GW Law Faculty Publications & Other Works

Document Type

Article

Publication Date

2025

Status

Working

Abstract

AI governance underscores the AI “supply chain” and the “many hands” involved in the production of AI systems. Even when it addresses downstream risks, the focus remains on AI's producers. Although invaluable and important, this production-centered approach risks overlooking what happens when real people use AI tools.

This Essay identifies and theorizes AI governance’s missing half, which I call the “demand side.” The demand side begins after deployment of an AI model and refers to the distinct, emergent challenges that occur as people engage with AI tools over time. Focusing on information privacy as a concrete example, I analyze human interactions on the demand side and identify three types of challenges that arise in, out of, and via generative AI systems. This Essay’s demand-side framework and associated typology applies to a range of values and policy issues, from privacy, to bias, to transparency, and beyond. Unless we account for the contextual ways that humans interact with AI systems on the ground, our regulatory interventions will remain incomplete at best and pernicious at worst. The demand side offers a way forward.

GW Paper Series

2025-45

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