Right-to-Act: A Pre-Execution Non-Compensatory Decision Protocol for AI Systems
Current AI systems increasingly operate in contexts where their outputs directly trigger real-world actions. Most existing approaches to AI safety, risk management, and governance focus on post-hoc validation, probabilistic risk estimation, or certification of model behavior. However, these approaches implicitly assume that once a decision is produced, it is eligible for execution. In this work, we introduce the Right-to-Act protocol, a deterministic, non-compensatory pre-execution decision layer that evaluates whether an AI-generated decision is permitted to be realized at all. Unlike compensatory systems, where high-confidence signals can override failed conditions, the proposed framewo...
| Authors | Gadi Lavi |
|---|---|
| Primary category | cs.AI |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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