Use of Copyright Works in Machine Learning: Search for a Balance of Interests of Copyright Holders and Society
DOI:
https://doi.org/10.47850/RL.2024.5.3.184-194Keywords:
copyright; artificial intelligence; machine learning; large language models; dataset; free use of works; fair use doctrineAbstract
The introduction of artificial intelligence opens up great opportunities, but at the same time poses new challenges for legislators and courts. One of these challenges is to find a balance between the interests of copyright holders of works used in machine learning and society interested in the development of artificial intelligence technology. In the article, the author analyzes the state of current copyright legislation and law enforcement practice. The subject of the study is a copyright infringement lawsuit filed by a group of writers (Paul Tremblay et al.) against the artificial intelligence developer OpenAI, which is being processed by the US District Court (Northern District of California): the author evaluates the use of works in machine learning for compliance with the conditions for applying the fair use doctrine. The author comes to the conclusion about the need to supplement cases of free use of works through use in machine learning systems.
References
Афанасьева, Е. Н., Фурман, Д. Д. (2023). Правовые аспекты обработки искусственными интеллектуальными системами объектов авторского права в процессе машинного обучения. Baikal Research Journal. Т. 14. № 4. С. 1643-1656.
Afanasyeva, E. N., Furman, D. D. (2023). Legal aspects of processing copyright objects by artificial intelligent systems in the process of machine learning. Baikal Research Journal. Vol. 14. No. 4. Pp. 1643-1656. (In Russ.)
Калятин, В. О. (2021). Проблема машинного творчества в системе права: регулирование создания и использования результатов интеллектуальной деятельности с применением искусственного интеллекта, зарубежный опыт и российские перспективы. Доклад НИУ ВШЭ. М.: Издательский дом Высшей школы экономики. [Электронный ресурс]. URL: https://www.hse.ru/mirror/pubs/share/482492820.pdf (дата обращения: 18.07.2024).
Kalyatin, V. O. (2021). The problem of machine creativity in the legal system: regulation of the creation and use of the results of intellectual activity using artificial intelligence, foreign experience and Russian prospects. Report from the National Research University Higher School of Economics. Moscow. [Online]. Available at: https://arxiv.org/pdf/2005.14165 (Accessed: 07 August 2024). (In Russ.)
Луткова, О. В. (2016). Доктрина добросовестного использования произведений в современном авторском праве США. Право. Журнал Высшей школы экономики. № 2. С. 186 199.
Lutkova, O. V. (2016). The fair use doctrine in modern US copyright law. Right. Journal of the Higher School of Economics. No. 2. Pp. 186-199. (In Russ.)
Назаров, Н. А. (2022). Машинное творчество и право: две части одного целого. Труды по интеллектуальной собственности. Т. 43. № 4. С. 101-110.
Nazarov, N. A. (2022). Machine creativity and law: two parts of one whole. Papers on intellectual property. Vol. 43. No. 4. Pp. 101-110. (In Russ.)
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., Amodei, D. (2020). Language Models are Few-Shot Learners. [Online]. Available at: https://arxiv.org/pdf/2005.14165 (Accessed: 18 July 2024).
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I. (2018). Improving Language Understanding by Generative Pre-Training. [Online]. Available at: https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf (Accessed: 18 July 2024).
Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., Fidler, S. (2015). Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books. [Online]. Available at: https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Zhu_Aligning_Books_and_ICCV_2015_paper.pdf (Accessed: 18 July 2024).
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
https://oc.philosophy.nsc.ru/remote.php/webdav/%D0%94%D0%BE%D0%B3%D0%BE%D0%B2%D0%BE%D1%80%20%D1%81%20%D0%B0%D0%B2%D1%82%D0%BE%D1%80%D0%BE%D0%BC%20RL-%D0%BF%D1%80%D0%B0%D0%B2.doc
