The Physical Evidence Gap
Why digitally valid evidence is not enough for high-consequence systems.
Read the perspective ↗
4SI Research
Independent research for advanced AI and high-consequence systems—beyond model-only analysis.
Research agenda
The program examines where physical evidence can change institutional control—and where it cannot.
How can a system establish that the expected human is physically present for a specific action?
How can a physical object remain verifiably bound to its claimed origin, custody and state?
When should an intelligent system be required to obtain renewed, physically grounded authority?
Which loss pathways can physical verification materially change—and at what cost?
Published work
Visual editions improve accessibility. DOI-backed and versioned records support durable citation.
Why digitally valid evidence is not enough for high-consequence systems.
Read the perspective ↗A physically grounded authority condition for systems approaching consequential execution.
Read the visual edition ↗A systems view of people, objects and action where digital certainty is insufficient.
Read the visual edition ↗Loss pathways, intervention points and the cost conditions under which an added boundary may be justified.
Open the research note ↗The full publication library, source index and citable records.
Open the library ↗Connect the research thesis to current incidents, positions and scenario analysis.
Explore Intelligence →Research standard
Research quality depends on provenance, separation of fact and inference, explicit limitations and durable records.
Prefer direct, official and persistent records. Identify provenance and date.
Distinguish documented fact, inference, proposed control logic and future capability.
State assumptions, boundary conditions, limitations and unresolved failure modes.
Publish versioned records and DOI-backed papers where durable citation matters.
Keep material corrections visible and connected to the original record.
Translate the claim into a question that a controlled workflow can answer.
Research collaboration
We collaborate where a defined institutional problem can produce evidence useful beyond a single implementation.