IP Australia (the Australian Patent Office) has recently refused a patent application filed by PayPal directed at machine learning models that tailor recommendations to consumers at the point of completing an online purchase with the aim of boosting consumer purchases and donations.
Paypal argued that the invention was technical – in that it solved the problem of applying machine learning to generate more accurate recommendations for customers, and that it was not a mere business idea. However, the application was refused on the basis that the system was not a ‘manner of manufacture’ within the meaning of section 18(1) of the Patents Act 1990 (Cth).
The test for whether computer implemented inventions meet the ‘manner of manufacture’ requirement is in a continuing state of flux following the split 3-3 decision of the High Court in 2022 (Aristocrat Technologies Australia Pty Ltd v Commissioner of Patents [2022] HCA 29). The split decision of Australia’s highest court means that the Full Court’s decision in that case stands, and that a single judge of the Federal Court is bound to follow it (but this is not the case in relation to other Full Federal Courts that may consider this issue).
The starting point in Australia is that a business method, or mere scheme, is not, per se, patentable. Where there is a computer involved, the computer must be integral to the invention and not simply the mechanism by which the invention is performed (Commissioner of Patents v RPL Central Pty Ltd [2015] FCAFC 177).
In this decision, the Delegate agreed with the Examiner and found that the invention was not technical in nature. While it utilised machine learning models to determine a personalised recommendation to the customer, the Delegate said that the invention did not relate to an improvement in the machine learning techniques, but to known techniques, utilised in a conventional way, to operate on specific data sets to product the recommendations.
Conventionally, to increase customer engagement, it was common at the priority date (December 2018) for additional purchase suggestions to be made to consumers when they were completing an online purchase. For example, a pop-up notification suggesting that the customer make a donation to a charity. However, these recommendations are not tailored to the specific consumer – but are made based on the popularity of the product or service being recommended.
PayPal’s system feeds information regarding a consumer who is completing a transaction into two machine learning models:
The recommendation scores generated by these models are then used as inputs to train an ensemble model that calculates a total recommendation score. This score is unique to each consumer.
The system presents the recommendation generated by the combination of the three machine learning models to the consumer at the checkout.
In determining whether an invention is a mere scheme or business method, or potentially patentable subject matter, consideration will be made of factors such as whether the:
PayPal submitted that the invention is a unique ensemble model trained by outputs from two other machine learning models that provides customised recommendations to consumers. As a result, the computer in PayPal’s system functions as an intelligent advisor, rather than an intermediary that implements a business method.
In this regard, Paypal relied on the observations of the Full Federal Court in Commissioner of Patents v RPL Central Pty Ltd [2015] FCAFC 177, in which the Court made a distinction between computers that function as an intermediary, and one that functions as an advisor:
"The computer is, in effect, operating as an intermediary in the user’s quest for an evaluation of his or her competency for a particular course and entitlement to obtain a qualification without participating in that course. However, the computer does not evaluate the user’s input to provide the answer. It is not functioning in the nature of an advisor or an artificial intelligence. Rather, the programming allows for a series of prepared words to be prepended to the user information, to turn the statement into a question," [emphasis is the Delegate’s]
From this, PayPal said that a data processing system functioning in the nature of an advisor or an artificial intelligence would be a manner of manufacture. The Delegate did not accept Paypal’s submission.
She found that the system did not involve a manner of manufacture within the meaning of the Patents Act on the basis that the invention was an abstraction or scheme:
“While this may be a complicated arrangement for data processing, it remains to my mind simply a scheme for processing data, with no improvement or adaptation to computer function which might afford patentability. For completeness, I do not consider that an application of machine learning must inevitably lead to an invention that is technical in substance simply because of the requirement for technical elements. All inventions implemented on computers inherently require technical elements, but the outcomes in [other recent Australian court cases concerning the patentability of computer implemented methods] clearly demonstrate that this is not sufficient to found patentability; something more is required”.
She also was not swayed by the fact that the application had been accepted in the USA.
This is the second recent decision in which IP Australia has rejected submissions that rely on the reasoning from RPL Central regarding artificial intelligence. In 2022, a patent application filed by Accenture for a machine learning based system that manages workplace incidents was also refused.
As to whether machine learning tools are patentable in Australia, this assessment must be made on a case-by-case basis. However, this decision serves as a reminder to potential patentees that, based on the current state of the law in Australia, the application of machine learning via a computer will not, without more, be patentable.