MATS Fellow:
Max Kamachee, Jonas Raedler
Authors:
Stephen Casper, Max Kamachee, Jordi Weinstock, Antonia Juelich, Jonas Raedler, Elise Racine
Citations
Abstract:
Frontier AI developers' model reports and the dedicated risk-assessment teams at governmental AI institutes such as UK AISI and US CAISSI now treat a major AI-enabled cyber, biological, or chemical terror event as a credible concern. But how, precisely, might such an event happen? What choices across the model lifecycle may contribute to it? This paper studies what current evidence suggests about how specific mistakes from AI developers, distributors, and governments may contribute to such an event.
The authors conclude with a set of 9 falsifiable predictions about how the first major AI-enabled cyber, bio, or chemical terrorism attack may occur and outline two illustrative hypothetical scenarios for such an event.
A Pre-mortem on The First Major AI-Enabled Terrorism Event and The Choices That Could Enable it: Plus 9 Predictions
Authors:
Max Kamachee, Jonas Raedler
Date:
October 15, 2026
Citations:
Gradient Routing Localizes and Removes Unintended Behaviors in RL
Authors:
Jake Ward, Shawn Hu, Aria Wong
Date:
October 12, 2026
Citations:
The MATS Program is an independent research and educational initiative connecting emerging researchers with mentors in AI alignment, governance, and security.
Each MATS cohort runs for 12 weeks in Berkeley, California, followed by an optional 6–12 month extension in London for selected scholars.