Robust AI Security and Alignment: A Sisyphean Endeavor?
cs.AI
Submitted: 2025-12-10
Updated: 2026-04-07
Comments: 17 pages, 1 figure. This version will appear in IEEE Security $ Privacy in June 2026
Journal ref: IEEE Security & Privacy, vol. 24, no. 3, pp. 52-58, May-June 2026
DOI: 10.1109/MSEC.2026.3678214
License: http://creativecommons.org/licenses/by/4.0/
The gist: This manuscript establishes information-theoretic limitations for robustness of AI security and alignment by extending Gödel's incompleteness theorem to AI.
Terminology
Abstract
This manuscript establishes information-theoretic limitations for robustness of AI security and alignment by extending Gödel's incompleteness theorem to AI. Knowing these limitations and preparing for the challenges they bring is critically important for the responsible adoption of the AI technology. Practical approaches to dealing with these challenges are provided as well. Broader implications for cognitive reasoning limitations of AI systems are also proven.
Sources
- ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs
- Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack
- Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition
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