Data Governance in the Age of Generative AI: A Critical Overview
Susan Ariel Aaronson delves into the complexities of data governance in the era of Generative AI in CIGI Paper No. 290, March 2024. She highlights the lack of a unified approach to managing the vast and intricate data sets that fuel Large Language Models (LLMs), posing significant ethical and legal challenges. Aaronson argues for a systemic methodology to ensure the data's integrity, transparency, and accountability, emphasising the urgent need for global standards in AI data governance. This paper sheds light on the urgent need for a cohesive framework that addresses the multifaceted nature of data underpinning generative AI technologies, proposing pathways towards more ethical and effective governance.