Editorial guide · prepared with AI assistance · Expert assessments
Expert authorship and AI-assisted content: what participation must mean
Distinguish writing, fact-checking, expert review and approval in AI-assisted content. Use contribution and version records instead of a misleading expert byline.
An expert byline should describe actual responsibility for the published work. If AI helped produce content, disclose the relevant use and state what the named person investigated, wrote, checked and approved. A name on a page or an AI-detection score cannot establish that an expert performed those tasks. The permitted use of AI also depends on the publication’s own rules.
Describe the work behind the name
Written by, reviewed by and fact-checked by describe different contributions. A specialist may check one technical section without reviewing the entire article. An editor may improve wording without inspecting the evidence. A person who approved the use of a quotation has not necessarily approved the surrounding conclusion.
Make the contribution specific enough that a reader can understand its scope. Identify the sections, questions or source checks covered, the version reviewed and the limitations left unresolved. Do not attach a broad expert-reviewed label to a document after a narrow conversation.
CRediT separates research activities, including investigation, analysis, original drafting and review/editing. ICMJE links scholarly authorship to contribution, approval and accountability, and says AI tools cannot take authorial responsibility. These are research-publication frameworks; borrowing their distinctions does not mean a commercial article has been peer reviewed. [S30] [S21]
A contribution record for AI-assisted work
An AI system can assist a workflow without being the accountable expert. The record should make that distinction visible. If nobody checked the underlying citation, do not turn an AI-generated reference list into a claim that the research was verified.
| Role | Question to resolve | Evidence to retain |
|---|---|---|
| Research | Who opened the underlying sources and evaluated relevance? | Source list, access dates and claim notes |
| Investigation | Who performed any original test or analysis? | Procedure, data and work record |
| Writing | Who produced or substantially rewrote the prose? | Draft history and AI-use description |
| Review | Which questions and sections did the reviewer check? | Review comments and unresolved issues |
| Approval | Who accepted which final version? | Version-specific approval record |
| Correction | Who can investigate an error after release? | Responsible contact and correction process |
A hypothetical review label with too much implied scope
Imagine an AI-assisted article comparing cloud-storage tools. A security specialist reads only the paragraph about encryption and confirms a correction to one term. Labelling the entire article reviewed by a security expert would imply work the specialist did not perform. This is a hypothetical editorial example, not a claim about a NamedProof article or expert.
A narrower description would say that the specialist reviewed the encryption terminology in the identified version. The pricing comparison, usability claims and test results would still need their own checks. If those checks were not done, the publication should say so or remove the unsupported material.
Approval should refer to the text actually published. A later change to the conclusion, translation or comparison can exceed the earlier review. Keep the older approval as a historical record, then obtain an appropriate review of the changed content before repeating the same label.
State the applicable AI-use policy
Some publications permit AI-assisted drafting with disclosure and human checking. Others reserve a category for personally written work. Read the applicable policy before assuming that disclosure makes every use acceptable. Transparent use and permitted use are separate questions.
Google’s guidance says that generative AI can help research and structure content, while generating many pages without useful value may violate its scaled-content rules. Google also recommends checking accuracy and giving readers context about creation. This is search-publishing guidance, not approval of a particular article or an expert-authorship claim. [S03]
NamedProof’s commissioned expert-review policy is stricter: the named expert must personally write original review text; AI-generated or AI-rewritten review prose is not accepted. Its automated research and generated profiles are separate outputs. This knowledge-base article is an AI-assisted editorial guide, not a commissioned expert-written review. [NP02]
Use records to investigate authorship concerns
If authorship is questioned, begin with the claimed contribution and available work records. Ask how the author reached the finding, which sources they inspected and how the final text changed. Notes and revision history can help assess the account, although no single record guarantees the truth of every statement.
NamedProof describes authorship checking as a manual editorial standard and says an AI detector is not proof of authorship. The policy concerns how commissioned work is handled; it does not establish that every submitted review has already passed a check. [NP02]
Before publishing, read the byline and method note as a reader would. They should let someone distinguish the writer, the investigator, any limited reviewer and the organization responsible for corrections. Where no human expert reviewed the guide, say that clearly. Accurate role descriptions are more useful than a stronger label that the work cannot support.
Sources and method
NamedProof editorial guide. Prepared with AI-assisted research and synthesis; the cited primary-source passages were checked for this guide. This is not a commissioned expert assessment and has not received human expert review. Examples labelled hypothetical are teaching examples, not client results.
Limitations
- This article is AI-assisted editorial synthesis, not personally written commissioned expert work.
- Authorship records support investigation; they are not automatic proof that every claim is correct.
Original contribution
A contribution-and-approval record and a hypothetical narrow technical check showing when a broad expert-reviewed label misrepresents participation.
Sources
- S30
Contributor Role Taxonomy (CRediT)
Scope: Research contributorship taxonomy.
Limitations: A role label is not proof of participation; these 14 roles are unrelated to Ivan's 14 editorial principles.
Material read: Official overview and role list read
Sources checked:
- S21
Defining the Role of Authors and Contributors
Scope: Medical journal recommendations.
Limitations: Not universal commercial law or certification; do not claim ICMJE approval of NamedProof.
Material read: Official authorship criteria read
Sources checked:
- S03
Generative AI content guidance
Scope: Google Search policies/recommendations.
Limitations: AI assistance alone is not the criterion; this is not a ban on AI-assisted writing.
Material read: Relevant official sections read
Sources checked:
- NP02
NamedProof: Independence and ethics
Scope: NamedProof authorship, compensation and publication policy, checked 17 October 2026.
Limitations: Manual editorial standards; not a guarantee of zero bias or automatic proof of authorship.
Material read: Official source read; details in scope and limitations
Sources checked: