Three Laws Blog: Law and Artificial Intelligence

Heidi Härkönen on The Impact of AI on the Fashion Section: A Moral Rights' Perspective @FashionLawHeidi @UniTurkuLaw @eLAWnora @Ire_Calboli @routledgebooks

Heidi Härkönen, University of Turku Faculty of Law, is publishing The Impact of Artificial Intelligence on the Fashion Sector: A Moral Rights’ Perspective in Routledge Handbook of Fashion Law (E Rosati and I Calboli, eds. Routledge, 2024). Here is the abstract.

This chapter discusses the copyright-related impacts that sophisticated artificial intelligence (AI) has on authors in the fashion sector. The increasing use of AI in fashion design may threaten the position of human designers, as AI is cost-efficient and, unlike human designers, is not entitled to IP rights over its ‘creations’. The fashion sector should be concerned about AI’s effects on human designers because they are already in a vulnerable position in the fashion value chain. From a copyright standpoint, the practices of the fashion industry in relation to the treatment of (human) designers are questionable. This is particularly visible in the way designers’ moral rights are systematically ignored, diluting designers’ authorial role and transparency in terms of the source of designs. At the same time, fashion companies’ increasing use of AI raises further transparency issues regarding the origin of designs, causing uncertainty both for consumers and rivals. Increasing attention to designers’ moral rights, in particular the right of attribution, could help to improve human designers’ position, balance the unjust status quo, and increase transparency. Moreover, a functional equivalent of the right of attribution to AI-generated output would improve transparency in fashion and creative sectors in general.

Download the chapter from SSRN at the link.

Lucchi on ChatGPT: A Case Study on Copyright Challenges for Generative AI Systems

Nicola Lucchi, Universitat Pompeu Fabra, Department of Law, has published ChatGPT: A Case Study on Copyright Challenges for Generative AI Systems at 2023 European Journal of Risk Regulation 1. Here is the abstract.

This article focuses on copyright issues pertaining to generative artificial intelligence (AI) systems, with particular emphasis on the ChatGPT case study as a primary exemplar. In order to generate high-quality outcomes, generative artificial intelligence (AI) systems necessitate substantial quantities of training data, which may frequently comprise copyright protected information. This prompts inquiries into the legal principles of fair use, the creation of derivative works, and the lawfulness of data gathering and utilization. The utilization of input data for the purpose of training and enhancing AI models presents significant concerns regarding potential violations of copyright. This paper offers suggestions for safeguarding the interests of copyright holders and competitors, while simultaneously addressing legal challenges and expediting the advancement of artificial intelligence technologies. This study analyzes the ChatGPT platform as a case example to explore the necessary modifications that copyright regulations must undergo to adequately tackle the intricacies of authorship and ownership in the realm of AI-generated creative content. Note: Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

Download the article from SSRN at the link.

Iaia on To Be, or Not To Be...Original Under Copyright Law, That Is (One of) the Main Questions Concerning AI-Produced Works @UniLUISS @GrurInt

Vincenzo Iaia, Luiss University, has published To Be, or Not to Be … Original Under Copyright Law, That Is (One of) the Main Questions Concerning AI-Produced Works at 71 GRUR International IX (2022). Here is the abstract.

This paper examines whether different types of AI-produced works, namely AI-assisted, AI-generated, and AI-genassisted works, are able to satisfy the originality requirement, as established within the EU copyright acquis. It will argue that even assuming that the choices of AIs can be deemed free, they could not be considered creative due to the anthropological footprint of copyright law which traditionally covers only human creativity. This implies that copyright protection can be granted only to outputs that display a sufficient level of original human intervention, which is most likely present in AI-assisted works and, depending on the case, in AI-genassisted works, too. The desirability of stretching copyright further to accommodate artificial creativity is also lessened by the risk that it could saturate the creative market due to an overexpansion of monopoly rights. Thus, the copyright solution will be evaluated together with some existing alternative legal tools, such as neighbouring rights, sui generis rights, patents, or even the absence of protection over AI-generated works to preserve a robust public domain.

The full text is not available for download from SSRN.

Joh on Equitable Legal Remedies and the Existential Threat to Generative AI @elizabeth_joh @UCDavisLaw

Elizabeth E. Joh, University of California, Davis, School of Law, Equitable Legal Remedies and the Existential Threat to Generative AI. Here is the abstract.

Generative AI programs like ChatGPT and Midjourney can produce text, images, and video because their models have been trained on vast amounts of books, pictures, art, and other media found on the internet. Training a large language model like ChatGPT, for instance, to “learn” patterns and relationships in billions of words allows these models to produce written text responsive to prompts. But these models have trained on digital information like novels and original art without obtaining permission. Unsurprisingly, the release of these generative AI tools has already prompted lawsuits by individuals and companies alleging that the use of their artistic works in the development of these models violates copyright law. Whether reliance on this type of training data violates copyright, and whether the outputs based on the training data constitute infringing derivative works are open and difficult questions. But these copyright claims also raise a separate issue: can plaintiffs seek remedies that would destroy generative AI programs?

Download the essay from SSRN at the link.

Senftleben on Generative AI and Author Remuneration @ivir_uva

Martin Senftleben, Institute for Information Law, University of Amsterdam, has published Generative AI and Author Remuneration. Here is the abstract.

With the evolution of generative AI systems, machine-made productions in the literary and artistic domain have reached a level of refinement that allows them to substitute human creations. Inevitably, the increasing sophistication of AI systems will disrupt the market for human literary and artistic creations. Generative AI systems provide literary and artistic output much faster and cheaper. It is foreseeable that authors of flesh and blood will be exposed to replacement effects. They may lose income due to machine substitution in sectors ranging from journalism and writing to music and visual arts. This development has a broader societal dimension. Human creations offer important impulses for the improvement of social and political conditions – impulses which AI-generated literary and artistic output is unlikely to provide. To enable human authors to continue their socially valuable work and devote time and effort to the creation of critical reflections of societal conditions, it is advisable to introduce remuneration rules that offer financial support for human literary and artistic creativity. The rights reservation option following from the regulation of text and data mining in the EU (Article 4 of the Directive on Copyright in the Digital Single Market) could serve as a basis for a remuneration system focusing on the use of human creations for AI training purposes. Considering legal and practical difficulties arising from this approach, however, it is preferable to follow an alternative path and introduce a levy system that imposes a general payment obligation on providers of generative AI systems. In contrast to remuneration systems based on AI training activities, this alternative approach does not weaken the position of the European AI sector and the attractiveness of the EU as a region for AI development. Even more importantly, an output-oriented AI levy system can be combined with mandatory collective rights management. The levies collected can be used to finance social and cultural funds that improve the living and working conditions of human authors. It is thus possible to ensure that the new revenue stream reaches individual creators directly and supports their creative work.

Download the article from SSRN at the link.

Bonadio and Trapova on Property Law in Gaming and Artificial Intelligence @enricobonadio @alinatrapova @CityLawSchool @ucl

Enrico Bonadio, City University London, The City Law School, and Alina Trapova, University College London, are publishing Property Law in Gaming and Artificial Intelligence in Handbook on Property Law & Theory (Chris Bevan, ed., Elgar) (Forthcoming). Here is the abstract.

This chapter focuses on copyright and patent aspects of AI in gaming. As is known, copyright law protects original creative expression, while patents safeguard new inventions capable of industrial application. On the copyright side, the central classic question is what video games are in terms of protectable subject matter. This issue of the video games’ legal nature is rather old, but still pertinent topic. By now, it has been widely accepted that video games are complex subject matter from a copyright perspective, comprising not just a software, but also graphic and sound elements that contribute to the unique creative value of the game. That said, different jurisdictions adopt varying approaches to the nature of video games with some classifying them as predominantly computer programs and others dissecting the different elements in the game or treating the game as an audio-visual work as a whole. Patents instead have historically attracted less attention. Nonetheless, these can be extremely important for some hardware, software, development tools and other middleware companies, but as it currently stands the considerable cost tied to patents renders them less utilised in the field. Against this background, AI has stepped in to not only disrupt classical IP models, but to also offer a wide range of immersive interactive experiences for gaming; thus, opening new avenues for exploitation. As far as copyright law is concerned, the infusion of an AI element into the game provokes questions of authorship when it comes to in-game creativity. Put differently, who is the author and owner of creative expressions when they are created by players within the context of playing the game where certain interactions are driven (and often dictated) by AI? When it comes to patents and AI in this industry, central issues revolve around whether inventions covering the video games’ mechanics constitute patentable subject matter because they have technical features (and not just an unpatentable set of rules developed to be executed by hardware including a console or computer); and in general, whether patents protecting video games are too broad so as to discourage technological progress in this field. This chapter starts with a brief explanation of the influence of AI in gaming (Section 2). It then moves to sketch out the copyright law authorship and in-game creativity challenges (Section 3). Next, it turns to the several patent law conundrums in the field (Section 4). The final part (Section 4) concludes the discussion by arguing that while AI in gaming has been rather recently implemented, the fast pace with which this creative industry develops will certainly quickly transform the experience of video game players, but also the manner in which one understands (intellectual) property in-game.

Download the chapter from SSRN at the link.

Kasdan and Pattengale on Once Thought Far-Off-In-The-Future Challenges to Copyright Law Posed by Artificial Intelligence Have Arrived: And I for One-Gulp-Welcome Our New Robot Overlords @michaelkasdan @WigginandDana @nyulaw

Michael Kasdan, NYU School of Law, and Brian A. Pattengale, Wiggin and Dana, LLP, are publishing Once Thought Far-Off-In-The-Future Challenges to Copyright Law Posed by Artificial Intelligence Have Arrived: And I for One—Gulp—Welcome Our New Robot Overlords in 58 les Nouvelles--Journal of the Licensing Executives Society (March 2023). Here is the abstract.

While we are still not in the realm of sentient machines, current-day iterations of artificial intelligence (AI) are demonstrating themselves to be potential sources of creativity which are challenging our understanding of authorship in the context of intellectual property. If AI can create new content based upon its “perceptions,” how is that distinct from human authorship and furthermore, how does or how should AI fit into the current U.S. copyright landscape?

Picht and Thouvenin on AI & IP: Theory to Policy and Back Again: Policy and Research Recommendations at the Intersection of Artificial Intelligence and Intellectual Property @UZH_en

Peter Georg Picht and Florent Thouvenin, both of the University of Zurich Institute of Law, have published AI&IP: Theory to Policy and Back Again Policy and Research Recommendations at the Intersection of Artificial Intelligence and Intellectual Property. Here is the abstract.

The interaction between artificial intelligence (AI) and intellectual property rights (IPRs) is one of the key areas of development in intellectual property law. After much, albeit selective, debate, it seems to gain increasing practical relevance through intense AI-related market activity, an initial set of case law on the matters, and policy initiatives by international organizations (e.g. WIPO, EPO) and lawmakers. Against this background, Zurich University’s Center for Intellectual Property and Competition Law (CIPCO) is conducting, together with the Swiss Intellectual Property Institute (IPI), a research and policy project that explores the future of intellectual property law in an AI context. This paper briefly describes the AI/IP Research Project and presents an initial set of policy recommendations for the development of IP law with a view to AI. The recommendations address topics such as AI-inventorship in patent law; AI-authorship in copyright law; the need for sui generis rights protecting innovative AI output; rules for the allocation of AI-related IPRs; IP protection carve-outs in order to facilitate AI system development, training, and testing; the use of AI tools by IP offices; suitable software protection and data usage regimes.

Download the article from SSRN at the link.

Trapova on Intellectual Property Law and Artificial Intelligence @alinatrapova @Elgar_Law

Alina Trapova, University of Nottingham School of Law, is publishing Intellectual Property Law and Artificial Intelligence in Encyclopedia of International Economic Law (Krista Nadakavukaren Schefer and Thomas Cottier, eds., Edward Elgar Publishing). Here is the abstract.

This entry looks at the interaction between intellectual property law (specifically copyright and patents) and artificial intelligence.

Download the essay from SSRN at the link.

Carroll on Rules of Engagement: Copyright and Automated Gatekeepers @SHULawReview @AUWCL @MikeCarroll_US

Michael W. Carroll, American University College of Law, has published Rules of Engagement: Copyright and Automated Gatekeepers’ Influence on Creative Expression at 52 Seton Hall Law Review 1137 (2022). Here is the abstract.

This Essay turns questions about artificial intelligence and copyright law around. Rather than focus on algorithms as potential authors, this Essay argues for more attention to the role of algorithms as gatekeepers on social media and how creators adapt their creative choices to meet the demands of these automated tastemakers. Using TikTok’s “For You” algorithm and its role in breaking Lil Nas X’s hit song “Old Town Road” as a case study, this Essay poses the question whether algorithmic gatekeeping is simply a difference in degree or a difference in kind from an artist’s perspective. While tentative, this Essay concludes that this change is a difference in kind because of the rule-bound nature of software, the absence of transparency and accountability for algorithmic decisionmaking, and the flawed data models that inform this form of cultural gatekeeping.

Download the essay from SSRN at the link.