Hardening Self-Recognition Evaluation: Protocol Clarity, Safer Terminology, and Privacy-First Biometric Routing

Context #

Recent work focused on strengthening how self-recognition is evaluated and communicated, while tightening privacy expectations for any workflow that could touch biometric signals. In parallel, persona and “universe” capabilities were integrated more broadly so that identity- and persona-related behaviors can be exercised in more realistic end-to-end flows.

The changes are best understood as three aligned goals: 1) make self-recognition evaluations harder to misinterpret, 2) prevent overclaims (especially around “self-awareness”), and 3) ensure biometric processing is gated and routed by jurisdiction-aware consent requirements.

What changed #

1) Clearer, stricter self-recognition evaluation guidance #

The self-recognition content was expanded to reduce category errors—specifically, the tendency to equate passing a mirror-style test with possessing a human-like self-concept.

Key additions and emphasis:

Separate behavioral evidence from cognitive inference: results should describe observable capabilities (e.g., calibration, contingency testing) without escalating into metaphysical claims.
Terminology guardrails: explicitly discourages describing systems as “self-aware” and instead recommends functional descriptions such as visual-motor calibration or source verification.
Protocol validity requirements: stresses controls like sham marking and visual inaccessibility of the mark, and includes decision points to detect failures like mirror agnosia (physics/interaction misunderstanding).
Gradient framing: encourages evaluating performance along a gradual recognition gradient rather than a binary pass/fail, supporting more diagnostic reporting.
Failure taxonomy and metrics: introduces structured failure-frame tagging and more granular evaluation metrics (e.g., time-to-recognition style measures) to prevent “blind” aggregate pass rates.

The biometric identity guidance was expanded with cross-jurisdiction considerations that treat biometric processing as high-risk and consent-sensitive.

Notable themes:

Jurisdiction-aware routing: before activating any camera/sensor inputs or processing biometric templates, determine jurisdiction; if unknown, default to a stricter global baseline.
Consent modality matters: terms-of-service acceptance is treated as insufficient where explicit/written release is expected; consent should be isolated and obtained before capture.
Local-match pattern preference: centralized storage of biometric templates is framed as higher risk, motivating designs that keep matching local where feasible.

3) Persona and “universe” integration for more realistic flows #

Persona capabilities were integrated more broadly across the system and surfaced through additional command and service areas. This supports:

exercising identity/persona behavior in richer scenarios,
aligning self-recognition interactions with safer narrative and communication patterns,
and enabling more consistent persona handling across interactive surfaces.

Why it matters #

Reduces overclaim risk: clearer language boundaries help prevent confusing “self-recognition behavior” with “self-awareness,” which is both scientifically and safety-wise problematic.
Improves evaluation usefulness: adding controls, a gradient model, failure taxonomies, and granular metrics makes results more reproducible and actionable.
Raises the privacy bar: biometric workflows become harder to trigger accidentally and easier to defend in audits, especially under strict regimes and “unknown jurisdiction” cases.

Outcome / impact #

Self-recognition evaluation is now more defensible: it is framed as a set of operational capabilities with explicit confounds, controls, and reporting rules.
Biometric-related features are positioned behind clearer consent and routing logic, reducing compliance and user-trust risk.
Persona and “universe” integration broadens the test surface for identity-related interactions, making it easier to validate behavior in end-to-end contexts.

Notes on scope #

A portion of the activity also included index reorganization and knowledge-pack evolution. These are treated as supporting work; the primary user-facing intent is the strengthened evaluation protocol, safer terminology, and privacy-first biometric gating.