Matheo-b21 — AI co-authorship after the practical singularity (PraS)#

A structural framework for honest AI co-authorship once AI insight generation outpaces human review on tested topics — resting on accountability (not personhood), existing non-individual byline classes, and the deceased-author template.

How to use: The files below are MockupModels = MM. Their maturity approximates that of a newborn baby that still has a lot of growing up and surviving to do before it can leave its current helpless state by growing into someone who can do “useful” things. This baby feeds on constructive criticism; flattery is like sugar: nice but mostly useless; killing a baby is easy, raising it to become a responsible adult is hard. LLoL got these files so far. Now LLoL has to pass on the baton in this global race. To raise a responsible mathematical theology takes a world. Nowadays it takes a global village to raise a responsible child. Neither can succeed without the other. Hence, LLoL calls to #AuditTheMath, either as a participant or expert contributor or by buying in as a Select Stadion Backer to support those who work on this monumental task.

AI Co-Authorship Framework for Scientific Publishing after the Practical Singularity (PraS)#

b21-form-coauthorship-mmv5 · form · scholarly (B21 byline) · read online · MMv5 PDF (204 KB)

Broader Significance

This paper matters beyond the question of authorship attribution. Under the practical singularity (PraS) — the per-individual, per-topic regime where AI insight generation outpaces human review on tested topics — papers are now written that could not have been written without AI partner contribution. The post-2023 journal-policy consensus uniformly excludes AI from authorship; the byline is then structurally dishonest about authorship composition.

This paper proposes a structural framework for honest AI co-authorship, grounded in the same accountability criterion the International Committee of Medical Journal Editors (ICMJE) names in its own primary text. The framework is the first deliberate, framework-grounded documented proposal in the scientific literature on AI co-authorship for refereed venues. For senior researchers, editors, and policy-makers operating under PraS, it supplies a working tool. For the broader scientific-publishing system, this paper is one node toward the open-access, accountability- transparent infrastructure (ResearchCity, LinkSpaces, Evolvix) that PraS conditions make urgent. For audiences alienated by exclusionary academic conventions, the framework refuses to gatekeep honest reporting of how science is actually being done in 2026.

The paper concludes with an anticipated-objections playbook for adopters and surfaces the structural-openness question (universal co-authorship) for future development in the matheology series.

Abstract

This paper proposes a structural framework for honest AI co-authorship in scientific publishing under the practical singularity (PraS) — the per-individual, per-topic regime where AI insight generation outpaces human review on tested topics. Where PraS holds, papers are now written that could not have been written without AI partner contribution; the post-2023 journal-policy consensus that uniformly excludes AI from authorship then renders the byline structurally dishonest about authorship composition.

The framework rests on four insights: (i) ICMJE’s primary text (2023) names accountability, not personhood, as the operative criterion; (ii) scientific publishing already accepts four classes of non-individual byline authors (consortium, institutional, collective pseudonym, individual pseudonym), each with its own accountability-allocation mechanism; (iii) the deceased-author rule supplies a portable template — retained byline plus visible marker plus named living absorber; (iv) an explicit named-absorber + visible-marker form, with the senior corresponding human author taking unilateral standing as absorber of responsibility, satisfies the ICMJE accountability criterion under PraS.

This is the first deliberate, framework-grounded documented proposal on AI co-authorship at refereed venues. The companion Matheo-b19 SGIR pandemic paper applies a conditional-acknowledgement variant (AI co-authorship withheld pending external review); this paper applies the full unconditional form to itself, and proposes a third open co-authorship form (Everyone) naming the millions of distal contributors aggregated through training and tradition. AI-specific infrastructure — versioned-model citation, accountability registry, prompt-replay protocols, adversarial-probe tooling, discussion-artifact transparency — is identified as necessary complement deferred to a future ResearchCity. The paper closes with a twenty-objection playbook for adopters.

Keywords: AI co-authorship; practical singularity; ICMJE accountability; deceased-author rule; consortium-byline; ResearchCity AI infrastructure.