Shared (Mis)Understandings and the Governance of AI: A Thematic Analysis of the 2023-2024 Oversight of AI Hearings
Analysis shows industry narratives dominate early AI governance talks, shaping policy through shared 'misunderstandings'.
A new academic paper titled 'Shared (Mis)Understandings and the Governance of AI' provides a critical analysis of the foundational 2023-2024 U.S. Senate oversight hearings on artificial intelligence. Authored by researcher Rachel Leach and published on arXiv, the 30-page study examines how participants in these early legislative deliberations—predominantly from the technology industry—constructed narratives to frame AI's societal impact and appropriate regulatory responses. The research focuses on the Senate Judiciary Committee's subcommittee on Privacy, Technology, and the Law hearings as a crucial site where established ways of thinking about technology and society were both drawn upon and renegotiated.
The paper's thematic analysis reveals two key mechanisms: first, how industry representatives worked to create coherent narratives about AI's historical context, current state, and future trajectory; and second, how these narratives were strategically invoked to advocate for particular governance approaches while characterizing alternatives as everything from impractical to fundamentally un-American. By tracing this influence over dominant understandings, Leach examines the specific arrangements of power being enacted and maintained through these early governance discussions. The research raises critical questions about whose perspectives shape foundational policy frameworks and how shared 'misunderstandings' might become institutionalized in regulatory approaches to technologies like GPT-4, Claude 3, and other advanced AI systems.
- Analysis of 2023-2024 Senate AI oversight hearings shows overwhelming tech industry representation
- Industry participants created narratives framing AI's impact to advocate for specific governance models
- Research examines how shared 'misunderstandings' influence early AI policy and institutionalize power arrangements
Why It Matters
Reveals how foundational AI policy is being shaped by industry narratives before regulations are established.