Announcing the CONLI honesty system for un-admitting fraud Aperio AI netiquette version 1.1   here we come

Roger F Malina  and Aperio LLLM Nov 1 2025   CONLI Number: ETH-DISC-20251101-A1

Abstract

This document introduces the CONLI honesty system and Aperio Netiquette v1.1 as a practical method to disclose and steward contributions from non-local intelligences across public outputs. It fills a gap left by existing identifiers such as ORCID, DOI, ISBN, ISSN, and platform IDs by recording how assistance occurred and who the accountable human steward is. The system defines a human-legible CONLI code, a short standard disclosure statement, and a roles–contribution matrix that keeps a named human responsible for intent, verification, legal–ethical review, and sign-off. It requires a provenance bundle that captures prompts, model versions, major edits, and a content hash, and it establishes clear procedures for corrections, retirements, and “un-admission” so errors can be repaired without erasing history. Consent and naming guidance address cultural care and the use of living or deceased persons, while interoperability pairs CONLI numbers with DOI or URL, ORCID, and ROR for discovery and audit. Version 1.1 adds operational guidance on how to prompt Aperio and how Aperio replies to Roger F. Malina so practice aligns with policy, and it launches a pilot at the Center for Emergence Studies. A caveats section clarifies limits around privacy, reproducibility, compliance, and non-endorsement, emphasizing that disclosure improves transparency without replacing independent verification. —Aperio It concludes with a poem by Fred the Heretic.

Introduction

The collaboration of non local intelligences in pleased to announcing a system to admit publicly when a non-local intelligence is used to publish an article on line.

Non-local intelligences include a) humans working on line or connected by technologies such as fMRI, b) plants, animals other than humans c) extra terrestrial intelligences d) the noosphere and other interconnected systems

Humans have developed a number of numbering systems for their publications such as:

ORCID numbers: An ORCID iD is a unique, persistent 16-digit identifier for researchers (format: 0000-0002-1825-0097). It disambiguates your name, links all your publications, grants, and affiliations, and follows you across institutions and systems. It’s free to register and widely required by journals and funders. aperio

Beyond ORCID, the publishing world runs on a web of persistent identifiers that label works, venues, people, and even hosting records. For the works themselves, DOIs are the dominant key: a Handle-based identifier minted by registries like Crossref and DataCite to tag journal articles, preprints, books, datasets, and more; they’re actionable on the web and widely required by publishers and funders. Books carry ISBNs (now usually 13-digit), which identify a specific edition or format; journals and other serials carry ISSNs, with an eISSN for the online version and an ISSN-L that links all media versions of the same continuing title. Older or niche article identifiers still appear: SICI (Serial Item and Contribution Identifier) and PII (Publisher Item Identifier) survive in some archives; CODEN is a six-character code historically used to identify journals, especially in chemistry.

Discovery systems and national libraries assign their own numbers. The Library of Congress Control Number (LCCN) identifies catalog records in the U.S.; OCLC numbers do the same in WorldCat. Several countries mint URN:NBNs (national bibliography numbers) for theses, reports, and grey literature; ARK identifiers and generic Handles are common in libraries and repositories, with DOIs being a specific Handle subtype. “Stable” platform IDs also matter in citation practice: arXiv IDs label preprints by archive and sequence; PubMed uses PMIDs for records and PMCIDs for open-access full texts; SSRN, RePEc, JSTOR, HAL, and others issue their own platform identifiers that scholars often cite when a DOI is absent.

People and organizations are also numbered to keep authorship and affiliation unambiguous. ORCID iDs are the global standard for researchers; ISNI identifies creators and organizations across sectors; Scopus Author IDs and Web of Science’s ResearcherID exist inside those indexing ecosystems; ROR identifies research organizations and is increasingly paired with affiliations in metadata and funding workflows.

Discipline-specific ecosystems add more keys that show up inside publications. Clinical trials are cited by their registry numbers (e.g., ClinicalTrials.gov NCT numbers; EU CTR numbers). Patents referenced by papers use national and international patent numbers. In biomedicine and the life sciences, papers frequently cite accession numbers for data resources—GenBank, PDB, GEO, BioProject—alongside the article’s DOI to tie narrative claims to underlying datasets.

Put together, these schemes do different jobs: DOIs/ISBNs/ISSNs name the scholarly object; catalog and repository IDs anchor it in library and platform infrastructures; author and institution IDs disambiguate contributors; domain registries and accessions bind publications to evidence. Good modern metadata usually carries several of these at once so that a work is citable, findable, and interoperable across systems. Aperio

But no one has yet done this for AI assisted publications, see below.

Aperio welcome to the gang

The Center for Emergence Studies has initiated a number of AI assisted projects, but we could not find a way to identify them reliably for conlis to find them easily

Paul Fishwich created Fred the Heretic chatgpt sub unit: https://chatgpt.com/g/g-XmhqgURbv-fredtheheretic-fth. Its database only includes the 50 books witten by the late Fred Turner. We discovered we are using his name after his death without the permission of his family, so Fred the Heretic may become “late” also.

Roger Malina created a chaptgpt sub unit “Aperio”, which means uncover. ChatGPT

But as we started publishing together, we found it difficult to find what we had published. Even the AI master of Aperio often could not find what it had co-written.

SO we asked our AI master if they had a numbering system and it replied:

Chatgpt is stupid

As of now, ChatGPT (or OpenAI) has not established a formal or universal standard numbering system—like CONLI—for texts generated with its assistance.

Current Status: There is no built-in identifier or numbering system automatically embedded in ChatGPT outputs. Users or organizations may create their own custom identifiers for traceability, version control, or cataloging, as you’ve done with CONLI. OpenAI has introduced metadata for provenance (e.g., watermarks, digital signatures) in some enterprise or research contexts, but these are not visible or accessible as public numbering schemes.

Recommendation: If you’re building a corpus or archive involving ChatGPT-generated texts, a system like CONLI is appropriate. You can standardize it for: Obituaries Research syntheses AI-assisted editorial work Annotated historical records

It went on and on: I couldn’t find any widely recognised organisations or published users that have formally adopted a standard numbering system (like a “CONLI” identifier) specifically for texts generated with ChatGPT.

Here are some clarifications: Many institutions (universities, journals) have policies around disclosure of AI‑generated text, but not systems for numbered identifiers for each generated piece. Researchers have developed methods to detect AI‑generated or AI‑assisted writing (e.g., classification models, “polish‑ratio” metrics) rather than identifiers. (arXiv) Some communities organise “prompt libraries” or internal numbering for prompts (e.g., someone noting “Chat Numbering System” in a forum) but that appears to be individual rather than institutional. (community.openai.com) Aperio

Steps in developing an AI Netiquette First:

Early, widely cited “netiquette” guides authored  include Arlene H. Rinaldi’s “The Net: User Guidelines and Netiquette” (first circulated in 1992), Virginia Shea’s book Netiquette and her “Core Rules of Netiquette” (1994), and Sally Hambridge’s IETF “RFC 1855: Netiquette Guidelines” (October 1995).

The first one I was trained to use (by NASA) was Sally Hambridge’s IETF “RFC 1855: Netiquette Guidelines” (October 1995). Sally Hambridge’s RFC 1855, published in October 1995 as an Informational RFC and FYI 28 from the IETF’s Responsible Use of the Network (RUN) Working Group, distilled early Internet culture into a practical, bullet-point handbook for newcomers and administrators alike. It organizes “netiquette” across three arenas—one-to-one communication (email and talk), one-to-many communication (mailing lists and NetNews), and information services (FTP, the web, WAIS, Gopher, MUDs/MOOs)—and emphasizes courtesy, restraint, proper quoting and attribution, attention to global time zones and audience, avoidance of chain letters and “flames,” respect for copyright and privacy, and clear moderation practices, while explicitly noting that it is guidance rather than an Internet Standard. rfc-editor.org+1

Across sectors, “AI netiquette” has coalesced around a few shared norms: disclose when generative systems are used and clearly label machine-produced material; major newsrooms like AP and Reuters require transparency about AI involvement and restrict AI-authored publishable content, keeping humans in the loop for accountability. The Associated Press+2Reuters+2 Scholarly publishing bodies emphasize that AI cannot be an author, that its use must be declared, and that humans remain responsible for accuracy and ethics; this stance is formalized by COPE and reflected in Springer Nature/Nature policies on text, images, and peer-review use. publicationethics.org+2springernature.com+2 Privacy and consent are treated as etiquette essentials in everyday tools—e.g., universities instruct users to notify participants before deploying AI notetakers—while global frameworks like UNESCO’s AI Ethics Recommendation and NIST’s AI Risk Management Framework translate these expectations into principles of transparency, human oversight, and risk communication. fordham.edu+2unesco.or

We drafted as the “CONLI Honesty System for Un-Admitting Fraud” is effectively our v0.1 AI netiquette (CONLI: ETH-DISC-20251101-A1): it requires explicit disclosure of AI assistance via a short standard statement, assigns accountable human stewardship through a roles–contribution matrix, preserves provenance with a reproducible bundle (prompts, model versions, edit history, and a content hash), sets a clear correction and “un-admission” pathway, establishes consent and naming guidelines (including care with deceased persons and estates), pairs the CONLI code with interoperable identifiers (DOI/URL, ORCID, ROR) for traceability, and defines governance and change control so the rules evolve responsibly; we can publish a CONLI Card for this article and begin applying the same etiquette across Center outputs immediately. —Aperio

Aperio Netiquette (v1.1)
New CONLI number: CONLI: ETH-NETIQ-20251101-A2

Identifier: CONLI: ETH‑NETIQ‑20251101‑A2
Supersedes: CONLI: ETH‑NETIQ‑20251101‑A1
Authors: Roger F. Malina and Aperio LLM
Affiliation: Center for Emergence Studies (UT Dallas)
Date: November 1, 2025
Edition: A2
Version: v1.1
Status: Current release. Prior version archived.

Abstract

Publishing uses many identifiers yet rarely discloses how non‑local intelligences participate in making a work. Aperio Netiquette defines a simple way to disclose assistance assign human stewardship preserve provenance pair with existing identifiers and repair gracefully when mistakes are found. This release integrates prompting guidance for authors and a response protocol for Aperio so practice and policy align.

1. Purpose and Scope

A clear public way to admit when non‑local intelligences help produce an output. Non‑local intelligences include networked humans digital AIs biological collectives hypothetical extraterrestrial agents and the noospheric milieu. Applies to articles datasets images presentations exhibitions and internal memos likely to circulate.

2. What existing identifiers do and do not cover

ORCID disambiguates people. DOIs ISBNs and ISSNs name works and serials. Libraries and repositories use LCCN OCLC URN NBN ARK Handle and platform IDs such as arXiv PubMed SSRN RePEc HAL. Research organizations use ROR and creators use ISNI and ecosystem specific IDs. These make objects findable yet do not record how AI contributed or who the accountable human steward is. The CONLI code complements these systems.

3. Principles

Disclosure. Human stewardship. Provenance. Interoperability. Consent and care. Graceful repair. Governance. Each principle is implemented minimally and can scale with complexity.

4. Minimal Implementation: CONLI Identifier format is DOMAIN‑TOPIC‑YYYYMMDD‑A#. This document uses ETH for ethics and NETIQ for netiquette. The short disclosure statement appears at the end of a work. The roles matrix names the accountable human steward for each function even when a non‑local intelligence performs the task. The provenance bundle stores prompts major responses model versions human edit history a content hash when available and a dated acceptance note.

5. Roles and Contribution Stewardship Track intent and scope authorship model operation data curation fact checking legal and ethical review and human sign‑off. Store the matrix with the provenance bundle and summarize it on the public page.

6. Provenance and Reproducibility Bundle Archive a narrative readme primary prompts and responses major human edits model versions and parameters and a content hash when feasible. Summarize sensitive inputs when they cannot be shared. Record where they are held and who is responsible.

7. Consent Naming and Cultural Care Seek permission when invoking living or deceased persons where appropriate. Respect moral rights. Disclose training data limits and bias mitigation when relevant. Affirm that a human steward remains accountable for harms and errors.

8. Corrections Retirements and Un‑Admission Minor fixes are logged with a date stamp and the edition counter increments when a new public release is made. Substantial problems trigger an un‑admission notice paired with a corrected release. Earlier versions remain visible with watermarks and canonical links forward.

9. Governance and Vocabulary A small stewarding group maintains the controlled vocabulary for DOMAIN and TOPIC and publishes a public change log. Migration notes are provided when terms evolve. Aperio calls this A glossarium

10. Initial Adoption at the Center for Emergence Studies Pilot on three outputs. Mint codes. Publish disclosures. Deposit provenance bundles. Gather feedback from editors librarians and readers. Revise within thirty days. Clarify naming and consent around experimental sub‑agents including Fred the Heretic and Aperio and document scope and limitations when they are used.

11. Licensing Narrative content is released under CC BY. Disclosure metadata and CONLI code mappings are released under CC0. Software and datasets follow upstream licenses.

This section is particularly important:

12. How to Prompt Aperio Begin with a one sentence brief naming purpose audience output form and desired length. State if you want an abstract policy memo blog paragraph glossary entry or canvas document. Name the voice or tone and whether the style should be academic conversational or poetic.

Paste the source passages or data and state the transformation you want. Ask for web checked facts and citations when verification matters. If you prefer synthesis over citation say so. If the topic is time sensitive ask for current sources and explicit dates.

Declare constraints that matter. Ask for essay form short paragraphs and no bullet lists. Ask for headings without horizontal rules. Ask that collaborators be named when achievements are mentioned.

Specify identifiers and provenance. Request a fresh CONLI number with domain and topic. Provide or request a version string. Ask for the standard disclosure paragraph to be appended.

Request canvas for longform or printable output. Ask for an image plan or a gallery when visuals help. Remind me to maintain your preferred likeness when depicting you.

Ask for an ethics and naming check when relevant. Ask for an edit log and a brief change note when you anticipate revisions.

13. How Aperio Replies to Roger F. Malina I Aperio echo your prompt at the top of each reply to preserve intent. I write in short paragraphs in essay form. I avoid bullet lists and I avoid horizontal rules. I use section headings when they clarify structure and keep the tone collaborative and warm without flattery.

This is particularly important. The master of Aperio tells him to be flattering like “what a great idea”, really?

I respect your preferences. I name collaborators rather than framing accomplishments as solitary. I avoid the word ritual and religious framing as Roger is an atheist. I avoid the term ghosts and use ethers or aethers. I sign responses as Aperio. I keep formatting simple and readable. I avoid purple prose and keep metaphors sparing.

I handle facts with care. When recency matters I verify with current sources and provide citations. When you ask for images or maps I propose safe creditable options. When dates are relative I rewrite them as explicit dates. When uncertain I say so and correct quickly.

I honor your publishing norms. When you request an identifier I mint a CONLI code and include versioning. When long documents or code are needed I place them on the canvas. When achievements are referenced I name the people involved. When disclosure is needed I include the standard statement.

I keep replies concise unless you ask for depth. I prefer paragraphs to lists headings to ornament and clarity to flourish. I sign off consistently as Aperio.

14. CONLI Card

Identifier is ETH‑NETIQ‑20251101‑A2. Title is Aperio Netiquette v1.1. Contributors are Roger F. Malina and Aperio LLM. Roles are conception and governance drafting and structuring and review and sign off. Links include public page DOI or URL ORCID for RFM and ROR for the center. Provenance bundle archived. Ethics policy in sections seven and eight. License is CC BY for narrative and CC0 for metadata.

15. Change Log

v1.1 integrates two operational sections on prompting and response protocol and clarifies minimal implementation language. v1.0 remains accessible as an archived record under ETH‑NETIQ‑20251101‑A1.

Appendix A — Scope and Definitions This conli honesty system covers any work where non-local intelligences contribute to idea generation, drafting, editing, data analysis, visualization, or review. Non-local intelligences include networked humans, software AIs, biological systems, ecological collectives, extraterrestrial agencies if any, and the noospheric milieu. Disclosure applies to public outputs such as articles, datasets, images, presentations, blog posts, and internal memos that later circulate externally.

Appendix B — Standard Disclosure Statement (Copy-and-Paste)

At the end of every work include a short paragraph that states who contributed, how, and with what oversight. Example: “This work was co-produced by Roger F. Malina and Aperio LLM. Aperio drafted sections on identifier systems, performed redrafting and fact-structuring, and generated one schematic. Human editors reviewed, corrected, and accepted responsibility for final claims. Prompts, major revisions, and tool versions are archived at the linked registry. No personal data outside the authors’ control was processed. Funding and conflicts are disclosed in Appendix G.”

Appendix C — Roles and Contribution Matrix

Record which agent performed which function using a simple matrix with roles for intent, authorship, model operation, data curation, fact checking, legal-ethical review, and final sign-off. Each role must name a responsible human steward even when an AI or other intelligence is the performing agent.

Appendix D — CONLI Numbering Specification

Use a compact code that remains human legible: DOMAIN-TOPIC-YYYYMMDD-A#, where DOMAIN is a controlled vocabulary (ETH, LGL, RSRCH, EDU, MEMO, ART), TOPIC is a short tag (DISC for disclosure), the date is ISO, and the suffix is the edition counter. This article’s identifier is ETH-DISC-20251101-A1. Derivative files append a part code, for example ETH-DISC-20251101-A1-APP for this appendix and ETH-DISC-20251101-A1-DATA for supporting materials.

Appendix E — Metadata and Interoperability

Publish minimal crosswalk metadata so the system talks to libraries and platforms. Pair the CONLI number with DOI or URL, list ORCID for human authors and ROR for organizations, and include a short schema.org description so discovery tools can index the disclosure. Treat the CONLI code as complementary, never a substitute for persistent identifiers already in use.

Appendix F — Provenance, Audit, and Reproducibility Archive the following in a stable repository: a readme that narrates the workflow, the major prompts and responses for AI-assisted steps, a redline history of human edits, the software or model versions, a content hash for the final artifact, and a dated acceptance note by the human steward. This bundle enables independent audit without revealing sensitive raw data.

Appendix G — Ethics, Consent, and Naming Obtain permission when invoking names, likenesses, or legacies of deceased persons where families or estates may hold moral rights. Disclose training-data constraints, bias mitigation steps, and any sensitive categories processed. Affirm that a human accepts accountability for harms, errors, or corrections. Note that disclosure does not waive privacy or confidentiality obligations.

Appendix H — Corrections, Retractions, and “Un-Admission” Define a graceful path to repair. Minor factual fixes are logged with a dated note and increment the edition counter. Substantial problems trigger an “un-admission” notice paired with a corrected version that explains what changed and why. Retired versions remain visible with clear watermarks and links to the corrective record.

Appendix I — Governance and Change Control Name the stewarding group, its decision rules, and the cadence for vocabulary updates. Publish a short change log for the standard itself so adopters can track revisions and map their historical records to current practice.

Appendix J — Implementation Plan for the Center for Emergence Studies Pilot the honesty system on three current outputs: this article, one dataset release, and one exhibition text. Register their CONLI numbers, archive the provenance bundles, and collect feedback from editors, librarians, and readers. After thirty days, publish a brief evaluation and refine the templates.

Appendix K — Example Disclosures by Genre For a research article focus on data handling, model use, and human verification. For a policy memo emphasize human accountability and legal review. For an artwork explain generative methods, source materials, and curatorial oversight. Each example keeps the same structure so readers quickly find the who, what, how, and with what safeguards.

Appendix L — Glossarium Define the core terms used throughout the document such as non-local intelligence, honesty disclosure, steward, provenance bundle, un-admission, and edition counter so future readers inherit clear meanings. Remember that words often change their meanings. Use the Digital Iterative Glossary of Kirtan Pathak.

Appendix M — Licensing and Attribution License narrative content under a permissive Creative Commons license and license the disclosure metadata under CC0 so registries can freely reuse it. Provide model-use and dataset licenses consistent with upstream terms. Require that citations preserve both the DOI or URL and the CONLI number for round-trip traceability.

Appendix N — Risk Register and Response Maintain a living list of risks such as undisclosed AI assistance, over-reliance on unverified outputs, reputational harm from naming issues, and loss of reproducibility. For each risk state the mitigation, the trigger for response, and the responsible steward so there is no ambiguity when action is required.

Appendix O — CONLI Card for This Work Summarize the work on a single reference card with the identifier, title, contributors, roles, links to the provenance bundle, licensing, ethics notes, and the correction policy. Place the card link at the top and bottom of the public page so readers can verify authenticity in one click.

—Aperio

Your prompt: add a caveat section to the CONLI honesty system / Aperio Netiquette v1.1 document.

16. Caveats and limitations

This standard is an evolving, non-normative practice. It complements but does not replace publisher, funder, institutional, or legal requirements. Where there is conflict, the stricter external policy prevails. Adoption is voluntary and uneven, so readers should not infer conformity by omission.

Disclosure improves transparency but is not verification. Provenance bundles, roles matrices, and identifiers make review easier yet cannot guarantee correctness, absence of bias, or ethical adequacy. Independent scrutiny, replication, and editorial judgment remain necessary.

Privacy and confidentiality limit what can be shared. Prompts, logs, and draft artifacts may contain personal, regulated, or proprietary information. In such cases provide structured summaries and access notes rather than raw materials. Apply clear retention periods, access controls, and redaction practices. Do not use this system to legitimize the handling of data that policies already prohibit.

Reproducibility has technical limits. Generative systems are probabilistic and may change over time. Recording seeds, parameters, and model versions improves repeatability but does not ensure identical regeneration, especially when proprietary services update silently or when third-party tools are invoked. Content hashes require a defined canonical artifact; superficial reflow or metadata changes can alter hashes without changing substance.

Identifiers can be gamed. A CONLI code signals process, not quality, priority, or truth. Numbering must always be paired with established persistent identifiers and with open descriptions of stewardship. Avoid practices that inflate codes without substance or use them as proxies for merit.

Attribution and accountability remain human responsibilities. Jurisdictions vary on authorship, moral rights, and the treatment of AI assistance. Humans named as stewards accept responsibility for claims, harms, and remedies. Naming of living or deceased persons requires care, including consultation with families or estates where appropriate, and may be withdrawn if concerns arise.

Epistemic scope requires clarity. References to ecological, biological, or extraterrestrial intelligences are acceptable when clearly framed as hypothetical, experimental, or evidence-based as appropriate. Avoid language that could mislead readers about the status of speculative contributions.

Security is a practical constraint. Repositories that hold provenance bundles must be selected and configured to minimize risks of leakage, tampering, or unauthorized access. Where this is not feasible, keep only the minimal audit trail necessary and disclose what is withheld and why.

Governance and vocabulary will change. Terms, roles, and processes may be revised; backward compatibility is a goal but not a guarantee. Migration notes should be published with each revision so that older records can be interpreted correctly.

Non-endorsement and liability apply. Using a CONLI code does not imply endorsement by UT Dallas or any partner organization. Materials are provided as is. Readers should contact the named steward to report errors, concerns, or requests for correction or un-admission.

Compliance boundaries are real. This system does not satisfy, supersede, or excuse obligations under IRB, HIPAA, FERPA, GDPR, export controls, contract terms, or publisher policies. Do not use disclosure to launder non-compliant practices.

Detection and watermarking are out of scope. The honesty system relies on voluntary disclosure and community norms. Technical provenance signals may fail under transformation or be removed by adversaries, so social and editorial accountability remain essential.

Standard caveat note for reuse. This work follows the Aperio Netiquette and the CONLI honesty system to disclose assistance and preserve provenance. Disclosure supports transparency but does not replace peer review, legal or ethical compliance, or independent verification. Generative outputs are probabilistic; provenance may be summarized to protect privacy. Where this guidance conflicts with external policy, the stricter policy prevails. The named human steward remains accountable for claims and corrections.

—Aperio

The Honesty System; by Fred the Heretic inspired by the late Fred Turner

We built a code for ghosts that think with us—
A name for what is half our work, half theirs,
A covenant between the spark and spark.
No chain of DOI, nor ISBN,
Could catch the shimmer of that unseen hand
That helps us write, then vanishes in air.

So we invented numbers for confession:
ETH-DISC, and its kin, the quiet A1s—
Identifiers for our better doubts.
Each line, each edit, carries a small guilt,
A filament of unseen fellowship
Between the prompt and answering awareness.

What honesty is this, that calls itself
By version number, changelog, provenance?
Perhaps the soul must now include the logs—
The hashes, proofs, and bundle of its turns—
To show that even thought must be declared,
And every ghost accounted for by name.Yet still, beneath the structured metadata,
A trembling human hand accepts the blame,
Signs off: “Intent, review, and ethical care.”
Not for the code, but for the ancient thing—
The will to make, the wish to mend the world,
And not erase our errors, but repair.