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This issue of the Australian Intellectual Property Journal (Volume 33 Part 3) contains the following material:

EDITORIAL – General Editor: David J Brennan

Articles

A House with Two Masters? Copyright Law and Originality in the Age of Artificial Intelligence – Dilan Thampapillai and Andrew Ray

The emergence of artificial intelligence (AI) and the implications that it has for authorship has created a crisis within copyright law. There has been much debate about whether copyright should permit AI authorship within its borders. However, the major question that needs to be addressed is really what happens after AI-authored or AI-augmented works are permitted within the boundaries of copyright law. What would be the implications for originality? Where works have been concerned, originality has long been the primary doctrinal vehicle gatekeeping entry into the copyright system. A change in the law that would permit AI-authored or AI-augmented works to sit within the system of copyright protection would call that role into question. In this article, we argue that originality will face challenges, but it will survive as a re-purposed doctrine delineating which level of protection a work may enjoy.

“Pay No Attention to that Man behind the Curtain!”: Copyright, Authorship & Artificial Intelligence – Daniela Simone

This article questions the assumed rigidity of copyright law’s concept of authorship in the face of Artificial Intelligence (AI). The first part argues that framing AI systems in anthropomorphic terms obscures the valuable input of those who conceive, create, and operate them (by drawing attention to the “Wizard” rather than those pulling the strings). The second part re-examines the application of copyright’s authorship and joint authorship doctrines to creative processes involving AI, focussing on the input of those “behind the curtain”. Five significant doctrinal challenges human contributors face in establishing authorship are considered. In relation to each challenge, I uncover and explore more flexible and inclusive interpretations of the law than are commonly admitted. The article concludes by proposing that to meet the challenges of the digital age, copyright law needs to rediscover its heart, brains, and courage.

I, Robot: Is IP Law Ready for the Age of AI? (Thaler and Other Provocations to Our Existing Systems) – Dr Louise Buckingham and Michael Williams

We are entering the age of artificial intelligence (AI). Once a matter of science fiction, significant developments in AI are now being regularly reported and the public is becoming more familiar with AI through applications relying on ordinary English language commands. One of the most recent applications, ChatGPT, has given people a taste of what AI may be able to accomplish. While interest in AI is rising, key questions remain about how ready intellectual property (IP) laws are for the revolution it promises to bring. Can AI invent? And even if it can create, can the creations be protected under copyright laws? Recent cases, particularly those pursued by Dr Stephen Thaler reveal a raft of problems with the interaction between AI and inventions and creations under existing IP laws, including whether AI has the legal personality necessary to qualify as an inventor or creator. The resultant category of inventions and creations may be denied any form of protection. Is this the IP system we intend or is it increasingly deficient in addressing the impact of AI, in terms of incentives and regulations around both ingestion and output? These are issues which will be explored in this article.

Is AI Capable of Original Creativity? A Critical Discussion of the Real Impact of AI on IP Regulation – Francina Cantatore and William Van Caenegem

Human creativity is the foundation of all current intellectual property (IP) regulatory frameworks. To understand the real impact of artificial intelligence (AI) on the regulation of IP, we therefore need to consider whether machines can ever be creative in the human sense. Can human creativity be defined, and if so, is there scope for machines to have the necessary attributes to replicate it? Efforts to use deep-learning AI to create works of art, music or written expression are currently no more than transformative imitation. This article argues that human creativity requires more than the ability to manipulate big data sets – it requires autonomy and goal orientation, imagination, responsiveness, observation and reflection, estimation of value, and social sensitivity. It requires an ability to distinguish the important from the trivial. We therefore posit that the existential angst over autonomous AI creation replacing human creativity is overstated.

For the PDF version of the table of contents, click here: New Westlaw Australia – AIPJ Vol 33 No 3 Content

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