Non-Specialist Governance, Not Non-Specialist Authorship: What the Coordination Knowledge Substrate Pattern Makes Available to Whom

Fuente: Zenodo
Enregistré dans:
Détails bibliographiques
Auteur principal: LI, WENXIN
Format: Recurso digital
Publié: Zenodo 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866901342850646016
author LI, WENXIN
author_facet LI, WENXIN
contents <p>Abstract<br>Claim 5 of the CKS pattern includes an architectural commitment to non-specialist governance: a<br>non-specialist must be able to inspect, modify, and override substrate content and orchestration rules in tools<br>they already use. The commitment is widely cited as evidence that CKS systems are accessible. It is also<br>widely conflated with a stronger and different claim — that non-specialists can perform all the work CKS<br>systems require, including substrate schema design, orchestration rule authoring, and cell construction. The<br>source paper distinguishes the two in §7.4, but the distinction is made as one positioning move inside Claim<br>5's defense rather than as a consolidated architectural statement, and the conflation is the most common<br>misreading of CKS's accessibility claim. This note formalizes the distinction. Non-specialist governance is<br>the architectural commitment that the rights named by human-governed (Li, 24 April 2026) are exercisable<br>by humans without specialist expertise. Non-specialist authorship is a different commitment the architecture<br>neither requires nor forbids; the source paper supports it as a labor mode, the proof-of-concept demonstrates<br>it in a regulated-industry setting, but the design pattern does not commit to it as a property. The note states<br>the definition, identifies the kinds of authorship work CKS systems contain and which roles each requires,<br>traces the architectural property to the conjunction of three commitments that produce it, and provides an<br>operational test.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19869532
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Non-Specialist Governance, Not Non-Specialist Authorship: What the Coordination Knowledge Substrate Pattern Makes Available to Whom
LI, WENXIN
Artificial Intelligence
Artificial intelligence
<p>Abstract<br>Claim 5 of the CKS pattern includes an architectural commitment to non-specialist governance: a<br>non-specialist must be able to inspect, modify, and override substrate content and orchestration rules in tools<br>they already use. The commitment is widely cited as evidence that CKS systems are accessible. It is also<br>widely conflated with a stronger and different claim — that non-specialists can perform all the work CKS<br>systems require, including substrate schema design, orchestration rule authoring, and cell construction. The<br>source paper distinguishes the two in §7.4, but the distinction is made as one positioning move inside Claim<br>5's defense rather than as a consolidated architectural statement, and the conflation is the most common<br>misreading of CKS's accessibility claim. This note formalizes the distinction. Non-specialist governance is<br>the architectural commitment that the rights named by human-governed (Li, 24 April 2026) are exercisable<br>by humans without specialist expertise. Non-specialist authorship is a different commitment the architecture<br>neither requires nor forbids; the source paper supports it as a labor mode, the proof-of-concept demonstrates<br>it in a regulated-industry setting, but the design pattern does not commit to it as a property. The note states<br>the definition, identifies the kinds of authorship work CKS systems contain and which roles each requires,<br>traces the architectural property to the conjunction of three commitments that produce it, and provides an<br>operational test.</p>
title Non-Specialist Governance, Not Non-Specialist Authorship: What the Coordination Knowledge Substrate Pattern Makes Available to Whom
topic Artificial Intelligence
Artificial intelligence
url https://doi.org/10.5281/zenodo.19869532