How Can an Innovative National IP Office Balance Its Roles as Technology Examiner and Technology Developer?

IP Australia incorporates the Australian Patent, Trade Marks, Designs, and Plant Breeder’s Rights (PBR) Offices, the core ‘business’ of which is to provide services to their ‘customers’ in respect of the administration and registration of Australian IP rights.  Indeed, IP Australia may be seen as a significant ‘exporter’ of such services considering that, for example, over 90% of applicants for Australian patent rights are foreign residents, as are over 50% of applicants for design registrations and PBRs.  In respect of its core services, IP Australia holds a true monopoly – no other government or private sector service provider can grant, or otherwise administer, enforceable IP rights in Australia.  IP Australia operates these services on a cost-recovery basis, i.e. it aims to fully recover the costs of service-provision through the official fees that it charges to its ‘customers’.

The scare quotes around the business-oriented terminology in the opening paragraph reflect my scepticism of the fashion for modelling government service provision as a form of business enterprise.  I am not alone in this scepticism.  Writing in the Harvard Business Review last year, Canadian business and management expert Henry Mintzberg noted that ‘[r]unning government like a business has been tried again and again, only to fail again and again’.  He also called the portrayal of citizens as customers a ‘misguided, overworked metaphor’, going on to observe:

Business is essential – in its place. So is government, in its place. The place of business is in the competitive marketplace, to supply us with goods and services. The place of government, aside from protecting us from threats, is to help keep that marketplace competitive and responsible.

Consistently with Mintzberg’s view on the appropriate role of government, IP Australia has a single Outcome under the Australian Government’s budget and accountability framework, which is:

Increased innovation, investment and trade in Australia, and by Australians overseas, through the administration of the registrable intellectual property rights system, promoting public awareness and industry engagement, and advising government.

Recently, however, we have seen IP Australia extending its services into areas that are, arguably, beyond this core mission, and engaging in activities in which it – again, arguably – positions itself in competition with private enterprise.  Examples include:

1. the TM Headstart service and Trade Mark Assist tool which, despite disclaimers that they are not substitutes for legal advice, compete directly with services provided by trade marks practitioners; and
2. the Patent Analytics Hub, which provides analysis, visualisation and interpretation of patent data, and competes directly with various patent search and analytics service providers, albeit ‘only’ for clients in the government and public research sectors – which actually includes some of the largest potential customers for these services in Australia.

Additionally, as I noted just last week, IP Australia is now engaged in its own internal IT development projects, applying machine learning techniques to patent classification and assessment of trade mark applications.  Its Chief Data Officer was also quoted last week by the online IT news outlet ZDNet, speaking on IP Australia’s efforts in relation to improving its business intelligence and analytics capabilities through internal ‘agile’ software development projects.

Just to be clear, I am not saying that all – or any – of this is necessarily a ‘bad’ thing.  IP Australia may, indeed, be the best-placed agency to be delivering these projects.  And, as I also pointed out in my article last week, it has by any standards – public or private sector – demonstrated over the past few years an impressive capability to deliver IT projects in a timely and cost-effective manner.  Certainly, IP Australia is not the only IP authority in the world to be engaging in such activities, with materials from the World Intellectual Property Organization (WIPO) May 2018 Meeting of Intellectual Property Offices (IPOs) on ICT Strategies and Artificial Intelligence (AI) for IP Administration revealing various projects ongoing at WIPO, the European Patent Office, the Russian Patent Office (Rospatent), the German Patent and Trade Mark Office, and others.

Even so, there is an argument to be made that IP Australia, as the agency responsible for regulation of registered IP practitioners (i.e. Australian patent and trade marks attorneys) is, at the same time, competing with those practitioners, albeit in a very limited capacity.  Furthermore, as the agency responsible for examining and registering (or refusing) IP rights in relation to new inventions – including software-based and machine learning technologies – IP Australia is also now itself engaged in developing such technologies.  This raises the question of whether any conflicts of interest arise as a result?  And, if so, what is the nature of those conflicts, and how should they be managed?

Machine Learning System Found Ineligible for Patenting

I was prompted to think about this issue as a result of a Patent Office decision issued late last week, rejecting yet another patent application for a computer-implemented invention on the basis that it was not for a patent-eligible ‘manner of manufacture’: HRB Innovations, Inc. [2018] APO 63.  There have, in fact, been a number of such decisions published recently (it is hard to keep up these days), however this one struck me in particular because it relates to machine learning technology.  In particular, HRB Innovations’ system uses clustering – an ‘unsupervised learning’ technique – to predict which sections of a tax return form (or automated ‘interview’) will be applicable to a given taxpayer based upon analysis of past tax returns of a range of different taxpayers.

Following an analysis of the invention as described in the patent specification, and consideration of the applicant’s submissions, the Hearing Office concluded (at [41]) that:

…it appears clear to me that cluster analysis techniques were part of the state of the art at the relevant time. In this respect, the substance of the invention must therefore relate to the use of cluster analysis to filter information and determine appropriate indicator variables and prototypes, for simplified tax review purposes. Whilst a computer system may be used to perform this in a quicker, more efficient manner, that outcome is not predicated by any enhancement in the computer system itself. That is, the act of using cluster analysis, generally, for its intended purpose, cannot be said to result in improvement in the functioning of the computer.

At one level, this is not an unreasonable conclusion.  I would agree that the ‘mere’ use of a known algorithm, for a purpose to which it is evidently applicable, and resulting in predictable success, should not be patentable.  I would argue, however, that this is more properly a question of obviousness, rather than subject-matter eligibility.  After all, if a person of ordinary skill in the field would look at a problem, quickly form the view that clustering should provide a solution, and then successfully implement that solution via nothing more than routine steps and trials, it can hardly be said that any inventive step has been taken in the process.

The Challenges of Applying ‘Known’ Machine Learning Methods

In my experience, however, machine learning algorithms are rarely so straightforward to apply.  Even if – as appears to be the case here – established clustering algorithms (such as DBSCAN, or OPTICS) are suitable, a problem is still liable to arise in defining something that can be clustered.  You cannot cluster tax returns.  First they must be converted into a suitable numerical form – typically a high-dimensional ‘feature vector‘ of quantities that together capture informative, discriminating and (ideally) independent characteristics of the items (in this case, tax returns) to be analysed.  Sometimes this is relatively straightforward, sometimes it can be automated (although it may not be obvious how or when this will work), and sometimes it will involve extensive efforts in ‘feature engineering’, along with a great deal of trial and experiment, by skilled data scientists.

The Hearing Officer has therefore hit the mark with the statement that ‘the substance of the invention must therefore relate to the use of cluster analysis to filter information and determine appropriate indicator variables and prototypes, for simplified tax review purposes’.  This is, as I understand it, the ‘feature engineering’ aspect of HRB Innovations’ system.

Where I disagree with the Hearing Officer, however, is that I do not consider it relevant whether the outcome is ‘predicated by any enhancement in the computer system itself’, as the decision suggests.  The proper question, in my view, is whether there was any invention involved, in the sense of any problem or difficulty being encountered and overcome by inventive ingenuity, in arriving at a working implementation, complete with an effective feature representation of the items to be clustered.

The outcome in this case might nonetheless be correct.  The onus is essentially on the applicant for a patent to ensure that the specification filed provides a sufficient disclosure to enable the decision-maker to identify and appreciate the nature of the contribution made by the invention to the relevant field of technology.  While I have not taken the time to read HRB Innovations’ specification in detail, it is possible that it contains insufficient detail to identify any ingenuity involved in the process of feature engineering.  But even if it does, to the extent that the Hearing Officer was seeking an ‘enhancement in the computer system itself’ as a basis for patent-eligibility, the applicant may not be in any better position.

Questions Raised by IP Australia’s Multifaceted Role

The correctness or otherwise of the HRB Innovations decision in particular is not, however, the point that I want to make here.  What I wish to highlight by the example is that IP Australia is, on the one hand, developing its own applications of machine learning while, on the other hand, exercising the power to refuse or grant patents relating to machine learning technology.  Indeed, vectorisation, automated feature extraction, and clustering are all techniques with application to areas of specific interest to IP Australia, including document classification, image recognition, and image search.

Now, while I have absolutely no reason to believe that there is any impropriety here – indeed, I would be very pleasantly surprised to discover that anybody at IP Australia has even given any substantive consideration to the issue at this relatively early stage – I do consider that this emerging situation raises questions that would be better addressed sooner rather than later, such as the following.

1. What are the implications of a patent-issuing agency engaging in technology development that – as with such activities in any enterprise – potentially risks infringing the rights of the very same patent-holders that it calls ‘customers’?
2. Should innovative technology developers in the commercial sector – including potential suppliers of technology solutions – be concerned that the patent-issuing agency is in a position to influence or direct policy in relation to the availability and scope of patent rights in areas where it also has an interest as a developer and consumer of technology?
3. Where do the legitimate interests of the wider community lie?  For example, if a government agency develops new and valuable IP in the course of its own internal development programs – including technology with the potential to be exported to other agencies around the world – should citizens have a reasonable expectation that the agency will take steps to identify and protect that valuable IP, just as shareholders would expect of a commercial business?
4. If so, under what conditions would it be appropriate for the Australian Patent Office to examine patent applications filed on behalf of the Commonwealth of Australia for inventions developed within IP Australia?

In relation to the last two points, it should be noted that this is not a situation that is completely without precedent – there is generally a number of patent applications filed each year in the name of the Commonwealth of Australia, including some that originate within the Department of Industry, Innovation and Science, which houses IP Australia.

Conclusion – No Easy Answers

I do not claim to have good answers to any of the above questions.  Certainly, whatever solutions there might be are not black-and-white.  It is not, for example, a matter of simply concluding that IP Australia should not be getting itself involved in any grey areas.  I actually think it is very positive that IP Australia is adopting an innovative approach to the delivery of its services.  Indeed, the agency is particularly well-placed to do this.  More than a third of staff in the examinations area at IP Australia hold masters or doctorate degrees, making them a potent resource for innovation.  As the recently-retired Director General Patricia Kelly has explained:

It wasn’t I who came forward and said, ‘Let’s look at AI and blockchain!’  The examiners, like everyone, are concerned about how AI will affect jobs. They came up with 80 suggestions on how AI could help, and they were pared down to about 17 or 18 impressive ideas.

The irony here is that IP Australia must know how much it is investing in its internal technology development, including its machine learning initiatives.  It must therefore also know that these costs are non-trivial, and that it is not at all routine or straightforward to make these technologies work effectively and at a production-ready level of quality and consistency.  And yet, with its other hand it is denying patent rights for inventions in this field on the basis that they do not make a sufficient contribution to the art to qualify for protection.  If that is right, then maybe those examiners’ ideas were not so ‘impressive’ after all.

Tags: Australia, Machine learning, Patent Office, Patentable subject matter, Public policy