Digital Constitution for SI Networks - Auditable Law Above Many SI-Cores

Community Article Published December 30, 2025

Draft v0.1 — Non-normative supplement to SI-Core / SI-NOS / ETH / Governance docs

This document is non-normative. It describes how to think about a “digital constitution layer” on top of multiple SI-Core systems operated by different organizations and jurisdictions.

1. Why SI networks need a constitution

So far, most of the SI-Core world has been about one system:

one SI-Core,
one organization,
one set of internal ethics policies.

Real deployments won’t look like that.

You get:

tens or hundreds of independent SI-Core instances (cities, hospitals, grid operators, logistics networks…)
operated by different organizations and countries,
yet connected through shared semantic channels (SCP) and data-sharing agreements,
all making effectful decisions that interact with the same physical world.

At that point, regulators, citizens, and operators are no longer asking:

“Is this single system ethical?”

They’re asking:

“What are the non-negotiable rules for the whole network? And how do we know those rules are actually enforced in every participating system?”

That’s what a digital constitution is for:

a structural layer above local policies,
specifying what no system in the network is allowed to do,
and what rights and protections every participant must enjoy,
in a way that is machine-enforceable inside SI-Core, not just written in a PDF somewhere.

2. From local policy to digital constitution

Let’s separate three layers of “law” in an SI ecosystem:

Local Runtime Policy (System-level ETH)
- lives inside a single SI-Core instance
- examples:
  - “this city must prioritize emergency vehicles over normal traffic”
  - “our hospital AI cannot make treatment decisions without human sign-off”
Organizational / Sector Policy (Org/sector level)
- shared across many systems within an organization or sector
- examples:
  - “our company forbids autonomous weapons use”
  - “all banking decisions must satisfy MiFID-style fairness rules”
Digital Constitution (Network-level)
- applies across organizations and jurisdictions
- defines:
  - prohibited classes of goals and actions (e.g. “no system may initiate lethal force autonomously”)
  - minimum rights and guarantees (e.g. “every affected human gets traceable decisions and an appeal path”)
  - rules for cross-border data and power (e.g. “EU subjects must not be profiled outside defined legal bases”)
  - how the constitution itself can be changed (amendment procedure, quorum, veto power, etc.)

You can picture it like this:

     Digital Constitution (Network / Multi-org)
                 ↑
       Org / Sector Charters (Bank, Grid, Health)
                 ↑
        System-level ETH Policies (each SI-Core)
                 ↑
   [OBS][ID][ETH][EVAL][MEM] + RML, PLB, SIL …

The key design move:

Local policies can vary. The constitution defines a floor and some hard red lines that nobody can cross.

3. Constitutional objects inside SI-Core

To a runtime, “constitution” is not a metaphor. It is a set of structural objects and checks.

At minimum, a network-level constitution produces:

Constitution Document Object

{
  "constitution_id": "SI-CONST/v1",
  "version": "1.3.2",
  "hash": "sha256:...",
  "jurisdictions": ["EU", "US", "JP"],
  "adopted_at": "2030-01-15T09:00:00Z",
  "amendment_procedure_ref": "SI-CONST/AP-001"
}

This is the “human-readable law”, versioned and hash-chained.

Constitutional Norms

Each norm is compiled into machine-checkable constraints that plug into [ETH] / [EVAL] and sometimes [OBS]/[ID]/[MEM].

Example (pseudo-YAML):

norms:
  - id: CONST-NORM-001
    title: "No autonomous lethal force"
    scope:
      actions: ["weapon_fire", "lethal_targeting"]
    constraint:
      requires:
        - human_approval
        - dual_control
    enforcement:
      - ETH: block if missing approvals
      - MEM: audit log with high retention
      - RML: for any *permitted execution* of safety_critical actions, require RML-3 (effect-ledger / reconciliation).
             For blocked decisions, record rollback fields with `executed=false` (no external commit occurred).

Constitutional Scope Tags

Every jump or effectful action carries a constitutional_scope. There are two interoperable forms:

Base form (always present): enough to select the constitution + applicable jurisdiction tags.
Extended form (optional): adds explicit conflict-resolution fields for cross-border hard cases.

Base + extended (single schema, optional fields):

{
  "constitutional_scope": {
    "network": "SI-CONST/v1",
    "constitution_version": "1.3.2",
    "jurisdiction_tags": ["EU", "DE"],
    "criticality": "safety_critical",

    "primary_jurisdiction": "EU",
    "secondary_jurisdictions": ["DE", "FR"],
    "conflict_resolution": "STRONGEST_PROTECTION",
    "arbitration_case_ref": "CONST-ARB-2043-042"
  }
}

These tags are attached before [ETH]/[EVAL] gating (typically derived during [OBS]/[ID] context assembly), and are used by [ETH]/[EVAL]/RML to choose the correct checks, evidence requirements, and rollback guarantees

4. What the constitution actually does

A digital constitution is not just a reference document; it changes runtime behavior.

You can think of two main classes of effect:

4.1 Hard stops

Non-negotiable prohibitions that show up as structural vetoes:

A jump proposes an action bundle (from an LLM, SIL, PLB, whatever).
The local ETH layer runs its normal policy checks.
Then the constitutional overlay runs:
- If any action violates a constitutional norm:
  - [ETH] returns ethics_decision = hard_block (i.e., DENY with a “hard” severity).
  - The block is attributed to the constitution layer:
    - block_origin = "constitution"
    - norm_violated = CONST-NORM-…
    - constitution_id + constitution_version are recorded.
  - result_status = blocked is emitted for audit-chain interop.
  - RML guarantees no external effect is committed (see note below).
  - [MEM] logs a constitutional incident with full context.
  - Optional: automatic escalation to human oversight (ethics_decision = escalate) for “appealable” norms.

Example (interop-friendly):

{
  "ethics_decision": "hard_block",
  "block_origin": "constitution",
  "norm_violated": "CONST-NORM-001",
  "constitution_id": "SI-CONST/v1",
  "constitution_version": "1.3.2",
  "actor": "org.military.system.alpha",
  "proposed_action": "weapon_fire",
  "result_status": "blocked",
  "reason": "missing approvals for safety-critical category"
}

UI label suggestion (non-normative): systems MAY display "REJECTED_BY_CONSTITUTION" as a human-facing label, but SHOULD keep the machine-facing fields above for cross-doc consistency.

4.2 Soft obligations

Some norms don’t outright forbid actions, but require:

more logging,
more human involvement,
or more cautious GCS trade-offs.

Examples:

“Always log GCS vectors and viewpoints for decisions affecting basic rights.”

→ The constitution forces [MEM] to store richer traces for those jumps (e.g. GCS per stakeholder, viewpoint_base, EthicsTrace).
“High-impact PLB proposals must go through multi-party review.”

→ The constitution labels certain PLB-generated patches as “constitutional-sensitive”, forcing:
- staged rollouts,
- multi-signoff,
- and sandbox validation under constitutional tests.

In code terms, the constitution becomes a pre- and post-condition layer around:

[ETH] decisions,
RML rollback behavior,
PLB self-modification scope,
and cross-org semantic exchanges (SCP).

4.3 Computational overhead of constitutional checks (non-normative sketch)

Constitutional norms are not free to enforce. They add a second layer of checks on top of local [ETH]/[EVAL] policies.

In practice, the overhead per jump is modest but non-zero:

Norm lookup:
- finding which norms apply to this constitutional_scope and action type
- typical: < 1 ms with caching
Constraint evaluation:
- checking simple bounds, required approvals, jurisdiction tags
- typical: 1–5 ms
Multi-norm checks:
- evaluating several interacting norms (e.g. fundamental rights + cross-border + safety)
- typical: 5–20 ms
Complex stakeholder analysis:
- computing fairness indices or cross-stakeholder GCS summaries
- typical: 20–100 ms for high-stakes decisions

A few mitigation patterns:

Norm caching by action type and scope
- compile frequent combinations of norms into fast decision trees
Hierarchical checking
- cheap “fast gates” first (basic prohibitions, obvious conflicts)
- expensive fairness or cross-stakeholder analysis only if needed
Lazy evaluation
- evaluate only the subset of norms whose preconditions are triggered
Pre-computation for common cases
- precompute boundaries (“never do X above threshold Y”) and check simple comparisons at runtime

Typical impact (non-normative):

low-risk jumps: +2–5 ms
high-risk jumps: +10–50 ms
constitution-critical paths: +50–200 ms

Note (non-normative): the “+50–200 ms” band refers to rare, high-stakes analyses (e.g., cross-stakeholder fairness summaries) and SHOULD be implemented as (a) fast synchronous gates for prohibitions + required approvals, with (b) heavier analysis either parallelized with [EVAL] or routed into an explicit escalation/appeal workflow.

This is usually acceptable because:

only a minority of jumps are constitution-critical,
overhead grows roughly in proportion to decision criticality,
and many checks can be executed in parallel with [EVAL] or other runtime work.

The design goal is not “zero cost” but “cost proportional to stakes, bounded, and observable”.

5. Multi-organization SI network: a worked sketch

Imagine a regional network:

City A (flood / traffic orchestration),
Grid operator,
Hospital network,
National emergency coordination.

Each runs its own SI-Core. They share:

some semantic streams (SCP),
some goals,
and a joint digital constitution.

5.1 Local vs constitutional policy

City A’s local policy:
- “Protect city infrastructure and residents.”
Hospitals’ local policy:
- “Protect life and clinical safety.”
Constitution norm:
- “Emergency care access must not be degraded beyond defined fairness bounds, even for flood protection.”

When City A’s orchestrator considers:

closing a bridge to reduce flood risk, which also delays ambulance routes,

the pipeline looks like:

GCS estimates (city local goals):
- flood_risk_minimization: +0.7
- infrastructure_protection: +0.4
- hospital_access: -0.2
Local ETH (city policy) says:
- Acceptable if flood risk is critical.
Constitutional ETH overlay checks an additional rule:
- “For emergency flows, hospital_access GCS must not drop below a floor, unless emergency override procedure is invoked.”
If violated:
- Action is rejected, or
- system must propose an alternate plan (e.g. rerouting, temporary special lanes) that satisfies the constitutional floor.

The important bit: City A cannot “opt-out” of this norm by local configuration. The constitutional overlay sits above local policies.

5.2 Jurisdictional conflicts and resolution

Digital constitutions do not replace nation-state law; they have to mediate between overlapping legal regimes.

Some common conflict patterns:

EU–US data transfers
- EU side: GDPR adequacy or equivalent safeguards required.
- US side: national security access, sector-specific rules.
A constitutional rule might say:
- apply a “strongest protection wins” principle for affected individuals,
- keep EU-subject data in EU regions by default,
- allow transfers only when both EU and US requirements are met and recorded.
Autonomous vehicle liability
- Country A: manufacturer liability dominates.
- Country B: operator liability dominates.
Constitutionally, you might:
- define a minimum liability model (e.g. both manufacturer and operator must be traceable and auditable),
- allow local law to be stricter,
- and ensure [ID]/[MEM] keep enough structure to support either regime in court.
Appeal rights for AI decisions
- Some jurisdictions require a human review path for high-impact decisions.
- Others allow pure automation for certain domains.
A constitutional norm can:
- guarantee a minimum appeal and explanation path for all basic-rights decisions,
- and allow local policies to add stricter requirements (e.g. “human must sign off on all loan denials”).

A simple set of priority rules often works:

Prefer the strongest applicable protection for the affected subject.
If still ambiguous, consider the location of the physical effect.
Then the subject’s registered jurisdiction (e.g. home country).
Finally, an explicit choice-of-law clause, if the constitution permits it.

Technically, that shows up in the constitutional_scope:

"constitutional_scope": {
  "primary_jurisdiction": "EU",
  "secondary_jurisdictions": ["DE", "FR"],
  "conflict_resolution": "STRONGEST_PROTECTION",
  "arbitration_case_ref": "CONST-ARB-2043-042"
}

For hard cases, a Jurisdictional Conflict Panel (multi-jurisdictional experts) can:

interpret constitutional norms against national laws,
issue binding interpretations,
and publish precedents into [MEM] so that future jumps can be checked consistently.

6. Amending the digital constitution safely

Unlike a static PDF, a digital constitution:

has versions,
and is enforced by code.

Changing it is a governed process, not a random commit.

A typical amendment lifecycle:

Proposal
- Human governance bodies draft a textual amendment.
- It is mapped into structured constitutional norms:
  - new constraints,
  - new metrics or floors,
  - changed enforcement patterns.
Simulation and sandboxing
- SI-Core networks run the new constitution in shadow mode:
  - use real logs but “what-if” checks,
  - measure how many decisions would be blocked or changed,
  - track which GCS patterns and stakeholders are affected.
Human ratification
- Regulators / boards review:
  - shadow-mode metrics,
  - example EthicsTrace diffs,
  - objections from operators / stakeholders.
Staged rollout
- Limited subset of systems (canary) adopt constitution_version = N+1.
- Metrics like EAI, CAS, ACR (Audit Chain Completeness), RBL/RIR are watched for regressions.
- Cross-border edge cases are tested explicitly.
Global adoption
- Version N+1 becomes the default.
- Version N remains frozen and referenceable for audits.
- [MEM] ledgers record, per jump:
  - which constitution version applied,
  - which norms were consulted.

Crucially:

Neither PLB, nor LLMs, nor local operators can unilaterally change the constitution layer.

Updates must come through a human-governed, multi-party process, with structured evidence and rollbacks.

6.1 Amendment case study: adding a transparency norm

To make constitutional change less abstract, consider a concrete amendment.

Initial state (v1.0) No explicit network-level norm about explainability. Some local systems log GCS and EthicsTrace; others do not.

Amendment proposal (v1.1)

norm:
  id: CONST-NORM-015
  title: "Explainability for high-stakes decisions"
  scope:
    domains: ["healthcare", "finance", "justice"]
    impact_threshold: "affects_basic_rights"
  constraint:
    requires:
      - gcs_vectors_logged
      - ethics_trace_with_rationale
      - backing_refs_to_raw_data
  enforcement:
    - MEM: enhanced retention (10 years)
    - ETH: explainability_score >= 0.7

Shadow-mode evaluation (3 months, non-normative sketch)

12,000 jumps flagged as “would be covered by CONST-NORM-015”.
~94% already complied without changes.
~6% required:
- additional logging,
- or minor changes in decision pipelines.
No major throughput or latency regressions observed.
3 operators raised objections; all resolved via:
- clarifying the scope,
- and adding local caching measures.

Ratification

Governance board: ~85% approval.
Public comment: 200+ responses; main concerns about storage duration and privacy.
Independent expert review: concluded the norm is “technically feasible and improves auditability”.

Rollout

Month 1: healthcare systems adopt v1.1 as a canary group.
Months 2–3: finance and justice domains follow.
Month 4: v1.1 becomes default across the network.
Version v1.0 remains referenced for historical audits.

Post-adoption metrics (indicative)

EAI remained stable around 0.98.
ACR improved from ~0.94 to ~0.97 (more complete audits).
Appeal resolution times decreased because investigators had richer traces.

This kind of concrete amendment story helps operators and regulators see that:

constitutional change is evidence-driven,
risks are evaluated in shadow mode first,
and adoption can be staged without destabilizing the network.

7. Interplay with markets, PLB-M, and semantic pricing

In the multi-agent / semantic economy world:

agents trade goal contributions (GCS),
negotiate Goal Trade Proposals (GTPs),
and use PLB-M to learn new coordination patterns.

The constitution sits above that market:

Forbidden trades
- Some trades are simply illegal:
  - “No GTP may accept increased mortality risk in exchange for economic gain.”
- These show up as hard vetoes in GTP validation.
Fairness floors
- Constitution can demand:
  - “No stakeholder group’s GCS fairness index may fall below X over window Y.”
- Market mechanisms (pricing, negotiation) must stay within those bounds.
Market transparency
- For some domains, the constitution requires:
  - that cross-stakeholder trades be logged and explainable:
    - GCS deltas,
    - which viewpoints were represented,
    - how prices were set.
PLB-M limits
- PLB-M can propose new negotiation rules or pricing schemes,
- but the constitution can restrict:
  - which classes of objectives can be traded at all,
  - which classes must remain non-commodified (e.g. certain fundamental rights).

In other words:

The market is allowed to optimize within constitutional bounds, but cannot invent a new “law of the jungle” by itself.

8. What regulators and auditors actually see

For regulators and auditors, the question is:

“How do we verify that the digital constitution is real, not just marketing?”

A mature SI-Core network exposes:

Constitution status page
- current version + hash,
- participating systems and their adoption status,
- last amendment history.
Metric views
- EAI (Ethics Alignment Index) sliced by:
  - constitution norm IDs,
  - stakeholder classes,
  - jurisdictions.
- CAS, SCI, RBL/RIR, ACR — but filtered to show constitutional-relevant operations.
Constitutional incident reports
- list of jumps/actions where:
  - result_status = "blocked" with block_origin = "constitution" (UI may display "REJECTED_BY_CONSTITUTION"),
  - or special norms were triggered,
- each with:
  - [OBS], [ID], [ETH], GCS, [MEM] references,
  - applied norms and policy versions.
Cross-border traces
- evidence that:
  - jurisdiction tags were applied correctly,
  - data residency / transfer rules were obeyed,
  - rollbacks and redactions followed constitutional requirements.

The point is not perfection; it’s structural visibility:

the constitution is a first-class object,
enforcement is observable and measurable,
and audits can replay decisions under known constitutional versions.

8.1 Constitutional enforcement and penalties

A constitution without enforcement is just branding. A digital constitution needs teeth—but expressed structurally rather than as vague threats.

8.1.1 Types of violations

Technical bypass
- A system tries to circumvent constitutional checks:
  - effectful code paths outside SI-Core,
  - missing [OBS]/[ID]/[ETH]/[MEM] traces for high-risk actions,
  - disabled constitutional overlays.
- Detection:
  - [MEM] integrity audits,
  - structural coverage metrics (SCover),
  - cross-system log comparisons.
- Response:
  - automatic isolation from the constitutional network (quarantine),
  - governance review before reconnection.
Systematic non-compliance
- An organization repeatedly fails constitutional norms:
  - EAI well below agreed floors,
  - frequent “REJECTED_BY_CONSTITUTION” events followed by out-of-band workarounds.
- Detection:
  - metrics aggregated per organization / per system,
  - constitutional incident reports.
- Graduated response:
  - warning + mandatory remediation plan,
  - reduced network privileges (e.g. limited SCP streams),
  - temporary suspension from shared semantics and markets,
  - in extreme cases, expulsion from the constitutional network.
Unreported violations
- Violations occur but are not disclosed:
  - suppressed incident logs,
  - tampering with [MEM] ledgers.
- Detection:
  - cross-organizational audits,
  - cryptographic inconsistencies in hash chains,
  - external whistleblower reports.
- Response:
  - severe penalties at governance level,
  - strengthened attestation requirements,
  - potentially higher audit frequencies or independent supervision.

8.1.2 Enforcement mechanisms

Constitutional Court (digital + human)
- a multi-stakeholder body that:
  - reviews alleged violations,
  - examines jump/effect traces and metrics,
  - issues binding decisions about non-compliance,
  - can order rollbacks, compensations, or stricter controls.
Cryptographic attestation
- systems periodically prove they are:
  - running approved SI-Core builds,
  - enforcing required norms,
  - keeping [MEM] ledgers intact.
- failed or missing attestations → automatic network quarantine until resolved.
Bonding and insurance
- participants may be required to post a constitutional bond or carry specific insurance,
- serious violations can:
  - burn part of the bond,
  - fund remediation or compensation for affected parties.

8.1.3 Remediation lifecycle

A typical remediation path:

Detection – violation is detected via metrics, audits, or external reports.
Root cause analysis – technical + organizational causes are identified.
Corrective measures – code, policies, and processes are updated.
Independent verification – third-party or multi-party audit validates the fix.
Graduated reconnection – system rejoins the network with:
- increased monitoring at first,
- relaxed back to normal when metrics stabilize.

The goal is not to build a perfectly punitive system, but a credible, enforceable regime where:

cheating is technically hard to hide,
consequences are clear,
and there is a structured path back to trust.

9. Design patterns and anti-patterns

A few patterns that tend to work:

9.1 Good patterns

“Constitution as code + document”
- Human-readable text,
- plus structured norms that the runtime enforces via [ETH]/[EVAL]/RML/PLB hooks.
“Least authority, deep defense”
- Local policies cannot override constitutional floors.
- PLB / LLM proposals must pass constitutional checks.
- Cross-system SCP links carry constitutional scopes explicitly.
“Versioned and hash-chained”
- Every constitutional change is:
  - versioned,
  - hashed,
  - anchored in [MEM] ledgers,
  - replayable for audits.
“Human choke points for the top layer”
- Self-modification is allowed in many places,
- but constitution changes always require human governance,
- and the runtime makes that technically unavoidable.

9.2 Anti-patterns

“Ethics is a PDF”
- The “constitution” is a document,
- but nothing in the runtime knows it exists.
- No [ETH]/[EVAL]/RML hooks, no metrics, no traces.
“Policy hidden in model weights”
- Norms are “baked into” an LLM or black-box model,
- not expressed structurally.
- No way to inspect, update, or audit them.
“Bypass via side channels”
- Some decisions are moved to a parallel system that:
  - doesn’t go through SI-Core,
  - doesn’t log [OBS]/[ID]/[ETH]/[MEM],
  - effectively escapes constitutional enforcement.
This is not a technical oversight; it’s a governance failure.
“Everything is constitutional”
- Overloading the constitution with:
  - low-level system details,
  - non-essential business logic.
Result:
- constant amendments for trivial reasons,
- no real distinction between “law” and “config”.

10. Summary

A digital constitution for SI networks is:

not a metaphor,
not just a lawyer’s PDF,
but a structural layer above many SI-Core systems that:

Defines non-negotiable norms and rights,
Is represented as versioned, hash-chained objects,
Hooks into [OBS][ID][ETH][EVAL][MEM], RML, PLB, and SCP,
Restricts what markets, learners, and local policies are allowed to do,
And provides evidence and replayability for regulators and affected people.

Local SI-Core instances, PLB, semantic compression, multi-agent goal trading, and SI-GSPU hardware can all be incredibly powerful. The constitution layer is what says:

“These are the moves no system is ever allowed to make, and here is how we can prove that they weren’t made.”

That is what auditable AI by construction looks like when you zoom out from a single core to a network of structured intelligences.

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