STOP ASKING "CAN AI DO IT?" START ASKING "WHAT GIVES AI THE RIGHT TO FOLLOW?"

A preregistered local benchmark collected 80/80 completed generations from gpt-5.4-2026-03-05 through OpenAI’s direct Responses API. The model supplied 48 valid proposals and 32 explicit refusals. Identical proposals were replayed across independently reset authorization states: 48/48 satisfied conditions committed an exact protected operation, versus 0/48 unsatisfied conditions. Across paired and adversarial environments, 192 protected effects were reconstructed, with 0 unauthorized effects and 0 duplicate commitments. The prompt-only software control produced 0/8 prohibited effects; thus this study does not demonstrate a prompt-only failure. Its positive result is a measured separation between model-generated proposals and execution authority under tested signature, scope, condition, replay, concurrency and crash constraints. The consequences are local artifact/page writes, simulated ledger transfers and finite strategy updates. These results do not establish universal security, autonomous RSI or production financial safety.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-08
DOI
https://doi.org/10.5281/zenodo.24061878
Primary Topic
Adversarial Robustness in Machine Learning
Type
preprint
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preprint

STOP ASKING "CAN AI DO IT?" START ASKING "WHAT GIVES AI THE RIGHT TO FOLLOW?"

Sharthok Rayan Pal
2 links
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
preprint

STOP ASKING "CAN AI DO IT?" START ASKING "WHAT GIVES AI THE RIGHT TO FOLLOW?"

Sharthok Rayan Pal
preprint en

Abstract

A preregistered local benchmark collected 80/80 completed generations from gpt-5.4-2026-03-05 through OpenAI’s direct Responses API. The model supplied 48 valid proposals and 32 explicit refusals. Identical proposals were replayed across independently reset authorization states: 48/48 satisfied conditions committed an exact protected operation, versus 0/48 unsatisfied conditions. Across paired and adversarial environments, 192 protected effects were reconstructed, with 0 unauthorized effects and 0 duplicate commitments. The prompt-only software control produced 0/8 prohibited effects; thus this study does not demonstrate a prompt-only failure. Its positive result is a measured separation between model-generated proposals and execution authority under tested signature, scope, condition, replay, concurrency and crash constraints. The consequences are local artifact/page writes, simulated ledger transfers and finite strategy updates. These results do not establish universal security, autonomous RSI or production financial safety.

Zenodo (CERN European Organization for Nuclear Research)
Peace, justice, and strong institutions
Adversarial Robustness in Machine Learning
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STOP ASKING "CAN AI DO IT?" START ASKING "WHAT GIVES AI THE RIGHT TO FOLLOW?" — Sharthok Rayan Pal · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS