Artificial intelligence and inventorship: patently much ado in the computer program
Pheh Hoon Lim, Phoebe Li · Journal of Intellectual Property Law & Practice · 2022
The debate on whether an artificial intelligence (AI) system could be an inventor for the grant of a patent is still making the headlines. Parallel applications submitted to patent offices around the world naming a creativity machine, the Device and Method for the Autonomous Bootstrapping of Unified Sentience (DABUS),1 as inventor have not met with success, leading to appeals in several courts. The matter was dismissed by the US District Court in Thaler v USPTO based on the plain statutory language of the Patent Act and precedent authority of higher courts,2 and, likewise, by the UK Court of Appeal in Thaler v Comptroller General of Patents, Designs and Trade Marks by a 2–1 majority.3 The trial judge in the Australian Federal Court held, however, that DABUS could be an inventor in Thaler v Commissioner of Patents,4 setting aside the Deputy Commissioner’s decision and remitting the matter for reconsideration.5 Pheh Hoon Lim is Senior Lecturer in Law, Auckland University of Technology, New Zealand. Phoebe Li is Senior Lecturer in Law, University of Sussex, England, UK. Sentient AI is still a fiction as existing AI systems are not fully autonomous. Courts in key jurisdictions demonstrate a cautious approach to claims of AI as inventor. General public consensus posits that AI does not pose unique challenges to the intellectual property system. Current frameworks and existing policy alternatives suffice as the key issue relies on ownership instead of inventorship. Inventorship could rest with persons such as the programmer or operator of the AI (and those selecting input or training data) subject to the test for inventive contribution. This would align with most international practice in naming a human inventor while full automation of AI inventions is still a myth. The core arguments in the patent offices and the courts involved the formalities and procedural requirements of naming the inventor in the applications, and, more importantly, the relevance of sentience or humanness of an inventor to the grant of a patent.6 The USA’s legislation defines an inventor as the ‘individual’ who invented or discovered the subject matter of the invention,7 interpreted as a natural person who performed the mental act of ‘conception’. Thus, ‘conception’ which begins in the mind of an inventor is the touchstone of inventorship. In the UK, an inventor must be the actual deviser of the invention with reference to a natural person’s inventiveness in being able to make or create something new.8 In most scenarios, joint inventorship would be claimed when multiple parties contribute to the inventive idea in the research and development phases. Posing the problems to be solved, answering those problems or identifying ways of improving a current solution, would be deemed as inventive contributions. However, financial backing or provision of basic materials or workspace would be non-inventive contributions.9 Despite the subtle difference in the definitions, the result is the same when assessing inventorship for inventions where a human is involved, as shall be demonstrated in the further discussion on the cases in Section 4 below. There is, arguably, no bar to patent eligibility and patentability where an AI system invents something that meets the requirements of novelty, an inventive step or non-obviousness and utility, and sufficiency of disclosure.10 The authors note the distinction between a computer implemented invention (CII) such as the DABUS machine itself (that discloses a type of AI), AI-Assisted and AI-Generated inventions (such as the ‘neural flame’ and ‘fractal container’ inventions by DABUS). In defining AI inventions, it is critical to distinguish between ‘AI-Assisted’ and autonomously ‘AI-Generated’ inventions. Currently, as all AI related inventions still require human input at varying levels, the full automation of an AI invention is thus a myth.11 It is doubtful that DABUS’ ability, ambitiously labelled as an autonomous bootstrapping device, can be said to be fully autonomous as a totally self-organizing system.12 While AI-Assisted inventions pose less significant challenge to the patent system as AI is used as a tool, AI-Generated inventions, on the other hand, leads to major debates on inventorship as it claims AI’s full autonomy in the innovation process. Many do not believe that artificial general intelligence (AGI) akin to human intelligence has arrived, as current AI can neither invent nor author without human intervention.13 Artificial intelligence is best viewed as a subset of computer implemented inventions (CIIs).14 AI inventions may comprise inventions that embody an advance in the AI field (e.g. a new neural network structure of an improved machine learning model or algorithm) or inventions that apply AI to another field and inventions that may be produced by AI itself.15 In terms of computer functionality, AI mimics cognitive functions associated with the human mind and the ability to learn.16 The DABUS machine, based on machine learning algorithms, is computer-implemented with neural network simulations or hardware-implemented neural networks as well as non-silicon-based computational systems. The background of the invention describes attempts made to build artificial neural systems of the size and complexity of the human brain. An artificial neural network has been described as a form of AI used to generate novel ideas (essentially collections of binary switches simulating neurons in a biological brain) to create, in Thaler’s case, a creativity machine that can create new inventions.17 The state of the entire collective of neural modules for joint activations and network chains is detected via machine vision or acoustic processing algorithms18 The thalamobot described in the patent document of DABUS refers to a recognition system based on ‘hot buttons’ that may trigger simulated neurotransmitter release. It may be embodied on a processor in a computer system which is separate from a computer system on which the model of the environment is generated (such as a brain scan). It may then communicate with the brain scan system to modify levels of noise and generate new ideas and promote learning within the model. The thalamic system is used to trigger other algorithms to implement strategies for adaptive learning through fusion with other memories.19 This article probes the fundamental issue on whether a computer program, as a computational tool that brings about a certain result, can be an inventor despite the ingenuity of the algorithms involved. The authors look back at the chequered path of computer programs in the past decades in attaining intellectual property rights under a dual track system of copyright and patent protection to contemplate its place to a claim of inventorship. We then review the relevant DABUS cases in three jurisdictions: the USA, Australia and the UK. 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The has that AI can innovation and creativity and be a tool in new human inventions and that the current pose a to innovation as the of AI systems In the current for inventorship could be improved to a of policy for has been of the which the authors are to is to the of inventor by it to for an AI system which This for recognition of the person who the to be an inventor and the for copyright Inventorship could rest with persons such as the programmer or operator of the AI or those selecting input such as training subject to the test for inventive a human inventor would be in with most international inventorship Inventorship or could be the of the person who made the is not nor akin to non-inventive contributions. the provision of is a or basic (such as the of or the would then be However, the was for the research and development of the then it would be to the person who made the as an inventor. The could be made for to be in the of inventorship at AI inventorship is on the of separate and which is the of that on the and in the existing could be in policy instead of while full automation is still a myth. Phoebe Li was by a grant from the UK and to the on Autonomous and The authors would to the for and on