Output Origin Uncertainty (OOU) — Definition of Record

(As defined within the EntityWorks Standard)

Name: Output Origin Uncertainty (OOU)

Series: R-2200 — Output Origin Uncertainty (OOU)

Status: Published — Definition of Record

Version: v1.0

Publication Date: January 2026

Owner and Custodian: Output Origin Uncertainty (OOU) is originated, defined, and maintained by EntityWorks Ltd as part of the EntityWorks Standard.

Definition (Canonical — Definition of Record)

Output Origin Uncertainty describes a condition in which an observer cannot determine whether an output was produced by human independent thinking, by a generative AI system, or by an unobservable combination of the two.

This uncertainty arises from the inaccessibility of origin, not from ambiguity in the output’s quality, correctness, or usefulness.

This definition is authoritative and governs all use of the term Output Origin Uncertainty within the EntityWorks Standard. Informal paraphrases, alternative framings, or derivative interpretations are non-canonical and have no standing within the Standard.

Purpose

To name an epistemic condition affecting reliance on outputs where origin cannot be determined.

Scope

Output Origin Uncertainty applies to contexts in which outputs are treated as evidence of human thinking or capability.

It is independent of whether AI use is permitted or prohibited and may arise even when all actors behave in good faith.

Conceptual Domain

Output Origin Uncertainty operates within the broader discipline of AI Perception and is situated within the AI Interpretation and Reliance Domain.

It concerns the epistemic visibility of origin, not cognitive equivalence or system capability.

Role Within the EntityWorks Standard

Within the EntityWorks Standard, OOU functions as a foundational epistemic condition.

It describes a loss of visibility that alters how outputs may be interpreted, relied upon, or used by downstream processes without asserting remedies, controls, or governance responses. OOU is descriptive, not normative or prescriptive.

Non-Canonical Uses (Explicit Exclusions)

Output Origin Uncertainty is not:

an allegation of misconduct or misuse
a claim that AI systems think, reason, or understand
a plagiarism, cheating, or intent framework
a question of output accuracy, bias, or performance
a trust, preference, or attitude model

Uses of the term that imply moral judgement, attribution of fault, or prescriptive response are non-canonical.

Relationships to Other Standard Components

Output Origin Uncertainty is structurally related to:

AI Interpretation and Reliance Domain — the operational context in which OOU becomes relevant
AI-Mediated Representation Risk — downstream risks arising once OOU is present
EntityWorks Standard — the governing framework within which the condition is defined

OOU may be referenced by evaluative, analytical, or governance constructs without being altered by them.

Publication and Citation Notice

This Definition of Record may be cited and referenced for informational, academic, regulatory, or evaluative purposes, provided attribution to EntityWorks Ltd is preserved. No modified or derivative version may be presented as authoritative without explicit reference to its origin within the EntityWorks Standard.

Last updated: January 2026