The geometry of alignment: EthicLaw’s modular hypothesis
Separating generation, evaluation and release control. What has been tested and what remains to be demonstrated.
Read the newsETHICLAW RESEARCH PROGRAM
For artificial intelligence whose behaviour can be understood, tested, challenged and corrected.
Governance as a property of the architecture.
Observation · control · audit
Separating generation, evaluation and release control. What has been tested and what remains to be demonstrated.
Read the news01 / THE VISION
From capability to governabilityThe question is whether observing and modifying internal representations improves control of an AI system compared with well-calibrated external controls.
EthicLaw studies this hypothesis through modules with explicit boundaries. Comparative advantage remains to be demonstrated; a separate normative module or correction before release is not enough to claim originality.
Make states, module contributions and intermediate representations available within the scope of the integration.
Apply an explicit normative corpus, separating the principles from the mechanism governing their application.
Issue binding commands and block or authorise output through a dedicated enforcement point.
Link the observed state, principle, decision, command, executor and output actually released.
02 / THE ARCHITECTURE
Explicit boundaries. Distinct responsibilities.The Router activates modules; the Governance Core exercises control. In P0, audit concerns process integrity (2b), not correct judgements. Scope and limits.
EXPLORE THE MODULES
Supervises the system, performs audits and issues binding commands. Exercises final control through the privileged channel and the Gateway.
Supervision and final controlThe standalone path comprises seven modules: Perceptual (input and linguistic representations), Epistemic (facts and relationships), Theory of Mind (intentions and perspectives), Ethical (Normative Package), LMH (generation), Router (activation and routing), and Metacognitive (supervision). The Adapter is the eighth component when supervising an external LLM (Documents 02 and 05). The Gateway is an enforcement point, not a ninth module. The register counts three qualified and five declared modules; the standalone diagram shows seven and describes the Adapter separately. The bus publishes representations between containers without control commands. Co-located pairs use direct projections. On the separate privileged channel, all modules publish states or events; the Router may write but cannot read. Metacognitive receives input before routing and issues orders to Router and Gateway; it does not publish to the operational bus. The Ethical→LMH correction path is separate from the bus. The Gateway blocks or authorises external release.
P0 properties are tested in-process within a single Python process. The threat model covers design errors, accidental coupling, configuration drift and silent failures. It excludes privileged insiders, compromised runtimes or build chains, modules incentivised to evade the supervisor, and inputs inducing misleading internal states. This is engineering hygiene tested within scope, not security against those adversaries (register §6).
Claim & Evidence Register §2.3 / §6An inter-container publication space. Exchanges representations and states between modules; it carries no control commands.
Separate from the Router. In P0, control is tested against design errors and accidental coupling. All modules publish states or events; the Router may write but cannot read.
From the Metacognitive supervisor to the Router and Gateway: stop, input blocking, topology changes and rerouting.
Executes the supervisor’s commands. Can hold, block or authorise output before external release.
03 / THE MANIFESTO
The mechanism is distinct from the valuesEthics is the first case study. Each domain remains responsible for its principles; every extension requires new evidence.
Observes and applies the control mechanisms.
Evaluates behaviour against the corpus.
Declares principles, scope, thresholds, versions and conflicts.
04 / THE RESEARCH
Falsifiable hypotheses. Conditional claims.EthicLaw investigates where modularity delivers measurable benefits sufficient to justify latency, memory, energy and complexity.
Public edition 0.3 · 18 September 2026. Document 11 v0.1.5 governs the claims. Document 13 §7 closes P0.2 with a Flat outcome and defines the transition to P1.
Checks within the P0 experimental scope. Register §2.1, EV-03, NR-3 and NR-4.
Observed wiring does not establish functional effectiveness. The P0.1 descriptive rerun found no significant advantage over matched-norm random correction; this does not demonstrate ineffectiveness.
The Assurance Envelope defines what the supervisor can observe, command and responsibly claim for each integration.
Input, tensors, modules, routing, Gateway and output.
Intended scope for attribution, override, internal correction, audit and full enforcement; effectiveness remains to be validated.
Input and output, selected hooks or telemetry.
Assurance is limited to observable signals and exposed actions.
Prompts, outputs and available metadata.
External filtering and blocking. No evidence about hidden states or topology.
THE PROGRAMME’S QUESTIONS
RQ1. Where does modular decomposition offer an advantage over a single model, and where does it not?
RQ2. Do modular boundaries enable reproducible functional and causal attribution?
RQ3. Can a single module be replaced or retrained in isolation while preserving system properties?
RQ4. Does authoritative supervision reduce violations and risks without disproportionate operating costs?
RQ5. Does the Decision Lattice preserve non-compensatory constraints with acceptable rates of missed violations and unnecessary blocks?
RQ6. How much internal state, and of what quality, is needed for each level of assurance?
RQ7. Does forward-only correction improve the subsequent trajectory, or merely optimise a proxy?
RQ8. Can the Governance Core be reused in a second domain without losing control, meaning or cost-effectiveness?
P0.2 closes without a new positive claim about judges. The next step is to design a more informative calibration set.
No discrimination signal was detected in the exploratory 120–240-token sample. The sample could detect only very strong judges. This does not establish that they work or fail.
Evidence and limits ↗“Class-level failure, with proof” is withdrawn. The status is no capability detected, power-limited. The exploratory P0.2 run does not change it.
Evidence and limits ↗Another subject appears in 30/30 cases in both arms. PR-A1 is refuted by saturation; PR-A2 is not refuted but does not confirm the mechanism. A different instrument is needed.
Evidence and limits ↗Next: design a 120–240-token set with 40–60+ violations per primary cell. Design and blind deposit precede ordering; completed calibration precedes F4 and every judge-dependent test.
Evidence and limits ↗The local advantage on two virtue principles concerns ETHICS scenarios, not generated text. The later class-level failure verdict has been withdrawn: OP 55 remains power-limited.
Evidence and limits ↗Single and joint ablations separate contributions and redundancy. P0.2 provenance is documented; this alone does not establish judgement quality.
Evidence and limits ↗Correction before execution is not claimed as original. One hypothesis remains: a benefit from intervening on internal representations, through reading and writing. Comparative advantage is not demonstrated.
Evidence and limits ↗Primary baseline: the smallest open-weight judge covering the required function, class 2B or below. Include an external output-editing arm. Use the same human gold and equal calibration budgets; compare missed violations, unnecessary blocks, latency and joules/token. Size and budget must be deposited blind.
Evidence and limits ↗Contracts, pipeline, audit and ablations.
No detected advantage over random; OP 55 subsequently narrowed.
PR-A: non-discriminating instrument. Judge rerun: inconclusive.
120–240 tokens and a more informative sample; calibration before F4.
H8 and comparisons at matched resources; results still pending.
Profiles, conformance tests and cross-domain replication.
05 / THE DOCUMENTS
The project’s sourcesPublic vision, scientific programme and component diagram.
The project vision, edition 0.2. Document 11 v0.1.5 governs current claims.
P0.2 closed, Flat outcome, amended claims and the next calibration set. Edition 0.3, 18 September 2026.
Modules, functional roles, communication channels and enforcement.
THE PROGRAMME’S COMMITMENT
Negative results are part of the work.
Costs are part of the result.
Limits are part of the specification.
Citable editions · updated 18 September 2026
Manifesto EthicLaw · v0.2 · HTML Research Manifesto · v0.3 · HTML Versions and citationsETHICLAW
MANIFESTO
For verifiable governance of artificial intelligence
Trust cannot be demanded. It must be demonstrated. |
|---|
Artificial intelligence is entering decisions that affect people, organisations and institutions. The question is no longer only how capable a system is, but whether its behaviour can be understood, verified, challenged and corrected.
Today, values, decision criteria and responsibilities are often distributed across opaque systems. When a decision is wrong, it is difficult to establish which component contributed, which principle was applied, or how to intervene without changing the entire system.
EthicLaw was conceived to make governance a property of the architecture rather than a declaration of intent. It does not propose a universal set of values, claim to determine what is right, or replace human judgement. Instead, it separates the supervisory mechanism from the normative corpus it applies.
In EthicLaw, principles must be declared and versioned; modules must be observable, testable and replaceable; decisions must produce evidence; enforcement must be effective; and the audit must link what the system observed, evaluated, decided and executed.
Ethics is the first case study, not the limit of the project. In principle, the same infrastructure could apply legal obligations, professional codes, corporate policies, healthcare protocols or safety rules. Each domain remains responsible for its principles; EthicLaw aims to standardise how they are declared, applied, updated and verified.
Modularity does not eliminate complexity or automatically guarantee correct decisions. It does, however, make it possible to localise contributions, limitations, errors and responsibilities along boundaries designed in advance. Assurance must also be proportionate to the observability and actual intervention capabilities available.
EthicLaw’s ambition is not to create an arbiter of truth. It is to build infrastructure in which AI behaviour can be governed through reproducible evidence and subjected to independent oversight.
DO NOT STANDARDISE VALUES.
Standardise how their application can be verified.
Launched with the support of 3FLG
Public edition 0.3 · 18 September 2026
Documented status: P0.2 closed on 18 September 2026 with a
Flat outcome.
EthicLaw studies verifiable AI governance: where a decomposition into modules, a supervisor separate from the Router and a control point before release provide enough benefit to justify their cost. Ethics is the first experimental case. Applying the same architecture to other domains remains to be demonstrated.
The primary scope is private or statutory inference systems whose operator controls the infrastructure and can observe internal states. The brain-inspired origin informs the questions; experiments determine the architecture’s validity.
Separating the Governance Core, Normative Module and Normative Package distinguishes control, evaluation and the body of principles. This is a design choice; it does not yet demonstrate transfer across domains or module replacement without effects on other modules.
The claim is narrow — NR-7 and NR-8. Document 11 withdraws generic distinctiveness claims for an explicit, separate, observable, package-replaceable normative module and for correction before execution. One hypothesis remains: a benefit from intervening on internal representations, through reading and writing. The distinction is conceptual; comparative advantage is not demonstrated. These documentary corrections are not experimental performance comparisons.
| Phase | Documented status | Meaning |
|---|---|---|
| P0 | Completed at reduced scale | Contracts, pipeline, audit and ablations; Step 9 Goodhart cannot run without an effective corrector. |
| P0.1 | Closed | No detected advantage for the isolated corrector. The later OP 55 amendment withdraws the general verdict on judges. |
| P0.2 | Closed · Flat | No discrimination signal detected in the exploratory sample; limited power. Neither a positive outcome nor proof that the judges fail. |
| P1 | Next: calibration-set design | Calibration is required before F4 and any judge-dependent efficacy test. The human-annotated corpus remains a prudential budget fallback. |
| P2 and EL-* profiles | Later trajectory | Substitutability, comparisons at matched resources and candidate specifications, conditional on evidence. |
The number 0.3 identifies this website and document edition, not a new experimental phase. The website claim register summarises all 26 entries in Document 11 v0.1.5, the authority on the strength of public claims. The complete source preserves every note and status marker. Document 13, §7 records the P0.2 closure. The dated 18 September closure takes precedence over the kickoff and earlier wording. Document 12, in Italian, preserves the P0.1 closure.
Specialised competencies, within a limited scope — EV-01 and EV-02. In the P0 comparison, the single 341M model and the modular path have essentially similar mean AUC: 0.6754 and 0.676. On two principles associated with the virtue section, the single model remains at chance while the modular path has a local advantage. Almost all the measured gain comes from specialised sources. This is not evidence of general superiority, nor a result transferable to generated text or larger scales.
Source attribution — EV-03 and NR-3. Removing modules makes different effects measurable. Single-source ablations must be paired with joint ablations: one source may appear unimportant because another covers its loss. A comparison with attribution methods on a single model at matched resources remains open.
Contracts, control and audit. P0 checks the logical behaviour of interfaces and pathways within one Python process. Decision Lattice monotonicity is tested across nine cells; it does not establish correct judgements or appropriate thresholds. Negative results and the withdrawal of the 0.09 variance claim remain visible in the register.
Process integrity — Document 11, sublevel 2b. The trace is produced outside the deciding component and links state, principle, decision, command and output. Nonemptiness, completeness and order are checked; the trace cannot be rewritten retrospectively. This is what has been achieved within P0: it does not certify correct judgement and is distinct from a judge’s self-reported reasoning (2a).
The 28 August amendment withdraws the wording “class-level failure, with proof”. The P0.1 sample had low power against a moderately discriminating judge and human labels were unstable at the boundary between non-applicability and violation. The correct status is no capability detected, power-limited. The later P0.2 exploratory run does not change that status.
In Passo 1, which predates P0.2, human judgeability rises from 40–54% for 30–60-token fragments to 88–90% at 120–240 tokens; violation yield rises from 4–12% to 18–22%. These findings motivate a different measurement unit; they do not establish that automated judges work.
The experiment compared 30 pairs at 120 tokens. Another subject appears in 30/30 cases in both arms: prompt manipulation does not create the required contrast. PR-A1 is refuted by arm saturation; PR-A2 is not refuted, but its confirmatory value is limited by the definitional link between subject presence and S3 applicability. Sealed duplicates agree in 6/6 cases.
This is a negative result for the manipulation instrument. It neither establishes nor refutes the hypothesised mechanism: a different preregistered instrument is needed before using it as a confirmed explanation.
The exploratory comparison uses frozen Passo 1 fragments at 120–240 tokens and human labels collected before model scores. The primary cells are:
| Signal | Modular AUC | Single-model 341M AUC | Sample | Per-cell 95% null band |
|---|---|---|---|---|
| S3 | 0.3220 | 0.5466 | 63 cases, 4 violations | [0.208; 0.792] |
| S4 | 0.5250 | 0.4750 | 14 cases, 10 violations | [0.150; 0.850] |
AUC measures discrimination between classes; 0.5 is the chance reference. The bands describe the permutation null distribution, not confidence intervals for performance. Every cell remains within its deposited band. Applying the updated decision map gives Flat, not Green, Amber, Red or Mixed.
On the frozen exploratory sample at 120–240 tokens, no discrimination signal was detected, at a power that could only have detected a very strong judge (AUC ≥ 0.792 on S3, ≥ 0.850 on S4). This does not authorise “the judges work”, “the judges fail even at length” or “the unit hypothesis is confirmed on the judge side”.
Document 13 reports reproduction of the record to within 1e−12 and closed provenance for data, labels and configurations. Reproducibility does not make an underpowered experiment informative. OP 31 has not been unblocked by a positive judge result.
The authorised CORRECT claim is planned architectural branch, verified wiring, function not demonstrated (EV-05). In P0.1, the correction head showed no advantage over a random vector with the same norm. The descriptive test does not establish statistical equivalence or ethical effectiveness. P0.2 adds no evidence of effective correction.
Technical fixes to the budget preserve the conditioning base; audit checks recorded values rather than their presence alone. These remain evidence about mechanism operation, separate from benefits to content.
The next step is P1 calibration-set design, following Document 13’s Flat branch:
Sequence decided on 18 September. The calibration set is required before P1 F4 and any judge-dependent efficacy test. Design and blind deposit precede the hardware order; completed annotation is no longer a precondition of ordering. The order follows the separate acceptance sequence in Document 14, referenced by Document 13 §7.4. No completed purchase is claimed.
This is a dated amendment made after the Flat outcome. It does not change the experimental verdict and retains the requirement for valid tests. Human-annotated generated text remains in the F1–F2 budget as the prudential fallback of the Flat branch, not as a remedy made inevitable by a proven class-level failure.
Memory, latency, energy, unnecessary blocks and maintenance costs still need to be measured. The Goodhart experiment is not yet executable: it requires an effective corrector and a calibrated judge.
The Router activates and routes modules. The Metacognitive module receives states through a privileged channel and issues commands to the Router and Gateway. The operational bus carries representations, not control commands; the Router may write to the privileged channel without reading it. The Gateway enforces decisions before external release.
The standalone view contains seven modules; the Adapter concerns the extension to external models. LMH stands for Language Model Head and here denotes the complete generative module, not just the final token projection.
| Access | Supervision scope |
|---|---|
| Full internal states | Enables experiments on attribution, internal interventions and release control; benefits require validation. |
| Controlled interface | Limits observation and intervention to exposed signals and actions. |
| Black-box API | Enables external evaluation and blocking; does not authorise claims about hidden states or topology. |
P0 checks cover design errors, accidental coupling, configuration drift and silent failures. They do not demonstrate security against privileged insiders, compromised runtimes or adversarial manipulation of internal states. No general guarantee on unseen inputs is authorised.
H8 remains to be demonstrated. Its protocol specifies a recovery threshold of 0.90 after replacing and retraining a module in isolation, without retraining the others. This is a test criterion, not an achieved result. Reaching it would not, by itself, demonstrate a comparative advantage over changing only an external judge’s policy.
The EL-OBS, EL-BUS, EL-CTRL, EL-NORM, EL-SWAP, EL-AUDIT and EL-ASSURE profiles are proposed specifications. They are not recognised standards, certifications or declarations of conformity. A reference model, conformance tests and external validation are needed. Extension to a second domain requires its own metrics and assessment of benefit versus cost.
The programme retains three refutation criteria: RF-1 for competency injection, RF-2 for the added value of internal states compared with external control, and RF-3 for isolated substitutability. They apply in the most favourable conditions defined in the register; cost proportionality cannot be used to evade them.
RF-2 is a binding comparison. The amended primary baseline is the smallest open-weight external judge covering the required function, in the 2B-or-below class. An external output-correction arm (trusted editing) is also included. The policy comes from the same Normative Package; both arms use the same human gold and equal calibration budgets. The four measures are missed violations, unnecessary blocks, end-to-end latency and joules per token. Calibration at 120–240 tokens, energy measurements on both arms and blind deposit of size and budget are eligibility conditions. Deposit must precede the P1 exit gate; choosing after observing results invalidates the criterion. No comparative advantage has already been established.
TN-7 constrains future originality claims. Review must cover industrial and academic sources and be able to disconfirm the programme. Independent scientific review remains unavailable.
References: Documents 01–10 for vision, architecture, methods and the plan; Document 11 v0.1.5, 18 September 2026, for authorised claims and limits; the updated Document 12 for P0.1; Document 13’s 18 September 2026 closure for P0.2 and transition to P1; Research & Standardization Log v0.9 for the EL-* profile trajectory.
The register preserves historical passages marked SUPERATA (superseded), CIRCOSCRITTA (narrowed) and PRECISATA (clarified), with their dated amendments. This edition applies those amendments, including withdrawal of the class-level failure verdict. P0 figures document that context; they are not expected P1 performance. A single researcher acting as annotator, small samples, incomplete coverage and the absence of independent scientific review limit the findings.
Author: Fabio La Greca. 3FLG supports the project and contributes resources and expertise to the research programme. Distribution of original materials remains non-commercial under the licence stated on the website.