Paper
Reducing Catastrophic Risk from AI with Systematic Monitoring and Evaluation of Rogue AI Progression
This article presents a structured framework of behavioral indicators that may signal progression toward potentially catastrophic threats from artificial intelligence systems. We adopt a pragmatic approach, inspired by established methodologies in cybersecurity and national security. By establishing clear metrics, indicators, and thresholds across multiple dimensions of AI capability and behavior, this framework enab · Authors: T. Bauer, W. P. Kegelmeyer, E. Begoli, A. Sadovnik, T. Emerson, C. Corley… · Published 2026-09-02 · arXiv:2609.03189
- Published
- 2026-09-02
- Authors
- 18
- arXiv
- 2609.03189
- Category
- cs.CY
Abstract
arXiv:2609.03189
T. Bauer, W. P. Kegelmeyer, E. Begoli, A. Sadovnik, T. Emerson, C. Corley, N. Generous, J. Moore, B. Bartoldson, R. Goldhahn, M. Goldman, M. Greaves…
This article presents a structured framework of behavioral indicators that may signal progression toward potentially catastrophic threats from artificial intelligence systems. We adopt a pragmatic approach, inspired by established methodologies in cybersecurity and national security. By establishing clear metrics, indicators, and thresholds across multiple dimensions of AI capability and behavior, this framework enables researchers and policymakers to implement evidence-based monitoring protocols.