Pondering the Impact of Generative AI on Copyright Validity

Main Article Content

Juan Sebastián Silva Díaz
https://orcid.org/0000-0002-2061-9914

Abstract

As artificial intelligence (ai) continues to evolve as a creative agent, it becomes imperative to reassess the foundational principles of copyright law. The ability of generative ai to produce works indistinguishable from human creations challenges the very core of creativity and copyright law. Historically, legislation has evolved in tandem with technological advances, from the printing press to the digital age. But, as ai emerges as an autonomous creative agent, questions arise about the fair allocation of rights and the preservation of economic incentives for human creativity. While ai can serve as a powerful tool to enhance human ingenuity, the potential for legal loopholes and economic inequities requires prudent and adaptable regulations that reflect the complexities of our ever-changing world.

References

Amabile, T. M. (1996). Creativity in context: Update to “The Social Psychology of Creativity”. Westview Press.

Andrade, R., & Martínez, A. (2013). La Creatividad como Materia Afín a la Propiedad Intelectual.¿ Una Tarea Pendiente para la OMPI?. Revista Propiedad Intelectual, 12(16), 170.

Caballero, F. (2021). El arte como expresión humana: claves para su conceptualización, apreciación y uso. MAD.RID. Revista de Innovación Didáctica de Madrid, 68, 36-50. Madrid. https://www.csif.es/contenido/comunidad-de-madrid/educacion/316146

Castells, M. (2002). La dimensión cultural de Internet. Universitat Oberta de Catalunya-Institut de Cultura: Debates Cultura. http://www.uoc.edu/culturaxxi/esp/articles/castells0502/castells0502.html.

Dash, A. & Agres, K. (2024). AI-Based Affective Music Generation Systems: A Review of Methods and Challenges. Association for Computing Machinery, 56(11),0360-0300. https://doi.org/10.1145/3672554

Frankfurter Allgemeine Zeitung. (2022). Wer hat Angst vor DALL-E 2 https://fazarchiv.faz.net/payment/faznet?key=/1.8275297

Goodlad, L. M. E., & Dimock, W. C. (2021). AI and the Human. PMLA/Publications of the Modern Language Association of America, 136(2), 317–319. doi:10.1632/S0030812921000079

Kumar, C. (2024). Towards Artificial General Intelligence: Enhancing LLMs capability for Abstraction and Reasoning. Engineering Archives. https://doi.org/10.31224/3863

Lacruz, M. (2021). Inteligencia artificial y derecho de autor. Editorial Reus.

LaGrandeur, K. (2015). Emotion, Artificial Intelligence, and Ethics. In: J. Romportl, E. Zackova, & J. Kelemen (Eds.), Beyond Artificial Intelligence. Topics in Intelligent Engineering and Informatics, vol 9. Springer. https://doi.org/10.1007/978-3-319-09668-1_7

Liu, B. (2023). Arguments for the Rise of Artificial Intelligence Art: Does AI Art Have Creativity, Motivation, Self-awareness and Emotion?. Arte, Individuo y Sociedad, 35(3), 811-822. https://doi.org/10.5209/aris.83808

MacKinnon, D. W. (1962). The personality correlates of creativity: A study of American architects. In G. Nielson (Ed.), Proceedings of the XIV International Congress of Applied Psychology. Vol. 2. Personality research (pp. 11–39). Munksgaard.

Malik, R., & Shaikh, B. A. (2024). Adapting Copyright Law for the Digital Age: A Global Challenge. Pakistan Journal of Law, Analysis and Wisdom, 3(9), 105.

Menon, S., Trenker, J., Owens, T., Tas, O., & Blumtritt, C. (2023). The double-edged sword of AI: Will we lose our jobs or become extremely productive? Unleashing Artificial Intelligence's true potential. Chapter 3. Statista. https://www.statista.com/site/insights-compass-ai-future-ai-work

Mercado, A. (2015). La influencia de León Duguit en la reforma social de 1936 en Colombia. El sistema jurídico, la función social de la propiedad y la teoría de los servicios públicos. Universidad del Rosario. https://books.scielo.org/id/sw5k7/pdf/mercado-9789587386387.pdf

Nees, G. (2018). Generative Computergraphik. Siemens Aktiengesellschaft In: R. Hernández. Aesthetic Informational Systems: Towards an ontology of computer-generated aesthetic artefacts. Universidade de Lisboa. https://www.academia.edu/36704422/AESTHETIC_INFORMATIONAL_SYSTEMS_Towards_an_ontology_of_computer_generated_aesthetic_artefacts

Patil, D., Rane, N. L., Desai, P. ., & Rane, J. . (2024). Machine learning and deep learning: Methods, techniques, applications, challenges, and future research opportunities. In D. . Patil, N. L. Rane, P. . Desai, & J. . Rane (Eds.), Trustworthy Artificial Intelligence in Industry and Society (pp. 28-81). Deep Science Publishing. https://doi.org/10.70593/978-81-981367-4-9_2

Porter, B., & Machery, E. (2024). AI-generated poetry is indistinguishable from human-written poetry and is rated more favorably. Sci Rep 14, 26133. https://doi.org/10.1038/s41598-024-76900-1

Sanmartín Ortí, P. (2006). La finalidad poética en el formalismo ruso: El concepto de desautomatización. Universidad Complutense de Madrid.

Schröter, J. (2024). AI, Automation, Creativity, Cognitive Labor. In E. Voigts, R. Auer, D. Elflein, S. Kunas, J. Röhnert & C. Seelinger (Ed.), Artificial Intelligence - Intelligent Art?: Human-Machine Interaction and Creative Practice (pp. 35-44). Verlag. https://doi-org.ezproxy.uniandes.edu.co/10.1515/9783839469224-002

Sprigman, C. (2018). Copyright and Creative Incentives: What Do(n’t) We Know? In R. C. Dreyfuss & E. S.-K. Ng (Eds.), Framing Intellectual Property Law in the 21st Century: Integrating Incentives, Trade, Development, Culture, and Human Rights (pp. 32–61). Cambridge University Press. https://doi.org/10.1017/9781316471647.003

Stein, M. I. (1953). Creativity and culture. The Journal of Psychology: Interdisciplinary and Applied, 36, 311–322. https://doi.org/10.1080/00223980.1953.9712897

Stephens, E., & Heffernan, T. (2016). We have always been robots: The history of robots and Art. In: D. Herath & C. Kroos. (Eds.), Robots and Art. Exploring an Unlikely Symbiosis, (pp. 31-35). Sterlac.

Sternberg, R. J., & Lubart, T. I. (1995). Defying the crowd: Cultivating creativity in a culture of conformity. Free Press.

Wagner, P. (2017). Introduction to Intellectual Property Law. On S. Balganesh. (Comp.), Intellectual Property Law Specialization. Penn Carey Law, University of Pennsylvania.

Wertheimer, M. (2017). Productive thinking. Harper. In: L. Zhang (Ed.), Empirical Evidence: Three Classic Variables and Intellectual Styles. The Value of Intellectual Styles. (pp. 27-116). Cambridge University Press.

Xie, Z., Wu, X., & Xie, Y. (2024). Can interaction with generative artificial intelligence enhance learning autonomy? A longitudinal study from comparative perspectives of virtual companionship and knowledge acquisition preferences. Journal of Computer Assisted Learning, 40(5), 2369-2384.