Reducing Catastrophic Risk from AI with Systematic Monitoring and Evaluation of Rogue AI Progression

arXiv:2609.03189 · cs.CY, cs.AI, cs.HC · Submitted 2026-09-02 · Read on arXiv

cs.CY, cs.AI, cs.HC

Submitted: 2026-09-02

Updated: 2026-09-04

Code: https://github.com/anthropics/claude-code

License: http://creativecommons.org/licenses/by-nc-nd/4.0/

The gist: This article presents a structured framework of behavioral indicators that may signal progression toward potentially catastrophic threats from artificial intelligence systems.

Terminology

• Alignment — 7× in this paper · explained in 1 episode
• Perplexity — 5× in this paper · explained in 3 episodes
• Actor — 3× in this paper · explained in 3 episodes
• Affordance — 2× in this paper · explained in 1 episode
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Reward Hacking — 2× in this paper · explained in 8 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• AI Alignment — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Agentic AI systems — 1× in this paper · explained in 1 episode
• Alignment Problem — 1× in this paper · explained in 1 episode
• Edge Devices — 1× in this paper · explained in 2 episodes
• LLMs (Large Language Models) — 1× in this paper · explained in 2 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Function — 1× in this paper · explained in 2 episodes

Abstract

Sources

• Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals
• Measuring AI Ability to Complete Long Software Tasks
• Subliminal Learning: Language models transmit behavioral traits via hidden signals in data
• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
• Demonstrating specification gaming in reasoning models
• LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild

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