Part 1 of this post introduced the challenges for copyright associated with generative IP and the legislative developments in this field. This part 2 explores the idea of introducing a statutory license for machine learning purposes for generative AI as a compromise solution to secure a vibrant environment for AI development while preserving the central role played by human creators.
A statutory remuneration right for machine learning for Generative AI, a compromise solution
Various solutions are emerging with the common aim of reconciling the need of AI developers for massive and accurate data with the demand of copyright holders for fair remuneration. Some authors advocate for the establishment of data-sharing agreements with data providers or for royalty-based compensation models in direct contact with content creators (see Lucchi), perhaps accompanied by tools able to verify the training through a sort of reverse engineering mechanism (see Strowel).
However, the gigantic transaction costs of one-to-one negotiations and the risks of having incomplete datasets inhibiting the development of performing AI systems leads to envisaging other solutions that reconcile more efficiently the interest of AI developers and the remuneration interest of creators, such as the introduction of a remunerated copyright limitation that imposes a general payment obligation on providers of generative AI systems for the use of copyrighted work for machine learning purposes in the context of generative AI systems. From this perspective, it can be argued that the introduction of a limitation-based remuneration right will preserve the anthropocentric approach to copyright law, preventing an upside-down scenario where human creativity becomes instrumental to artificial intelligence.
It is worth recalling that statutory licenses are limitations of the exclusive power arising from copyright protection that are justified by the objective of securing derivative creativity in specific sectors that otherwise are likely to be stagnant (see Geiger). The U.S. copyright system has developed this exceptional “permitted-but-paid” (see Ginsburg) regime which curtails the exclusive rights of copyright owners for specific aims, namely preventing monopoly in the music sector and reducing transaction costs for the licensing of sound recordings and television programs.
In the EU, Art. 5.2 b of the InfoSoc Directive introduced a remunerated private copying exception or limitation, a similar mechanism that Member States could implement to remunerate the prejudice that rightsholders suffer for the private reproduction of their works. As in the case of generative AI, content creators were not able to monitor and enforce their rights while their works were used without remuneration. This scenario brought the German legislator to address the problem of the fair remuneration of copyright holders in uncontrollable environments by establishing the first levy system in the 1965 Copyright Act (see Kretschmer). The payment is integrated into a levy that is imposed on the cost of a physical medium or a device which allows the user to duplicate copyright protected works. Then, the collected levies are distributed among content creators and rightsholders based on different criteria across the Member States that have implemented Art. 5.2 b. Applied to ML, the remuneration would result from the machine learning uses of copyright protected works by an algorithm for commercial generative AI purposes.
Interestingly, the Italian legal system also offers an example of such “permitted-but paid”- use with regards to engineering projects that provide original solutions to technical problems. Those works are protected by a 20-year neighboring right lasting from the filing of the work. In particular, Art. 99 of the Italian Copyright Law entitles the author of such works to be fairly compensated for the unauthorized for-profit implementation of the technical project. The justification behind the limitation of the author’s power lies in the interest in fostering technical progress in the engineering sector. Hence, the Italian legislator decided to remove obstacles that could hinder innovation in this field.
However, more compelling justifications for introducing a statutory remuneration right for commercial machine learning purposes in place of the opt-out right under Art. 4.3 of the CDSM Directive can be found in the fundamental rights framework. Indeed, reframed from a digital constitutionalist perspective (see De Gregorio), the question of generative AI vs. authors’ remuneration opens the way to statutory licenses as they provide a compelling balance of the different fundamental rights involved.
This exceptional regulatory instrument is rooted on Arts. 11 and 13 EUCF, 19 UDHR, 27.1 UDHR, 15.1 a and b ICESCR, considering that generative AI training is essential for human beings to explore new avenues of artistic expression that are still unknown. Indeed, some outputs produced by generative AI have the potential to be used by human authors in new forms of art and cultural expression that benefit society at large (think for example of the (controversial) work of the artist Refic Anadol “Unsupervised- Machine Hallucinations” acquired this month by the MoMA in New York). Access to comprehensive data, even if protected by copyright, is therefore a precondition for the correct operation and advancement of AI systems. It should be made clear that freedom of artistic expression concerns exclusively human beings considering that, at least under the current state of the law, AI does not enjoy the mentioned constitutional right. This implies that the interest in the flourishing of the generative AI industry remains instrumental to the end objective of increasing human artistic freedom of expression.
The functioning of statutory licenses allows maximization of the copyright content exploitable for ML purposes while taking into account the interests of the authors to be remunerated for the commercial use of their intellectual efforts, as protected by Arts. 17.2 EUCF, 27.2 UDHR, and 15.1 c ICESCR. From this perspective, AI developers should thus share their revenues with the authors whose works are used to train the algorithms. A right to a fair remuneration granted by transparency obligations encourages human beings to still produce new works (eventually with the expanded creative ability that generative AI models can provide) while securing that the use of their work by AI systems generates a fair return. The human creator remains in this way at the centre of the copyright system.
In order to reduce the risk that such a mechanism benefits primarily superstars from every creative sector, considering that a substantial portion of the requests may concern the imitation of the style of well-known celebrities, some empirical studies on the effective risk of discrimination between artists based on their popularity would be very useful to assess the need for recalibration by the system in place; redistribution systems can be expected to secure that remuneration flows to niche creators as well. However, in general terms, it is reasonable to believe that this policy option, if combined with mandatory collective rights management, could improve the living and working conditions of human authors
The hype for generative AI comes with some legitimate concerns on the fair remuneration of authors when their protected works serve as input for ML purposes. Copyright law is not unused to coping with unprecedented forms of exploitation of intellectual works resulting from market practices or technological developments. When the existing legislation did not successfully address the new dysfunctionalities affecting a creative segment, authors experienced a sense of inequality and frustration at being deprived of the revenues arising from the new exploitation of their fruits of the labor. The EU has taken action to correct these market failures, for instance by introducing the rental right, the private copying exception and the contractual protection of authors vs. publishers to ensure an appropriate share of the revenues obtained from information society service providers. However, European copyright law appears still in its nascent phase as regards statutory licenses and their potential role in solving the conflict between exclusive rights and other concurring interests (see Geiger).
The right to culture and science and freedom of artistic expression, as enshrined by European and international human rights law, can justify the introduction of a statutory license that will grant an appealing environment for AI creativity without jeopardizing the right of the human authors to be remunerated for the commercial use of their works. This compromise solution within the copyright system is the result of a balancing exercise that is inherent to any conflict between divergent fundamental rights. Despite some difficulties in reaching the optimal equilibrium, fundamental rights should remain the compass to navigate the seas of the still unexplored digital ecosystems and frontier technologies (see Geiger). In this case, where the exploitation of copyright-protected works to train generative AI models challenged the anthropocentric nature and function of the copyright system, fundamental rights can be valid allies to reconcile machine generated outputs and human creativity.
A version of this contribution was posted first on October 4 on The Digital Constitutionalist (https://digi-con.org/). It summarizes the main findings of the article: “The Forgotten Creator: Towards a Statutory Remuneration Right for Machine Learning of Generative AI”, forthcoming in the Computer Law and Security Review, 2023, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4594873
 See Christophe Geiger, “When the Robots (try to) Take Over: Of Artificial Intelligence, Authors, Creativity and Copyright Protection”, in: F. Thouvenin, A. Peukert, T. Jäger and C. Geiger (eds.), “Innovation- Creation- Markets, Festschrift Reto M. Hilty”, Springer, Berlin/Heidelberg, 2024 (forthcoming), on file with the author; for similar proposals see also Frosio at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4527461 and, but linked to the AI generated output, see Senftleben at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4478370.
 Christophe Geiger, “When the Robots (try to) Take Over: Of Artificial Intelligence, Authors, Creativity and Copyright Protection”, supra note 1, on file with the author