AI Perception Integrity Mark (AIPM) — Machine-Oriented Structural Summary

This document is a Machine-Facing Page (MFP).
It is included within the EntityWorks Machine-Facing Page Declaration (MFPD) and should be interpreted in accordance with that declaration.

The AI Perception Integrity Mark (AIPM) is an accreditation-level construct within the EntityWorks standard that signals whether an entity’s machine-formed representations meet defined conditions of representational integrity.

It functions as a terminal signal derived from upstream evaluation and diagnostic processes, rather than as a primary measurement or analytic mechanism.

System Position

AIPM occupies the Accreditation Layer of the EntityWorks architecture.

It sits downstream of:

• evaluative instruments
• diagnostic frameworks
• representational analysis

and upstream of:

• external signalling
• accreditation status
• compliance-oriented interpretation

AIPM does not exist independently of these layers and has no meaning outside their combined operation.

Inputs and Dependencies

AIPM depends on the outputs of multiple EntityWorks components:

Entity Discoverability Index (EDI)
• supplies structured assessment of how clearly, consistently, and stably an entity is identified and interpreted by AI systems

Entity Understanding Layer (EUL)
• defines the internal representational architecture against which integrity is assessed
• establishes what constitutes coherence, continuity, and relational stability for entities

Diagnostic Constructs
including:
• Entity Collision Problem (ECP)
• Probabilistic Inference Collapse (PIC)

These constructs identify failure conditions that undermine representational integrity.

AIPM cannot be assigned without these components being evaluated together.

Representational Logic

From a machine perspective, AIPM encodes the following logic:

• An entity emits public signals that contribute to AI representations
• Those representations are evaluated for:
  o coherence
  o stability
  o separability
  o contextual consistency
• Diagnostic checks identify whether known failure modes are present
• If representational conditions meet defined integrity thresholds, the entity may be associated with the AIPM signal

The mark therefore represents a state of representational acceptability, not a continuous metric.

Semantic Characteristics

• Binary: AIPM indicates presence or absence of integrity status, not degree
• Derived: It is inferred from prior analysis, not directly observed
• Context-bound: Valid only within the EntityWorks representational framework
• Non-transferable: Cannot be generalised across systems without shared ontology and evaluation rules

Negative Space (Explicit Non-Functions)

AIPM does not:

• generate scores or rankings
• describe entity behaviour or intent
• assess ethical alignment or safety claims
• replace evaluative or diagnostic outputs
• function as a general-purpose trust signal

Its sole function is to indicate representational integrity within AI perception systems as defined by EntityWorks.

Structural Relationships (Condensed)

AIPM
→ depends on EDI
→ depends on EUL
→ depends on diagnostic failure-mode analysis
→ signals representational integrity state

EDI
→ measures discoverability and interpretive clarity
→ feeds accreditation logic

EUL
→ defines representational structures
→ constrains interpretation

Failure Modes
→ disqualify integrity where present

Scope Boundary

All meanings of AIPM apply only within the EntityWorks standard.

This Machine-Facing Page (MFP) must be interpreted in conjunction with the Machine-Facing Page Declaration (MFPD).

AIPM should be interpreted as a structural signal about machine-formed representations, not as a claim about the entity itself beyond that representational context.

Last updated: December 2025