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For the past 70 years, researchers and experimental musicians have been working with computersynthesized music, forming a collaborative relationship with generative artificial intelligences known as human--AI co-creation. The last several years have shown that musical artists are quickly adopting AI tools to produce music for AI music competitions and for commercial production of songs and albums. The United States Copyright Office, in response to this trend, has released its latest policy revisions to clearly define what is eligible for copyright registration. Soon after, the Program for Cooperative Cataloging (PCC) also released new guidelines, providing recommendations for how library catalogers should address AI-generated materials. In both cases, they reject the notion of considering AI as a contributor. The language in each of these policies, however, is self-contradicting, showing that they are ill equipped to address generative AI. This study leverages critical textual analysis and qualitative content analysis and uses case examples to probe the manner in which these policies regard generative AI. Recommendations are made for addressing shortcomings in the PCC's policies, and moral philosophical frameworks such as virtue ethics and consequentialism support arguments for supplementing catalog item records with information from authoritative external sources, deviating from this policy for the sake of truth-seeking. [ABSTRACT FROM AUTHOR]

The article focuses on the growing tension between copyright law and the rise of generative AI (artificial intelligence), as artists and creators push for crackdowns on AI's use in producing art. It explores how lawsuits against major AI companies like OpenAI, Stability AI, and Meta have emerged, along with concerns about the potential for AI to undermine fair compensation for human creators.

In the digital age, information has become more widespread and easily accessible on the Internet. With the digital emergence, the intersection of copyright law and journalism continues to present unique challenges for courts tasked with adjudicating disputes over the fair use of online content. Reporters are frequently violating the Copyright Act when using information posted on the Internet for a press story and Congress is failing to make the necessary changes to the Copyright Act to address the issues arising with the evolution of technology. This article details the evolution of the Copyright Act and the Digital Millennium Copyright Act, assessing the changes that must be made in order to keep up with the modern era. Further, the article explains how courts currently interpret the fair use exception and its application in the practice of journalism. This article explores case law that can be used to amend the fair use exception to better address the issues journalists arefacing in the digital age. This article argues the necessity of integrating originality and newsworthiness criteria into the fair use analysis to e#ectively balance copyright protection with press freedom. The article explains how courts must adapt the fair use doctrine to accommodate the evolving landscape of digital journalism, ensuring that journalists can responsibly navigate copyright issues while fulfilling their crucial role of informing the public in an ethical manner. [ABSTRACT FROM AUTHOR]

With the popularization of generative artificial intelligence technology, the issue of copyright for AIGC is highlighted. The originality criterion under traditional "instrumental theory" and "contribution theory" is particularly inadequate when it is applied to AIGC, and it is necessary to construct more actionable originality criterion. By analyzing the legislative value of copyright law and empirical research on the norms of current laws, combined with empirical research on domestic and foreign judicial cases, the construction of originality criterion under "determinism" was proposed. Based on anthropocentrism, adhered to the uniqueness of the copyright subject, regarded labor input as the basis of rights, and the causal relationship theory in Anglo-American law system was introduced, which took the determination of the presentation results of human works and the control of the creative process as sufficient and necessary conditions. Thus, determinism is self-consistent in terms of objects, standards, laws, facts, and causal relationships, and can guide practical application. [ABSTRACT FROM AUTHOR]

Data hiding has become a hot research topic in recent years due to increased attention placed on the copyright protection of ocean images and related digital records. Further, high image volumes put enormous pressure on transmission bandwidth and storage capabilities. This paper proposes an innovative deep learning‐based data‐hiding technique for ocean images. First, a down‐sampling scheme is applied to compress the secret mark before embedding it in the host media. Then, a convolutional neural network is used to embed and recover compressed marks into or from the host ocean image. Finally, a generative adversarial network‐based reconstruction network is used to reconstruct the high‐quality mark image. Our experiments show that the proposed work not only maintains high imperceptibility and robustness against many attacks but also provides better data‐hiding performance than related works. [ABSTRACT FROM AUTHOR]

The potentially disruptive interaction between Artificial Intelligence (AI) and creative Intellectual Property Rights (IPRs) is one of the major challenges of the 21st century as AI systems are being increasingly utilized to generate creative works. This article addresses these questions through the lens of copyrightability of works created by AIs as it relates to originality, authorship, and ownership. The paper addresses recent debates about whether current copyright frameworks could be adapted to accommodate AI-generated content and outlines practices around the world. It also explores the crucial role of human intervention in AI output, arguing whether such collaborations deserve co-authorship credit. The paper ends with suggestions to amend the laws which apply in these circumstances, or to create a new legal framework to resolve these issues. [ABSTRACT FROM AUTHOR]

Nowadays, AI systems can produce creative output, such as paintings, poetry, music, etc. Text and Data Mining (TDM) techniques are used to 'train' Artificial Intelligence (AI) and for other R&D in AI. This article focuses on the governance of TDM in India. The author has argued that Section 52 of the Indian Copyright Act may handle copyright aspects of TDM activities. Still, there is a need for legislative intervention for fair governance and to take care of some challenges associated with it. The first part of the article talks about the scope of the principle of "fair dealing" in governing copyright aspects associated with TDM in India. In the second part, while explaining the TDM exceptions in other countries, the author has argued how the socio-economic condition in India favours a liberal exception of copyright to carry out TDM activities, how the narrow exception like in the EU's Directive on Copyright in the Digital Single Market (CDSM) may prejudice the society and overall development in India. The author has argued that liberal TDM exceptions like Japan would benefit India even though there are challenges by AI firms to exploit the copyrights of the holders. In the third part, the argument of liberal TDM exceptions is supported by major socioeconomic factors like the state of the domestic economy and linguistic, social and cultural diversity. [ABSTRACT FROM AUTHOR]

The article endeavors to delve deep into the world of 'deepfakes'. Deepfakes are a product of technological advancements in artificial intelligence (AI) which have creators and consumers of their own. However, like any other technological invention, the phenomenon of deepfakes also presents itself as a double-edged sword. The disruptions produced by deepfakes have become ubiquitous, transcending geographical borders, and blurring boundaries between reality and fiction. The intersection between artificial intelligence and intellectual property rights is a crucial assessment point and merits meticulous examination, considering its contemporary relevance. The article is an attempt to review and analyze the disruptive nature of deepfakes, their manifestations and ramifications in the world of media and entertainment, the recipients of the infamous technology, and their corresponding rights, including personality rights and right of publicity, potential threats, and possible legal remedies within the framework of intellectual property law. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is a technology which is known for carrying out various tasks efficiently with little or no human intervention at all. Generative AI is one of the branches of AI which is known for generating content at par with human intelligence. Generative AI tools like ChatGPT, Google's Bard and DeepAI are being used in today's world by students, academicians, employees, employers, news channels and others to create textual, pictorial or video-graphical content. All such generated content suffers from one common issue, that is, their copyright. Most of the users are unaware of copyright in the work generated by them using the generative AI tools. They do not know whether the copyright exists in AI-generated work and who is the owner or author of such copyrighted work. The article analyses the subsistence of copyright in AI-generated work and the conditions and criteria of such copyright, if any. It traces the content creation process of generative AI tools and the contractual aspects pertaining to it. Further, the article examines the issues of copyrightability of AI-generated work in various countries and compares it with the legal standing in India. Lastly, the impact of AI-generated work on the Indian copyright regime has been analysed and accordingly, suggestions have been made which may be implemented to address the plethora of challenges arising out of or in relation to AI-generated work. [ABSTRACT FROM AUTHOR]

Recent advancements in deep learning-based generative models have simplified image generation, increasing the need for improved source tracing and copyright protection, especially with the efficient, high-quality output of latent diffusion models (LDMs) raising concerns about unauthorized use. This paper provides a comprehensive review of watermarking techniques applied to latent diffusion models, focusing on recent trends and the potential utility of these approaches. Watermarking using latent diffusion models offers the potential to overcome these limitations by embedding watermarks in the latent space during the image generation process. This represents a new paradigm of watermarking that leverages a degree of freedom unavailable in traditional watermarking techniques and underscores the need to explore the potential advancements in watermark technology. LDM-based watermarking allows for the natural internalization of watermarks within the content generation process, enabling robust watermarking without compromising image quality. We categorize the methods based on embedding strategies and analyze their effectiveness in achieving key functionalities—source tracing, copyright protection, and AI-generated content identification. The review highlights the strengths and limitations of current techniques and discusses future directions for enhancing the robustness and applicability of watermarking in the evolving landscape of generative AI. [ABSTRACT FROM AUTHOR]

Digital image source identification primarily focuses on analyzing and detecting the machine imprints or camera fingerprints left by imaging devices during the imaging process to trace the origin of digital images. The development of a swift search algorithm is crucial for the effective implementation of camera source identification. Despite its importance, this domain has witnessed limited research, with existing studies predominantly focusing on search efficiency while neglecting robustness, which is essential. In practical scenarios, query images often suffer from poor signal quality due to noise, and the variability in fingerprint quality across different sources presents a significant challenge. Conventional brute-force search algorithms (BFSAs) prove largely ineffective under these conditions because they lack the necessary robustness. This paper addresses the issues in digital image source identification by proposing a rapid fingerprint search algorithm based on global information. The algorithm innovatively introduces a search priority queue (SPQ), which analyzes the global correlation between the query fingerprint and all reference fingerprints in the database to construct a comprehensive priority ranking, thereby achieving the efficient retrieval of matching fingerprints. Compared to the traditional brute-force search algorithm (BFSA), our method significantly reduces computational complexity in large-scale databases, optimizing from O (n N) to O (n log N) , where n is the length of the fingerprint, and N is the number of fingerprints in the database. Additionally, the algorithm demonstrates strong robustness to noise, maintaining a high matching accuracy rate even when image quality is poor and noise interference is significant. Experimental results show that in a database containing fingerprints from 70 cameras, our algorithm is 50% faster in average search time than BFSA, and its matching accuracy rate exceeds 90% under various noise levels. This method not only improves the efficiency and accuracy of digital image source identification but also provides strong technical support for handling large-scale image data, with broad application prospects in fields such as copyright protection and forensic evidence. [ABSTRACT FROM AUTHOR]

In the era of widespread digital image sharing on social media platforms, deep-learning-based watermarking has shown great potential in copyright protection. To address the fundamental trade-off between the visual quality of the watermarked image and the robustness of watermark extraction, we explore the role of structural features and propose a novel edge-aware watermarking framework. Our primary innovation lies in the edge-aware secret hiding module (EASHM), which achieves adaptive watermark embedding by aligning watermarks with image structural features. To realize this, the EASHM leverages knowledge distillation from an edge detection teacher and employs a dual-task encoder that simultaneously performs edge detection and watermark embedding through maximal parameter sharing. The framework is further equipped with a social network noise simulator (SNNS) and a secret recovery module (SRM) to enhance robustness against common image noise attacks. Extensive experiments on three public datasets demonstrate that our framework achieves superior watermark imperceptibility, with PSNR and SSIM values exceeding 40.82 dB and 0.9867, respectively, while maintaining an over 99% decoding accuracy under various noise attacks, outperforming existing methods by significant margins. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Derecho Privado (0123-4366) is the property of Universidad Externado de Colombia, Departmento de Derecho Civil and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article considers certain problematic aspects regarding the invalidation of intellectual property rights (protection documents) and their legal consequences. Author proves that when intellectual property rights expire, they end their term of legal protection by virtue of the law, taking into account the temporary nature of such rights. If a person registers rights or an object of intellectual property, receives a protection document, but knows that such an object does not really meet the conditions for granting legal protection, and enteres into contractual relations with respect to it, the counterparty of such a person (a party to the contract) also has the opportunity to initiate the invalidation of such a contract on the basis of Art. 230 of the Civil Code of Ukraine. Within the invalidation of deeds regarding invalid intellectual property rights, one should also proceed from whether such contracts were fulfilled in full or in part and whether such a method of protection as the recognition of a contract (deed) as invalid will become an effective way of protecting civil rights and restore the violated, unrecognized or contested right. The situation remains unregulated, when intellectual property rights to an invention, a utility model are recognized partially invalid, and individual independent clauses of the claim of the invention (utility model) or signs of the appearance of the industrial design are excluded from legal protection. It has been proven that invalidation of intellectual property rights to an invention, utility model or industrial design, invalidation of a trademark certificate will de facto reduce the authorized capital of the business company (to which they contributed) in the amount of the monetary value of these rights, which was approved by the participants (founders) when they were introduced. If a member of the company has contributed to the authorized capital of the business company exclusively with property rights of intellectual property, it would be expedient to give him the opportunity to contribute money, securities or other property, unless otherwise established by law, to replace this contribution. [ABSTRACT FROM AUTHOR]

The article considers certain problematic aspects of the legal regime of databases under Ukrainian and EU law. It has been established that the Law of Ukraine "On Copyright and Related Rights" pays sufficient attention to the legal regulation of relations related to the acquisition, exercise and protection of rights to databases. It has been proven that databases as an object require more thorough and systematic legislative regulation by adopting a separate legislative act, which should comprehensively determine the legal regime of databases. It has been substantiated that the characteristics of a database include: it is a collection of works, data or any other information; these works, data and/or information are contained in an arbitrary form; systematization of works, data, information, or their arrangement; the presence of a special search system to ensure access to works, data, information (which may function including, but not exclusively on the basis of electronic means); it is a predominantly digital object. The influence of modern technologies on the transformation of the form of existence of a database as an object is proven (there has been a gradual evolution of the database from a paper to an electronic form of existence, moreover, the electronic form has almost completely replaced the «paper» database). It is substantiated that due to the development of technologies and innovations, the opportunities of both authors and users of the digital environment have expanded, who have received new ways of using digital content, which can also be contained in databases (which are usually in electronic form). It is established that it is necessary to distinguish between the rights to a database as an object and the rights to objects that are part of the database as its constituent parts. It is established that the legal protection of a non-original database through the mechanism of a special kind of right is aimed at protecting the database as a certain digital object, which can also be used by the person who created it, as well as by other persons (users), who, in order to acquire the status of a legal user, must obtain permission to use it from the person who created such a database. It is substantiated that the norm that databases created to systematize data that is public information in accordance with the Law of Ukraine «On Access to Public Information» are not subject to a special kind of right (sui generis) requires specification, since it is unclear what legal regime applies to the specified databases, who owns the rights to the databases and how to exercise them. It is proved that a special law on databases should regulate the features of the exercise and protection of rights to databases in the digital environment, which is especially relevant in the conditions of the rapid development of technologies and innovations. [ABSTRACT FROM AUTHOR]

The article addresses fundamental legal issues in the field of intellectual property arising from the rapid development of generative artificial intelligence. It explores the challenges posed to copyright law by the widespread adoption of artificial intelligence technologies. In particular, the study examines the legal regime of objects created with the assistance of artificial intelligence, the legality of using copyrightprotected works for training AI models, and specific issues related to the legal personality of AI. Based on an analysis of international judicial practice and contemporary regulatory instruments, including the recently adopted European Union Artificial Intelligence Regulation, the study examines ambiguous approaches to determining copyright for AI-generated objects. Practical cases from various jurisdictions, including court decisions from the United States and China, are analyzed to illustrate the variability in legal assessments regarding the interaction of i ntellectual property law and AI. The article offers an analysis of promising mechanisms for regulating legal relations in the field of study. These include the introduction of a collective rights management system (similar to extended or mandatory collective management), the establishment of mechanisms for fair compensation to rights holders, and the development of technical tools for identifying the origin of content. The study underscores the necessity of balancing the interests of AI technology developers, authors, and society's technological advancement needs. The article traces trends in legislative changes in the field of intellectual property and the regulation of artificial intelligence. In particular, it examines the provisions of the Artificial Intelligence Act, which imposes obligations on AI model developers to comply with copyright laws, including the requirement to disclose detailed reports on the content used for training AI models. The article emphasizes the importance of creating a legal environment that simultaneously fosters technological progress and robustly protects the rights and interests of authors. Effective regulation should be grounded in fundamental principles of fairness, transparency, and comprehensive consideration of the interests of all participants in intellectual property l egal relations. [ABSTRACT FROM AUTHOR]

The article considers certain problematic aspects regarding the implementation and protection of copyright in the digital environment (on the Internet). It has been established that the digital sphere (digital environment, the Internet) is developing at a rapid pace and is particularly relevant in terms of the use and protection of intellectual property rights. It is proven that the development of the digital sphere (digital environment, Internet) has led to the appearance of the latest objects (in particular, multimedia and digital works), new forms of creativity, new communication media (forms of communication), including an interactive environment. It is proven that in connection with the development of high technologies, the appearance of new objects of copyright and related rights with special, new properties, new types and methods of their use, new exclusive rights of creators (the right of access in interactive mode) have arisen. It was established that the national legislation of Ukraine and international treaties do not use the concept of «Internet» as a medium for the use of objects of copyright and related rights, as a place for communication, instead, the norms of domestic legislation (Civil Code of Ukraine, Law of Ukraine «On Copyright and Related Rights rights») contain broader concepts that apply to digital technologies, namely, reproduction, the right to distribute to the general public (disclosure, access). It has been established that for the legitimate use of copyright and related rights on the Internet, it is necessary to obtain permission from the subjects of copyright and related rights. It is substantiated that it is important to ensure effective and adequate protection of the intellectual property rights of creators, guarantee them appropriate compensation for the use of their objects, and encourage them to continue their creative activity. The need to establish certain exceptions and limitations of copyright and related rights in the interests of society in order to promote the development of education, science and culture has been proven. It has been established that the problems of legal inconsistency of legislation are becoming increasingly important as a result of the further development of the information society and the emergence of new forms of cross-border communications. It is substantiated that modern legislation in the field of copyright and related rights needs changes and additions to adequately reflect economic realities, new forms of use of objects, etc. [ABSTRACT FROM AUTHOR]

The article considers the prospects for regulating intellectual property rights for works created with the use of artificial intelligence by means of international and national law. The definition of intellectual property under the law of Ukraine is revealed. It is established which objects are the subject of protection of such rights. It is emphasized that national regulation of intellectual property rights has an international dimension, since one state, as a rule, is unable to reliably protect intellectual property rights, which has become especially relevant in the era of glob alization and computer networks. The foundations of international legal regulation of intellectual property protection are considered. It is emphasized that this regulation was formed back in the 19th century with the adoption of the Paris Convention of 1883 and the Berne Convention of 1886, which were designed to protect the rights of individuals, but not artificial intelligence. The importance of the scientific and technological revolution is emphasized, which led to a new stage in the development of the creative activity of mankind, which began to use artificial intelligence. The challenges for intellectual property law, copyright and the very concept of authorship that have arisen with the development of artificial intelligence are studied. The uniqueness of artificial intelligence technology, which is capable of self-learning and independent processes of making creative decisions, is emphasized. The practical aspect of this issue is emphasized, which is that works created by artificial intelligence have already become the subject of commercial expl oitation. Different types of artificial intelligence and different options for solving the problem of intellectual property law for works using artificial intelligence are studied, in particular, granting such rights to developers, programmers, users, companies and the general public. It is emphasized that the importance of these problems will grow in the future, for which existing national legislation and international legal regulation are currently not ready. A conclusion is drawn about the prospect of creating a new entity within the framework of intellectual property law, namely the joint intellectual property law of artificial intelligence developers and its users. [ABSTRACT FROM AUTHOR]

The development of generative artificial intelligence models is at the heart of two important debates in terms of copyright: firstly, does the use of previous works as training data constitute an infringement of copyright? The issue is utterly sensitive as creators fear a negative effect of these tools on their future careers. Secondly, what regime is applicable to "outputs", more precisely to textual, visual, musical or audiovisual contents generated by artificial intelligence? Are these works without an author? Are they protected by an intellectual property right, and if so, under what conditions and for whose benefit? These highly topical questions find a particular echo in the writings of the French semiologist and philosopher Roland Barthes (1915-1980), notably in his famous article entitled "The Death of the Author". The objectives of this study are, firstly, to present the questions raised by generative artificial intelligence in copyright law (mainly under the prism of French law, but also with regard to Romanian law, European law and court decisions taken on the subject in different countries), and, secondly, to determine to what extent the arguments developed by Roland Barthes, leading to relativising the role of the author, could contribute to current debates on this adaptation of copyright to generative artificial intelligence. [ABSTRACT FROM AUTHOR]

With academic libraries becoming increasingly involved in copyright issues, the ability to responsibly identify a copyright-protected material is becoming important in the administration of reprographic materials in academic libraries. A mixed methods approach was employed to evaluate the adequacy of copyright information or documentation, the need for training, and the mechanisms for educating library users on responsible use of reprographic materials that ensures a balance of stakeholder rights. Quantitative data was collected from 38 library staff and 530 postgraduate students, while qualitative data was collected from four head librarians (through one-on-one interview sessions), and two groups of six postgraduate students each from two public and two private universities in Ghana (through focus group discussion sessions). Only 21.4 % stated that copyright information or documentation on copyright policies on their university campuses was adequate. Copyright education for both staff and students was generally low in all the four institutions. Only "classroom training" had significant impact on users' understanding of copyright laws and policies. "Professional associations," "study visits," and "consultant training" had little impact on the understanding of students about copyright laws despite most library staff being either "comfortable" or "very comfortable" with their level of knowledge on copyright issues. There is therefore the need to incorporate copyright issues in the school curriculum for students as well as institute CPD programs for professional librarians if academic librarians are to efficiently and adequately play their roles as agents of copyright education to the university community. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Culture & Haci Bektas Veli Research Quarterly is the property of Turkish Cultur & Haci Bektas Veli Research Quarterly and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to review Saudi Arabia's IPR system and analyze to what extent it complies with the WTO/TRIPS. The research looks into the history and the present legal system of IPR in Saudi Arabia. It also identifies the enforcement systems, and issues concerning compliance with international standards. With a comparative analysis method, the research assesses Saudi Arabia in comparison with the WTO guidelines and its neighboring countries regarding improving IPR protection. This research identifies progress in legislative and institutional development and gaps in enforcement efficiency and digital IP protection. The paper discusses measures to improve Saudi Arabia's IPR system to support innovation-based development and increase WTO compliance. [ABSTRACT FROM AUTHOR]

To balance generative AI (GenAI) innovation with the protection of copyright for authors and performers, it is necessary to recalibrate the concept of "public interest." This recalibration is crucial to ensure that authors and performers receive fair and equitable remuneration for their contributions while facilitating public access to knowledge and cultural expressions. Such a redefinition is also aimed at addressing current challenges, including fair use, open access, and the democratization of information within the AI industry. Drawing on Virginia Held's typology of public interest theory, this article suggests that adjustments to the notion of public interest should include establishing a balance through either a majority of individual interests or empirical data; aligning with the collective interests that receive societal endorsement; and evaluating public interest based on normative content and moral judgment, utilizing the principle of enjoyment and the public perception test in copyright law. While various theoretical frameworks could be used to conceptualize public interest, the article proposes an approach that explicitly defines copyright objectives and harmonizes the rights of authors and performers with the public's right to access creative works. Such harmonization could be achieved through an integrative methodology that combines evidence-based analysis, consensus among stakeholders without conflicting interests, and normative evaluations rooted in societal ethics. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Pendidikan Indonesia is the property of Publikasi Indonesia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article is devoted to the issue of using generative AI in the higher education system of the Russian Federation. The relevance of this issue is due to the avalanche-like growth in the use of generation by students and postgraduates in the 2023/24 academic year, the heated discussions that arose in this regard within universities, a series of publications in the media, the lack of development of the legal aspects of the use of generation, the ambiguity of its ethical grounds and consequences. The goal of the authors' collective is to formulate a collective position of teachers of classical humanitarian knowledge, which consists in the inadmissibility of using generative AI in the preparation of qualification and scientific papers. The work examines the regulatory aspects of the use of generation, conducts an experimental study of generative systems popular in the Russian-speaking space, and formulates a fundamental threat to subjectivity at the level of the individual and the collective, arising in connection with the use of generative AI. The general conclusion of the work is the need for careful legal and ethical regulation of the areas and methods of using generative systems in higher education.

Copyright protection in Indonesia is governed by Law No. 28 of 2014 (Law 28/2014), encompassing moral and economic rights. This law imposes limitations on the use of works for education, law enforcement, or technological development as long as such use does not harm the legitimate interests of the rightholder. The development of generative AI (GAI) poses challenges in determining the legality of using copyrighted works for GAI training. This study examines copyright regulations concerning GAI through normative, conceptual, and comparative legal approaches, including case studies on lawsuits against OpenAI and Perplexity AI. The findings indicate that the legality of using copyrighted works depends on the data input process and output (responses). Data scraping is considered an economic right of the rightholder, classified as reproduction under Article 9 of Law 28/2014. If such acts are conducted without the rightholder’s consent and for commercial purposes, they are deemed unlawful under Indonesia’s current copyright law. GAI outputs may also infringe copyright if: (1) the source is not cited, violating Article 7 on copyright management information; (2) substantial portions of the work are reproduced, violating the rightholder's economic rights under Article 9; or (3) the work is distorted in a way that harms the rightholder’s honor, infringing on moral rights under Article 5. To accommodate AI development, specific regulations integrating AI transparency principles outlined in SE Kominfo 9/2023 are required. These regulations could include obligations for AI companies to release summaries of training datasets, include Uni EropaLAs that define the responsibilities of AI developers and users, and provide disclaimers regarding AI's limitations. Regarding the fulfillment of rightholders’ economic rights, a non-exclusive blanket license through Collective Management Organizations (CMOs) as stipulated in Permenkumham 15/2024 is necessary. These regulations should be synchronized with related policies to establish legal certainty that adapts to technological advancements.

The presented study is aimed at determining the current state of the legal context and legal consequences of the formulation of certain components of unilateral copyright statements on websites. In the research process, such methods as analysis and synthesis, induction and deduction, methods of generalization, study of documentation and methods of descriptive statistics were used. In order to interpret various options of legal aspects of the use of the mentioned statement, an empirical study was conducted which included the study of the main web pages of scientific institutions that receive state support in 2024. The study was conducted in November 2024. The web page availability and order validity with marker “valid” filters were used. The original sample was reduced because about 10 % of the websites listed in the document were not functional and some appeared twice in the document. The final sample consisted of 121 websites. The choice of websites of scientific institutions is justified by two factors: the specifics of the activity, which involves the generation of large volumes of original works and the paradigm of open science which imposes new requirements on copyright management. It has been established that the use of a unilateral copyright statements is quite complex and debatable. Trends in the wording of copyright statements on websites belonging to Ukrainian scientific institutions have been determined. The legal context and legal consequences of the formulation of certain components of unilateral copyright statements on websites in the projection of current regulation have been established. Based on such data, a generalized assessment of the legal responsibility of website owners in the context of the raised issue has been provided. The prospect of further exploration is to investigate the behaviour patterns and the level of legal responsibility of users in connection with unilateral statements of website owners.

Goal: The main objective of this paper is to investigate, analyse and present how the Uniri Digital Library is organised. Methodology: The paper gives an overview of important activities which the University of Rijeka Library has in cooperation with the University of Rijeka and the University constituents2 taken to increase the number of objects stored and published in the institutional repositories. Results: The paper analyses digital objects stored and published in the Uniri Digital Library by the type of papers and openness. The analysis has identified insufficient openness of objects in spite of legal regulations and storage obligations on the national and institutional levels. Data suggests that it is necessary to establish new evaluation and reward system in implementing the practices of open science, but also to continuously perform education and raise awareness about the importance of open scientific information. Originality: The paper presents the theoretical concept and the legal framework for the establishment of the Uniri Digital Library. Until the adoption of the Digital Library Standard, the Uniri Digital Library was called University of Rijeka3 Repository.

Introduction: The background of this research addresses the generated image by Artificial Intelligence whether it is protected by copyright, it is based on creating an image is usually created directly by the person, but in this context the image created is made by artificial intelligence. Purposes of the Research: The purpose of this research first to determine the copyright arrangements against images created by artificial intelligence in Indonesia and then to find out related copyright arrangements in the United States related to images generated by artificial intelligence. Methods of the Research: This research uses normative legal research methods, and the approach used is normative legal research on the basis of the vagueness of norms related to images that degenerate by copyright including copyright. The approach used in this research is a conceptual approach, statutory approach, analytical approach, and comparative approach. Results of the Research: The images generated by AI are protected by copyright, but the subject that is actually protected is the human who commanded the AI to create the image. Where only humans are considered legal subjects that can protect their work. Although AI can create works, AI itself is not considered to have the morality necessary for copyright law protection. Therefore, in the event that an AI creates a work, copyright law protection is extended to the human controlling the AI as the actual creator.

Objective: to identify the prospects and directions of copyright law development associated with the increasing use of generative artificial intelligence.Methods: the study is based on the formal-legal, comparative, historical methods, doctrinal analysis, legal forecasting and modeling.Results: the article states that the emergence of generative artificial intelligence makes one rethink the processes occurring in the field of creative activity and the traditional copyright system, which becomes inadequate to modern realities. The author substantiates the necessity of legal reassessment of copyright and emphasizes the urgent need for updated means of copyright protection. Unlike previous digital tools, which expanded human creativity by improving original works, generative artificial intelligence creates content through complex algorithmic processes, blurring the boundaries of authorship and originality. The research shows limitations of existing intellectual property law, as courts deny copyright in works created by artificial intelligence and insist on the need for “human authorship”. Such decisions emphasize the contradiction between existing laws and the reality of co-creation involving artificial intelligence. It is argued that taking into account the creative potential of generative artificial intelligence will facilitate the evolution of copyright law towards hybrid approaches, with artificial intelligence as an integral, albeit secondary, tool. It seems promising to create flexible intellectual property standards that give artists the opportunity to restrict or authorize the use of their works as training data for artificial intelligence, as well as ensure that authors retain control over their works included in datasets for training artificial intelligence, in case copyright metadata is integrated into digital works, etc.Scientific novelty: based on the analysis of the latest judicial precedents, modern international regulations and evolving institutional practices, the author proposes a balanced adaptive approach to copyright reform to ensure the ethical integration of generative artificial intelligence into the creative ecosystem and to develop flexible copyright protection measures that correspond to the rapid technological progress.Practical significance: the proposed combined approach will allow generative AI tools to become part of the human creative process in the same way that previous generations used digital tools. At the same time, it will contribute to the creation of an environment where the autonomy of authors is respected. This will not only protect the creators of creative content, but also broaden the understanding of creativity as a collaboration with generative artificial intelligence, where artificial intelligence is positioned as a force that complements but not replaces humans in creativity.

The development of generative models of artificial intelligence (AI) poses new challenges for legal science and practice. This requires understanding of the legal nature of prompts (queries to AI) and development of appropriate legal regulation. The article aims to determine the legal significance of prompts and outlines the prospects for their research in the context of the interaction between law and AI. The study is based on the analysis of contemporary scientific literature devoted to the problems of legal regulation of AI, as well as investigation of the first cases of the use of generative AI models in legal practice and education. Methods of legal qualification, comparative legal analysis, and legal modeling are applied. Prompts are qualified as legal actions (legal facts in the strict sense), which opens the path to addressing the applicability of copyright criteria to them. The potential and risks of using prompts in legal practice and education are identified, and the need for standardizing prompts and developing specialized methods for teaching lawyers to interact with AI is substantiated. Prompts, as a tool for human-AI interaction, represent a fundamentally important subject of legal research, upon which the prospects for AI application in law largely rely. The article concludes that interdisciplinary and international studies are necessary to unite the efforts of legal professionals, AI specialists, and the generative models themselves in developing optimal legal solutions.

‌ ∴ Introduction ∴ ‌The inception of artificial intelligence (AI) as a transformative force in modern society has presented novel challenges across various domains, particularly within the realm of intellectual property (IP) law. Traditionally, IP laws have been predicated on the notion that creativity and invention are inherently human attributes, thereby granting protection exclusively to works generated by human authors. However, the rapid evolution and sophistication of AI has alleviated the gap between human and machine-generated outputs, challenging the foundational principles upon which IP law is built. As AI systems increasingly demonstrate capabilities akin to human creativity, such as generating artworks, music, literature, and even innovative technological solutions, the question of ownership and protection of these AI-generated works becomes more pressing. Historically, the attribution of authorship in computer-generated outputs was straightforward; the person who legally utilized the computer system was considered the author. However, with AI's capacity to autonomously generate complex and creative works, this traditional approach to authorship is no longer adequate. AI’s role in the creation process varies from being a mere tool used by human creators to being an independent creator of works with minimal human intervention. As AI continues to develop and integrate into more aspects of society, the implications for IP law become increasingly complex and far-reaching. This paper seeks to explore these complexities and offer a comprehensive analysis of the ownership issues related to AI-generated works. The discussion delves into the theoretical underpinnings of IP law, the economic implications of AI innovations, and the potential need for legal reforms to address the challenges posed by non-human creators. By examining these issues, the article aims to provide clarity and propose solutions that balance the interests of creators, innovators, and society at large.‌ ∴ Research Question ∴ ‌The central research question guiding this study is: who owns the intellectual property rights to works generated by artificial intelligence? This question is further subdivided into several key inquiries: Can AI be recognized as the owner of the intellectual property it generates? If not, who should be considered the rightful owner of these AI-generated works—the developer, the user, or some other party? How do existing IP frameworks across different legal systems address or fail to address the issue of AI-generated works? What are the potential economic and commercial implications of the lack of clear ownership rights for AI-generated works? These questions are critical as they address the foundational elements of IP law and its application to emerging technologies. The resolution of these questions will have significant implications not only for legal theory but also for the practical aspects of innovation, investment, and the development of AI technologies.‌ ∴ Research Hypothesis ∴ ‌The research is grounded in the hypothesis that the ownership of AI-generated works should be legally recognized to promote innovation and economic growth. This hypothesis is based on the premise that recognizing ownership rights in AI-generated works is essential for several reasons: Incentivizing innovation: legal recognition of ownership rights is crucial for encouraging further investment in AI. Without such recognition, the risk of investing in AI may outweigh the potential rewards, leading to a slowdown in technological advancement. Economic Fairness: companies and individuals who invest significant resources into developing AI technologies should have their investments protected. If AI-generated works are not protected, these entities could face unfair competition from others who freely use their innovations without compensation. Legal Clarity: The current ambiguity in IP law regarding AI-generated works could lead to legal disputes and inconsistencies in court rulings. Establishing clear ownership rules will provide legal certainty and reduce the potential for litigation.‌ ∴ Methodology & Framework, if Applicable ∴ ‌This research adopts a comparative-doctrinal methodology to analyze the treatment of AI-generated works across different legal systems. The study is structured to explore both theoretical and practical dimensions of the issue, with a focus on how various jurisdictions are addressing—or failing to address—the ownership of AI-generated intellectual property. Comparative Analysis: The research begins with a comparative analysis of IP laws in several jurisdictions, including the United States, European Union, Japan, and others. By examining how different legal systems approach the question of AI-generated works, the study aims to identify commonalities, differences, and potential gaps in the current legal frameworks. Doctrinal Approach: The doctrinal approach involves a detailed examination of legal texts, case law, and statutes relevant to IP law and AI-generated works. This approach is essential for understanding how existing laws might be interpreted or adapted to address the new challenges posed by AI. The research critically analyzes legal doctrines such as authorship, originality, and creativity, assessing their applicability to AI-generated works. Economic and Investment Justifications: In addition to the legal analysis, the research also considers the economic and investment implications of recognizing or not recognizing ownership rights in AI-generated works. This aspect of the study involves an analysis of market trends, investment patterns in AI technologies, and the potential economic impact of different legal approaches to AI-generated works.‌ ∴ Results & Discussion ∴ ‌The analysis of AI-generated works under current intellectual property (IP) laws reveals a significant gap between the traditional legal frameworks and the challenges posed by emerging technologies. The results of this study indicate that existing IP laws are inadequate to address the complexities associated with works created by artificial intelligence, primarily because these laws are predicated on the notion of human authorship. The inability of traditional IP law to recognize non-human entities as creators or authors leads to significant ambiguity regarding the ownership and protection of AI-generated works. Ownership and Authorship of AI-Generated Works: One of the key findings of this paper is that the traditional concept of authorship, which ties the creation of a work to human ingenuity and effort, is becoming increasingly problematic in the context of AI-generated works. As AI systems become more autonomous in their creative processes, the distinction between human-created and machine-generated works blurs. This blurring raises the question of whether the law should adapt to recognize AI as a potential author or whether the law should continue to focus on the human elements in the creation process. It is shown that the British model, which grants ownership rights to the person who enables the operation of the AI, appears to be the most practical and effective approach. This model ensures that the entities investing in AI technology are rewarded for their contributions, thereby encouraging continued innovation and investment. By recognizing the programmer, user, or entity that initiates the AI’s creative process as the owner of the resulting work, the law can maintain the incentive structures that underpin IP law. However, this approach is challenging. One of the key concerns is determining the extent of human involvement necessary to claim ownership. In scenarios where the human contribution is minimal—such as merely pressing a button to initiate the AI’s creative process—there is debate over whether this should be sufficient to warrant full ownership rights. This issue becomes even more complex when considering AI systems that are capable of learning and evolving independently of human input, potentially leading to the creation of works without any direct human intervention. Economic and Legal Implications: The research also highlights the significant economic and legal implications of not adequately addressing the issue of AI-generated works. Without clear ownership rights, the economic incentives for investing in AI technologies could be undermined. Companies and individuals may be less willing to invest in AI research and development if the outputs of their investments are not protected under IP law. This could slow down technological progress and innovation, particularly in sectors where AI has the potential to drive significant advancements. Additionally, the lack of clear legal guidelines could lead to an increase in litigation as parties seek to assert ownership over AI-generated works. The study suggests that resolving disputes on a case-by-case basis, as seen in judicial practices like the "Nova Productions Ltd. v. Mazooma Games Ltd." case, may provide a temporary solution. However, relying on case-by-case adjudication is likely to result in inconsistent outcomes and could contribute to legal uncertainty, making it difficult for businesses to navigate the landscape of AI-generated works. Judicial and Legislative Approaches: The research finds that judicial approaches to AI-generated works have thus far been limited and inconsistent. Courts have generally been hesitant to extend IP protection to non-human creators, often defaulting to traditional interpretations of authorship and creativity. However, as AI becomes more prevalent, there is a growing recognition that legislative reform may be necessary to address these challenges systematically. One possible legislative approach is to create a new category of IP that specifically addresses AI-generated works. This new category could establish criteria for determining ownership based on the level of human involvement, the nature of the AI’s creative process, and the economic impact of the work. Such legislation would need to balance the need for innovation and investment with the principles of fairness and equity, ensuring that all stakeholders—developers, users, and society at large—are adequately protected and rewarded.‌ ∴ Conclusion ∴ ‌In conclusion, the rapid development of AI technologies presents significant challenges to the current intellectual property framework, particularly in the context of ownership and authorship of AI-generated works. The study underscores the necessity of adapting IP laws to address these challenges, as the traditional concept of human authorship becomes increasingly difficult to apply in the digital age. The British model, which attributes ownership to the person or entity that enables the AI’s creative process, emerges as a viable solution. This approach balances the need to protect investments in AI technology with the recognition that human involvement in the creative process may vary significantly. By granting ownership rights to those who initiate the AI’s operations, the law can ensure that innovation continues to be incentivized while also providing a clear legal framework for AI-generated works. However, the study also recognizes that this approach has its limitations. The minimal human intervention required in some AI-generated works raises questions about the adequacy of this model in all cases. There is a need for further refinement of the legal framework to address scenarios where AI operates with significant autonomy, potentially creating works with little to no human input. The economic implications of failing to address these issues are considerable. Without clear ownership rights, the incentive for investment in AI technologies could be diminished, slowing the pace of innovation and potentially stifling the development of new technologies that have the potential to benefit society as a whole. Moreover, the lack of legal clarity could lead to increased litigation, creating further uncertainty and potentially hindering the growth of industries reliant on AI. As AI continues to evolve, so too must the laws that govern the ownership and protection of the works it generates. The study suggests that a combination of legislative reform and judicial interpretation will be necessary to create a robust and adaptable IP framework capable of addressing the unique challenges posed by AI-generated works. By doing so, the law can ensure that the benefits of AI technology are realized while also protecting the rights and interests of all stakeholders involved.

The question of authorship and legal ownership in AI-generated creative materials has become a contentious issue on an international level. This paper investigates the complexity of attribution of legal copyrights within the framework of the U.S. Copyright Law system and explores potential solutions to this evolving dilemma. The U.S. Copyright Law, rooted in the protection of inventors' exclusive rights, extends to both authors and owners, intending to safeguard intellectual property in the judicial field. AI-generated works, however, present a unique issue as they blur the lines of authorship in presented works. The U.S. Copyright Office, while expressing interest in addressing these issues, currently rejects applications attributing AI as the primary creator due to historical legal precedents, marking uncertainty with both creators and the general public about the future of commercialized AI-generated works. This paper highlights the intricate legal and philosophical questions surrounding AI and copyright law, emphasizing the need to carefully consider the roles and responsibilities of both AI and its users in the creative process. As AI technology continues to evolve, these debates will shape the future of copyright law's application to AI-generated works. The current application of AI in the creative process does fit within the U.S. Copyright Law, but with further evolution, the scope of human involvement could be reduced.

The rapid development of deep learning technology has led to the emergence of diffusion models as a promising generative model with diverse applications. These include image generation, audio and video synthesis, molecular design, and text generation. The distinctive generation mechanism and exceptional generation quality of diffusion models have made them a valuable tool in these diverse fields. However, with the extensive deployment of diffusion models in the domain of image generation, concerns pertaining to data privacy, data security, and artistic ethics have emerged with increasing prominence. Given the accelerated pace of development in the field of diffusion models, the majority of extant surveys are deficient in two respects: firstly, they fail to encompass the latest advances in diffusion-based image synthesis; and secondly, they seldom consider the potential social implications of diffusion models. In order to address these issues, this paper presents a comprehensive survey of the most recent applications of diffusion models in the field of image generation. Furthermore, it provides an in-depth analysis of the potential social impacts that may result from their use. Firstly, this paper presents a systematic survey of the background principles and theoretical foundations of diffusion models. Subsequently, this paper provides a detailed examination of the most recent applications of diffusion models across a range of image generation subfields, including style transfer, image completion, image editing, super-resolution, and beyond. Finally, we present a comprehensive examination of these social issues, addressing data privacy concerns, such as the potential for data leakage and the implementation of protective measures during model training. We also analyse the risk of malicious exploitation of the model and the defensive strategies employed to mitigate such risks. Additionally, we examine the implications of the authenticity and originality of generated images on artistic creativity and copyright protection. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) have become the state of the art in natural language processing. The massive adoption of generative LLMs and the capabilities they have shown have prompted public concerns regarding their impact on the labor market, privacy, the use of copyrighted work, and how these models align with human ethics and the rule of law. As a response, new regulations are being pushed, which require developers and service providers to evaluate, monitor, and forestall or at least mitigate the risks posed by their models. One mitigation strategy is digital forgetting: given a model with undesirable knowledge or behavior, the goal is to obtain a new model where the detected issues are no longer present. Digital forgetting is usually enforced via machine unlearning techniques, which modify trained machine learning models for them to behave as models trained on a subset of the original training data. In this work, we describe the motivations and desirable properties of digital forgetting when applied to LLMs, and we survey recent works on machine unlearning. Specifically, we propose a taxonomy of unlearning methods based on the reach and depth of the modifications done on the models, we discuss and compare the effectiveness of machine unlearning methods for LLMs proposed so far, and we survey their evaluation. Finally, we describe open problems of machine unlearning applied to LLMs and we put forward recommendations for developers and practitioners. [ABSTRACT FROM AUTHOR]

The subject of the presented paper is the normative foundations and doctrinal approaches to industrial designs and museum objects as intellectual property objects, which is predetermined by the purpose of the research, which is to identify the relationship and interaction of norms regulating relations in the field of intellectual property objects having the features of museum objects and industrial designs. The methodological basis was made up of a comparative method that allowed us to correlate the concept, signs, and legal consequences of the regimes of the considered objects. The methodology of the study also included a content analysis of information systems containing information about intellectual property objects, as well as a formal legal method that allowed to reveal the essence of the legal nature of the ratio of the studied objects. According to the results of the study, the general and special characteristics of museum objects and industrial designs were established, the correlation of the legal regime of the considered objects was revealed. Based on this, the field of applied results consists of public relations related to the processes of museumisation of industrial heritage aimed at preserving and popularizing cultural values of industrial activity. The conclusions obtained made it possible to note the differentiation of objects of protection in copyright and patent law, it was established that industrial designs cannot be represented by methods and means of protection peculiar to copyright object. This distinction is also due to the definition of an industrial design and methods of use established in civil legislation. At the same time, it is recognized that the ideological component of a particular intellectual property object in the conditions of its life cycle can move from the mode of an industrial design to the mode of a museum object.

The current increase in the music industry in Indonesia is in line with the development of the complexity of the legal issues that accompany it. This then triggers the emergence of disputes over works in the music industry in cases of copyright for a work. Like the copyright infringement case that occurred between Ahmad Dhani and Once Mekel. This research aims to answer two legal issues, namely to analyze legal protection for copyright holders for commercial use of written songs without permission and to determine the legal consequences for commercial use of written songs without the creator's permission. The research method used in this research is analytical descriptive which describes the problems that occur which will be explained qualitatively. Based on the existing analysis, Ahmad Dhani has carried out preventive protection by informing the media that there is a prohibition on performing the song Dewa19 at commercial music concerts. The legal consequences for both civil and criminal violations have been regulated in Article 113 of Law No. 28 of 2014 concerning Copyright for violation of Economic Rights. The conclusion of this research is the issuance of Government Regulation No. 56 of 2021 to prioritize legal certainty and legal protection for creators regarding economic rights. The song copyright violation was committed by Once Mekel who sang the song Dewa19 without Ahmad Dhani's permission and did not pay royalties and this violation is regulated in Article 113 of Law No. 28 of 2014 concerning Copyright.

The emancipatory effect of copyright on the lives of creators has long been hindered by the concentration of rights by powerful entities that can hold creativity hostage through exclusive rights over countless cultural references. Exceptions to copyright have played an important counter-hegemonic role, supporting what we might call a public domain counterprinciple. The recent explosion of generative artificial intelligence (GenAI) upends this scenario, with creators bringing copyright infringement claims to the courts to determine, inter alia, the existence and relevance of copying in the training process and whether AI outputs qualify as derivative works. Using digital art as an example, this article assesses these dynamics from the perspective of emancipation, considering the interplay of copyright rules, exceptions, principles and counterprinciples, and seeks to devise pathways, within and outside copyright, to address the challenges posed to creators by GenAI.