AIFC-053: Multi-Community Governance

Status: Draft 0.1
Standard: AI-First Community Standard
Short name: AIFC
Builds on:

• AIFC-000 Manifest of the AI-first community
• AIFC-001 Core Concepts
• AIFC-002 Community Model
• AIFC-003 Values and Purpose
• AIFC-004 Feedback and Change Proposals
• AIFC-010 Knowledge Structure
• AIFC-011 Operational DNA
• AIFC-014 Human Cockpit Layer
• AIFC-020 Human-Managed AI
• AIFC-021 AI as External Expert Capacity
• AIFC-022 AI-NDA Boundary
• AIFC-023 AI as Team Member
• AIFC-050 Community Interface
• AIFC-051 Enterprise Interface
• AIFC-052 Shared Values Layer

Purpose of this document: Define Multi-Community Governance as a mechanism for governed cooperation, decision-making, escalation, values alignment, shared risk, AI involvement, and conflict resolution between multiple communities. This document describes how communities can cooperate without losing identity, responsibility, boundaries, and ownership of their know-how.

1. Purpose of this document

This document defines Multi-Community Governance.

An AIFC community is a unit with purpose.

In practice, however, many decisions, risks, and opportunities cross the boundary of a single community.

This concerns, for example:

• multiple teams inside a company,
• multiple departments,
• multiple companies,
• customers and suppliers,
• a company and a regulator,
• a company and a local community,
• an AI vendor and a customer company,
• a state and citizens,
• states in relation to each other,
• people and represented ecosystems,
• current and future generations.

Multi-Community Governance addresses the question:

How are decisions made and cooperation governed when impact crosses one community?

2. Core principle

The core principle of this document is:

When impact crosses community boundaries, governance must cross community boundaries too.

AIFC says:

No community should optimize locally while exporting unmanaged risk to others.

Local efficiency must not hide system impact.

3. Definition

Multi-Community Governance is a governed mechanism through which multiple communities coordinate decisions, values, risks, work, knowledge sharing, AI involvement, escalation, and responsibility in situations where impact crosses one community.

It may include:

• shared purpose alignment,
• Shared Values Layer,
• multi-community interface,
• decision ownership,
• escalation path,
• conflict resolution,
• shared risk assessment,
• AI-NDA Boundary coordination,
• data sharing rules,
• Operational DNA protection,
• feedback loop,
• cross-community change proposals,
• representation of affected communities,
• audit,
• review cycle.

Minimum requirement

When a decision or AI workflow significantly affects multiple communities, it must be clear which communities are affected and how their interests, values, and risks are considered.

4. Why Multi-Community Governance matters

Without Multi-Community Governance, typical problems emerge:

• one team optimizes its KPIs and harms another team,
• a company optimizes costs and transfers burden to customers,
• a vendor maximizes AI adoption and increases customer lock-in,
• an AI agent accelerates delivery and creates security risk,
• automation reduces human work and weakens Human Capability Reserve,
• an enterprise increases performance but transfers ecological impact outside its metrics,
• a state optimizes the economy and overlooks future generations,
• one community decides about another without representation.

Multi-Community Governance prevents local success from becoming system debt.

Minimum requirement

An AIFC community must be able to recognize when its decision creates impact beyond its own community boundary.

5. Community boundary

Community boundary defines where the direct responsibility, ownership, and governance of one community ends.

A boundary may be:

• organizational,
• legal,
• data-related,
• value-related,
• knowledge-related,
• economic,
• geographic,
• technical,
• or ecological.

Multi-Community Governance begins where impact, risk, or dependency crosses this boundary.

Minimum requirement

Significant interfaces must know the community boundary and the situations in which it is crossed.

6. Affected community

Affected community is a community significantly affected by a decision, workflow, AI system, product, or change.

An affected community does not have to be the decision owner.

It may be:

• customer,
• support team,
• operations,
• another company,
• local community,
• future user,
• regulated subject,
• citizens,
• children,
• future generations,
• ecosystem.

Minimum requirement

Critical decisions must assess which communities are affected communities.

7. Represented community

Some communities do not have a direct voice in decision-making.

For example:

• children,
• future generations,
• animals,
• forests,
• rivers,
• oceans,
• climate,
• soil,
• local ecosystems,
• weakly represented social groups.

These communities may be represented through:

• people,
• institutions,
• law,
• science,
• data,
• AI analysis,
• ethical rules,
• public participation.

AI may help make their signals visible.

AI must not take responsibility for representing them.

Minimum requirement

For decisions with significant impact on weakly represented communities, it must be stated whether and how they are represented.

8. Multi-community purpose alignment

Communities do not need to have the same purpose.

But significant cooperation requires at least minimal alignment.

Questions:

• Why are we cooperating?
• What is the shared outcome?
• What interests differ?
• What would end the cooperation?
• Where could misuse emerge?
• Who carries responsibility for impact?

Minimum requirement

Significant multi-community cooperation must have a clear shared purpose or explicitly described differences in purposes.

9. Multi-community shared values

Multi-Community Governance must use the Shared Values Layer.

This means:

• naming shared values,
• naming compatible values,
• naming conflicting values,
• naming non-negotiable boundaries,
• identifying value priorities,
• defining escalation for values conflict.

Minimum requirement

Significant multi-community cooperation must have a values frame or reference to the Shared Values Layer.

10. Decision ownership

In a multi-community situation, it must be clear who decides.

We distinguish:

• decision owner,
• affected community,
• consulted community,
• approving community,
• veto holder,
• escalation owner,
• accountable sponsor,
• implementation owner.

AI may prepare input.

AI must not be the final decision owner for a critical multi-community decision.

Minimum requirement

Critical multi-community decisions must have a defined decision owner and affected communities.

11. Consultation

Not every affected community must have a veto.

But significantly affected communities should at least be consulted proportionally to impact.

Consultation may be:

• formal review,
• feedback request,
• representative input,
• risk assessment,
• public comment,
• customer advisory,
• stakeholder workshop,
• AI-assisted synthesis of feedback.

Minimum requirement

Significantly affected communities must have a proportionate opportunity to provide input, or the reason this is not possible must be recorded.

12. Consent and approval

Some situations require explicit consent or approval.

For example:

• sharing restricted data,
• AI processing of non-public know-how,
• change of contractual obligations,
• impact on customer rights,
• work with Operational DNA,
• AI use in sensitive decision-making,
• change of security boundary,
• public representation of another community.

Minimum requirement

A multi-community workflow must distinguish consultation, consent, approval, and veto.

13. Conflict resolution

Conflicts between communities are normal.

They may be:

• value-related,
• economic,
• technical,
• security-related,
• legal,
• operational,
• capacity-related,
• reputational,
• ecological.

Conflict resolution must define:

• who owns the conflict,
• how it is recorded,
• what values are affected,
• which communities are affected,
• how it escalates,
• who decides,
• how the trade-off is recorded,
• when the decision is reviewed.

Minimum requirement

A significant multi-community conflict must be recorded and resolved through a defined mechanism.

14. Cross-community feedback loop

Multi-Community Governance must support feedback between communities.

For example:

• a customer warns a company about a problem,
• support passes a pattern to a product team,
• an AI agent warns leadership about misalignment,
• a vendor warns about a model change,
• citizens warn a state about policy impact,
• ecological data warns about environmental degradation.

Feedback must be convertible into:

• observed signal,
• risk,
• opportunity,
• change proposal,
• Decision Record,
• strategy update,
• interface update,
• skill update,
• workflow conversion.

Minimum requirement

Multi-community cooperation must have a mechanism for cross-community feedback.

15. Cross-community change proposal

A change proposal may affect multiple communities.

It must include:

• proposed change,
• reason,
• affected communities,
• values impact,
• risk impact,
• data impact,
• AI impact,
• Operational DNA impact,
• decision owner,
• consultation requirements,
• implementation owner,
• review date.

Minimum requirement

Change proposals with multi-community impact must mark affected communities and values/risk impact.

16. Shared risk assessment

Risk must not be assessed only from one community’s perspective.

Example:

• for the team, AI automation is cheap,
• for the customer, it is non-transparent,
• for security, it is risky,
• for the company, it increases lock-in,
• for people, it reduces capability.

Shared risk assessment evaluates impact across communities.

Minimum requirement

Critical multi-community decisions must assess risks from the perspective of affected communities proportionally to impact.

17. Risk transfer

Risk transfer is a situation where one community reduces its own risk or cost by moving it to another.

Examples:

• a company reduces support costs but increases the burden on customers,
• a team accelerates delivery but creates maintenance debt,
• a vendor reduces its own costs but increases customer lock-in,
• an AI workflow reduces human work but weakens Human Capability Reserve,
• a state increases economic output but transfers ecological cost to future generations.

Minimum requirement

AIFC governance must detect and name significant risk transfer.

18. Shared benefit

Multi-Community Governance should not address only risk.

It should also seek shared benefit.

Questions:

• How can cooperation create value for multiple communities?
• How is value distributed?
• Who carries the cost?
• Who receives the benefit?
• Who is invisibly burdened?
• How is fairness measured?

Minimum requirement

Significant multi-community cooperation must distinguish who carries costs and who receives benefits.

19. Data sharing governance

Multi-community cooperation often involves data sharing.

Data sharing governance must address:

• data classification,
• purpose limitation,
• allowed recipients,
• AI access,
• retention,
• storage,
• processing location,
• training use,
• derived knowledge,
• audit,
• revocation,
• breach response.

Minimum requirement

Sharing non-public data between communities must have an explicit data sharing boundary.

20. AI-NDA Boundary across communities

The AI-NDA Boundary is more complex when AI works across communities.

It must be clear:

• whose data AI processes,
• for what purpose,
• in what environment,
• who owns it,
• who sees prompts,
• who sees outputs,
• where derived knowledge is stored,
• whether data may be combined,
• whether data may be used for training,
• what happens during an incident.

Minimum requirement

AI processing of non-public know-how from multiple communities must have an explicit multi-community AI-NDA Boundary or equivalent agreement.

21. Operational DNA across communities

Operational DNA of one community must not be transferred to another community in an unmanaged way.

Especially sensitive situations include:

• vendor access,
• consulting engagement,
• AI migration,
• joint venture,
• outsourcing,
• shared AI agent,
• platform onboarding,
• due diligence,
• acquisition,
• ecosystem integration.

Minimum requirement

Sharing or AI processing of Operational DNA between communities must have an owner, boundary, audit, and exit mechanism.

22. AI agents operating across communities

An AI agent may work across community boundaries.

For example:

• a vendor agent helps a customer,
• an enterprise agent reads data from multiple teams,
• a support agent connects the customer and product team,
• a governance agent collects signals across communities.

Such an agent must have:

• role,
• scope,
• owner,
• affected communities,
• allowed data,
• forbidden data,
• allowed actions,
• forbidden actions,
• approval rules,
• AI-NDA Boundary,
• audit,
• fallback,
• exit strategy.

Minimum requirement

A cross-community AI agent must have an explicit interface, owner, and boundary.

23. AI-generated cross-community proposals

AI may detect problems across communities.

Example:

• AI finds that company KPIs push support toward behavior that harms customers.
• AI finds that a vendor workflow increases lock-in.
• AI identifies a values conflict between strategy and backlog.
• AI warns about ecological or social impact.

AI may formulate a proposal.

But a multi-community decision must have a human or community decision owner.

Minimum requirement

AI-generated cross-community proposals must be marked as proposals and reviewed by a responsible governance role.

24. Multi-community auditability

Decisions and workflows with multi-community impact must be auditable proportionally to risk.

An audit should make it possible to determine:

• who decided,
• who was consulted,
• what values were affected,
• what risk was accepted,
• which communities were affected,
• what data was shared,
• how AI helped,
• what boundaries applied,
• what fallback existed,
• when the decision will be reviewed.

Minimum requirement

Critical multi-community decisions must have a Decision Record or audit trail.

25. Human Cockpit Layer for multi-community governance

The Human Cockpit Layer may make multi-community governance visible.

It may show:

• affected communities,
• shared values,
• values conflicts,
• active interfaces,
• cross-community risks,
• open proposals,
• AI-generated signals,
• data sharing boundaries,
• decision owners,
• escalation paths,
• represented communities,
• unresolved conflicts,
• review dates.

The Human Cockpit Layer helps people see the system impact of decisions.

Minimum requirement

Responsible roles must have a human-accessible view of critical multi-community relationships, conflicts, and decisions.

26. Multi-community Source of Truth

Multi-community cooperation may need a shared or federated Source of Truth.

Options:

• one community holds the authoritative source,
• each community holds its own source and shares an interface,
• a shared governance repository exists,
• a shared decision log exists,
• a shared values record exists,
• a shared risk register exists.

AIFC prefers a federated approach when centralization would threaten community ownership.

Minimum requirement

Multi-community cooperation must define where the authoritative source for shared decisions, rules, and interfaces is.

27. Federated governance

Federated governance means each community preserves its own identity, Source of Truth, and responsibility, while cooperating through defined interfaces.

Federated governance is suitable when:

• communities are independent,
• they have their own values,
• they have their own legal responsibility,
• they share only part of their knowledge,
• they need to cooperate without centralization.

Minimum requirement

When centralization is not appropriate, Multi-Community Governance must use a federated model with clear interfaces and decision boundaries.

28. Multi-community governance levels

AIFC may distinguish levels.

Level 0 - Informal awareness

Communities know about each other, but have no governed interface.

Level 1 - Basic interface

There is a description of cooperation, contacts, purpose, and boundaries.

Level 2 - Shared governance

There are shared values, decision rules, escalation, and feedback.

Level 3 - Federated source of truth

There are connected artefacts, Decision Records, risk registers, and shared interfaces.

Level 4 - AI-operable multi-community governance

Interfaces are human-readable, agent-actionable, software-verifiable, with governed AI involvement and auditability.

Minimum requirement

Significant long-term multi-community cooperation should reach at least Level 2.

29. Multi-community governance lifecycle

Multi-community governance has a lifecycle.

discovered
-> mapped
-> interface_defined
-> values_aligned
-> governance_active
-> reviewed
-> updated
-> retired

Discovered

A dependency or impact was identified.

Mapped

Affected communities were identified.

Interface defined

The interface was described.

Values aligned

Values and conflicts were named.

Governance active

Cooperation runs according to rules.

Reviewed

A review was performed.

Updated

The interface or rules were updated.

Retired

The cooperation ended or was replaced.

Minimum requirement

Significant multi-community governance must have lifecycle status and review mechanism.

30. AI-first Earth perspective

AIFC allows a broader perspective: a community may be a company, state, world, or Earth.

AI-first Earth is not a world governed by AI.

It is a world where human communities use AI to better understand themselves, other communities, and the living system of which they are part.

Multi-Community Governance at this level must include:

• human communities,
• weakly represented communities,
• future generations,
• ecosystems,
• scientific data,
• legal representation,
• ethical boundaries,
• human responsibility.

Minimum requirement

AIFC must not reduce multi-community governance only to relationships between organizations; it must allow representation of wider impacts.

31. Suggested metadata

Example metadata for a Multi-Community Governance Record:

multi_community_governance:
  id:
  title:
  status: discovered | mapped | interface_defined | values_aligned | active | under_review | updated | retired | archived
  owner:
  related_communities:
  affected_communities:
  represented_communities:
  collaboration_purpose:
  governance_level: 0 | 1 | 2 | 3 | 4
  shared_values_layer:
  community_interfaces:
  decision_owner:
  consulted_communities:
  approval_required_from:
  veto_holders:
  escalation_path:
  feedback_loop:
  data_sharing_boundary:
  ai_nda_boundary:
  operational_dna_boundary:
  cross_community_ai_agents:
  risk_assessment:
  risk_transfer_detected: true | false
  benefit_distribution:
  authoritative_source:
  shared_decision_log:
  audit_required: true | false
  review_cycle:
  last_reviewed:
  version:

Example metadata for a Cross-Community Change Proposal:

cross_community_change_proposal:
  id:
  title:
  status: draft | proposed | under_review | accepted | rejected | deferred | implemented | verified | closed
  owner:
  proposing_community:
  affected_communities:
  represented_communities:
  purpose:
  proposed_change:
  values_impact:
  risk_impact:
  data_impact:
  ai_impact:
  operational_dna_impact:
  risk_transfer:
  shared_benefit:
  consultation_required:
  approval_required:
  decision_owner:
  implementation_owner:
  related_decision_record:
  review_date:

These structures are illustrative.

The final schema should be defined in the agent-actionable layer of the standard.

32. Anti-patterns

AIFC rejects the following anti-patterns.

32.1 Local optimization, externalized harm

One community improves its KPIs by transferring cost or risk to another.

32.2 Affected community not identified

A decision affects other communities, but they are not named.

32.3 No representation

A weakly represented community is significantly affected, but nobody represents its interests.

32.4 Vendor governs the relationship

A vendor effectively defines the cooperation rules because the customer has no interface, boundary, or exit strategy of its own.

32.5 AI as hidden cross-community actor

An AI agent works across community boundaries without an explicit owner and boundary.

32.6 Shared data without shared governance

Communities share data but have no shared rules for purpose, retention, AI access, and derived knowledge.

32.7 Values conflict hidden as delivery issue

A values conflict between communities is treated as ordinary delivery delay.

32.8 No cross-community feedback

One community consistently feels the impact of another community’s decision but has no way to send the signal.

32.9 Centralization without consent

One community centralizes the knowledge or governance of other communities without clear consent and boundaries.

32.10 AI decides for represented communities

AI represents weakly represented communities by itself without human, institutional, or ethical responsibility.

33. Minimal requirements

In the area of Multi-Community Governance, an AIFC community must at minimum:

1. Recognize when a decision or AI workflow significantly affects multiple communities.
2. Identify affected communities for critical decisions.
3. State whether and how weakly represented communities are represented.
4. Give significant multi-community cooperation a shared purpose or explicitly described differences in purposes.
5. Give significant multi-community cooperation a values frame or reference to the Shared Values Layer.
6. Assign a decision owner to critical multi-community decisions.
7. Give significantly affected communities a proportionate opportunity to provide input, or record why not.
8. Distinguish consultation, consent, approval, and veto in multi-community workflows.
9. Record and resolve significant multi-community conflict through a defined mechanism.
10. Provide a mechanism for cross-community feedback.
11. Mark affected communities and values/risk impact in change proposals with multi-community impact.
12. Assess risks from the perspective of affected communities for critical multi-community decisions.
13. Detect and name significant risk transfer.
14. Distinguish who carries costs and who receives benefits in significant cooperation.
15. Provide an explicit data sharing boundary for sharing non-public data between communities.
16. Provide a multi-community AI-NDA Boundary or equivalent agreement for AI processing of non-public know-how from multiple communities.
17. Give sharing or AI processing of Operational DNA between communities an owner, boundary, audit, and exit mechanism.
18. Give cross-community AI agents an explicit interface, owner, and boundary.
19. Mark AI-generated cross-community proposals as proposals and review them by a governance role.
20. Give critical multi-community decisions a Decision Record or audit trail.
21. Give responsible roles a human-accessible view of critical multi-community relationships, conflicts, and decisions.
22. Define the authoritative source for shared decisions, rules, and interfaces.
23. Use a federated model with clear interfaces and decision boundaries when centralization is not appropriate.
24. Bring significant long-term multi-community cooperation to at least governance Level 2.
25. Give significant multi-community governance lifecycle status and review mechanism.
26. Allow representation of wider impacts, not only relationships between organizations.

34. Summary

Multi-Community Governance addresses situations where a decision, AI workflow, risk, or value crosses the boundary of one community.

An AIFC community must not optimize only itself if doing so transfers cost, risk, or harm to another.

AIFC therefore says:

Identify affected communities.
Make values conflicts visible.
Prevent unmanaged risk transfer.
Keep decision ownership explicit.
Let AI reveal cross-community signals, not own cross-community decisions.

Multi-Community Governance is the foundation for scaling AIFC from team to company, state, world, and Earth.

Multi-Community Governance turns cross-community impact into governed responsibility.