R0029/2026-03-27/Q001 — Query Definition

Research	R0029 — Plural Voice Attribution
Run	2026-03-27
Query	Q001

Query as Received

Has anyone proposed a mechanism, standard, or framework for attributing AI contributions to collaborative human-AI work? Look at academic institutions, publishers, professional organizations, and standards bodies for formal proposals, guidelines, or emerging norms.

Query as Clarified

• Subject: Formal frameworks, standards, and proposals for attributing AI contributions in collaborative work
• Scope: Mechanisms that go beyond simple disclosure to structured attribution — analogous to how CRediT taxonomy attributes human contributions
• Evidence basis: Published proposals from academic institutions, standards bodies, professional organizations, and publishers; peer-reviewed research on attribution norms; working tools or toolkits
• Temporal sensitivity: Rapidly evolving field; most relevant work dates from 2023-2025

Ambiguities Identified

1. "Attributing AI contributions" could mean legal authorship (copyright), academic authorship (byline credit), or contribution acknowledgment (disclosure). The query appears to encompass all three but the distinction matters for what counts as a "framework."
2. "Collaborative human-AI work" is broad — it could include AI as a tool (spell-checking) through to AI as a generative partner (writing drafts). The threshold for what constitutes "collaboration" is itself contested.
3. The query asks about "formal proposals" but the boundary between informal norms and formal standards is blurry in an emerging field.

Sub-Questions

1. Have standards bodies (NISO, ISO, etc.) proposed or adopted AI-specific attribution standards?
2. Have academic researchers proposed formal frameworks for AI attribution beyond binary disclosure?
3. Have any working tools or toolkits been built to operationalize AI attribution?
4. How does the existing CRediT taxonomy relate to or accommodate AI contributions?
5. What is the emerging consensus (if any) on whether attribution should be structured or freeform?

Hypotheses

ID	Hypothesis	Description
H1	Yes — multiple formal frameworks exist	Several formal frameworks, standards, or structured proposals for AI attribution have been published by credible institutions
H2	No — only ad hoc disclosure norms exist	No structured attribution frameworks exist; the field has only binary disclosure requirements (used AI / did not use AI)
H3	Emerging but immature — proposals exist but no consensus standard	Some structured proposals have been made but the field is pre-standardization, with no dominant framework adopted