Upstream Dual-Use: Modelling, Epistemic Authority, and Institutional Harm in AI Systems

The dual-use problem of artificial intelligence is often treated as arising downstream issue arising at the point of deployment. We explore the hypothesis that dual-use is rooted upstream, in modelling and training practices that confer epistemic authority on AI systems before use. Focusing on design choices, data selection, and validation processes, we show how institutional reliance on AI systems displaces responsibility from human and organizational collectives onto the models themselves. With brief reference to cases, the paper reframes dual-use as a problem of epistemic legitimation, with direct relevance for accountability and peace-oriented AI research.