Three Laws

Goold on Artificial Authors: Case Studies of Copyright in Works of Machine Learning

Patrick Russell Goold, City University London, The City Law School, has published Artificial Authors: Case Studies of Copyright in Works of Machine Learning in volume 67 of the Journal of the Copyright Society of the USA (2020). Here is the abstract.

The Article investigates whether creative works produced via machine learning algorithms qualify for copyright protection. Previous research into this question has been largely theoretical. By contrast, the Article introduces four empirical case studies of works produced via machine learning. The Article examines the copyrightability of such works under U.S., E.U., and U.K., law. The Article concludes that such works are sufficiently original to qualify for copyright protection. This conclusion casts into doubt prior literature that finds works of machine learning algorithms to be outside the scope of copyright protection.

Download the article from SSRN at the link.

Specht on Copyright Protection for Algorithm Products @louisa_specht

Louisa Specht, University of Bonn, is publishing Copyright Protection for Algorithm Products? in Wettbewerb in Recht und Praxis 2021. Here is the abstract.

A portrait of a somewhat pale-looking man painted in a style of an artist dead for over 340 years now: “The Next Rembrandt” is an incredibly realistic 3D print work created in 2016 based on data mined from 346 original Rembrandt paintings via algorithm. When the line between man and machine blurs, our existing laws governing inherent anthropocentric rights reach their limits of adequacy — such as copyright protections. Are such algorithm generated works copyright protected and shall they be copyright protected? Do we need to change copyright to protect them? The paper proposes a "phase model" for copyright protection of such algorithm products de lege lata and a new neighboring right de lege ferenda.

Download the article from SSRN at the link.

Liebesman and Young on the AI Author in Litigation @tjsl @SLULAW @AUWCL

Yvette Joy Liebesman, Saint Louis University School of Law, and Julie Cromer Young, Thomas Jefferson School of Law and American University College of Law, have published The AI Author in Litigation at 69 Kansas Law Review 103 (2020). Here is the abstract.

Many scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity. . However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on another’s. A cause of action is meaningless if a copyright owner cannot enforce it by suing the infringer or if the infringer is judgement-proof. Thus, when contemplating whether an emancipated AI—or any non-human—can be an author under the Copyright Act, part of that examination should be whether the AI which created the work can sue or be sued for infringement. . This article considers issues from the theoretical, like civil procedure and remedies, to the practical, such as legal representation and discovery. How is an AI served with a lawsuit? What would be an adequate, enforceable remedy for an AI’s infringement? Is an AI even bound by our laws? Additional questions—and procedural barriers—are raised when considering other roles an AI might play in an infringement action: as a witness, a co-party, or even a plaintiff seeking to protect its own creative expression. . This morass of legal headaches goes beyond any doctrinal issues regarding authorship, and provide ample reason to keep legal authorship in the hands of humans or entities controlled by humans—at least until legal procedure catches up to technological realities and possibilities for litigation that AI parties present.

Download the article from SSRN at the link.

White and Matulionyte on AI Painting the Bigger Picture for Copyright Ownership @rita_matu

Courtney White (no affiliation) and Rita Matulionyte, Macquarie Law School, have published Artificial Intelligence Painting The Bigger Picture For Copyright Ownership. Here is the abstract.

To receive copyright protection in Australia works must be original, amongst other requirements. The originality standard involves ‘independent intellectual effort’ that originates from an actual person. The reality of today’s creativity domain is that works are not always originating from actual persons. Due to impressive advancements in technology, some works are being created by artificial intelligence and without the involvement of an actual person. These works cannot meet copyright requirements under current law and subsequently do not receive copyright protection. This paper endeavours to answer a two-tiered question posed by the challenges artificial intelligence works have on traditional concepts of copyright. Firstly, should copyright subsist in works created by AI? Secondly, who would possibly be the copyright owner for such works? Answering these questions involves a discussion of utilitarian and natural rights theories and references to US and UK discussions on the conversation around copyright and artificial intelligence.

Download the article from SSRN at the link.

Craig and Kerr on the Death of the AI Author @CraigCarys @ianrkerr

Carys J. Craig, Osgoode Hall Law School, and Ian R. Kerr, University of Ottawa, Common Law Section, have published The Death of the AI Author. Here is the abstract.

Much of the second-generation literature on AI and authorship asks whether an increasing sophistication and independence of generative code should cause us to rethink embedded assumptions about the meaning of authorship, arguing that recognizing the authored nature of AI-generated works may require a less profound doctrinal leap than has historically been suggested. In this essay, we argue that the threshold for authorship does not depend on the evolution or state of the art in AI or robotics. Instead, we contend that the very notion of AI-authorship rests on a category mistake: it is not an error about the current or potential capacities, capabilities, intelligence or sophistication of machines; rather it is an error about the ontology of authorship. Building on the established critique of the romantic author figure, we argue that the death of the romantic author also and equally entails the death of the AI author. We provide a theoretical account of authorship that demonstrates why claims of AI authorship do not make sense in terms of 'the realities of the world in which the problem exists.' (Samuelson, 1985) Those realities, we argue, must push us past bare doctrinal or utilitarian considerations of originality, assessed in terms of what an author must do. Instead, what they demand is an ontological consideration of what an author must be. The ontological question, we suggest, requires an account of authorship that is relational; it necessitates a vision of authorship as a dialogic and communicative act that is inherently social, with the cultivation of selfhood and social relations as the entire point of the practice. Of course, this ontological inquiry into the plausibility of AI-authorship transcends copyright law and its particular doctrinal conundrums, going to the normative core of how law should — and should not — think about robots and AI, and their role in human relations.

Download the article from SSRN at the link.

Schoenberger on Deep Copyright: Up--and--Downstream Questions Related to Artificial Intelligence and Machine Learning @d_schoenberger

Daniel Schoenberger, Google Inc., Google Zuerich, has published Deep Copyright: Up - And Downstream Questions Related to Artificial Intelligence (AI) and Machine Learning (ML) at Droit d’auteur 4.0 / Copyright 4.0 145 (Jacques De Werra, ed., Geneva and Zurich, Schulthess Editions Romandes, 2018).

Artificial intelligence (AI) systems are increasingly capable of taking over tasks that until recently required cognitive abilities, such as the creation of literary texts, melodies or images. Already commercial applications reach the market, whose outputs would arguably be considered as creative, if produced by a human author. Also, systems have become capable of translating all kinds of text including prose between dozens of languages. One enabler for this development is (deep) machine learning (ML), which may require input from copyrighted works to train the respective models in becoming “creative”. The present essay discusses some of the legal and philosophical issues that arise from these developments, looking both at the status of the “downstream” generated works, and the possible constraints that copyright law might impose on the materials the systems need for learning and hence for their “upstream” modelling.

Download the essay from SSRN at the link.

Abbott on AI, Big Data, and Intellectual Property: Protecting Computer-Generated Works in the UK @LawAtSurrey

Ryan Abbott, University of Surrey School of Law; UCLA School of Medicine, is publishing Artificial Intelligence, Big Data and Intellectual Property: Protecting Computer-Generated Works in the United Kingdom in Research Handbook on Intellectual Property and Digital Technologies (Tanya Alpin, ed., Elgar Publishing) (forthcoming). Here is the abstract.

Big data and its use by artificial intelligence (AI) is changing the way intellectual property is developed and granted. For decades, machines have been autonomously generating works which have traditionally been eligible for copyright and patent protection. Now, the growing sophistication of AI and the prevalence of big data is positioned to transform computer-generated works (CGWs) into major contributors to the creative and inventive economies. However, intellectual property law is poorly prepared for this eventuality. The UK is one of the few nations, and perhaps the only EU member state, to explicitly provide copyright protection for CGWs. It is silent on patent protection for CGWs. This chapter makes several contributions to the literature. First, it provides an up-to-date review of UK, EU and international law. Second, it argues that patentability of CGWs is a matter of first impression in the UK, but that CGWs should be eligible for patent protection as a matter of policy. Finally, it argues that the definition of CGWs should be amended to reflect the fact that a computer can be an author or inventor in a joint work with a person.

Download the essay from SSRN at the link.

Garry Kasparov On AI and Humanity

Chess champion Garry Kasparov considers the future interaction of AI and humans in his new book Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins (Public Affairs, 2017), arguing that it's time to accept the role of AI in our lives. More here in a BBC Future Now article. 

Guadamuz on Whether Androids Dream of Electric Copyright: A Comparative Analysis of Originality in AI Generated Works @technollama

Andres Guadamuz, University of Sussex, is publishing Do Androids Dream of Electric Copyright? Comparative Analysis of Originality in Artificial Intelligence Generated Works in the 2017 volume of the Intellectual Property Quarterly. Here is the abstract.

The advent of sophisticated artificial neural networks has opened new artistic opportunities, but also a variety of new legal challenges. Computer programs such as Google's Deep Dream can take an image and process it in manners that resemble biological networks, producing artwork that is both unique and unpredictable. The law is not unfamiliar with the challenges of artificial intelligence, in the past academics and policymakers have had to deal with the legal implications of autonomous agents in contract formation, just to name one are of interest. However, for the most part the implementation of smart systems has been limited in their reach and scope, and in many instances autonomous agents required quite a lot of direction from the programmer, following a very stringent set of rules. This meant that for the most part all rights, responsibilities and liabilities arising from artificial agents fell squarely on the program creator. Neural networks are different, these systems have the potential to generate works in which human interaction is minimal. Modern copyright law has been drafted to consider originality as an embodiment of the author’s personality, and originality is one of the main requirements for the subsistence of copyright. So, what happens when you remove personality from the equation? Are machine-created works devoid of copyright? Do we need to change copyright law to accommodate autonomous artists? This session will explore this and other questions.

Download the article from SSRN at the link.

Abbott on AI and the Future of Patent Law

Ryan Abbott, Southwestern Law School and UCLA School of Medicine, has published I Think, Therefore I Invent: Creative Computers and the Future of Patent Law. Here is the abstract.

An innovation revolution is on the horizon. Artificial intelligence has been generating inventive output for decades, and now the continued and exponential growth in computing power is poised to take creative machines from novelties to major drivers of economic growth. A creative singularity is foreseeable in which computers overtake human inventors as the primary source of new discoveries. In some cases, a computer’s output constitutes patentable subject matter, and the computer rather than a person meets the requirements for inventorship. Despite this, and despite the fact that the Patent Office has already granted patents for inventions by computers, the issue of computer inventorship has never been explicitly considered by the courts, Congress, or the Patent Office. Yet the issue of whether a computer can be an inventor is an eminently practical one — not only do inventors have ownership rights in a patent, but failure to list an inventor can result in a patent being held invalid or unenforceable. Drawing on dynamic principles of statutory interpretation and taking analogies from the copyright context, this article argues that creative computers should be considered inventors under the Patent and Copyright Clause of the Constitution. Treating nonhumans as inventors would incentivize the creation of intellectual property by encouraging the development of creative computers. The article proceeds to address a host of challenges that would result from computer inventorship, ranging from ownership of computer-based inventions, to displacement of human inventors, to the need for consumer protection policies. This analysis applies more broadly to nonhuman creators of intellectual property, and explains why the Copyright Office came to the wrong conclusion with its new Human Authorship Requirement. Just as permitting computer inventorship will further promote the progress of science, so too will permitting animal authorship promote the useful arts. Finally, computer inventorship provides insight into other areas of patent law. For instance, computers could replace the hypothetical skilled person that courts use to judge inventiveness. This would provide justification for raising the bar to patentability and address one of the most serious criticisms of the patent system — that too many patents of questionable value are issued. Creative computers may require a whole rethinking of the baseline standard for inventiveness, and potentially of the entire patent system.

Download the article from SSRN at the link.