*Please note that the links to the content in this Part will direct you to Westlaw AU.<\/p>\n
To purchase an article, please email: LTA.Service@thomsonreuters.com<\/a> or contact us on 1300 304 195 (Australian customers) or +61 2 8587 7980 (international customers) during business hours (Mon-Fri, 8am-6pm AST).<\/p>\n This issue of the Australian Intellectual Property Journal<\/em> (Volume 33 Part 2) contains the following material:<\/p>\n EDITORIAL<\/a> \u00e2\u20ac\u201c Special Guest Editor: Dilan Thampapillai<\/em><\/p>\n Click here to access on New Westlaw<\/a><\/p>\n Optimising Intellectual Property in the Age of AI Creativity: Perspectives from the United States<\/strong><\/em><\/a> \u00e2\u20ac\u201c David J Kappos and Kevin M Kuate Fodouop<\/p>\n Artificial Intelligence (AI) is increasingly becoming a subject of, and contributor to, innovation across industries. These AI-related inventions raise important intellectual property (IP) law issues, most notably under copyright and patent law. Copyright law must grapple with the issue of \u00e2\u20ac\u0153AI as author\u00e2\u20ac\u009d and patent law faces the issue of \u00e2\u20ac\u0153AI as inventor\u00e2\u20ac\u009d. AI also raises novel challenges for patent law\u00e2\u20ac\u2122s subject matter eligibility, non-obviousness and disclosure requirements. Additionally, AI implementers and other data owners should consider how IP can protect data \u00e2\u20ac\u201c the fundamental ingredient of all AI systems. As AI continues to rapidly transform every industry and field of innovation, AI implementers and data owners should take proactive steps to stay ahead of the curve in adapting to corresponding changes in available IP protection for their AI and data assets. This article provides AI implementers with 10 practical steps to begin the process of optimising their AI-related IP.<\/p>\n Click here to access article on New Westlaw<\/a><\/p>\n Beyond AI Ownership; or, the Continuing Problem of Software Patenting in the AI Landscape<\/strong><\/em><\/a> \u00e2\u20ac\u201c Shubha Ghosh<\/p>\n Artificial intelligence (AI) developments point to new futures, which can be better understood by looking back at the developments in computer science and software copyright. This article attempts to illuminate that past while setting forth a responsive path for AI patent law and policy. In many ways, AI patenting continues the problems arising from software patents. Furthermore, AI inventions resuscitate the debates over man and machine that bedeviled the field of cybernetics. This article has elaborated upon the intersection between AI theory and software theory, drawing on developments in computer science, to set forth the conceptual issues of AI, software, and patenting.<\/p>\n Click here to access article on New Westlaw<\/a><\/p>\n Artificial Intelligence and the Right to Communicate to the Public in Copyright: Lessons from the United States<\/strong><\/em><\/a> \u00e2\u20ac\u201c Cheryl Foong<\/p>\n Automated systems increasingly determine what copyright consumers encounter on online platforms. If an Artificial Intelligence (AI) system selects copyright content and communicates it to the public, should the platform proprietor be liable for infringing that right and on what basis? This article analyses United States (US) and Australian copyright law on the right to communicate to the public and contrasts strict liability principles (such as volition) with fault-based secondary liability principles. Importantly, it analyses the policy considerations underlying these legal principles and critically evaluates the suitability of current laws to address automated communications. This article explains how Australian law could draw from US vicarious liability principles to address AI-facilitated communications, as such principles could bridge the gap between strict and fault liability. The principles provide a more nuanced approach that permits consideration of the characteristics of AI systems on a case-by-case basis, rather than casting a wide net that extends primary infringement to all choices delegated to AI systems.<\/p>\n Click here to access article on New Westlaw<\/a><\/p>\n The EU Copyright Exceptions for Text and Data Mining: (Un)suitable Model Solution for the Development of Artificial Intelligence?<\/strong><\/em><\/a> \u00e2\u20ac\u201c Novak Vuji\u00c4\u008di\u00c4\u2021<\/p>\n Two copyright exceptions for text and data mining (TDM) have been recently introduced in European Union (EU) law. The first \u00e2\u20ac\u0153stronger\u00e2\u20ac\u009d exception covers TDM conducted for the narrow purposes of scientific research by research organisations (non-profit or tasked with a public interest mission) and cultural heritage institutions. The second \u00e2\u20ac\u0153weaker\u00e2\u20ac\u009d exception refers to TDM in general, but the rightholders have the power to opt out from it (and after doing so, to license TDM of their content). These exceptions have become a target of immense criticism concerning their (un)suitability to adequately support further development of artificial intelligence in the European Union. This article offers an overview of both the EU TDM copyright exceptions and the ongoing critical discussions accompanying them. The aim is to determine what lessons and\/or guidelines could be drawn from this EU experience for other countries that might be considering the introduction of a TDM copyright exception in their national laws.<\/p>\n Click here to access article on New Westlaw<\/a><\/p>\n For the PDF version of the table of contents, click here: Westlaw AU – AIPJ Vol 33 No 2 Contents<\/a> or here: New Westlaw Australia – AIPJ Vol 33 No 2 Contents<\/a>.<\/p>\n Click here to access this Part on Westlaw AU<\/a><\/p>\n Click here to access this Part on New Westlaw AU<\/a><\/p>\nArticles<\/h3>\n