domain are likely to be analysed more closely. These inventions have a greater chance of claim features being excluded for being “non-technical”. These domains typically have an aim of increasing profit. The more this aim is explicit in the patent application, the more likely a “non-technical” objection will be raised. For example, the following inventions are more likely to have features excluded from an inventive step evaluation for being “non-technical”: intelligent organisation of playlists in a music streaming service; adaptive electronic trading of securities; automated provision of electronic information in a company hierarchy; and automated negotiation of online advertising auctions.
Exclusions from Patentability
A third issue that arises is that individual features of the claims fall within the exclusions of Article 52(2) EPC. In the field of machine learning and artificial intelligence systems, there is an increased risk of claim features being considered to fall into one of the following categories: mathematical methods; schemes, rules and methods for performing mental acts or doing business; and presentations of information. These will briefly be considered in turn below.
The field of machine learning is closely linked to the field of statistics. Indeed many machine learning algorithms are an application of statistical methods. Academic researchers in the field are trained to describe their contributions mathematically, and this is required for publication in an academic journal. However, the practice of the European Patent Office, as directed by the Boards of Appeal, typically regards statistical methods as mathematical methods. In their pure, unapplied form they are considered “non-technical”.
Schemes, Rules and Methods for Performing Mental Acts
A claim feature is likely to be considered part of schemes, rules and methods for performing mental acts when the scope of the feature is too broad or abstract. For example, if a claimed method step also covers a human being performing the step manually, it is likely that the scope is too broad.
Schemes, Rules and Methods for Doing Business
Claim features are likely to be considered schemes, rules and methods for doing business when the information processing relates to a business aim or goal. This is especially the case where the information processing is dependent on the content of the data being processed, and that content does not relate to a low-level recording or capture of a physical phenomenon.
For example, processing of a digital sound recording to clean the recording of noise would be considered “technical”; processing row entries in a database of information technology assets to remove duplicates for licensing purposes would likely be considered “non-technical”.
Presentation of Information
Objections that features relate to the presentation of information may occur when the innovation relates to user experience (UX) or user interface (UI) features.
For example, a machine learning algorithm that adaptively arranges icons on a smartphone according to use may receive objections on the grounds that features relate to mathematical methods (the algorithm) and presentation of information (the arrangement of icons on the graphical user interface). As per Guideline G-II, 3.7.1, grant is unlikely if information is simply displayed to a user and any improvement occurs in the mind of the user. However, it is possible to argue for a technical effect if the output provides information on an internal state of operation of a device (at the operating system level or below, e.g. battery level, processing unit utility etc.) or if the output improves a sequence of interactions with a user (e.g. provides a new way of operating a device). Again, a technical problem needs to be demonstrated and the machine learning algorithm needs to be a tool to solve this problem.
Subfields of ML and AI
In certain subfields of machine learning and artificial intelligence, there is a tendency for Boards of Appeal and Examining Divisions to consider inventions more or less “technical”. This is often for a combination of factors, including field of operation of appellants, the history of research and traditional applications, and the background and public policy preferences of staff of the European Patent Office.
For example, machine learning and artificial intelligence systems in the field of image, video and audio processing are more likely to be found to have “technical” features that can contribute to an inventive step under Article 56 EPC. A convolutional neural network architecture applied to image processing is more likely to be considered a “technical” contribution that the same architecture applied to text processing. Similarly, it may be argued that machine learning and artificial intelligence systems in the field of medicine and biochemistry have “technical” characteristics, e.g. if they operate on data originating from mass spectrometry or medical imaging.
However, advances in search, classification and natural language processing are more likely to be found to have “non-technical” features that cannot contribute to an inventive step under Article 56 EPC. These areas of machine learning and artificial intelligence systems are often felt to be “technical” by the engineers and developers building such systems. However, it is a nuance of European case law that these areas are often deemed to have claim features that fall into an excluded “business”, “mathematical” or “administrative” category.
A recent example may be found in case T 1358/09. The claim in this case comprised “text documents, which are digitally represented in a computer, by a vector of n dimensions, said n dimensions forming a vector space, whereas the value of each dimension of said vector corresponds to the frequency of occurrence of a certain term in the document”. The Board agreed with the appellant that the steps in the claim were different to those applied by a human being performing classification. However, the Board concluded that the algorithm underlying the method the claim did not “go beyond a particular mathematical formulation of the task of classifying documents”. They were of the opinion that the skilled person would have been given the (“non-technical”) text classification algorithm and simply be tasked with implementing it on a computer.
What Should We Not Do?
Managers and executives of commercial enterprises are often habituated into selling innovations to a non-technical audience. This means that invention disclosures often describe the invention at an abstract “marketing” level. When an invention is described in a patent application at this level, inventive step objections are likely.
The fact that mathematical formulae may comprise excluded “non-technical” features is difficult for inventors and practitioners to grasp. Often equations at an academic-publication level are included in patent specifications in an attempt to add technical character. This often backfires. While such equations may be deemed “technical” according to a standard definition of the term, they are often not deemed “technical” according to the definition applied by European case law.
In general, objections are more likely in this area when the scope of the claim is broad and attempts to cover applications of a particular algorithm in all industries. Applicants should be advised that trying to cover everything will likely lead to refusal.
What Should We Do?
Chances of grant may be increased by ensuring an examiner or Board of Appeal member can clearly see the practical application of the algorithm to a specific field or low-level technical area.
Patent attorneys drafting patent applications for machine learning and artificial intelligence systems should carefully consider the framing and description of the invention in the patent specification. In-depth discussions with the engineers and developers that are implementing the systems often enable innovations to be described more precisely. Given this precision, innovations may be framed as a “technical” or engineering innovation, i.e. a technical solution to a technical problem. This increases the chance of a positive opinion from the European Patent Office.
Often features of an invention will have both a business advantage and a “technical” advantage. For example, a machine learning system that learns how to dynamically route data over a network may help an online merchant more successfully route traffic to their website; however, this improved method may involve manipulation of data packets within a router that also improves network security. A patent specification describing the latter advantage will have a greater chance of grant than the former, regardless of the actual provenance of the invention. A practitioner may work with an inventor to ensure that initial business advantages are distilled to their proximate “technical” advantages and effects. For cases where data does not relate to a low-level recording or capture of a physical phenomenon, it is recommended to ensure that any described technical effect applies regardless of the content of the data.
When considering exclusion for “mental acts”, a risk of a “non-technical” objection may be reduced by ensuring that your method steps exclude a manual implementation. Note that this exclusion does not necessarily prevent other objections being raised (see T 1358/09 above).
When drafting patent applications, it is also important to describe the implementation of any mathematical method. In this manner, pseudo-code is often more useful than equations. It is also important to clearly define how attributes of the physical world are represented within the computer. Good questions to ask include: “What data structures and function routines are used to implement the elements of any equation?”, “How is data initially recorded, e.g. are documents a scanned image such as a bitmap or a markup file using a Unicode encoding?”, “What programming languages and libraries are being used?”, or “What application programming interfaces are important?”.
Practitioners do need to be concerned with including overly limiting definitions within the claims; however, a positive opinion is more likely when specific implementation examples are described in the patent specification, followed by possible generalisations, than when specific implementation examples are omitted and the description only presents a generalised form of the invention along with more detailed mathematical equations.
To be successful in search, classification and natural language processing, one approach is to determine whether features relating to a non-obvious technical implementation may be claimed. This approach often goes hand in hand with a knowledge of academic publications in the field. While such publications may disclose a version of an algorithm being used, they often gloss over the technical implementation (unless the underlying source code is released on GitHub). For example, is there any feature of the data, ignoring its content, which makes implementation of a given equation problematic? If inventors have managed to reduce the dimensionality of a neural network using clever string pre-processing or quantisation then there may be an argument that the resultant solution is implementable on mobile and embedded devices. Reducing a size of a model from 3 GB to 300 KB by intelligent selection of pipeline stages may enable you to argue for a technical effect.
Do Not Believe The Hype?
Despite the hype, machine learning and artificial intelligence systems are just another form of software solution. As such, all the general guidance and case law on computer-implemented inventions continues to apply. A benefit of the longer timescales of patent prosecution is that you ride out the waves of Gartner’s hype cycle. In fact, I still sometimes prosecute cases from the end of the dotcom boom…
Obtaining a strong, enforceable patent that protects your software invention is often difficult. Here I will touch on some approaches to stack the odds in your favour.
Why is it difficult to patent software?
There are a number of hurdles that must be overcome to obtain a patent for a software invention. These include:
Being new: at least one aspect of your invention must differ from other solutions available to the public. This includes solutions described in other patent applications, blog posts, manuals, online documentation and white papers.
Being inventive: not only must your invention have a differing feature, that differing feature needs to be non-obvious. If the differing feature is common knowledge, e.g. is a common feature described in text books or on Wikipedia, and it is straightforward to use it in the context of the other known features, then your invention will be deemed obvious. Likewise if the differing feature is described in another document, and it would be obvious to combine this other document with the pre-existing solution providing the other features, then your inventive will be said to lack an inventive step.
Being patentable: your software invention must meet requirements set by law for patentable subject matter. Each jurisdiction has slightly different rules. Normally, statute sets some very broad categories of excluded subject matter. Individual cases and hearings then provide a body of case law that says which areas are allowable and which areas are not. For example, in Europe you need to show that the differing feature provides a ‘technical’ effect, which is often an engineering improvement.
Patenting software also taxes patent attorneys and patent examiners. With mechanical products, you can often see and feel the invention. Similarly, pharmaceutical inventions may be defined through sets of well-defined chemical formulae. Software is harder to visualise – there may be multiple technology layers in an implementation stack and many non-essential interoperating parts. This can often lead to poor patent specifications and misunderstandings.
Also if a patent claim is too specific then it will be easy for a software developer to work around. Most inventions will need to transcend a particular programming language or technology to cover ports to different platforms and to future-proof a patent’s value. However, if a patent claim is too broad, it is often deemed too abstract to be patentable and may also run afoul of clarity provisions.
What do these difficulties mean in practice?
In practice these difficulties often lead to:
Low grant rates;
High prosecution spend; or
These factors often interact to form a vicious cycle of mutual distrust: too many poor quality patent specifications are filed, leading to cynicism from patent examiners and the public, which leads to knee-jerk rejections and lobbying, which in turn undermines confidence in the system from businesses.
What can we do?
The first thing software companies can do is to find the right patent attorney or attorney firm. There are a few attorneys who deal with software day-in-day-out. These need to be sought out. Look for an attorney with experience of working for a large software company, e.g. Microsoft, IBM, Hewlett-Packard, Oracle, SAS, Amazon, Google. The European Patent Office allows you to search by representative to see example applicants.
The second thing software companies can do is to set high standards for their patent specifications. The recent change in practice in the US will hopefully catalyse this. Technical or engineering features should be defined in detail; any high-level marketing terms or IT jargon should be jettisoned. A strong technical problem should be eluded to, and there should be a good set of tiered fall-back positions, each with their own defined engineering advantages.
The third thing software companies can do is to keep on top of the case law in different jurisdictions. Your patent attorney may offer to help you with this. At a simple level, a one page table can show what kind of inventions have been allowed and what kind of inventions have been refused. For example, UK hearing officers often find that database management improvements are not allowed, whereas European examiners find these are technical.
The European Patent Office has now published a case law summary for 2014 as Official Journal supplementary publication 4/2015. Sections I-C-4.1, I-C-5.1, II-A-1, and II-E-1.4 discuss case law that relates to computer-related inventions. The relevant passages are extracted and commented on below.
T 407/11 held that the relevant skilled person in the context of providing computer-system users with operating assistance via a user interface (e.g. error messages or warnings) was an expert in software ergonomics concerned with the userfriendliness of human-machine interfaces rather than an expert in software programming or in computer technology in the strict sense.
The objective problem to be solved by that skilled person was to prevent a situation whereby the user’s action caused an electronic data-processing system to execute a called function differently from intended (or even to fail to execute it at all).
In the board’s view, however, the technical effect claimed in the application (simpler operation of an object-oriented user interface, facilitating initial use and subsequent familiarisation, especially for beginners or upgrading users, and so making the resulting method easier and more intuitive to learn) could not be considered a directly derivable consequence of the distinguishing features, because attributes such as “simpler operation” or “easy and intuitive familiarisation” were generally subjective, i.e. depended on the user’s individual preferences and experience or intellectual capabilities, while the classification of users as “beginners”, “upgraders” or “advanced” was generally based on a variety of criteria which were not clearly defined.
This suggests that providing objective definitions of technical effects (e.g. millisecond time savings) may help to support an inventive step under European practice. It also further indicates a need to avoid reference to “user”-based advantages.
Applications of Algorithms
In T 2035/11 the application mainly related to navigation systems that could be tailored to a user’s particular wishes. The focus of the application was on the route-planning functionality of a navigation system.
The board held that the subject-matter of claim 1 lacked an inventive step within the meaning of Art. 52(1) and 56 EPC. It noted that mathematical algorithms may contribute to the technical character of an invention only in so far as they serve a technical purpose (see e.g. decision T 1784/06). The purpose of the algorithm was the mere display of an optimal path to the user for cognitive processing. The user could act on the information, but did not need to.
As stated in decision T 1670/07, a technical effect may arise from either the provision of data about a technical process, regardless of the presence of the user or its subsequent use, or from the provision of data (including data that on its own is excluded, e.g. produced by means of an algorithm) that is applied directly in a technical process.
In the case at issue, the data was produced by means of an algorithm and was not applied directly in a technical process, so neither possibility applied.
Warning on Generalisation
In T 2231/09 the patent in suit concerned a method of representing and analysing images. Claim 1 of the main request set out that “… at least one said descriptor element is derived using only a subset of pixels in said image.”
The board considered the expression “subset of pixels” to be problematic under Art. 84 EPC 1973 and stressed that, while a certain degree of generalisation may be permitted, features as claimed should make it possible to clearly identify features of embodiments that are covered by the terms of a claim. Moreover, the generalised subject-matter as claimed should make it possible to understand the technical problem to be solved.
When amending claim 1, the applicant had put forward a new interpretation according to which a “region” could mean the whole image, and a “subset” could correspond to all pixels of the region. The board considered this interpretation to be inconsistent with essential parts of the described embodiments, according to which a subset corresponded to only some of the pixels of a region. The subject-matter of claim 1 was thus unclear when interpreted in the light of the description.
The board also stated that the requirements of clarity and support by the description in Art. 84 EPC 1973 were designed to reflect the principle that the terms of a claim should be commensurate with the invention’s technical contribution to the art. Taking into account the description, the board regarded the division of the image into regions and subsets as essential for achieving the technical effect underlying the invention. Therefore, the subject-matter of claim 1 was not supported by the description. The board concluded that claim 1 did not comply with Art. 84 EPC 1973.
This indicates the need, when drafting claims for computer-related inventions, to provide clear and unambiguous definitions of terms used within the claims. This is especially important when features of the claims relate to abstract entities, e.g. data within a data processing system.
Added Subject Matter and Features without Technical Contribution
In T 1779/09 the board considered that the appellant had found itself exactly in the situation envisaged in decision G 1/93 (OJ 1994, 451). As emphasised in Headnote II of G 1/93, “a feature which has not been disclosed in the application as filed but which has been added to the application during examination and which, without providing a technical contribution to the subject-matter of the claimed invention, merely limits the protection conferred by the patent as granted by excluding protection for part of the subject-matter of the claimed invention as covered by the application as filed, is not to be considered as subject-matter which extends beyond the content of the application as filed within the meaning of Art. 123(2) EPC.” These principles were confirmed in G 2/98 (OJ 2001, 413) and G 2/10 (OJ 2012, 376). The board in the case at issue concluded that a limiting feature which generally would not be allowable under Art. 123(2) EPC could, under certain conditions, nevertheless be maintained in the claim of an opposed patent in the particular situation addressed in decision G 1/93. It then complied with Art. 123(2) EPC by way of a legal fiction. In the case at issue, the term “only” was introduced during the examination proceedings and successfully objected to under Art. 100(c) EPC in proceedings before the opposition division by the former respondent. Since the board considered the term to be truly limiting, its deletion would extend the protection conferred and thereby infringe Art. 123(3) EPC. However, the board held that the exclusive limitation did not influence the solution of the technical problem as understood from the application as originally filed, and hence provided no technical contribution to the claimed invention (see also decision T 384/91, Headnote II). It merely excluded protection of part of the invention described in the application, thus not giving any unwarranted advantage to the applicant. Claim 1 of the appellant’s sole request was therefore deemed to comply with Art. 123(2) EPC.
A presentation given as a CIPA Webinar on 25 February 2014.
Provides an introduction to software as it relates to patenting and an overview of current practice in UK and Europe. Details of relevant legislation and case law are provided, together with some tips for drafting.
Provided according to the terms set out here: http://www.eip.com/legal.php – i.e. does not constitute legal advice and should be taken as guidance.
Following this case, the claims of a patent application are assessed for “technical” and “non-technical” features. Only “technical” features may be used to demonstrate an improvement over previous publications.
The term “technical” is necessarily fuzzy; it has been defined in a piece-meal manner by European case law. However, it is generally taken to mean clearly relating to a field of science or engineering. Features relating to “administration” or “business” are considered “non-technical”.
Useful Case Law
The cases below provide examples of the thinking of the UK Patent Office.
T_0505/09: in this case, an invention related to a method for identifying defective program code. At an abstract level, certain testing techniques were agreed to form part of the common general knowledge. However, there was no objection that the invention related to “non-technical” features. Instead, emphasis was put on what written evidence relating to the invention was published before the application was filed.
T_1893/08: in this case, information on data definitions was provided in the form of a common language file represented in a different language to first and second languages for compilation. The first language had an “import” statement that imported the common language file. The board concluded that compiler features provided a solution to a “technical” problem and did provide an inventive step when compared to the cited art.
T_1216/08: this case featured authentication of software in a dynamic loading environment. A validator generated a digital signature based on a portion of a program image, wherein pointers in the image that required “fixing up” by a program loader were excluded from the portion. Implicitly, these features were considered “technical” and an inventive step was found.
T_0702/08: in this case, a patent claim referred generally to “process objects” and “task objects”. These terms were considered to have a broad meaning encompassing the general concept of a “goal” or “objective” at an administrative management level. It was concluded that there was no unambiguous correlation between the described “objects” and object-oriented programming. Hence, a specific technical mapping between abstract concepts and their technical implementation needs to be set out in any patent application.
T_0077/08: here the main difference between a patent claim and a previous publication was that a business logic rule was expected as an expression rather than a statement in a programming language. It was considered obvious that both formulations would be considered. It was questioned whether making a system more “flexible” was a “technical” problem.
T_2078/07: in this case the invention, using metadata to describe data types, was found not to provide “a further technical effect” over fundamental programming conventions. It was “simply an advice on how to write a program”.
T_1928/07: this case referred generally to “event processes”, “tasks”, “inclusion” and “execution” in a programming context. These terms were not defined in terms of concrete, rather than abstract, features. The case was thus rejected for lacking clarity.
This article is a brief summary of the UK position on patenting inventions associated with computer programming.
In the UK, it may be difficult to obtain a granted patent for inventions relating to computer programming.
These inventions may not be allowed by the UK Patent Office on the basis that they relate solely to a “computer-program”, a “mental act”, a “business method” or a “mathematical method”.
However, while patent applications for application-level software are most likely to be refused, certain improvements at a low, technical level may be allowed.
Defining Cases: Symbian and Halliburton
The defining cases in this area are Symbian and Halliburton (see links for full references).
Symbian concerned adapted dynamic link libraries (DLLs) with two parts: a fixed part and an extension part. Even though it was directed to a method implemented in practice by a computer program, it was found not to be solely a computer program as it made a computer work better as a matter of practical reality. From this case, an improvement at the level of the operating system or below could form the basis of a granted patent. The UK Patent Office appears to dislike the citing of Symbian; frugal use is recommended.
Halliburton made it easier to obtain a granted patent for inventions that could be performed mentally. In the past, these would be rejected. Now, inventions that are described as “computer-implemented methods” are not rejected just because the “method” could be performed mentally.
Hearings from the UK Patent Office in this area suggest it will be difficult, but not impossible, to obtain a granted patent for a computer programming invention.
Much will depend on the language of the patent application and the particular examiner considering the case. It must be shown that there is more than would be expected when simply running a better program on a computer.
Useful Case Law
The cases below provide examples of the thinking of the UK Patent Office.
O/173/08: the invention involved “taking an existing computer program, analysing the instructions … and applying [parallel processing code] substitutions so that the program will operate more quickly”. This may be performed at runtime using a “rules-based system for converting the original code into more efficient code”. This was found to relate to “the generation of more efficient program code rather than an improvement in the operation of the computer system”, i.e. to be an improvement in “programming” and thus excluded for being a “compute program as such”.
O/066/06: in this case, data received from trace units associated with a processor was used to adapt compilation in real time. The Hearing Officer stated that compilers per se were not patentable for being a mental act; it is likely this is now overturned by Haliburton. The result of the invention was “a faster, more accurate compiler, able to adapt and improve in an iterative manner each time the compiler is used”. This was seen to be a “technical” rather than “cosmetic” advantage, and the case was allowed.
O/057/06: this case involved the application of a reduced set of Java® Bytecode instructions, i.e. multiple Bytecode instructions were reduced to a single virtual machine instruction. Even though the Hearing Officer acknowledged that Reduced Instruction Set Computers (RISC) were well known, he found that the application related to a non-obvious “invention” under UK patent law. Following from this a patent should be granted. His logic was that hardware-based RISC processors were unarguably patentable, providing a clear technical effect of being faster and more economical. Hence, a software-based version should not be excluded simply because it is implemented on a programmed computer.
O/036/10: this case involved a simulation system comprising a new arrangement for debugging software enabling a user to locate bugs more quickly and more effectively. Here, however, the computer running the software was “entirely conventional”. The software made “a computer, work differently in the sense of processing data in a different way, but it [did] not make it work better, faster or more reliably in terms of its performance”. No “deep level” technical improvement was located. Thus the application was refused.
* By referring to software in inverted commas I am indicating that the term “software” patent is not often used within the profession, which prefers the terms “computer programs” or “computer-implemented inventions”.
With regard to protecting computer games at the UK IPO see the Practice Notice: