AIHood
MII-29 · Evidence Report

Your robot's insurability, on one page

This report synthesizes your identity checklist and capability selection into the read an underwriter needs: how complete your identities are, your exposure across the A1–A5 misuse ladder, what moves a premium, and what to fix first.

00MII completeness
Early — major gaps

0 of 29 identities declared across 0 selected capabilities. Trust Score posture plugs in here once assessed.

Identity completeness by cluster

Machine0/8
Makers0/4
AI0/4
People0/5
Governance0/8

A1–A5 misuse exposure

Escalating tiers of not-as-intended use. Exposure is lower where the identities that prove or refute a tier are present.

a1High exposure

A1 · Foreseeable operator error

Misused within intended scope — a wrong step or skipped check.

a2High exposure

A2 · Out-of-ODD / off-label

Run outside its declared scene or task boundary.

a3High exposure

A3 · Unauthorized modification

Part swapped, model jailbroken, or a non-approved OTA applied.

a4High exposure

A4 · Unauthorized control / takeover

Remote hijack, credential abuse, or commands from an unverified controller.

a5High exposure

A5 · Autonomous boundary breach

The robot itself acts beyond its granted authority.

Premium-impact factors

Low identity completeness — raises premium and may cap coverage.
Weak governance identities — evidence and accountability gaps raise premium.
Weak maker/provenance identities — supply-chain recourse is harder.
High exposure on at least one misuse tier raises premium.

Fix these identities first

Machine-body identity
Hardware root-of-trust
AEM / evidence-module identity
Main-controller SoC identity
Sensor identity

Illustrative prototype report. Not a verified audit, not a bound insurance quote; premium factors are directional.