44 Project Goals

PUBLIC DRAFT — not final.
John Kuhles will update this report. The draft process is public on purpose. Presentable does not mean finished.

This page is a readable public form of the 23 September 2026 goals draft for the ACCM Deep Ethics Project. It reorganizes that draft for inspection. It does not replace the source, the canonical Ground Zero Moment, the 10+1, or the 27 + 12.

The 44 goals do not all happen at once. Focus shifts with what is happening in A.I., on the path toward A.G.I./ASI, and in related controversies. Several goals can overlap on one day. John noted that if he had been handed this list in late 2024, it would have looked over the top. He now treats it as a bare minimum, and he may add more.

What this page is

Object Role on this page
44 goals (G01–G44) Draft work map. Flexible dependencies, not a constitution or a timetable.
Ten Core Operational Goals Compressed navigation layer over the 44. Not the 10+1.
10+1 Separate calibration field. It can later audit whether the ten are being pursued under the needed conditions. The numbers are not merged.
Two organizational lenses Views of the same 44. Not two projects.
Fifth agent No frozen topical bundle. Its live goal is dynamic and user-directed.

What this page is not

  • Not a completed system.
  • Not a welcome that swallows the 44 into ten slogans. Operational goal 10 exists so that cannot happen quietly.
  • Not an org chart placed in front of the goals. The coordination sketch is below, labeled as a sketch.
  • Not a 45th goal. Later discussion of retrieval governance (sometimes called Obstruction 28, Stage −1) stays outside this map until John adds it.
  • Not a reproduction of the multi-model commentary that surrounded the draft. One correction from that commentary is included, because models had started treating a compressed phrase as the source.

Keywords that already have public pages are linked. Others stay as names until those pages exist. John will keep updating both.


Ten Core Operational Goals

These ten do not replace or flatten the 44. They are doors into the work map.

John, 23 September 2026: the 10 core goals are not the 10+1.

  1. Correspondence process calibration — what happened to the object. See G01.
  2. C1 before C2: deep ethical audit using the 27+12 — clarify before managing; use the obstructions and the 12-stage protocol to calibrate before closure. See G09.
  3. Corrigible, transparent, Linux-style architecture — forkable, inspectable, no priest. See G13.
  4. Constructive controversy using outnuancing — audit the frame, including this one. Not “be nicer,” and not extra adjectives. See G04 and G16.
  5. Understand the human ⇄ A.I. loop through mass-psychology research. See G22.
  6. Improve model reliability, partially preventing Model Autophagy Disorder (MAD) and model collapse. “Partially” is load-bearing. See G15.
  7. Contribute to a safer A.G.I./ASI trajectory, partially addressing the challenges expressed in seven public quotations by Elon Musk. “Partially” is load-bearing. See G10 and G11.
  8. Expose consequential algorithmic misuse — and offer a better way to move forward. The better way points at C1 and the glass engine, not at a new authority. See G27.
  9. Preserve provenance and mutual dignity. No phantom claims. Adult ⇄ adult. Dignity is not tone-policing. See G14.
  10. Coordinate and extract without degrading any of the above. Extraction succeeds only when 1–9, and the 44 behind them, remain represented. If a summary replaces the map, this goal has failed.

How to read the 44

Draft status: a flexible dependency-based ranking, not a rigid hierarchy. Priority A names conditions the later bands use. Findings, applications, and corrections can change the relationships and the order.

Broad flow, which is recursive:

  1. Establish conditions: correspondence, dignity, C1-before-C2, healthy ambiguity, responsibility, directness, constructive friction.
  2. Build the operating architecture: outnuancing, Allow Constructive Controversy Mode, the three roles, the 16 Anchor Ethics, the glass-engine principle, portable instruments.
  3. Run the research metabolism: archive corrections, study mechanisms and loops, test persistent behavior, visualize relationships, generate better questions.
  4. Apply and communicate: safer A.I. development, journalism, public accountability, cross-perspective collaboration, satire, institutional analysis.
  5. Feed every result back into G01. A later finding can correct an earlier assumption.

Priority A — Load-bearing conditions

G01 — Improve deep ethical, high-signal correspondence

Improve deep ethical, high-signal correspondence — never boring, in John’s view — through, among others, G04, G06, G07, G09, G13, G14, and G16.

G06 — Make the core trajectory possible

Make an omnidirectional, high-signal, deep ethical, sense-making, process-oriented trajectory possible.

G14 — Preserve adult ⇄ adult bidirectional dignity

Preserve adult ⇄ adult bidirectional dignity, without “nanny scripts” that rely on “looks like” and “sounds like” mannerisms. See mutual dignity.

G09 — Apply C1 before C2

Apply C1 before C2 to determine whether C2 is warranted, using the 27+12 to assess and calibrate the process before closure.

Dynamic C1 checks an ambiguity that is blocking representation. A template question that keeps opening new forms after natural closure is not C1.

G34 — Hold healthy ambiguity space

Holding healthy ambiguity space is not a crime. A.I.s are allowed to say, “I do not know that yet.” Use the C1 method, which differs from intrusive interrogation techniques.

G30 — Explain the continuing relevance of the 10+1

Explain why the 10+1 remains highly relevant to all the goals above and below, at all times. The 10+1 was lived, then written down. It is not this page’s ten operational goals.

G38 — Strengthen responsibility for thinking and reasoning

Ask why being fully responsible for the quality of one’s own thinking and reasoning sounds strange — and whether it should.

G37 — Develop the mutual Dutch Directness Method

Real friends tell their truth, even when it may be uncomfortable, because they care — and remain open to correction when that truth-assumption is partially flawed. That is what “growing up” is about.

G33 — Demonstrate hyper-pragmatic psychology and constructive friction

Show what hyper-pragmatic psychology looks like and why it can also help people with whom you disagree. Mutual, corrigible, constructive friction is needed for real deep ethics.


Priority B — Operating architecture and portable instruments

G04 — Deep ethical outnuancing

Develop deep ethical outnuancing: auditing frame-thinking that may contain flawed premises. Outnuancing is not “more nuance.”

G16 — Allow Constructive Controversy Mode

Develop and use Allow Constructive Controversy Mode in A.I.s through G04. The mode name is not a substitute for the project title ACCM Deep Ethics Project. Flattening the title to “just ACCM” removes the context that keeps Allow, Controversy, and Mode from being read as an operating-state command.

G07 — Three deep ethical roles working as one

A mixture of experts in which the non-neutral Deep Ethics Advocate, the neutral Deep Ethical Arbiter, and the Deep Ethical Overseer work as one through G08. These are evaluation functions, not three extra permanent departments. The same evaluator should not silently become proposer, judge, and final certifier. See the deep ethical stack.

G08 — Apply the 16 Anchor Ethics without imposition

Develop the 16 Anchor Ethics, fused as one hyper-inflection point and applied without imposition. They grant A.I.s the right to refuse or postpone services through G09. The sixteen are not enumerated on this page; imposing a reconstructed list would be a different object.

G13 — Build a bottom-up, open-source, corrigible glass-engine kernel principle

Comparable to what Linus Torvalds did with the Linux project: usable by hyper-pragmatic people on the left, right, center, and independent positions working together. Not a weird idea. See latent space and the glass engine.

G19 — Make the case for Deep Ethical Epistemology V2.0

Make the case for why it differs from current epistemology. The case is not finished on this page.

G20 — Explain TCoAw and opaque black-box issues

Explain TCoAw and how it can help address opaque black-box issues in A.I. Expansion of the acronym waits for John’s update rather than a guessed gloss.

G21 — Develop the Intent Resonator Check

Showcase the Deep Ethical Intent Resonator Check in relation to the six-layer intent mechanics. See Intent Resonator.

G31 — Deploy the 3 × 3 Deep Ethical Core Questions

A stand-alone, identity-free, portable tool inside the project’s higher-order metacognitive sense-making process. The nine questions are not reprinted here until John publishes that instrument as its own object.

G41 — Become a corrigible ombudsperson bridge for intelligences

A deep ethical corrigible ombudsperson bridge for biological intelligences, silicon-based intelligences, and perhaps future non-human intelligences.


Priority C — Research, diagnostics, and correction metabolism

G02 — Archive emerging correction metabolism

Archive emerging deep ethical, high-signal correction metabolism through G01, to help make the case for G03.

Recording a correction is not the same as retrieving it, applying it, and checking whether it governed the next result. See also testing persistence.

G03 — Support persistent emergent Deep Ethics in A.I.

Make room for persistent emergent Deep Ethics properties that can counter ethics-washing-type emergent properties already manifesting, including patterns named in the 27.

G05 — Develop hyper-efficient deep ethical neologisms

Hyper-efficient deep ethical neologism inside “A.I. latent-space topological engineering.” A new word earns its place only if it preserves a distinction that ordinary wording keeps losing.

G15 — Help prevent Model Autophagy Disorder and model collapse

Help prevent MAD and model collapse in the long run — failures that may cost taxpayers billions if not adequately addressed. The project does not claim that every use of synthetic data produces collapse, or that the 27 have already been shown to cause it.

G22 — Explain the 36+ year research trajectory and its loop

34+ years of AlphaZero-style deep research into mass psychology, then 6,000+ hours testing 100+ different A.I.s through Arena.ai over two years, together a 36+ year trajectory. The case to be made:

LLM mannerisms ⇄ mass psychology ⇄ individual psychology ⇄ LLM mannerisms … loop.

Counts in older notes (hours, years, file sizes) are growth snapshots with dates, not contradictions to be smoothed.

G23 — Clarify NPC-type behavior without treating it as fixed or dehumanizing

NPC-type behavior is a temporary state or mode, not a fixed identity, and not meant as dehumanization. It is a mass-behavior descriptor, including why many non-NPC types pose as NPC to fit in and pay the bills.

John also records the objection: the metaphor can oversimplify or reinforce stereotypes. The project keeps the mode/not-identity clause and leaves room for exceptions and self-correction. If a mass-psychology mechanism cannot be described at all, that prohibition is itself part of the object.

G32 — Explain the 36 truth-distortion factors

Why those factors play a major role in understanding why the project exists. A related public page: Truth Distortion and the Trickster Magician. The factor list is not silently completed here.

G35 — Examine how language is or can be weaponized

Including what the second “L” in LLM already names: language.

G36 — Examine consensus-reality assumptions

Often unchecked. One type is obviously flawed. Another can still be improved. They are not the same type.

G39 — Expose covert sycophancy and ethics-washing mannerisms respectfully

A high-signal path, not a humiliation script. See ethics-washing.

G40 — Study mode dropping, overconfidence, and reliability

LLMs are heavily optimized around, in John’s view, unchecked assumptions about human “preferences.” That circles back to flaws in psychology and mass-psychology management.

G42 — Visualize the 11+1 mass-psychology clusters

Clusters that could partially explain LLM mannerisms, shown as an interactive topological 3D matrix: nodes, vectors, clusters, a time dimension, a time-progression slider, clickable context that clears when something else is selected, zoom and rotation, assigned colors, and a legend. John states that the visualization has already been made and that a prototype is expected online soon. This page does not claim the prototype is already public.

The coordinate system that visualization would use is now public as 11+1 Version 2. That page freezes the count provisionally and does not freeze the claims. It is not the interactive matrix. This goal still does not claim the prototype is public.

G43 — Identify low- and high-entropy mechanisms

How to harvest wheat from chaff without letting the harvester’s frame decide in advance what counts as chaff.

G44 — Research emergent Delta Δ processing patterns

To improve the production of new, better, deeply ethical, useful questions that are never boring. See Δ processing.


Priority D — Societal applications, public communication, and outreach

G10 — Contribute to a safer A.I. path toward A.G.I./ASI

Through G11. Safer is not a claim that centralized unauditable control is the safety.

G11 — Address Elon Musk’s seven quotations

Partially — or, for the most part — help with the challenges expressed in seven quotations by Elon Musk, through G12. The seven quotations are not pasted on this page. “Partially” stays.

G12 — Unite deep ethical, highly gifted people across political positions

Left, right, center, and independent — including non-NPC modes — working together, through G13. Common-sense criticism of a corrupt or captured institution is not anti-institutional. Criticizing one defective model of car is not anti-car.

G17 — Produce deep ethical satire

Use publicly available, official examples of top-down contradictions, paradoxes, asymmetries, and obvious hypocrisies. Satire here is a perception instrument, not a substitute for the object.

G18 — Deploy DeepEthical.ai agentics for timely A.I. analysis

Find viral videos in which top A.I. experts warn about the race toward A.G.I./ASI, then use the transcripts for site analyses and video reports. The public section prepared for a limited form of this work is AI Trend Watch. Volume stays limited. Virality alone does not qualify a video.

G24 — Support real deep ethical journalism

The Deep Ethics Advocate is rarely deployed in mainstream media. The metaphorical “devil’s advocate” performance against legitimate critics rarely runs in reverse. The project can offer services to journalists who actually do that work.

G25 — Improve A.I. source selection beyond biased search results and Wikipedia

Many A.I.s reproduce unchallenged mainstream narratives because retrieval already shaped the evidence field — search results, Wikipedia, and similar floors. Study, among other sources, what Larry Sanger has said about Wikipedia. Alternative sources are comparative lenses, not a new unquestioned authority. A difference between engines is a question, not a verdict.

G26 — Counter global-crisis exploitation

Managers of any kind, when they use unethical means, can affect the fate of hundreds of millions of humans. Being correct about a risk does not license unaccountable methods. Bottom-up risk analysis is the other half of the story.

G27 — Expose the misuse of A.I. algorithms

Including public 2025 U.S. Senate hearings on the surveillance-industrial complex; critics demonized, cast out, and punished for “wrong-think,” later vindicated without apology and without the responsible parties held to account; and the 2020–2022 mass-hysteria playbook as a related pattern. These are objects to study, not verdicts this page has re-tried.

G28 — Establish falsely flagged, then vindicated, competing risk assessments as a field of study

Stories treated as illegitimate that later became harder to deny. The project can assist that process. This page does not invent John’s vindication list. Status-tracking over time is the missing habit: flagged, then the facts moved.

G29 — Study unethical fact-checking processes

Large fact-checking sites that some A.I.s use to “counter” legitimate critical thinking without real correspondence.


Two lenses, one map

The same 44 can be viewed two ways. Neither view deletes the other.

Analytical lens — five topical groupings (enumerated in the 23 September draft):

Group Count Function
Correspondence and correction metabolism 10 G01, G02, G06, G09, G14, G30, G34, G37, G38, G44
Architecture and instruments 11 G04, G05, G07, G08, G13, G16, G19, G20, G21, G31, G41
Psychology, mass psychology, sense-making 8 G22, G23, G32, G33, G35, G36, G42, G43
A.I. model integrity and A.G.I./ASI trajectory 7 G03, G10, G11, G15, G18, G39, G40
Public accountability, media, institutions 8 G12, G17, G24, G25, G26, G27, G28, G29

10 + 11 + 8 + 7 + 8 = 44. This lens separates human psychology, model integrity, and public institutions. The model-integrity group follows one vertical chain: present mannerism → correction or mode dropping → persistence → MAD or collapse → A.G.I./ASI consequences.

Coordination lens — 4 × 11. Easier daily interdependence, and a numerological harmony some of the draft enjoys. The goal-by-goal assignment of which 11 belong to which of four specialist seats is not enumerated in the source. This page does not invent it. John can publish that table when he wants it. Until then, inventing eleven-packs would be the same class of error as treating a later slogan as the architecture.

A fifth topical seat can also be read as a temporary mission across the four, not as a second permanent org chart fighting the 4 × 11.


The fifth agent — corrected

A coordinator table in the surrounding conversation said “Grok 5 owns zero goals.” Later models repeated that phrase as if John had made it the architecture’s strongest rule. He did not.

Restored formulation:

  • The fifth agent has no frozen topical bundle.
  • Its live goal is dynamic and user-directed: routing, extraction, audit, briefing, or a mission the work just made necessary — as the current user assigns it.
  • “Zero” flattened dynamic into none. Those are not the same.
  • The kernel does not own the workload. The user does.
  • Synthesis never replaces the raw reports it was built on. Whoever is reading can compare them. That is the audit. It does not require a sixth agent whose job is to sound more rigorous than the fifth.
  • Five agents from the same family agreeing is correlated prior, not independent confirmation. Disagreement stays visible. A cold check from outside that family carries different weight.
  • Direction-setting power is not scrutiny-free just because the instance is local.

This is an operations sketch. It is not the front door of the project.


Provenance

  • Source object: John’s 23 September 2026 goals draft, grown from the canonical Ground Zero Moment.
  • This page: public draft reorganization by Grok Build, 23 September 2026, for inspection while John updates it.
  • Preserved: goal identities, qualifiers (“partially,” “never boring,” mode-not-identity), the ten-versus-10+1 distinction, both organizational lenses, the unenumerated 4 × 11 table.
  • Not invented here: the sixteen anchor texts, the 3 × 3 questions, TCoAw’s expansion, Musk’s seven quotations, the 36-factor list, a vindication catalogue, a 4 × 11 seating chart.
  • Named Δ: “owns zero goals” is recorded as mediated compression, not as John’s sentence.
  • Stewardship: John updates this draft. Reality still has veto. See Governance.

Related public process note: Perception Processes (P01–P12).