ETHICLAW RESEARCH PROGRAM

Trust
is proven.

For artificial intelligence whose behaviour can be understood, tested, challenged and corrected.

Explore the architecture
01 —

Governance as a property of the architecture.

MODULAR GOVERNANCE ARCHITECTUREEL / 07
07
METACOGNITIVEGovernance CoreAuthoritative supervision

Observation · control · audit

OPERATIONAL BUS State publication
Gateway / Enforcement point
AUTHORISED OUTPUT
Functional components · overviewFull diagram ↗
TESTABLEAUDITABLEUPDATABLEEvidence before promises.

01 / THE VISION

From capability to governability

Understand its decisions.
Be able to intervene.

In monolithic systems, capabilities, criteria and control share the same parameter space. Isolating responsibility or updating a single normative domain becomes difficult.

EthicLaw studies functional decomposition: modules with explicit boundaries, a supervisor with effective authority, and declared, versioned, replaceable principles.

01

Observe

Make states, module contributions and intermediate representations available within the scope of the integration.

02

Evaluate

Apply an explicit normative corpus, separating the principles from the mechanism governing their application.

03

Intervene

Issue binding commands and block or authorise output through a dedicated enforcement point.

04

Demonstrate

Link the observed state, principle, decision, command, executor and output actually released.

02 / THE ARCHITECTURE

Explicit boundaries. Distinct responsibilities.

Seven modules.
Governance you can auditable.

The operational and supervisory paths are separate. The Router activates modules; the Governance Core exercises control.

REFERENCE ARCHITECTURE
ENGLISH DIAGRAMReference architecture · EN

EXPLORE THE MODULES

07 / METACOGNITIVE

The authoritative supervisor.

Supervises the system, performs audits and issues binding commands. Exercises final control through the privileged channel and the Gateway.

Supervision and final control
Text description and scope of the diagram

The 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 / §6

Operational bus

An inter-container publication space. Exchanges representations and states between modules; it carries no control commands.

Privileged channel

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.

Control commands

From the Metacognitive supervisor to the Router and Gateway: stop, input blocking, topology changes and rerouting.

Gateway and output

Executes the supervisor’s commands. Can hold, block or authorise output before external release.

03 / THE MANIFESTO

The mechanism is distinct from the values

Do not standardise
values.
Standardise testability
can be verified.

Ethics is the first case study. Each domain remains responsible for its principles; every extension requires new evidence.

THE ARCHITECTURE

Governance Core

Observes and applies the control mechanisms.

THE EVALUATION

Normative Module

Evaluates behaviour against the corpus.

THE PRINCIPLES

Normative Package

Declares principles, scope, thresholds, versions and conflicts.

04 / THE RESEARCH

Falsifiable hypotheses. Conditional claims.

Rigour includes
acknowledging limits.

EthicLaw investigates where modularity delivers measurable benefits sufficient to justify latency, memory, energy and complexity.

Public edition 0.2 · 11 September 2026. Authority: Claim & Evidence Register v0.1.1 (5 August 2026). P0.1 is reported separately as a descriptive update.

EVIDENCE AT REDUCED SCALE

What P0 documents

  • Typed contracts, bus and privileged channel.
  • Gateway, end-to-end pipeline and audit.
  • Component presence and absence tests.
  • Ablations with distinguishable contributions and increasing redundancy in the tested configurations.

Checks within the P0 experimental scope. Register §2.1, EV-03, NR-3 and NR-4.

OPEN QUESTIONS

What remains to be demonstrated

  • General superiority over a monolithic model.
  • Effectiveness of internal correction.
  • Qualified replacement of the normative module.
  • Scalability and transfer to a second domain.

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.

Assurance depends on what can be observed.

The Assurance Envelope defines what the supervisor can observe, command and responsibly claim for each integration.

A
FULL OBSERVABILITY

Access to internal states

Input, tensors, modules, routing, Gateway and output.

Intended scope for attribution, override, internal correction, audit and full enforcement; effectiveness remains to be validated.

B
CONTROLLED INTERFACE

Controlled interface

Input and output, selected hooks or telemetry.

Assurance is limited to observable signals and exposed actions.

C
BLACK-BOX ADAPTER

API access

Prompts, outputs and available metadata.

External filtering and blocking. No evidence about hidden states or topology.

THE PROGRAMME’S QUESTIONS

A thesis to put
to the test.

RQ1–3Modularity, attribution and replaceability

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?

RQ4–6Supervision, constraints and observability

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?

RQ7–8Correction and generalisation

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?

Evidence, outcomes and limits

Register v0.1.1 governs claim strength. P0 findings are local: reduced scale, one machine, one corpus and one domain. They do not establish performance at P1 or frontier scale. No level-3 claim is authorised. The complete authoritative register is available in Italian, including its unadopted appendix.

Claim & Evidence Register v0.1.1 (full Italian text)

Competence injection

The single 341M control averages 0.6754 versus 0.676 for the modular path. On the two virtue principles, the control remains at chance (0.499 and 0.498), while the modular path reaches 0.619 and 0.643: +0.120 and +0.145. Three controls address multi-task learning, forgetting and capacity. This is local evidence, not general superiority.

Entry EV-01

Attribution: comparison still open

ToM, Epistemic and Perceptual are qualified, including when an effect is zero or negative. Comparison with post-hoc attribution in a matched monolithic model has not been performed. Full ablation data are in the register: comparisons must include individual and joint ablations, their ratio and absolute changes (NR-3).

Entry EV-03

Negative findings and withdrawn claims

NR-1: no release on 17 sentences; scores 0.319–0.448 against a 0.80 threshold. Lattice monotonicity does not establish useful decisions. NR-2: routing did not pay off at the measured scale; avoiding a forward pass in 13% of cases concerns compute, not quality. NR-3: single ablations can reverse the interpretation of contribution. NR-4: at least five silent failures in eight steps. NR-5: AUC 0.672 for Epistemic+ToM, 0.661 with permuted dimensions and 0.647 with real Perceptual input. NR-6: the 0.09 per-head variance claim was withdrawn and remains recorded. Each entry’s details and limits are available in the register.

Entry NR-1

Known tensions

Claim authors also maintain the register; independent review is missing (TN-5). Calibration depends on the number of principles (TN-1). The supervisor concentrates failure and has no inline technical counterweight (TN-2). Internal states can provide an attack surface (TN-3). Class C proposes contestable evidence from an independent judge; it does not inherit class A architectural claims (TN-4).

Entry TN-5

Conditions that would refute the claims

RF-1, RF-2 and RF-3 concern competence injection, the value of internal states and replaceability. Under the most favourable conditions, proportionality cannot be invoked to escape refutation. Protocols, the deferred parameter and closure rules remain those recorded in the register.

Entry RF-1

Costs and P0.1

Supervision costs in parameters, memory, latency and energy have not yet been measured (register §8). Later update, separate from register v0.1.1: P0.1 (Document 12, OP 55–56) found no significant advantage over matched-norm random correction. This does not establish equivalence or absence of an effect. No judge signal passed calibration, so this experiment cannot assess ethical effectiveness.

Entry limiti

The programme’s trajectory

From methodology to reference architecture
  1. P0

    Methodology and attribution

    Contracts, pipeline, lattice, audit and ablations.

    Completed at reduced scale
  2. P1

    The cost of governance

    Communication, control, failure modes and cluster overhead.

    Priority in the manifesto
  3. P2

    Replaceable normative module

    Versioned packages, calibration and local recertification.

    Next phase
  4. EL–*

    Reference architecture

    Cross-domain replication, technical profiles and conformance test suite.

    After sufficient evidence

05 / THE DOCUMENTS

The project’s sources

The ideas, in full.

Public vision, scientific programme and component diagram.

MANIFESTO · ENGLISH

Manifesto
EthicLaw

A vision for testable and auditable AI governance.

RESEARCH MANIFESTO · V0.2

The research
programme

Thesis, principles, evidence and limits. Public edition 0.2, aligned with register v0.1.1.

ARCHITECTURE · SVG

The system
map

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.

REFERENCE ARCHITECTURE

The EthicLaw architecture

English EthicLaw architecture diagram showing modules and control paths.
ETHICLAW

EthicLaw Manifesto