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pith:WLYWF7HC

pith:2025:WLYWF7HC2LGDOVUWBURW3QZBHL
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Robust AI Security and Alignment: A Sisyphean Endeavor?

Apostol Vassilev

Extending Gödel's incompleteness theorem establishes fundamental information-theoretic limits on the robustness of AI security and alignment.

arxiv:2512.10100 v2 · 2025-12-10 · cs.AI

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4 Citations open
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Claims

C1strongest claim

This manuscript establishes information-theoretic limitations for robustness of AI security and alignment by extending Gödel's incompleteness theorem to AI.

C2weakest assumption

That AI systems can be modeled as formal axiomatic systems in a manner that allows direct application of Gödel's incompleteness results to their security and alignment properties.

C3one line summary

AI security and alignment cannot achieve full robustness because any sufficiently powerful AI inherits incompleteness-style limitations from formal systems.

References

12 extracted · 12 resolved · 2 Pith anchors

[1] doi: 10.1145/321832.321839 2022 · doi:10.1145/321832.321839
[2] doi: 10.48550/ARXIV.2210.14707. D. Glukhov, I. Shumailov, Y. Gal, N. Papernot, and V. Papyan. LLM censorship: A machine learning challenge or a computer security problem?, · doi:10.48550/arxiv.2210.14707
[3] URLhttps://arxiv.org/abs/2307.10719. S. Goldwasser, M. P. Kim, V. Vaikuntanathan, and O. Zamir. Planting undetectable backdoors in machine learning models.https://arxiv.org/abs/2204.06974,
[4] ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs
[5] Why Language Models Hallucinate · arXiv:2509.04664

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Receipt and verification
First computed 2026-05-20T00:01:37.655089Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

b2f162fce2d2cc3756960d236dc3213ae65fbd30a087e068b8be2fa127f8868c

Aliases

arxiv: 2512.10100 · arxiv_version: 2512.10100v2 · doi: 10.48550/arxiv.2512.10100 · pith_short_12: WLYWF7HC2LGD · pith_short_16: WLYWF7HC2LGDOVUW · pith_short_8: WLYWF7HC
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WLYWF7HC2LGDOVUWBURW3QZBHL \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: b2f162fce2d2cc3756960d236dc3213ae65fbd30a087e068b8be2fa127f8868c
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2025-12-10T21:44:10Z",
    "title_canon_sha256": "ec29d7f1938e3743fd1632f692552b22de93be8d079dfdefc89d28d049b26deb"
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