Final published version
Licence: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Intellectual Property Rights at the Training, Development and Generation Stages of Large Language Models
AU - Kirchhübel, Christin
AU - Brown, Georgina
PY - 2024/5/20
Y1 - 2024/5/20
N2 - Large Language Models (LLMs) prompt new questions around Intellectual Property (IP): what is the IP status of the datasets used to train LLMs, the resulting LLMs themselves, and their outputs? The training needs of LLMs may be at odds with current copyright law, and there are active conversations around the ownership of their outputs. A report published by the House of Lords Committee following its inquiry into LLMs and generative AI criticises, among other things, the lack of government guidance, and stresses the need for clarity (through legislation, where appropriate) in this sphere. This paper considers the little guidance and caselaw there is involving AI more broadly to allow us to anticipate legal cases and arguments involving LLMs. Given the pre-emptive nature of this paper, it is not possible to provide comprehensive answers to these questions, but we hope to equip language technology communities with a more informed understanding of the current position with respect to UK copyright and patent law.
AB - Large Language Models (LLMs) prompt new questions around Intellectual Property (IP): what is the IP status of the datasets used to train LLMs, the resulting LLMs themselves, and their outputs? The training needs of LLMs may be at odds with current copyright law, and there are active conversations around the ownership of their outputs. A report published by the House of Lords Committee following its inquiry into LLMs and generative AI criticises, among other things, the lack of government guidance, and stresses the need for clarity (through legislation, where appropriate) in this sphere. This paper considers the little guidance and caselaw there is involving AI more broadly to allow us to anticipate legal cases and arguments involving LLMs. Given the pre-emptive nature of this paper, it is not possible to provide comprehensive answers to these questions, but we hope to equip language technology communities with a more informed understanding of the current position with respect to UK copyright and patent law.
M3 - Conference contribution/Paper
SP - 13
EP - 18
BT - Proceedings of LEGAL2024: Workshop on Legal and Ethical Issues in Human Language Technologies @LREC-COLING-2024
A2 - Siegert, Ingo
A2 - Choukri, Khalid
PB - European Language Resources Association (ELRA)
ER -