Copyright Implications Research Articles

Mining, Scraping, Training, Generating: Copyright Implications of Generative AI

ABSTRACTGenerative AI (GenAI) impacts the ways we create, engage with, and understand creative and intellectual works. These new forms of sociotechnical (inter)action pose challenges for existing legal regimes, ethical frameworks, and social relationships. This research undertakes an in‐depth copyright analysis of GenAI based on U.S. law, focusing on its fair use doctrine and conceptions of transformation. This work finds that courts' characterization of uses as primarily either “expressive” or “mediating” is an important, though often implicit, factor in their decisions. Furthermore, while “transformative use” has dominated fair use decisions for the past thirty years, findings from this research suggest that GenAI may usher in a renewed emphasis on the doctrine's market harms element which, in application, may be dispositive with respect to GenAI outputs. This work concludes by offering recommendations aimed at clarifying that the value of copyright arises from social and relational aspects of creative practice and sociotechnical transformation. Arguments and rationales that (over)emphasize atomization and algorithmic decontextualization of the material properties of creative works are unlikely to attend to the underlying purpose of the Act: “[t]o promote the Progress of Science and the useful Arts”.

Issues and Possibilities in Regulating Artificial Intelligence (AI) Related To Copyright in Indonesia

This paper discusses the challenges and opportunities of regulating artificial intelligence (AI) and its implications for copyright, with a focus on the Indonesian context. Internationally, the United States and the European Union have begun to develop AI regulations, although they are not yet fully comprehensive. Indonesia, while lacking detailed regulations, has developed a National Strategy for Artificial Intelligence 2020-2045 to guide the development of this technology. Key challenges include regulatory ambiguity, insufficient protection of personal data, and ethical issues. Copyright in Indonesia, under Law No. 28 of 2014, provides automatic protection for works that are original and embodied in tangible form. In the context of works created by AI, there are two views: first, AI works cannot be copyrighted because they lack personal characteristics and human creative process; second, AI works can be copyrighted because of their ability to create complex works and as an incentive for AI users. This article concludes that the government needs to rewrite copyright law to accommodate AI works, given their potential as a significant source of innovative and creative works.

Three-Dimensional Functional Brand Protection in Indonesia After the Implementation of Law Number 6 of 2023 (Comparison of Regulations in the United States and Japan)

Since the entry into force of the Law No. 20 of 2016 on Trademarks and Geographical Indications, Indonesia has officially granted recognition to 3 (three) dimensional trademarks. Nevertheless, this Act only provides provisions concerning the formality requirements for filing applications for registration of 3 (three) dimensional trademarks. Substantially, the Act No. 6 of 2023 on the Establishment of Government Regulations replaced the Law No. 2 of 2022 on the Creation of Works into the Act adding a provision in article 20 of the Act no. 20 of 2016 that forms of a functional nature cannot be registered as trademarks. There is no explanation of the meaning of functional form in this Act. Based on this problem, the author tries to study the implications of the current Copyright Act using grammatical interpretation methods as well as using a comparative approach to the provisions in the United States and Japan. This article explains about the three-dimensional distinctive force, associated with the secondary meaning theory. Based on research in literature, it is known that there is a breakdown between trademarks and patents in the registration of forms of a functional nature. This article also reinforces the argument that a functional form cannot be protected as a trademark.

Generative Visual AI in News Organizations: Challenges, Opportunities, Perceptions, and Policies

The use of AI-enabled text-to-image generators, such as Midjourney and DALL-E, raises profound questions about the purpose, meaning, and value of images generally, and the production, editing, and consumption of images in journalism specifically. This study explores how photo editors (or their equivalents) in seven countries perceive and/or use generative visual AI in their editorial operations and outlines the challenges and opportunities they see for the technology. It also identifies the extent to which these news organizations have policies governing how generative visual AI is used or, if not, the principles that they feel should inform their development. Participants identified mis/disinformation as the primary challenge of AI-generated images, also raising concerns about labor and copyright implications, the difficulty or impossibility of detecting AI-generated images, the potential for algorithmic bias, and the potential reputational risk of using AI-generated images. Conversely, participants saw potential for using AI for illustrations and brainstorming, while a minority saw it as an opportunity to increase efficiencies and cut costs.

Navigating the Grey Area: Copyright Implications of AI Generated Content

Navigating the Grey Area: Copyright Implications of AI Generated Content

Copyright Law and the Lifecycle of Machine Learning Models

Machine learning, a subfield of artificial intelligence (AI), relies on large corpora of data as input for learning algorithms, resulting in trained models that can perform a variety of tasks. While data or information are not subject matter within copyright law, almost all materials used to construct corpora for machine learning are protected by copyright law: texts, images, videos, and so on. There are global policy moves to address the copyright implications of machine learning, in particular in the context of so-called “foundation models” that underpin generative AI. This paper takes a step back, exploring empirically three technological settings through detailed case studies. We set out the established industry methodology of a lifecycle of AI (collecting data, organising data, model training, model operation) to arrive at descriptions suitable for legal analysis. This will allow an assessment of the challenges for a harmonisation of rights, exceptions and disclosure under EU copyright law. The three case studies are:Machine learning for scientific purposes, in the context of a study of regional short-term letting markets;Natural Language Processing (NLP), in the context of large language models;Computer vision, in the context of content moderation of images.We find that the nature and quality of data corpora at the input stage is central to the lifecycle of machine learning. Because of the uncertain legal status of data collection and processing, combined with the competitive advantage gained by firms not disclosing technological advances, the inputs of the models deployed are often unknown. Moreover, the “lawful access” requirement of the EU exception for text and data mining may turn the exception into a decision by rightholders to allow machine learning in the context of their decision to allow access. We assess policy interventions at EU level, seeking to clarify the legal status of input data via copyright exceptions, opt-outs or the forced disclosure of copyright materials. We find that the likely result is a fully copyright-licensed environment of machine learning that may have problematic effects for the structure of industry, innovation and scientific research.

Способен ли искусственный интеллект написать статью в юридический журнал?

In this article, we explore the potential of artificial intelligence (AI), in particular, ChatGPT based in GPT 4.0 model, to create articles in the field of legal studies. We analyze the pros and cons of employing AI in jurisprudence, specifically focusing on its capacity to adapt to intricate legal terminology, evolving legislation, and nuanced argumentation. The primary emphasis is placed on potential inaccuracies that may emerge in AI-generated text, as well as the underlying causes and subsequent ramifications. Furthermore, we discuss the copyright implications for works created via AI and propose possible solutions. In conclusion, we outline the current limitations and future prospects for leveraging AI in both legal practice and scholarly research. A substantial portion of the article is entirely generated by AI.

Governing ghostbots

This article discusses the legal implications of a novel phenomenon, namely, digital reincarnations of deceased persons, sometimes known as post-mortem avatars, deepfakes, replicas, holographs, or chatbots. To elide these multiple names, we use the term 'ghostbots'. The piece is an early attempt to discuss the potential social and individual harms, roughly grouped around notions of privacy (including post-mortem privacy), property, personal data and reputation, arising from ghostbots, how they are regulated and whether they need to be adequately regulated further. For reasons of space and focus, the article does not deal with copyright implications, fraud, consumer protection, tort, product liability, and pornography laws, including the non-consensual use of intimate images (‘revenge porn’). This paper focuses on law, although we fully acknowledge and refer to the role of philosophy and ethics in this domain.We canvas two interesting legal developments with implications for ghostbots, namely, the proposed EU Artificial Intelligence (AI) Act and the 2021 New York law amending publicity rights to protect the rights of celebrities whose personality is used in post-mortem ‘replicas’. The latter especially evidences a remarkable shift from the norm we have chronicled in previous articles of no respect for post-mortem privacy to a growing recognition that personality rights do need protection post-mortem in a world where pop stars and actors are routinely re-created using AI. While the legislative motivation here may still be primarily to protect economic interests, we argue it also shows a concern for dignitary and privacy interests.Given the apparent concern for the appropriation of personality post-mortem, possibly in defiance or ignorance of what the deceased would have wished, we propose an early solution to regulate the rise of ghostbots, namely an enforceable ‘do not bot me’ clause in analogue or digital wills.

Unchain My Art – Copyright Implications of Tokenized Artworks Under US and EU Law

Unchain My Art – Copyright Implications of Tokenized Artworks Under US and EU Law

Copyright Implications of the Use of Generative AI

Copyright Implications of the Use of Generative AI

Scientometric analysis of 3D printing in libraries, and implications for copyright

3D printing is a process whereby users can create a three-dimensional solid object of any shape by operating a 3D printer using a digital design, thereby creating their own designs or replicate and electronically customize scanned objects. The technology has existed for several decades; however, it was not until around 1990 it really gained momentum (Van Wiele, 2019). In this paper the authors investigated research on 3D printing in libraries and copyright through a scientometric analysis, by searching in Web of Science for libraries, 3D printing and copyright. The data was mapped in WoS-viewer, to show the most important authors, the most cited documents, and the most cited sources. 107 results from WoS Core Collection for “3D printing” AND copyright was found. Also, the authors researched library websites in Norway for guidelines and rules concerning copyright and 3D printing. Norwegian copyright law does not mention 3D printing as such, so how are academic and public libraries teaching or mentoring copyright issues to patrons and students?

Ross, Trevor. Writing in Public: Literature and the Liberty of the Press in Eighteenth-Century Britain

Ross, Trevor. <i>Writing in Public: Literature and the Liberty of the Press in Eighteenth-Century Britain</i>

Copyright implications for the aggregation of audiovisual content in Greece

PurposeThis paper aims to attempt to provide an overview of the copyright legal framework for audiovisual resources in Europe and Greece, how Audiovisual (AV) content is currently licensed by Greek providers and how licenses or copyright exceptions enable its reuse. The motivation for this work was the development of an aggregation service for audiovisual resources in Greece, the Open AudioVisual Archives (OAVA) platform.Design/methodology/approachCopyright licenses and exceptions in the European Union and in Greek Legislation have been thoroughly reviewed along with the reuse of content, based on the terms of Fair Use, Rights Statements and Creative Commons. Licensing issues for the most well-known aggregation services, such as Europeana, Digital Public Library of America, Trove, Digital New Zealand and the National Digital Library of India, have also been studied and considered. Audiovisual content providers in Greece have been recorded, and their licensing preferences have been analyzed. Pearson’s chi-square test was applied to test the relationship between the provider’s type, resources’ genre and licenses used.FindingsDespite the abundance of copyright legislation in the European Union and in Greece, audiovisual content providers in Greece seem to ignore it or find it difficult to choose the right license. More than half of them choose to publish their resources on popular audiovisual platforms using the default licensing option provided. Creative Commons licenses are preferred for audiovisual content that falls into the following categories: open courses (almost exclusively) and interviews and digital collection/research projects (about half of the content).Originality/valueThis paper examines audiovisual content aggregation, in the EU and Greece, from a legal point of view. To the best of the authors’ knowledge, it is the first attempt to record and analyze the licensing preferences of Greek AV content providers.

‘Meta-Choreographies’ Between the Desktop and the Stage

How does one re-use pre-existing material in order to form an expanded choreographic practice of relating to audio-visual archive without being considered of stealing or lacking originality? Copying, re-using and appropriation, not innocent from copyright implications but often entrapped in the modernist myth of originality, are practices that have been enhanced by the growth of the digital archive available on the internet and the expansion of the online public space. In light of this surge that challenges the body-to-body dance transmission, this text analyzes copying, re-use and appropriation as forms of citation, both audio-visually and corporeally, through the work of the Italian choreographer, performer, educator and filmmaker Jacopo Jenna who connects fragments of preexisting works to create unexpected visual and corporeal associations that prompt us to re-think the dance canon. His work, based on a meta-choreographic and meta(dance)cinematic technique, moves between screen and stage, two-dimensional and three-dimensional space and brings into dialogue immaterial bodies and gestures stored in our collective memory with flesh bodies on stage. But, what issues and possibilities does this practice of disembodied transmission from screen-to-body entail?

Documenting Indigenous oral traditions: Copyright for control

AbstractSimilar to the other forms of cultural heritage, Indigenous oral traditions are collected and held often by outsiders to the community. There are a number of instruments addressing this problem, but none of them provide complete control over such works. This article will focus on the possibility and instances of copyright being used to control oral traditions, both by outsiders and the Indigenous communities. The article will first provide an overview of the applicable legal areas (cultural property law, Indigenous rights, and intellectual property rights), and then it will assess different stages in the treatment of oral traditions. It will discuss the copyright implications for not only the traditions themselves but also their documented versions, subsequent copies, adaptations, and new works in order to provide a full picture of the relationship between control and copyright.

Deep representation-based transfer learning for deep neural networks

In recent years, deep neural networks (DNNs) have become the de facto models for practically all visual tasks and most temporal analysis tasks due to the abundance of available labeled data and advances in computational resources. Deep transfer learning, a learning paradigm that investigates how deep neural networks can leverage knowledge from other domains, has been successful in many practical applications. Most deep transfer learning methods rely on directly available source domain data, especially instances-based and mapping-based methods. However, the source domain data required for transfer cannot be provided in some cases because of personal privacy or copyright implications. In this regard, we propose a deep representation-based transfer learning method for deep neural networks to deal with transfer scenarios without source domain data. The proposed method induces the target deep neural network to learn the similarity structure between source deep representations by minimizing the representational similarity discrepancy between the networks, thereby transferring the domain knowledge from the source network to the target network. In addition, the proposed method combines the boosting-based deep representation transfer method to more fully utilize the source domain knowledge, so that the target network learns in both the reweighted source deep representation and target deep representation to further improve the generalization ability. The proposed method is applied to image classification and time series prediction tasks and achieves better transfer performance than other similar methods, which shows that the method has good practicability and generality in practical applications.

Copyright implications of emulation programs

How emulation programs might be affected by new claims of copyright infringement.

Tiny, Tiny Copyright: An Examination of the Copyrightability of Sampler Instruments and Its Impact on Derivative Works

Tiny, Tiny Copyright: An Examination of the Copyrightability of Sampler Instruments and Its Impact on Derivative Works

Observing creativity in fashion: implications for copyright

Observing creativity in fashion: implications for copyright

Book Review: Copyright for Schools: A Practical Guide, 6th Edition

New for 2021 is the sixth edition of Copyright for Schools: A Practical Guide, by Carol Simpson and Sara E. Wolf. Ms. Simpson is an attorney and former professor of library and information science, with additional experience as a school librarian, teacher, and district library administrator. Ms. Wolf is a professor in Auburn University’s College of Education, with research interests in library media and technology and experience in institutional copyright policy development. The book is designed to address the copyright issues and questions that tend to arise for K-12 teachers, school librarians, and school administrators, though librarians in other contexts such as public libraries and higher education would likely find its contents useful too. The sixth edition updates previous editions by adding content on the copyright implications of streaming video services and cloud computing, issues related to disability, responding to cease-and-desist letters, openly licensed resources and Creative Commons licenses, and the implications of the Music Modernization Act. The latest edition of the book also contains a concordance (a table of legal citations and the principles for which they stand), and more robust legal citations than previous editions.