翻訳待ち：Robust AI Security and Alignment: A Sisyphean Endeavor?

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。

--> [Submitted on 10 Dec 2025 (v1), last revised 7 Apr 2026 (this version, v2)] Title:Robust AI Security and Alignment: A Sisyphean Endeavor? View a PDF of the paper titled Robust AI Security and Alignment: A Sisyphean Endeavor?, by Apostol Vassilev View PDF HTML (experimental) 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. Comments: 17 pages, 1 figure. This version will appear in IEEE Security $ Privacy in June 2026 Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2512.10100 [cs.AI] (or arXiv:2512.10100v2 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2512.10100 arXiv-issued DOI via DataCite Related DOI: https://doi.org/10.1109/MSEC.2026.3678214 DOI(s) linking to related resources Submission history From: Apostol Vassilev [view email] [v1] Wed, 10 Dec 2025 21:44:10 UTC (165 KB) [v2] Tue, 7 Apr 2026 12:47:26 UTC (166 KB) Full-text links: Access Paper: View a PDF of the paper titled Robust AI Security and Alignment: A Sisyphean Endeavor?, by Apostol Vassilev View PDF HTML (experimental) TeX Source view license Current browse context: cs.AI new | recent | 2025-12 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Loading... Data provided by: Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)