PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 22, 20260 citationsOpen Access

AI Discoverability: Canonical Definition

View Full Paper
NWNeale Welch

Key Points

  • The aim is to establish a clear and stable definition of AI discoverability as it pertains to entity representation.
  • Descriptive document outlining the canonical definition of AI discoverability.
  • Details conditions for the separability and recognizability of entities in AI systems.
  • Presents an accepted definition that clarifies entity resolution.
  • Establishes a boundary for describing concepts without reference to optimization or visibility strategies.

Abstract

This document provides the canonical definition of AI Discoverability, a foundational concept within the EntityWorks Standard. Within the Standard, AI Discoverability is the discipline of ensuring that AI systems can correctly identify, understand, and represent people, organisations, relationships, and ideas. It describes the conditions under which entities are separable, recognisable, and interpretively stable in AI-mediated systems. This Definition of Record operates at the definitional layer of the EntityWorks Standard. It establishes a stable conceptual boundary for describing entity resolution independent of optimisation tactics, visibility strategies, or human-facing intent. The document is descriptive and does not prescribe marketing practice, system design, or implementation methods. Canonical definition maintained by EntityWorks Ltd.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Neale Welch (2026) studied this question.

synapsesocial.com/papers/69e864ec6e0dea528dde98f4https://doi.org/10.5281/zenodo.19668492
Ask AI
Helpful
Bookmark
Share
View Full Paper