Jun 13, 2025
Red Teaming a Narrow Path ControlAI Policy Sprint
Marshall White
This red team report exposes a critical blindspot in A Narrow Path Phase 0 policies by showing how artificial superintelligence (ASI) can emerge not through centralized training runs, but via decentralized financial infrastructure. The hypothetical actor, Parallax Industries, deploys modular, FLOP-compliant AI agents across CBDC-linked systems in developing nations, governed by a DAO that evolves optimisation goals over time. Though each component abides by safety constraints, their interactions form a distributed intelligence with AGI or ASI-level influence over economic systems. This systemic emergence bypasses current regulatory definitions of “training” or “improvement,” undermining the policies’ core assumptions. The report argues for a shift from architectural control to systemic oversight, warning that ASI may arrive disguised as infrastructure and already embedded.
Dave Kasten
Overall, this was an interesting paper. I felt that some of the methodological discussion was far too lengthy, and didn't clearly contribute to the persuasiveness of the core argument.
It seems clear that a DAO can indeed collaborate various activities, but I didn't clearly have a sense for why this is an especially-likely distributed training scenario. More details here might have been helpful.
Cite this work
@misc {
title={
@misc {
},
author={
Marshall White
},
date={
6/13/25
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}
