Browsing by Subject "Copyright"

Artificial Intelligence (AI) has become an ubiquitous technology in society with ever more diverse applications. Different AI systems have become especially pervading in the domain of creative arts, where they can near-autonomously generate content. For example, there is a number of software that allow generation of musical output with minimal specifications from the user of the AI system. Where the creative process combines human and machine labor, results of such joint efforts can be called ‘AI-assisted output’. Ascertaining the legal status of AI-assisted output forms the crux of this Master’s thesis. On one hand, the research is concerned with the copyrightability of AI-assisted output. This question pertains to musical output produced with the assistance of illustrative AI systems of AIVA and Jukebox. The research adopts a legal comparative method in this regard: it seeks to assess how the copyright laws of EU and England could accommodate the AI-assisted output. Evidently, the focus in the analyses of the respective systems will revolve around their conceptions of originality, the key requirement to qualify for copyright protection. As a counterpart for the legal comparative study into the feasibility of copyright protection of AI-assisted output, the second prong of the research probes into the desirability of protecting such output. In other words, the research seeks to establish the merits of protecting AI-assisted outputs by juxtaposing the underlying, theoretical rationales of copyright law against AI-assisted output. To this end, the research aims to survey how the relationship between the human author and AI system interacts with the different rationales of copyright. Against this backdrop, the research preludes by looking into the foundations of AI and the selected legal systems. AI is examined retrospectively with a view on how the technology has emerged and how machine learning, the most prominent method of modern AI, has significantly increased the autonomy of AI systems. The illustrative AI systems of the research, AIVA and Jukebox, match the foregoing trends. However, in exploring the features of the systems, variance can be perceived in the amount of influence the user may be able to exert in the creative process of the musical output. The research then proceeds to provide a thorough picture of the framework of copyright law. In the first half of the section, the origins of the law are traced back to the civil law and common law traditions that underlie most copyright systems. Thereafter, the utilitarian and deontological rationales that underpin those systems are discussed including an exposition of the legal and economic discipline’s relationship with copyright law for later discussion. The second half of the section zeroes in on the copyright laws of the selected legal systems. It first notes the influence from the international framework of copyright and some general discussion on AI and its output on that level. Following up, the respective schemes of awarding copyright protection under EU and English law are broken down into their constituent parts. As per alluded, the crux of the analyses are on their respective standards of originality. In the EU, the notion is construed as an exercise of identifying ‘author’s own intellectual creation‘; specifically, the CJEU is concerned with the identification of creative choices that can take place in different phases of the creative process. In England, the standard of originality denotes first and foremost origination: the pertinent artifact should originate from the author and no one else. In addition, the English standard seeks to establish the exercise of skill, labor and judgment in its creation of the right kind. In the analytic section of the research, the illustrative systems of AIVA and Jukebox are then related against the copyright systems. The section begins with an application of the standards of EU and England against the output from the AI systems in abstract; no concrete samples from the systems are studied but rather the focus is on how their users may harness their features. Herewith, the amount of user engagement in the creative process becomes the key in both system; where the user can apply creative choices in the different phases of the production or alternatively exert skill, labor and judgment as opposed to mere generation off output with the systems, there is very likely an original work at stake. Hereby, the two AI systems diverge when examined in isolation; whereas AIVA provides the user with a vast amount of tools to interact with their product, Jukebox has little to offer in terms of post-processing. Accordingly, whereas output from AIVA would very unlikely fail to meet the standards of either jurisdiction, output from Jukebox could potentially be barred where no human intervention can be perceived from the final product. The section concludes with a survey of alternative forms of protections for AI-assisted output. As per the foregoing discussion, it is noted how the deontological rationales have limited application in justifying the protection of output that have minimal human involvement. It follows that the economic-utilitarian grounds are emphasized and options that spur therefrom. The related rights regime, a new sui generis right and alternatives that disregard considerations of originality and authorship are explored with alike conclusions: the alternatives do not serve as a backdoor protection but are rooted in valuing socially beneficial activities. Evidently, with AIVA and Jukebox, it would have to be evidenced that their generated output merits protection from a market failure. In light of the foregoing discussion, there is no such substantiation. Accordingly, it would be best to leave AI-assisted output in the lower end of the spectrum of human interaction well alone to preserve the balance between private and public interests.