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The WisdomTwin Trust Layer: A Testable Control Specification for Role-Specific AI Decision Support

Roman Bodnarchuk, Co-Founder and CEO, WisdomTwin, Inc.. ORCID 0009-0004-3113-2118

WT-200-001Version 1.0September 24, 2026Open access, CC BY 4.0

Working paper; not peer reviewed. This is a proposed control specification, not a description of verified product functionality or regulatory certification. No enterprise deployment, security evaluation, or human-participant study was conducted for this paper. No DOI has been assigned.

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Bibliographic details.

Identifier
WT-200-001, version 1.0
Type
Working paper / preprint (proposed control specification)
Published
September 24, 2026
Status
Proposed control specification. Working paper; not peer reviewed.
DOI
No DOI assigned.
License
Creative Commons Attribution 4.0 International (CC BY 4.0), original text
Language
English
File
PDF, 9 pages, 107,408 bytes
PDF SHA-256
db77d28b385e16c33245eca75bf68540aaca5eb7229d7dc6cb1d66ea0714ce92

Abstract

A role-specific AI assistant creates value only if an authorized recipient can use its evidence without mistaking a generated recommendation for the authority of an officeholder. This paper translates the judgment-latency framework of WT-100-001 into a proposed Trust Layer: a set of enforceable boundaries around data admission, role memory, retrieval, response delivery, and delegated action. The design treats authorization as specific to the requesting person, intended recipient, source, purpose, time, and requested action. It separates historical precedent from current policy and decision authority, requires safe decline when evidence or permissions are uncertain, and specifies an audit record without requiring disclosure of private model reasoning. Voice meetings and multi-party conversations receive explicit audience controls. A traceability matrix connects principal failure modes to testable controls and release evidence. The contribution is a falsifiable specification for future implementation and evaluation. No claim is made that the proposed controls have been implemented, independently validated, or shown to satisfy any particular legal regime.

Subject terms

  • role-specific AI
  • authorization
  • provenance
  • decision rights
  • enterprise memory
  • human oversight
  • auditability
  • judgment latency

How to cite

Bodnarchuk, R. (2026). The WisdomTwin Trust Layer: A testable control specification for role-specific AI decision support (WisdomTwin Working Paper WT-200-001, Version 1.0). WisdomTwin, Inc.

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Declarations

What this paper is and is not.

  • Interest and authorship: Prepared for Roman Bodnarchuk, WisdomTwin co-founder and CEO, who has a financial interest in the proposed system. Generative AI assisted in synthesis, drafting and production. Named authorship does not imply independent technical validation.
  • Evidence and data: No new empirical data, enterprise records or human-participant research. Requirements and examples are conceptual. The author is responsible for the final text and any later submission.
  • Funding: No additional research-funding information was supplied for this companion draft.
  • Publication: Working paper, not peer reviewed; DOI unassigned. CC BY 4.0 applies to original text. Third-party sources retain their own rights.

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