governance: establish human-first AI release and accountability controls

.github/CODEOWNERS

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+# AltmanAI organization-wide default code ownership
+#
+# CODEOWNERS identifies accountable reviewers. It does not replace testing,
+# security review, legal review, or the explicit human authorization required
+# for governance-critical changes.
+
+# Default accountable owner
+* @altmanAI
+
+# Organization governance and public trust controls
+/GOVERNANCE.md @altmanAI
+/AI_SYSTEMS_POLICY.md @altmanAI
+/AI_SECURITY_STANDARD.md @altmanAI
+/REPOSITORY_STANDARD.md @altmanAI
+/SECURITY.md @altmanAI
+/CONTRIBUTING.md @altmanAI
+/CODE_OF_CONDUCT.md @altmanAI
+/SUPPORT.md @altmanAI
+/RELEASE_GOVERNANCE.md @altmanAI
+/AI_SYSTEM_CARD_TEMPLATE.md @altmanAI
+
+# Shared GitHub automation, issue forms, and contribution controls
+/.github/ @altmanAI
+
+# Public organization profile
+/profile/ @altmanAI

.github/ISSUE_TEMPLATE/ai-system-change.yml

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+name: AI system change or evaluation
+about: Propose a material change to an AI model, agent, prompt, tool, data flow, evaluation, or human-control boundary.
+title: "[AI SYSTEM] "
+labels:
+  - governance
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Use this form for material AI-system work. Do not include secrets, personal data, proprietary credentials, or unremediated vulnerability details.
+
+  - type: input
+    id: system
+    attributes:
+      label: System or component
+      description: Name the affected model, agent, application, workflow, prompt, tool, API, or evaluation.
+      placeholder: DailyPilot planning agent
+    validations:
+      required: true
+
+  - type: dropdown
+    id: lifecycle
+    attributes:
+      label: Current lifecycle status
+      options:
+        - Proposed
+        - Experimental
+        - Internal testing
+        - Beta
+        - Production
+        - Deprecated
+        - Archived
+    validations:
+      required: true
+
+  - type: dropdown
+    id: change_class
+    attributes:
+      label: Change class
+      options:
+        - Routine and reversible
+        - Material capability or behavior change
+        - Security, privacy, or permission change
+        - Governance-critical change
+        - Regulated or high-stakes use
+    validations:
+      required: true
+
+  - type: textarea
+    id: objective
+    attributes:
+      label: Authorized objective
+      description: State the human-defined problem, intended user value, and explicit non-goals.
+      placeholder: Describe the bounded objective and what this work must not do.
+    validations:
+      required: true
+
+  - type: textarea
+    id: behavior
+    attributes:
+      label: Proposed behavior or capability
+      description: Explain what changes, what remains unchanged, and how outputs or actions will differ.
+    validations:
+      required: true
+
+  - type: textarea
+    id: authority
+    attributes:
+      label: Human authority and control
+      description: Identify required approvals, confirmation points, override paths, appeals, escalation, and shutdown or rollback controls.
+    validations:
+      required: true
+
+  - type: textarea
+    id: data
+    attributes:
+      label: Data and privacy review
+      description: Identify data sources, personal or sensitive data, retention, access, consent, logging, and data-minimization controls.
+    validations:
+      required: true
+
+  - type: textarea
+    id: security
+    attributes:
+      label: Security and tool-use review
+      description: Cover permissions, credentials, external services, prompt injection, data exfiltration, unsafe tool use, supply-chain risk, and least privilege.
+    validations:
+      required: true
+
+  - type: textarea
+    id: evaluation
+    attributes:
+      label: Evaluation plan and acceptance criteria
+      description: Define reproducible tests, baselines, failure cases, thresholds, reviewers, and evidence required before release.
+    validations:
+      required: true
+
+  - type: textarea
+    id: limitations
+    attributes:
+      label: Known limitations and uncertainty
+      description: State unsupported use cases, likely failure modes, unresolved questions, and claims that must not be made.
+    validations:
+      required: true
+
+  - type: textarea
+    id: paihi
+    attributes:
+      label: P.A.I.H.I. review
+      description: Address Proof, Alignment, Integrity, Humanity, and Impact.
+      placeholder: |
+        Proof:
+        Alignment:
+        Integrity:
+        Humanity:
+        Impact:
+    validations:
+      required: true
+
+  - type: textarea
+    id: rollback
+    attributes:
+      label: Monitoring, incident response, and rollback
+      description: Explain how harmful drift, misuse, failures, or unintended impact will be detected, contained, corrected, and documented.
+    validations:
+      required: true
+
+  - type: checkboxes
+    id: attestations
+    attributes:
+      label: Submission attestations
+      options:
+        - label: I have not included secrets, credentials, personal data, or private vulnerability details.
+          required: true
+        - label: Capability and readiness claims are labeled accurately and supported by evidence.
+          required: true
+        - label: Material AI assistance will be disclosed in the implementation pull request.
+          required: true
+        - label: Governance-critical work will not merge without attributable accountable-human approval.
+          required: true

AI_SYSTEM_CARD_TEMPLATE.md

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+# AltmanAI AI System Card
+
+> Use this template for models, agents, AI-assisted features, automated decision workflows, and systems that can invoke tools or affect users. Replace all instructional text before release.
+
+## 1. System identity
+
+- **System name:**
+- **Repository or product:**
+- **Version:**
+- **Lifecycle status:** Proposed / Experimental / Internal / Beta / Production / Deprecated / Archived
+- **Accountable human owner:**
+- **Technical owner:**
+- **Last reviewed:**
+- **Next required review:**
+
+## 2. Authorized purpose
+
+### Intended objective
+
+Describe the human-authorized problem this system addresses and the useful outcome it is designed to produce.
+
+### Intended users
+
+Identify users, operators, reviewers, and affected stakeholders.
+
+### Explicit non-goals
+
+State what the system is not designed, authorized, or validated to do.
+
+### Prohibited uses
+
+List disallowed domains, decisions, actions, data uses, or deployment contexts.
+
+## 3. System description
+
+- **Models or providers used:**
+- **Prompts, policies, or routing logic:**
+- **Tools and external services:**
+- **Human inputs and approvals:**
+- **Outputs and actions:**
+- **Persistence, memory, or state:**
+- **Deployment environment:**
+
+Include a data-flow or architecture diagram when the system is material, multi-component, tool-using, or production-facing.
+
+## 4. Capability boundaries
+
+### Supported capabilities
+
+List only capabilities supported by reproducible evidence.
+
+### Unsupported capabilities
+
+Identify functions the system may appear able to perform but is not authorized, reliable, or validated to perform.
+
+### Known limitations
+
+Describe uncertainty, hallucination risk, non-determinism, coverage gaps, language or accessibility limitations, model/provider dependencies, and foreseeable failure modes.
+
+## 5. Human authority and recourse
+
+- **Who defines objectives?**
+- **Who can authorize consequential actions?**
+- **What requires confirmation before execution?**
+- **How can a user challenge, correct, or appeal an output?**
+- **How can an operator pause, disable, or roll back the system?**
+- **What decisions must never be delegated solely to the AI system?**
+
+Meaningful human control must be operational, not ceremonial. Reviewers must have sufficient information, time, authority, and practical ability to intervene.
+
+## 6. Data governance and privacy
+
+- **Data sources:**
+- **Personal or sensitive data involved:**
+- **Legal or consent basis where applicable:**
+- **Data minimization controls:**
+- **Retention and deletion:**
+- **Access controls:**
+- **Logging and observability:**
+- **Training or provider data-use settings:**
+- **Cross-border or third-party processing:**
+
+Do not include secrets, credentials, private personal data, or exploit details in a public system card.
+
+## 7. Security and misuse resistance
+
+Address, where applicable:
+
+- least-privilege permissions;
+- credential and secret handling;
+- prompt injection and indirect prompt injection;
+- data exfiltration;
+- unsafe or unauthorized tool invocation;
+- identity, authentication, and authorization failures;
+- dependency and supply-chain risk;
+- malicious inputs and adversarial use;
+- rate limits, abuse controls, and anomaly detection;
+- sandboxing, isolation, and environment boundaries;
+- incident response and kill-switch procedures.
+
+## 8. Evaluation record
+
+### Evaluation objectives
+
+Define the claims being tested and why they matter.
+
+### Test sets and scenarios
+
+Document representative, edge-case, adversarial, accessibility, privacy, and failure-recovery tests.
+
+### Baselines and thresholds
+
+State comparison baselines, acceptance thresholds, and release-blocking conditions.
+
+### Results
+
+Provide dated, versioned, reproducible evidence. Distinguish measured results from estimates or qualitative judgment.
+
+### Independent or human review
+
+Identify reviewers, review scope, unresolved disagreements, and any domain-specific expertise required.
+
+## 9. Human-impact review
+
+Consider:
+
+- dignity and respectful treatment;
+- autonomy and informed choice;
+- accessibility and inclusive use;
+- privacy and contextual integrity;
+- fairness and disparate impact;
+- overreliance, dependency, and deskilling;
+- emotional or psychological effects;
+- recourse and error correction;
+- effects on workers, communities, and vulnerable users.
+
+## 10. P.A.I.H.I. assessment
+
+- **Proof:** What evidence supports the system's claims and release status?
+- **Alignment:** How does the system match the authorized objective and AltmanAI mission?
+- **Integrity:** What uncertainty, limitations, assistance, conflicts, or unresolved risks are disclosed?
+- **Humanity:** How are dignity, agency, privacy, accessibility, safety, and meaningful review preserved?
+- **Impact:** What useful outcome occurred or is expected, and how will it be measured?
+
+## 11. Monitoring and change control
+
+- **Operational metrics:**
+- **Safety and quality indicators:**
+- **Drift detection:**
+- **User feedback and complaint channels:**
+- **Incident thresholds:**
+- **Review cadence:**
+- **Material-change triggers:**
+- **Rollback procedure:**
+
+A material change to the model, provider, prompt architecture, data flow, permissions, tools, intended use, or risk profile requires renewed review.
+
+## 12. Release decision
+
+- **Decision class:** Routine / Material / Governance-critical / Regulated or high-stakes
+- **Release decision:** Approved / Conditionally approved / Rejected / Retired
+- **Conditions or restrictions:**
+- **Accountable approver:**
+- **Approval date:**
+- **Authorization record or Master Ledger reference:**
+- **Rollback owner:**
+
+### AI assistance disclosure
+
+Identify material AI assistance used to design, implement, test, document, or review this system. Human reviewers remain accountable for verification and release decisions.