The author also highlights the potential risks associated with the widespread use of LLMs, including copyright-related risks and other possible harms caused by hallucinations and bias. The article points out that the Llama 2 license, as an example, prevents using Llama to "improve" non-Llama LLMs, suggesting that fuzzy definitions benefit rights holders and those with the largest legal resources. The author concludes by emphasizing the need for understanding and managing these risks, particularly for enterprise technology leaders.
Key takeaways:
- Generative AI's derivative works pose a legal challenge in terms of intellectual property ownership and copyright.
- There is a lack of legal precedent for data derivatives, which are set to become more common with the advent of open source large language models (LLMs).
- LLMs are changing the game due to centralization, as they can generate variable outputs applicable in numerous ways, and incentives, as copyright holders and major platform companies can benefit from broad definitions of LLM derivatives.
- The legal uncertainty surrounding data derivatives has been the status quo in software, but the advent of LLMs and their widespread use could increase exposure to risk.