The repercussion of Artificial Intelligence on Literary and Artistic Property Rights

Legal and Political Research Vol 11, N°01, June (2026) / 652-665 The Repercussions of AI on Literary and Artistic Property Rights تداعيات الذكاء االصطناعي على حقوق الملكية األدبية والفنية Chaoua Hellal * University of Echahid Cheikh Larbi Tebessi, Tebessa, Algeria [email protected] Date of send: 35/04/2026 Date of acceptance: 24/06/2026 Date of publication ;11/06/2026 ـ ــــــــــــــــــــــــــــــــــــــــــــــــ ـ ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ ـــــــــــــــــــــــــــــ Abstract: This study examines the impact of artificial intelligence on literary and artistic property rights. Employing a descriptive-analytical method, it addresses the question of how copyright law can accommodate AI-assisted or AI-generated output without undermining the human-centered core of authorship and existing copyright in prior works. The article argues that AI does not render copyright law obsolete; on the contrary, AI highlights ambiguities that must be resolved. Current guidance in the U.S. clarifies that fully AI-generated works are not copyrightable — only works with significant human creative input qualify. Thus, the rise of AI emphasizes the need to clarify: (a) what level of human creativity is needed to qualify an AI-assisted work for protection, and (b) whether and how AI training involving copyrighted materials should be regulated. Artificial intelligence has progressed from a mere technical tool to a direct creator of texts, images, music, and other works. This shift makes AI relevant not only for innovation and digital policy, but also for the core of copyright law, since it affects both new works and the use of pre-existing works. The central question is no longer whether AI matters to copyright, but how far existing legal concepts can be stretched in a technologically altered creative environment. Keywords: Artificial intelligence; literary and artistic property rights; AI Act. * Corresponding author

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 356 Introduction Artificial intelligence (AI) has moved beyond a merely technical or assistive function and is now extensively used in creative processes, transforming the creative environment.1 In fact, AI-generated art and literature have taken off in recent years. This evolution raises novel challenges for intellectual property: existing legal regimes were designed for human creativity and may not fully contemplate works produced by machines.2 The legal difficulty arises because literary and artistic property rights were conceived in a human-cantered legal order: they protect ―authors’‖ creations and grant authors exclusive rights. 3 For example, the Berne Convention protects ―every production in the literary… domain‖ by authors, implicitly presupposing a human author.4 Modern courts and policymakers have thus affirmed a human-authorship requirement: AI-generated works are generally non-protectable when no human creator is involved5. With comparative practice evolving rapidly, the central question is how to ensure that existing works used in AI systems remain effectively protected. To answer this question, the article uses a descriptive-analytical method and first clarifies the conceptual foundations of authorship and the protection of pre-existing works under current law. The legal difficulty arises from the fact that literary and artistic property rights were traditionally built around the human author. Under the Berne Convention, authors of literary and artistic works6 have exclusive economic rights (e.g. to authorize reproductions) as well as moral rights over their works. Similarly, Algerian law organizes protection through Ordinance No.03-05 of 19 July 2003 on copyright and related rights.7 These laws were conceived for human creators and their creative expressions.8 Recent developments illustrate the significance of the issue. In the United States, both the Copyright Office and courts have reiterated that works created entirely by machines fall outside copyright. For example, the D.C. District Court in Thaler v. Perlmutter held that only human beings can be authors under U.S. law. The court noted that an AI-generated work that met all technical criteria for protection still lacked copyright because ―only human beings qualify as authors‖. This reaffirmation in turn aligns with the Copyright Office’s consistent position that human authorship is required for protection. In other words, under current doctrine, AI creations without creative human involvement receive no copyright.9 Accordingly, the central research problematic of this article is: How can literary and artistic property rights law account for AI-generated output? To address this, we adopted a descriptive-analytical approach and divided the research into three parts. Part I first examines the conceptual foundations of copyright (the nature of protected works, authorship requirements, etc.). Part II then analyses the impact of AI technologies on these foundations — for example, whether AI can be treated as a tool or co-author, and how AI affects the requirements of originality and human

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 356 creativity. Finally, Part III proposes legal solutions and policy recommendations, including how Algerian law (and similar regimes) might adapt. Firstly: The Conceptual and Legal Foundations of Literary and Artistic Property Rights in the Age of AI Literary and artistic property rights are traditionally based on the protection of human creativity, originality, and authorship. The rise of artificial intelligence challenges these principles by generating creative works with limited or no human intervention, raising complex issues of authorship and ownership. Consequently, scholars and international organizations are calling for a reexamination of copyright doctrines to determine how AI-generated content should be treated within existing legal frameworks.10 1. The legal foundations of literary and artistic property rights The legal foundations of literary and artistic property rights are based on the recognition of authors’ economic and moral rights over their original works. International instruments, particularly the Berne Convention, guarantee automatic copyright protection and grant authors exclusive control over the use and reproduction of their creations. These rights are justified by the view that creative works reflect the author’s intellectual effort and personal expression, warranting both proprietary and moral protection.11 1.1. Definition, characteristics and legal nature of literary and artistic property rights Literary and artistic property rights comprise the branch of intellectual property law that protects ―literary and artistic works‖ and related rights. International law, notably the Berne Convention, defines the protected field broadly as ―every production in the literary, scientific and artistic domain, whatever the mode or form of its expression‖ (Article 2(1)). In domestic law, this is embodied in provisions protecting works of authorship, such as the eight traditional categories listed in the U.S. Copyright Act (e.g. literary works, music, artwork). These rights combine pecuniary (economic) interests and extra-pecuniary (moral/personal) interests of authors. Economically, they grant authors exclusive exploitation rights (reproduction, distribution, etc.), thereby incentivising creation. These rights also implicitly recognize the author’s personal connection to the work – for instance, through moral rights of attribution and integrity (long upheld especially in civil-law countries) and through rights of disclosure or withdrawal. In short, literary/artistic rights12 rest on the notion of a human creator whose personality13 and labor infuse the work. This dual character (economic and personal) remains fundamental to copyright’s normative foundation. Literary and artistic property rights (often called ―authors’ rights‖ or ―droits d’auteur‖ in civil-law countries) refer to the bundle of rights granted to creators of expressive works. These rights protect authors of books, music, art, films, software, and other original works. They typically include economic rights (such as the

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 355 exclusive right to reproduce, distribute, and perform the work) and moral rights (such as the right to claim authorship and to object to derogatory alterations). For example, the Berne Convention explicitly grants authors the exclusive right to authorize reproduction of their literary and artistic works. In this sense, literary and artistic property rights are a branch of property law protecting intangible creative expressions. They benefit not only the creator as a source of economic reward but also the author’s personal and reputational interests (through moral rights). Legally, literary and artistic property rights are treated as sui generis intellectual property rights grounded in authorship. The rationale is that copyright law creates a normative framework to incentivize creation by granting authors a limited monopoly over their works. In other words, copyright is considered a special type of monopoly right bestowed on authors. This distinguishes it from ordinary contract or property rights – it is essentially a legal regime designed to encourage cultural production. The formal conditions for protection (such as fixation, originality, and human authorship) define the regime’s scope, while the rights themselves (economic and moral) define the author’s privileges under the law. 1.2. Objectives, scope and limits of protection The protection of literary and artistic works serves multiple objectives. Primarily, it rewards and incentivises creativity by granting authors exclusive rights over their creations (reproduction, distribution, etc.). By securing a fair return on creative effort, the regime encourages investment in new works. At the same time, the law balances these exclusive rights with public interest considerations through limited exceptions and limitations (e.g. quotation, education, fair dealing, and – since the 2019 DSM Directive – text- and data-mining for research). For example, recent scholarship notes that adopting exceptions (such as a data-mining exception or author compensation mechanisms) could reconcile AI development with copyright protection. Moreover, special rights (like moral rights) protect the author’s non- economic interests (paternity, integrity) and ensure credit and control over how the work is used. In sum, literary and artistic rights aim to foster creativity and cultural dissemination, while preserving the author’s connection to the work. The primary objective of copyright is to stimulate the creation and dissemination of culture by giving authors control over their works. By doing so, it balances public access with fair compensation for creators. For instance, exclusive reproduction rights enable authors to exploit and license their works commercially, while statutory limits (like fair use or exceptions) prevent abuse. In most systems, moral rights complement this by protecting non-economic interests (authorship and integrity) even after the economic rights expire. Traditionally, copyright protects fixed ―original‖ works of authorship – that is, creative works reflecting some minimal degree of creativity. The idea/expression dichotomy means that copyright does not cover bare ideas or facts, only their concrete expression. Nor does it protect works that are too trivial (e.g. mechanical instructions without creative authorship). The scope of protection is constrained by

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 353 formalities (fixation, authorship) and exceptions (quotation, research exceptions, etc.). For example, the Berne Convention allows compulsory licenses and certain free uses where they ―do not conflict with a normal exploitation‖ of the work. These built- in limitations reflect a compromise between the interests of authors and the public. 2. The legal and technical framework of AI The legal and technical framework of artificial intelligence is based on principles of transparency, accountability, human oversight, and safety. International instruments such as the OECD AI Principles, UNESCO’s Recommendation on the Ethics of AI, and the EU AI Act promote trustworthy and human-centric AI systems. From a technical perspective, effective AI governance requires reliable data management, algorithmic transparency, cybersecurity, and continuous risk assessment throughout the AI lifecycle.14 2.1. Concept and main characteristics of AI Artificial intelligence is generally understood as a machine-based system capable of generating outputs such as predictions, recommendations, decisions, or content that influence physical or virtual environments. The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) establishes a risk-based regulatory framework, distinguishing between:  prohibited AI practices (Article 5),  high-risk AI systems (Article 6 and Annex III),  AI systems subject to transparency obligations (Article 50), and  minimal-risk systems that remain largely unregulated. This approach reflects the principle that legal obligations should increase in proportion to the risks posed to health, safety, and fundamental right.15 Notably, Article 60 of the AI Act imposes transparency obligations on providers of generative AI: users must be informed when content (images, text, audio) is AI- generated, especially to flag deepfakes or politically-relevant material. The Act also lists prohibited practices (e.g., social scoring, covert biometric ID). In short, AI law acknowledges categories of systems (generative models, machine learning, etc.) and imposes duties (data quality, logging, transparency) tailored to the technology’s potential impact. 2.2. Types of AI relevant to literary and artistic production The most legally significant form of artificial intelligence in the creative sector is generative AI, which uses machine-learning models to produce new content, including images, text, music, and audio-visual works. These systems rely on advanced architectures such as Generative Adversarial Networks (GANs), diffusion models, and neural networks capable of learning patterns from large datasets and generating novel outputs in response to user prompts. Their growing ability to create expressive works has raised important legal questions concerning authorship, copyright ownership, and the use of protected works in training datasets.16

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 356 Because generative AI systems learn from and transform existing data, they raise fundamental questions regarding authorship, originality, and copyright ownership. Legal scholarship commonly distinguishes between three situations: (1)- a human uses AI merely as a tool or assistant; (2)- AI produces output with only minimal human input; and (3)- AI acts entirely autonomously.17 Each scenario has different implications for protection under existing rules. Some scholars suggest allowing for the possibility of ―non-human authors‖ in law, placing AI creators and owners on the policy agenda, but the prevailing trend is to focus on the human input in each case.18 2.3. The legal relevance of AI to L&AP rights AI relates to literary/artistic rights in two main ways. First, it can circumvent human authorship by producing new works without direct human creative control. Courts and officials note that copyright law traditionally requires a human author, so purely AI-originated works challenge that premise. Second, AI is highly dependent on pre-existing works as data.19 In generating art, AI systems ingest and remix vast amounts of copyrighted material. This raises significant infringement risks: using copyrighted works as training data can itself be an unauthorized use. Legal scholarship therefore focuses on how to treat these AI-internal uses – for example, by crafting (or expanding) exceptions and licensing solutions for text- and data-mining. In both respects, AI forces a re-evaluation of core principles: who is an ―author‖ of the output, and how to protect the original works that feed AI models.20 Given this framework, the introduction of AI raises novel questions. AI systems can now autonomously generate text, images, music, and other creative content. Does this mean the outputs automatically have copyright, or should they be treated as ineligible? Traditional copyright cannot assign authorship to a machine (non-human). Thus, outputs created wholly by AI (with no human creative input) have been deemed uncopyrightable in the U.S. – reflecting the principle that copyright ―protects the expression of ideas by humans,‖ not machine output. The U.S. Copyright Office reiterated this: only works ―with sufficient human authorship‖ can be protected.21 However, AI’s role is often more subtle. Many AI outputs result from human prompts, edits, or curation. In such cases, the human’s creative input may imbue the result with enough originality to qualify as an ―AI-assisted‖ work. The law must thus distinguish between: (1)- AI as a mere tool or intermediary (similar to a camera or typewriter), and (2)- AI as a creative force itself. If AI is a tool, the human guiding it is the author; if AI is ―autonomously‖ generating works, conventional authorship is missing. This distinction matters for protection and for the legal status of uses of protected works in training.22 Additionally, AI challenges notions of originality and copying. When an AI system generates a piece, is it a ―copy‖ of training data or a new expression? Cases

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 356 pending in the U.S., such as Andersen v. Stability AI, address whether scraping copyrighted images to train AI constitutes reproduction. If courts decide that training is copyright infringement, this could impose licensing requirements on AI developers. If not, it might spur legislative or treaty efforts to clarify the rules. In sum, AI’s emergence forces a reexamination of the fundamental principles of literary and artistic property rights, without necessarily overturning those principles. Instead, AI highlights where definitions (e.g., ―author‖, ―originality‖, ―reproduction‖) must be clarified for the machine era.23 Secondly: The Impact of AI on L&AP Rights The impact of artificial intelligence on literary and artistic property rights lies in its ability both to generate creative content and to rely on copyrighted works for training. This dual role challenges traditional copyright concepts, particularly authorship, originality, and reproduction, while prompting calls for clearer legal frameworks governing AI-generated works and the use of protected content in machine learning.24 1. AI-generated outputs and the conditions of protection Copyright protection of AI-generated content generally depends on the presence of meaningful human authorship and originality. Works created with substantial human creative input may qualify for protection, whereas fully autonomous AI- generated outputs are typically not protected under current copyright laws.25 1.1. The challenge to human authorship The most immediate legal challenge posed by AI-generated output is the human authorship requirement. In U.S. law and similarly in most jurisdictions, copyright protection attaches only to works of human creation. Recent U.S. decisions have made this explicit: for example, in Thaler v. Perlmutter the court held that works produced solely by an AI (―Creativity Machine‖) lack the required human author.26 Copyright law recognizes only human authors as creators of protected works. In Naruto v. Slater, the court confirmed that non-human entities cannot qualify as copyright authors, a principle that has been extended by analogy to AI-generated works. Accordingly, artificial intelligence cannot itself hold authorship rights under current copyright frameworks. 27 The U.S. Copyright Office likewise states that extending copyright to ―material whose expressive elements are determined by a machine‖ would undermine copyright’s goals. The practical upshot is that AI-generated outputs are not protectable on the AI’s account.28 However, when a human merely uses an AI as a tool (providing detailed instructions or making creative selections), the output may qualify as a ―joint‖ creation or primarily human creation. For example, when a human author selects and arranges elements of an AI-generated image (as in the ―Zarya of the Dawn‖ case), copyright was granted for the human-curated aspects but not for the raw AI content. In sum, current practice suggests focusing on the human in the loop: works ―made

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 356 with‖ AI can be protectable as human authorship, but works ―made by‖ AI alone generally cannot.29 1.2. Originality and the role of human creative control Originality remains a fundamental requirement for copyright protection and is increasingly important in AI-related works. Under U.S. copyright law, originality requires independent creation and a minimal degree of human creativity. In Feist Publications, Inc. v. Rural Telephone Service Co.,30 the Supreme Court confirmed that copyright protects only works containing some creative expression. The Court rejected the ―sweat of the brow‖ doctrine, holding that effort alone does not justify copyright protection. Therefore, facts, data, and purely mechanical compilations are not protected unless their selection or arrangement reflects creative human judgment.31 On the other hand, if the user exercises substantial creative control over the AI process and output, the human may impart sufficient originality. In practice, courts have insisted on human ―direction‖ or ―guiding hand‖ as the dividing line: ―[c]opyright has never stretched… to protect works generated by new forms of technology absent any guiding human hand,‖ and human authorship is a ―bedrock requirement‖. 32 Thus, originality in the AI era depends on the extent and character of the human contribution – the ―selection, coordination or arrangement‖ of AI-generated material by a person (as in the Zarya guidance) can create a protectable work, whereas mere output of the machine cannot.33 2. AI and the protection of pre-existing works 2.1. The use of protected works in training AI systems The second major issue is how to handle AI’s use of copyrighted works during training. Most generative models rely on massive datasets of existing art, and this ―scraping‖ poses potential infringement of reproduction or adaptation rights. Policymakers have generally moved away from allowing AI systems to freely appropriate copyrighted material without consequence.34 Instead, the trend is toward promoting licensing and fair use. For example, an EU Code of Practice for generative AI (2023) encourages companies to comply with intellectual-property laws and obtain licenses for training data, rather than rely on unclear de facto permissions.35 Similarly, recent studies and proposals (e.g. the EU’s text-and-data mining exception in Directive 2019/790) suggest tailored exceptions: some scholars argue for a compulsory data-mining exception for research, or payments to authors whose works are used in training. The key point is that existing laws remain the starting point: there has not been wholesale abandonment of copyright for AI. The emphasis is on clarifying and updating the legal framework (through exceptions or new rights) so that AI training can proceed without unremedied infringement.36

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 336 2.2. Risks of imitation, derivative output and deepfakes A related concern is downstream misuse of AI: after training, AI systems can generate ―imitation‖ works and deepfakes that mimic existing artists’ styles. These outputs can threaten both economic and non-economic rights of original creators. For example, an AI-generated image that closely imitates a living artist’s style may harm that artist’s reputation or dilute their market. Transparency measures are one proposed remedy: the EU AI Act (2024) requires that AI-generated images, deepfake media and politically-relevant synthetic texts be clearly labeled as such. However, labeling alone is insufficient to eliminate harm. The real-world impact goes beyond market substitution to moral and reputational interests – the ―personal connection‖ between author and work can be undermined by unauthorized mimicking or ―fake‖ continuations of an artist’s oeuvre.37 Consequently, some countries are considering stronger controls on AI-generated deepfakes and derivatives to protect personal rights of authors and performers (analogous to protections in French droit moral or the U.S. ―personal rights‖ recognized for certain artistic works). Ultimately, the challenge will be to strike a balance between fostering innovation and guarding against non-market harms (such as violation of an author’s honour or privacy) that AI might facilitate.38 Conclusion The rapid advancement of artificial intelligence has significantly reshaped the field of literary and artistic creation, raising fundamental questions about the continued adequacy of legal frameworks traditionally grounded in human creativity, authorship, and originality. This study has demonstrated that, despite remarkable technological progress, contemporary copyright systems remain firmly anchored in the principle of human authorship. Whether under international copyright instruments, national legislation, or emerging regulatory initiatives, legal protection continues to depend on the existence of meaningful human intellectual contribution. Consequently, while AI systems are capable of generating increasingly sophisticated creative outputs, works produced entirely without human intervention generally fall outside the scope of copyright protection. The research further highlights two major categories of legal challenges arising from the development of generative artificial intelligence. The first concerns the status of AI-generated works and their compatibility with traditional copyright requirements. The growing capacity of AI systems to produce literary, artistic, and audiovisual content has intensified debates regarding authorship, originality, and ownership. Nevertheless, current legal practice largely confirms that copyright protection remains contingent upon a sufficient degree of human creative involvement, making the human contribution the decisive factor in determining the protectability of AI-assisted works.

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 336 The second challenge relates to the extensive use of copyrighted materials in the training of AI models. Generative systems rely heavily on large datasets composed of pre-existing works, creating uncertainty regarding reproduction rights, licensing requirements, and permissible text-and-data mining activities. At the same time, AI technologies facilitate the creation of imitative works, stylistic reproductions, and deepfakes capable of affecting not only the economic interests of authors but also their moral rights, reputation, identity, and artistic integrity. These concerns reveal that the legal implications of AI extend beyond traditional questions of copyright infringement and encompass broader issues relating to human dignity, authenticity, and the protection of creative personality. The findings of this study therefore suggest that artificial intelligence does not invalidate the foundations of literary and artistic property rights. Rather, it exposes the need to clarify, refine, and adapt existing legal concepts to new technological realities. Fundamental copyright principles—including human authorship, originality, protection of creative expression, and respect for moral rights—remain capable of providing an appropriate normative framework for addressing AI-related challenges. The task facing legislators is not to replace these principles but to ensure their effective application within an increasingly digital and algorithm-driven creative environment. Results of the Study: The research has produced several important findings. First, human authorship continues to constitute the essential basis of copyright protection, with fully autonomous AI-generated works generally remaining outside the scope of legal protection under existing copyright regimes. Second, AI-assisted creations may benefit from copyright protection when a human author exercises substantial creative judgment through the design, selection, arrangement, modification, or refinement of the generated content. Third, originality remains a central condition for protection, although its assessment increasingly requires careful examination of the nature and degree of human participation in AI-assisted creative processes. Fourth, the use of copyrighted works for training AI systems represents one of the most complex and unresolved issues in contemporary copyright law, particularly with regard to reproduction rights, licensing requirements, and text-and-data mining exceptions. Recommendations: In light of these findings, several recommendations may be advanced. Legislators should establish clearer criteria for determining when AI-assisted works satisfy the threshold of human creativity necessary for copyright protection. The principle of human authorship should be preserved as the cornerstone of literary and artistic property rights, while recognizing the role of AI as a creative tool that supports rather than replaces human intellectual activity.

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 336 A transparent legal framework governing AI training data should be developed, including obligations concerning the disclosure of data sources and the lawful use of copyrighted materials. Specific legal exceptions for text-and-data mining should be introduced or refined, particularly for scientific research and public-interest purposes, while maintaining appropriate safeguards for copyright owners. International cooperation should be encouraged in order to promote greater harmonization of legal standards governing artificial intelligence and copyright, particularly through the work of international organizations and multilateral initiatives. At the national level, Algerian copyright legislation should be modernized to address AI-generated content, the use of copyrighted works in machine learning, algorithmic transparency obligations, and the protection of authors against harmful synthetic reproductions. Margins : 1- Caldwell Mackenzie, What Is an ―Author‖? Copyright Authorship of AI Art Through a Philosophical Lens, Houston Law Review, vol. 61, issue 2, pp.181-184. 2- Shakeri Zahra, The Literary and Artistic Property Law System in the Age of Artificial Intelligence: Considerations for Policymaking, Journal of Public Policy and Law, Univ. of Tehran, 2025. - U.S. Copyright Office, Copyright and Artificial Intelligence: Part 2, NewsNet No.1060, 29 Jan. 2025. 3- Regulation (EU) 2024/1689; Commission AI Act page; Commission FAQ on transparency obligations. 4- Berne Convention arts 2, 6bis, 9. - Ordinance No 03-05 on Copyright and Related Rights. 5- Phelan Ryan N., How U.S. Copyright Law on Artificial Intelligence Authorship Has Gone the Way of the Monkey, PatentNext blog, 27 Sept. 2023). 6- World Intellectual Property Organization, TRT/BERNE/001, Berne Convention for the Protection of Literary and Artistic Works (as amended on September 28, 1979) (Authentic text). 7- Ordinance No.03-05 of 19 Joumada El Oula 1424 corresponding to July 19, 2003, on Copyright and Related Rights, dated 23 Jumada I 1424 AH, corresponding to July 19, 2003, Official Gazette No.44. 8- Historically, the first law protecting copyright was issued in Britain in 1710 and was called the Queen Anne Act. The first law protecting industrial property appeared much earlier, in 1474 in Venice, Italy. The first Convention concluded in this regard was the Berne Convention on September 19, 1886, which Algeria joined by Presidential Decree 97-341 dated September 13, 1997, Official Gazette No. 61. The World Intellectual Property Organization (WIPO) was also established as a United Nations agency and began its activities in 1970. 9- Bondari Negar, AI, Copyright, and the Law: The Ongoing Battle Over Intellectual Property Rights, IP & Technology Law Society, University of Southern California, 2025. 10- World Intellectual Property Organization (WIPO), Artificial Intelligence and Copyright, WIPO Magazine, October 2017, pp.1-4.

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Hellal Chaoua The Repercussions of AI on Literary and Artistic Property Rights 336 World Intellectual Property Organization (WIPO), Artificial Intelligence and Intellectual Property, WIPO AI and Frontier Technologies Portal, 2025. - Gaffar, H., Copyright Protection for AI-Generated Works: Exploring Originality and Ownership in a Digital Landscape, Asian Journal of International Law, Vol. 15, No. 1, 2025, pp.45-62. 11- Ricketson, S., & Ginsburg, J. C., International Copyright and Neighbouring Rights: The Berne Convention and Beyond (2nd ed.). Oxford University Press, 2006, pp.89-95. - World Intellectual Property Organization (WIPO). (1978). Guide to the Berne Convention for the Protection of Literary and Artistic Works (Paris Act, 1971), pp.11-16. - Berne Convention for the Protection of Literary and Artistic Works, Articles 5 and 9. 12- Berne Convention arts 2, 6bis, 9, 10 ; Regulation (EU) 2024/1689 arts 50, 53, 55 13- Article 74 of the Algerian Constitution 14- OECD, Recommendation of the Council on Artificial Intelligence (OECD Legal Instrument No. 0449), 2019, Principles 1.1–1.5 and Recommendations 2.1–2.5. - UNESCO, Recommendation on the Ethics of Artificial Intelligence, 2021, paras. 10-26, pp.15-23. - European Union, Regulation (EU) 2024/1689 (AI Act), arts. 5–15, establishing the risk-based framework for AI systems. - OECD, AI Principles, 2019/2024 update. 15- Regulation (EU) 2024/1689 (AI Act), Official Journal of the European Union, OJ L 2024/1689, 12 July 2024, Article 3(1). - Nicolas A. Smuha, Regulation 2024/1689 of the European Parliament and Council of June 13, 2024 (EU Artificial Intelligence Act),‖ International Legal Materials, Vol. 64, No. 1 (2025), pp.4-8. 16- Sordo, Z. et al., Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Models,‖ Journal of Imaging, Vol. 11, No. 8, 2025, p.2. - Miah, J. et al., Generative AI Model for Artistic Style Transfer Using Convolutional Neural Networks, 2023, pp.1-3. - Creswell, A. et al., Generative Adversarial Networks: An Overview, IEEE Signal Processing Magazine, 2018, pp.53-65 17- Abbott, Ryan. The Reasonable Robot: Artificial Intelligence and the Law. Cambridge University Press, 2020., pp.53-61 - Ginsburg, Jane C. & Budiardjo, Luke Ali., Authors and Machines, Berkeley Technology Law Journal, Vol. 34, No. 2, 2019. 18- European Parliament, Policy Department for Citizens’ Rights and Constitutional Affairs. Intellectual Property Rights and Distributed Ledger Technology with a Focus on Artificial Intelligence, 2021. 19- U.S. Copyright Office. Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, 88 Fed. Reg. 16190 (2023). - Ginsburg, Jane C. & Budiardjo, Luke Ali, Op.cit., pp.344-347 - Andersen, Birgitte et al., Copyright and Generative AI: A Literature Review, Journal of Intellectual Property Law & Practice, Vol. 19, No. 2, 2024. 20- Senftleben, Martin, et al. Copyright and Artificial Intelligence: A Study for the European Parliament, European Parliament, 2020., pp.35-46. - World Intellectual Property Organization (WIPO). Revised Issues Paper on Intellectual Property Policy and Artificial Intelligence, 2020. - Guadamuz, Andres., A Scanner Darkly: Copyright, Fair Use and Artificial Intelligence.‖ WIPO Journal, Vol. 14, No. 1, 2022, pp.18-24. - Andersen, Birgitte et al., Op.cit., pp.99-103. 21- Senftleben, Martin, et al., Op.cit., pp.35-46. - Directive (EU) 2019/790 on Copyright in the Digital Single Market (DSM Directive). Articles 3–4

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