Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review
It addresses the problem of fair use in generative AI for researchers and policymakers, but is incremental as it synthesizes existing literature without new empirical results.
This paper systematically reviews stakeholder goals and expectations in the generative AI supply chain to assess whether fair use arguments for training models align with copyright law's objective of promoting science and arts, identifying research gaps and future avenues for policymakers.
Through a systematization of generative AI (GenAI) stakeholder goals and expectations, this work seeks to uncover what value different stakeholders see in their contributions to the GenAI supply line. This valuation enables us to understand whether fair use advocated by GenAI companies to train model progresses the copyright law objective of promoting science and arts. While assessing the validity and efficacy of the fair use argument, we uncover research gaps and potential avenues for future works for researchers and policymakers to address.