About & policies · Journal of Reproducible Statistics

AI use

last updated 2026-07-10

Many venues restrict undisclosed AI; audits keep finding secret AI-written reviews anyway. Our answer is to do openly and accountably what others do secretly: this journal uses AI in review, says so plainly, labels its output, and puts a named human's signature on every decision.

For authors

  • You may use AI tools — in research, analysis and writing. Used well, they improve papers.
  • Disclose the use. The submission form asks how AI was used (assistance, editing, content generation, none); generated content requires a short note on what and where. The disclosure appears in the published article.
  • A named human is accountable for every part. AI is never an author and cannot be one: authorship means approving the work and answering for it. Whatever a tool drafted, the listed authors have verified it and own it.
  • You are responsible for AI failure modes — above all fabricated references. Every reference in every submission is verified against the scholarly record, and submission requires an explicit attestation that the reference list is real and checked. A fabricated reference is treated as an integrity finding, not a typo (see publication ethics).

For the journal — our own AI use, disclosed

  • Submissions are assessed by an agentic AI pipeline under named-human sign-off, described step by step in the peer-review policy. AI use in review is never concealed from authors.
  • Every AI-generated review artifact is labelled as such, including the reviewer-panel reports, which are written by openly synthetic reviewer personas with visibly artificial names.
  • No decision is autonomous. A named human editor reads the assessment record and signs every accept, revision request and rejection. Authors can escalate any AI-influenced decision to an independent human through the appeals procedure.

Confidentiality of your manuscript

  • Manuscripts under review are processed through a commercial model API under a data processing agreement with EU standard contractual clauses: submissions are not used to train models and are deleted under contractual retention limits. We never run your manuscript through consumer AI apps.
  • Manuscript content is not persisted into the review system's configuration or memory; what is stored is the structured assessment record.
  • Sensitive data never touch a cloud model. Datasets handled under the journal's privacy-preserving data service are processed in a controlled environment only — see data & code availability.

Why AI at all

The pipeline is what makes the journal's promise affordable and universal: because assessment is fast, transparent and cheap, we can verify references on every submission and re-execute results before publication — checks most journals cannot staff. The AI is the proof behind the reproducibility promise, and the human signature is the accountability behind the AI.