Abstract
The proliferation of artificial intelligence systems capable of composing, performing, and producing music has exposed fundamental tensions within the European Union's intellectual property framework. This article examines the ownership disputes that arise when a music composer and a sound engineer collaborate using AI-assisted tools to produce a musical work, and assesses the extent to which existing EU copyright law, related rights, and contract law can accommodate the outputs of such collaboration. It applies the European Commission's four-step test for the copyrightability of AI-assisted outputs to a hypothetical scenario involving a jointly produced electronic album, and concludes that the work is unlikely to satisfy the originality and human intellectual effort requirements of EU copyright law as interpreted by the Court of Justice of the European Union. The article then examines alternative protective regimes, including neighbouring rights (phonogram producers' rights, broadcasters' rights, and performance rights) and contractual arrangements under the Information Society Directive. It argues that the current EU framework creates a protection gap for collaborative AI-assisted musical works and proposes three reforms: the extension of the neighbouring rights framework to recognise a distinct category of AI-facilitated creative outputs; the introduction of mandatory contractual disclosure obligations for AI-generated content distributed on digital platforms; and the amendment of the Digital Single Market Directive to address the allocation of rights in human-AI collaborative works. The analysis draws upon the jurisprudence of the Court of Justice of the European Union, comparative perspectives from the United Kingdom's Computer-Generated Works provision, and the regulatory implications of the EU Artificial Intelligence Act 2024.
Keywords: artificial intelligence; copyright; EU law; AI-generated music; neighbouring rights; originality; authorship; digital music production; sound engineers; composers
1. Introduction
Artificial intelligence music composition has emerged as one of the most commercially significant and legally contested applications of generative AI technology. Systems such as AIVA, Endel, Xhail, Boomy, and Amper Music enable users with varying degrees of musical expertise to produce compositions that are, to the untrained ear, indistinguishable from works composed entirely by human musicians. The global market for AI-generated music is projected to grow substantially in the coming years, driven by demand from the advertising, gaming, film, and streaming industries for affordable, customisable musical content.
The legal questions raised by these technologies are not entirely novel. Scholars have grappled with the copyrightability of computer-generated works since at least the 1960s, and the United Kingdom legislated specifically for the protection of such works in section 9(3) of the Copyright, Designs and Patents Act 1988. What is new, however, is the scale, sophistication, and commercial ubiquity of AI music systems, and the collaborative dynamics they produce between human participants in the creative process. When a music composer and a sound engineer jointly employ an AI system to conceive, execute, and produce a musical work, the question of who owns the resulting output, and under what legal framework, engages some of the most fundamental principles of European intellectual property law.
This article examines these questions through the lens of EU copyright law, neighbouring rights, and contract law. It adopts a hypothetical case study in which a music composer and a sound engineer collaborate using an AI music composition system to produce a new electronic album. The composer provides high-level creative direction (genre, mood, tempo), the sound engineer configures the technical parameters and post-production, and the AI system generates the compositional content, the melodic structures, harmonic progressions, rhythmic patterns, and arrangements. Neither the composer nor the engineer writes the musical notation, performs the instruments, or determines the specific creative choices that constitute the final compositions.
The article is structured as follows. Section 2 examines the spectrum of AI involvement in creative production and the taxonomies proposed in the scholarly literature for distinguishing between AI-assisted and AI-generated works. Section 3 applies the European Commission's four-step test for the copyrightability of AI-assisted outputs to the hypothetical case, drawing upon the jurisprudence of the Court of Justice of the European Union. Section 4 examines alternative protective regimes: neighbouring rights (phonogram producers' rights, broadcasters' rights, and performance rights) and contractual arrangements. Section 5 analyses the implications of the EU Artificial Intelligence Act 2024 and the Digital Single Market Directive for the governance of AI-generated musical content. Section 6 proposes reforms to the EU framework for the equitable allocation of rights in AI-assisted musical works. Section 7 concludes.
2. Taxonomies of AI Involvement in Creative Production
2.1 The Spectrum of Human-Machine Interaction
The legal analysis of AI-generated creative works must begin with a clear understanding of the degree of human involvement in the creative process. The literature has proposed several taxonomies for classifying the relationship between human creators and AI systems.
Lee identifies two categories: computer-assisted works, in which the computer functions as a tool directed by a human creator, and computer-generated works, in which the computer produces the output autonomously after initial programming, with minimal subsequent human involvement. Lee observes that in computer-generated works, the machine can adapt its processes to unanticipated occurrences, and its productive outputs are determined entirely by its acquired capacities rather than by contemporaneous human direction.
Abbott places AI creative works on a three-part spectrum: works created using a computer as a tool (where human creative input predominates), intermediate works (where there is a collaborative dynamic between human and machine), and works created by a computer (where no human creative input can be identified in the output). Abbott acknowledges the difficulty of distinguishing the first two categories in practice but notes that the distinction carries significant legal consequences. Where no human author or inventor can be identified, Abbott characterises the outputs as computer-generated works, analogous to what American jurisprudence terms "emergent works".
Bohler proposes a more granular four-part classification: AI co-production, in which the human uses AI as a tool; human selection of a work that has been wholly developed by AI; brute-force creation, in which AI generates every possible permutation within defined parameters; and fully autonomous creation, in which the computer independently develops and selects the work with no human interaction other than the initial programming. Bohler argues that the first two categories may be copyrightable, whilst the latter two are not.
Dornis characterises the AI systems capable of independent creative production as combinations of hardware and software that have evolved through machine learning, the development and training of algorithms to discover structure and patterns in data and apply their acquired knowledge to novel data. This evolutionary dimension distinguishes contemporary AI music systems from earlier forms of computer-assisted composition, in which the computer merely executed instructions encoded by the human programmer.
2.2 Implications for the Hypothetical Case
In the hypothetical case that structures this article, the composer and sound engineer occupy an ambiguous position on these taxonomies. They provide initial creative parameters (genre, mood, instrumentation preferences), configure the AI system's technical settings, and undertake post-production editing. However, they do not compose the musical content: the melodic lines, harmonic structures, rhythmic arrangements, and orchestration are generated by the AI system. The work therefore falls between Lee's categories of computer-assisted and computer-generated, closer to Abbott's intermediate category, and closer to Bohler's first category (AI co-production) than to the third or fourth. This taxonomic ambiguity is precisely what makes the case legally interesting and practically consequential.
As Miller observed in his influential formulation, "behind every good robot is a good person". The question is whether the contribution of the persons behind this particular AI system, the composer and the sound engineer, is sufficient to ground a claim to authorship, copyright, or any other form of legal protection under EU law.
3. The EU Copyright Framework: Applying the Four-Step Test
3.1 The European Commission's Framework
In its 2020 report on trends and developments in artificial intelligence and their challenges to the intellectual property rights framework, the European Commission proposed a four-step analytical framework for assessing whether an AI-assisted output is eligible for copyright protection under EU law. The four criteria are: (i) the output must be a literary, scientific, or artistic work; (ii) the output must be the product of human intellectual effort; (iii) the output must be original; and (iv) the work must be expressed with sufficient precision and objectivity to be identifiable as a protected work.
3.2 Criterion One: Literary, Scientific, or Artistic Work
The Berne Convention for the Protection of Literary and Artistic Works requires that the subject matter be a literary, scientific, or artistic work. Musical compositions, including electronic and digitally produced music, fall squarely within the Berne Convention's enumeration of protected subject matter. The AI-generated electronic album in the hypothetical case satisfies this criterion without difficulty, as the output is a musical work within the meaning of both the Berne Convention and the EU copyright acquis.
3.3 Criterion Two: Human Intellectual Effort
The EU copyright system is founded upon the tradition of author's rights, which requires that copyright protection be linked to the creative expression of a natural person. Although the Berne Convention does not define the term "author", its text and context imply that a natural person must have created the work. Article 2(6) provides that protection shall operate for the benefit of the author, and Article 6bis requires that the work bear the imprint of human creation.
The Court of Justice of the European Union has consistently held that copyright protection attaches to works that reflect the author's personality and creative choices. In Cofemel, the CJEU confirmed that the subject matter must be original in the sense that it constitutes the author's own intellectual creation, reflecting the author's free and creative choices. In Painer, Advocate General Trstenjak observed that technical aids, such as a camera or a computer, can facilitate the creation of human creations, provided that the human author has made creative choices that are reflected in the final output.
In the hypothetical case, the question is whether the contribution of the composer and the sound engineer constitutes human intellectual effort sufficient to ground authorship. The composer provides genre and mood parameters; the sound engineer configures technical settings and undertakes post-production processing. However, the compositional substance, the specific melodic, harmonic, and rhythmic content of the musical works, is generated by the AI system. The users did not build the software, choose the training data, compose the musical material, or exercise creative control over the specific outputs. Their role was limited to initiating the generation process and selecting from the AI system's outputs.
The author submits that this level of human involvement is insufficient to constitute human intellectual effort within the meaning of the EU copyright acquis. The human contribution is operational rather than creative: it triggers and frames the AI system's autonomous creative processes but does not determine the specific creative content of the output. The hypothetical case therefore fails this criterion.
3.4 Criterion Three: Originality
The CJEU has established a harmonised standard of originality across EU copyright law. In Infopaq International, the Court held that copyright protects original works, in the sense that they are the author's own intellectual creation. In Levola Hengelo and Cofemel, the Court clarified that originality requires that the subject matter reflect the author's free and creative choices, expressing the author's personality. In Painer, the Court confirmed that a creative synthesis of ideas at different phases of the production process may be sufficient to qualify the result as a protected work, provided the human author has made creative decisions reflected in the final outcome.
The determination of originality in the context of AI-assisted outputs is complicated by three types of restrictions identified by Hugenholtz and Quintais: rule-based restrictions (where the output is determined by pre-set rules rather than creative choice), technical restrictions (where the technical characteristics of the system constrain the range of possible outputs), and informational or functional external restrictions (where the nature of the subject matter limits the scope for creative expression).
The Kluwer Copyright Blog has proposed that the creative process in AI-assisted works be assessed through three iterative phases: conception (the creation and development of a work through selection and arrangement decisions), execution (the transformation of the plan into draft versions of the final product), and redaction (the modification and refinement of the output prior to release).
Applied to the hypothetical case:
Conception: The selection of genre, mood, tempo, and instrumentation provides high-level parameters but does not constitute the detailed creative decisions, the specific musical notes, chord progressions, rhythmic patterns, melodic contours, and arrangements, that constitute the compositional substance of a musical work. The AI system makes these decisions autonomously. The human contribution at the conception stage is therefore insufficient.
Execution: The AI system autonomously generates the musical compositions. The users do not perform the instruments, sing, or direct the performance. The execution phase is dominated by the AI system, with no direct human creative intervention in the generation of musical content.
Redaction: Post-production editing by the sound engineer (mixing, mastering, equalization, compression) constitutes technical processing rather than compositional creativity. Hugenholtz has observed that the creative decisions made during the redaction phase may contribute to the originality of the overall product. However, in the instant case, the redaction involves the technical refinement of AI-generated content rather than the substantive alteration of its compositional character.
The author concludes that the electronic album produced in the hypothetical case does not satisfy the originality criterion as interpreted by the CJEU, because the compositional substance of the work is not the product of the free and creative choices of a human author.
3.5 Criterion Four: Expression with Sufficient Precision and Objectivity
The fourth criterion requires that the work be expressed in a manner that is identifiable with sufficient precision and objectivity. Despite the unpredictability that characterises machine learning outputs (the so-called "black box" problem), the electronic album will likely satisfy this criterion. The album exists as a fixed, identifiable musical recording. Both the composer and the sound engineer intended to produce a musical work, and the output is congruent with that general intention.
3.6 Conclusion on Copyrightability
The hypothetical electronic album satisfies the first and fourth criteria of the European Commission's four-step test but fails the second (human intellectual effort) and third (originality). Under the current EU copyright framework, as interpreted by the CJEU, the work is not eligible for copyright protection. Neither the composer nor the sound engineer can claim authorship, because the compositional substance of the work is the product of the AI system's autonomous processes rather than of their free and creative choices.
This conclusion carries significant practical consequences. The composer and sound engineer have invested time, resources, and expertise in the production of the album. They bear the commercial risk of its creation. Yet under EU copyright law, they have no authorial claim to the output. This protection gap demands examination of alternative legal regimes.
4. Alternative Protective Regimes
4.1 Neighbouring or Related Rights
The limitations of copyright law for AI-assisted creative outputs direct attention to the related rights framework. Unlike copyright, neighbouring rights do not require a causal link between a natural person's creative expression and the protected subject matter. They are granted to protect the organisational, financial, and technical contributions of persons involved in the dissemination of creative works, rather than the creative act of authorship itself.
Kucukali has argued that the neighbouring rights framework is more appropriate for AI-generated works than copyright, drawing an analogy between AI-generated works and anonymous works, which have been protected under the Rome Convention for decades. If a performer can hold a neighbouring right over the performance of an anonymous work, Kucukali contends, then a natural person should be able to hold a neighbouring right in an AI-created work. This analogy is instructive for the present analysis.
Three categories of neighbouring rights are relevant to the hypothetical case.
4.1.1 Phonogram Producers' Rights
A phonogram is defined as the exclusive aural fixation of a performance's sounds. The term is used in both the Rome Convention and the WIPO Performances and Phonograms Treaty (WPPT), though only the latter provides a digital-era outlook. Fixation, in its simplest formulation, is the embodiment or representation of sounds that may be reproduced or transmitted via a device. The concept encompasses computer-generated or computer-assisted music productions stored on a hard drive or other digital equipment. Crucially, phonogram producers' rights do not require human authorship. The right vests in the phonogram's producer: the person (natural or legal) who initiated and is responsible for the first fixation.
In the hypothetical case, both the composer and the sound engineer initiated the production of the electronic album and are responsible for its first fixation. They therefore qualify as joint phonogram producers. The phonogram right grants them the right to authorise or prohibit the reproduction, distribution, rental, and making available of the sound recording, subject to the provisions of the Rental and Lending Directive and the WPPT. This protection applies irrespective of whether the compositional content was generated by an AI system, because the right attaches to the fixation of sounds rather than to the authorship of the underlying composition.
4.1.2 Broadcasters' Rights
Broadcasters' rights protect the act of broadcasting, defined as "transmission by wireless means for public reception of sounds or images and sounds". This right does not require human creative contribution; only an act of broadcasting is required. If the composer and sound engineer choose to broadcast or publicly transmit the AI-generated album, they will acquire broadcasters' rights over that transmission. The European Commission has noted that in member states where broadcasting extends to webcasting, this protection may apply to continuous, unfixed music generation and streaming projects powered by artificial intelligence.
4.1.3 Performance Rights
Performance rights grant performers the right to exclusive exploitation in respect of their performances. Like broadcasters' rights, no creative act is required to activate this protection; it is sufficient that the work is publicly performed. The European Commission has reported that the act of performance also includes digital performance, such as digital streams. If the composer or sound engineer performs or presents the AI-generated album in any public context, whether live, through digital streaming, or through broadcast, they will acquire performance rights.
4.2 Contract Law
Contract law provides a further protective mechanism where copyright and neighbouring rights prove insufficient. Kucukali observes that despite the absence of a unified contract law in the EU, the Information Society Directive permits the contractual exploitation of copyright and neighbouring rights. A contractual framework is arguably better suited to AI-generated works than copyright, because the legal uncertainties created by the "black box" nature of AI operations can be addressed through bespoke contractual provisions.
In the hypothetical case, the composer and sound engineer may enter into a collaboration agreement addressing: joint ownership or defined shares in the output; licensing terms for commercial exploitation; royalty-sharing arrangements; allocation of liability for any infringement claims arising from the AI system's use of training data; termination and reversion provisions; and representations regarding the extent of AI involvement in the creative process. This contractual arrangement provides legitimate protection for each party, and is a viable complement to the neighbouring rights framework.
The contractual approach is not without limitations. Copyright provides protection against third parties (erga omnes), whereas contractual rights bind only the contracting parties (inter partes). A contractual arrangement therefore cannot prevent third-party copying or commercial exploitation of the AI-generated work in the same way that copyright or neighbouring rights can. Additionally, the contracts offered by AI music platforms such as AIVA frequently take the form of click-wrap agreements with limited negotiability, creating information asymmetries and unequal bargaining power between the platform and the user.
Despite these limitations, contract law provides the most flexible and commercially practical mechanism for governing the relationship between collaborators in AI-assisted music production.
5. The Regulatory Landscape: The EU AI Act and the Digital Single Market Directive
5.1 The EU Artificial Intelligence Act 2024
The EU Artificial Intelligence Act, which entered into force in 2024, establishes a risk-based regulatory framework for AI systems deployed within the European Union. Whilst the Act does not directly address intellectual property allocation, it imposes transparency obligations that are relevant to the governance of AI-generated creative content. Article 52 requires that AI systems intended to interact with natural persons be designed and developed in such a way that the persons are informed that they are interacting with an AI system. Generative AI systems, including music composition tools, are subject to disclosure obligations requiring that AI-generated content be identified as such.
These transparency requirements have implications for the music industry. If AI-generated compositions must be disclosed as such when distributed on digital platforms, the commercial and legal dynamics of AI music production will shift. Consumers, licensees, and rights-collecting societies will be able to distinguish between human-composed and AI-generated works, with potential consequences for licensing fees, royalty distribution, and the eligibility of AI-generated works for awards, grants, and other forms of recognition that presuppose human authorship.
5.2 The Digital Single Market Directive
The Digital Single Market (DSM) Directive of 2019 introduced significant reforms to EU copyright law, including provisions on the use of protected works in text and data mining, the liability of online content-sharing service providers, and the rights of authors and performers in contractual relationships. Article 17 imposes obligations on online content-sharing service providers to obtain authorisations from rightsholders for works uploaded by their users, and to implement content recognition technologies to prevent the availability of unauthorised works.
The DSM Directive is relevant to AI-generated music in two respects. First, the text and data mining exceptions in Articles 3 and 4 have implications for the training of AI music systems on copyrighted musical works. AI music composition systems are typically trained on large datasets of existing musical works, raising the question of whether the ingestion of copyrighted material for training purposes constitutes reproduction within the meaning of EU copyright law, and whether the text and data mining exceptions apply. Second, Article 17's content recognition obligations may struggle to accommodate AI-generated works. If an AI-generated composition bears similarities to existing copyrighted works because the AI system was trained on those works, content recognition systems may flag the AI-generated output as infringing, even where no deliberate copying occurred.
5.3 Comparative Perspective: The United Kingdom
The United Kingdom's Copyright, Designs and Patents Act 1988 provides a notable comparative perspective. Section 9(3) stipulates that in the case of a literary, dramatic, musical, or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken. This provision grants authorship, and thereby copyright protection, to the human person who made the arrangements necessary for the computer to generate the work, even where the creative substance of the output was produced by the machine.
Were the hypothetical case to arise under UK law rather than EU law, the outcome might differ. The composer and sound engineer, as the persons who made the arrangements necessary for the AI system to produce the electronic album, could arguably claim authorship under section 9(3). The UK provision thus addresses the protection gap that characterises the EU framework, though it does so through a legal fiction that has attracted scholarly criticism for its lack of conceptual coherence with the originality requirements of copyright law.
The UK provision nonetheless demonstrates that legislative solutions to the protection gap are possible. Whether the EU should adopt a similar approach, or develop an alternative framework, is a question to which this article returns in the following section.
6. Proposals for Reform
The analysis in the preceding sections demonstrates that the current EU framework creates a protection gap for collaborative AI-assisted musical works. The composer and sound engineer in the hypothetical case cannot claim copyright in the album, because the compositional substance is AI-generated. They can claim neighbouring rights (phonogram producers' rights, broadcasters' rights, performance rights) and contractual rights, but these provide less comprehensive protection than copyright and do not resolve the underlying doctrinal question of who owns the creative output of a human-AI collaboration.
This article proposes three reforms.
6.1 A Distinct Neighbouring Rights Category for AI-Facilitated Creative Outputs
The EU should introduce a new category of neighbouring right specifically designed for creative outputs produced through human-AI collaboration. This right would vest in the natural person or persons who initiated, directed, and oversaw the AI-assisted creative process, analogous to the phonogram producer's right but extending to the compositional content as well as the sound recording. The right would be of shorter duration than copyright (for example, 25 years from first publication, as opposed to the life of the author plus 70 years for copyright), reflecting the reduced level of human creative contribution. It would grant the holder the exclusive right to authorise or prohibit the reproduction, distribution, communication to the public, and making available of the work, and would be subject to the same exceptions and limitations as existing neighbouring rights.
This proposal draws upon the analogy between AI-generated works and anonymous works developed by Kucukali, and upon the UK's computer-generated works provision, whilst avoiding the conceptual difficulties of attributing authorship (and the full suite of author's rights, including moral rights) to persons whose creative contribution falls short of what the CJEU's originality standard requires.
6.2 Mandatory Contractual Disclosure Obligations
The EU should require that all musical works distributed on digital platforms include a disclosure of the extent of AI involvement in the creative process. This obligation should extend to both the platform and the content provider. It should specify: (a) whether the work was composed, in whole or in part, by an AI system; (b) the identity of the AI system used; (c) the nature of the human contribution (conception, direction, selection, editing, post-production); and (d) the contractual arrangements governing the allocation of rights between the human collaborators and, where applicable, the AI system's developer or operator.
This transparency requirement would enable rights-collecting societies, licensees, and consumers to assess the nature of the creative process and allocate value accordingly. It would also facilitate the operation of the content recognition systems mandated by Article 17 of the DSM Directive, by providing the metadata necessary to distinguish between AI-generated and human-composed works.
6.3 Amendment of the DSM Directive
Article 18 of the DSM Directive, which grants authors and performers the right to appropriate and proportionate remuneration for the exploitation of their works and performances, should be amended to address the specific circumstances of human-AI collaboration. The amendment should clarify: (a) that persons who direct, oversee, and undertake the arrangements necessary for an AI system to produce a creative work are entitled to remuneration for the exploitation of that work, even where they do not qualify as authors within the meaning of the copyright acquis; (b) that AI system developers and operators owe transparency obligations to the persons who use their systems for creative production; and (c) that contractual terms in click-wrap or standard-form agreements that purport to assign all rights in AI-generated outputs to the platform operator are subject to the fairness and proportionality principles established by the DSM Directive.
7. Conclusion
This article has examined the intellectual property rights available to a music composer and a sound engineer who collaborate using an AI system to produce an electronic album under the EU legal framework. Applying the European Commission's four-step test, it has concluded that the work is unlikely to satisfy the originality and human intellectual effort requirements of EU copyright law as interpreted by the CJEU. The creative substance of the work, the compositional content, is the product of the AI system's autonomous processes rather than of the free and creative choices of the human collaborators.
The article has demonstrated that the composer and sound engineer can obtain protection through alternative regimes: neighbouring rights (phonogram producers' rights, broadcasters' rights, and performance rights) and contractual arrangements. These regimes provide meaningful protection but do not fill the doctrinal gap at the heart of EU copyright law. The article has proposed three reforms: a new neighbouring rights category for AI-facilitated creative outputs; mandatory disclosure obligations for AI involvement in musical works distributed on digital platforms; and an amendment of the DSM Directive to address remuneration and contractual fairness in the context of human-AI collaboration.
The rapid proliferation of AI music composition tools demands that the EU legislature engage with these questions. The current framework, designed for a world in which creative works were the product of identifiable human authors, is not adequate for a world in which the most commercially significant creative processes involve collaboration between humans and machines. The question is not whether EU law will need to adapt, but whether it will do so in a manner that equitably allocates rights and responsibilities among all participants in the creative process, human and artificial alike.
Notes
Bibliography
Abbott R, 'Artificial Intelligence, Big Data and Intellectual Property: Protecting Computer Generated Works in the United Kingdom' in Research Handbook on Intellectual Property and Digital Technologies (Edward Elgar 2020)
Bohler HM, 'EU Copyright Protection of Works Created by Artificial Intelligence Systems' (University of Bergen 2017)
Bulayenko O and others, 'AI Music Outputs: Challenges to the Copyright Legal Framework - Part I' (Kluwer Copyright Blog, 22 April 2022)
Bulayenko O and others, 'AI Music Outputs: Challenges to the Copyright Legal Framework - Part II' (Kluwer Copyright Blog, 25 April 2022)
Dornis TW, 'Artificial Creativity: Emergent Works and the Void in Current Copyright Doctrine' (2020) 22 Yale Journal of Law and Technology 1
European Commission and others, Trends and Developments in Artificial Intelligence: Challenges to the Intellectual Property Rights Framework: Final Report (Publications Office 2020)
Gaon AH, The Future of Copyright in the Age of Artificial Intelligence (Edward Elgar 2021)
Hugenholtz PB and Quintais JP, 'Copyright and Artificial Creation: Does EU Copyright Law Protect AI-Assisted Output?' (2021) 52 IIC-International Review of Intellectual Property and Competition Law 1190
Kucukali BT, 'The Protection of AI-Generated Works under European Copyright Law: Toward Adoption of a Neighbouring Rights Approach' (University of British Columbia 2022)
Lee JA, '177 Computer-Generated Works under the CDPA 1988' in Lee JA, Hilty R and Liu KC (eds), Artificial Intelligence and Intellectual Property (OUP 2021)
Miller AR, 'Copyright Protection for Computer Programs, Databases, and Computer-Generated Works: Is Anything New since CONTU?' (1993) 106 Harvard Law Review 977
Rosati E, Originality in EU Copyright: Full Harmonization through Case Law (Edward Elgar 2013)
Tan X and Li X, A Tutorial on AI Music Composition (2021)
Akintunde Idowu is a Barrister and Solicitor of the Supreme Court of Nigeria. He holds an LLM in IP and IT Law (High Merit) from Trinity College Dublin and an LLB (Upper Second Class Honours) from Obafemi Awolowo University. His research interests include intellectual property in AI-generated creative works, algorithmic governance, data protection law, and the regulation of artificial intelligence.
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