Reconstructive Authority Model: Runtime Execution Validity Under Partial Observability
New research shows attestation alone fails 42% of the time at low coverage levels.
Marcelo Fernandez of TraslaIA has published a new paper introducing the Reconstructive Authority Model (RAM), a framework designed to ensure runtime execution validity for autonomous systems operating under partial observability. The paper, part of the Agent Governance Series (Paper P5), argues that existing governance mechanisms like trusted execution environments, oracle-signed state proofs, and cryptographic attestation are structurally insufficient because they only enforce integrity of computation and state projections, not coverage of what is measured. RAM defines a reconstruction gate that reasons over an explicit coverage envelope comprising proven state, declared assumptions, and an acknowledged unobservable residual, permitting execution only when coverage is adequate for the action class. When coverage is insufficient, RAM narrows privileges dynamically or fails closed.
The paper formalizes RAM with two theorems proving attestation insufficiency and RAM necessity, along with three corollaries, and presents a hybrid RAM+Attestation architecture with privilege-narrowing. Synthetic experiments with 100,000 runs (seed=42) show RAM achieves zero invalid execution rates at all coverage levels, while attestation-based systems exhibit an invalid execution rate of 0.423 at low coverage and 0.233 even at full coverage, the latter arising from undefined-state handling failures undetectable by integrity checks alone. This reframes execution validity as a coverage reconstruction problem, distinct from and complementary to integrity guarantees provided by attestation. The work is available on arXiv (2604.22898) and Zenodo.
- RAM separates integrity from coverage, achieving zero invalid execution rates across all coverage levels in 100,000 synthetic experiments.
- Attestation-based systems fail with 42.3% invalid execution at low coverage and 23.3% even at full coverage due to undefined-state handling failures.
- RAM defines a reconstruction gate that narrows privileges dynamically or fails closed when coverage is insufficient for the action class.
Why It Matters
This reframes AI safety as a coverage problem, offering a practical path to reliable autonomous agents.