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PAI-Kernel

The problem. AI systems increasingly mediate decisions about humans — about cognitive influence, about whose authority shapes whose thinking. Current deployment models leave humans dependent on provider goodwill for the protection of their cognitive sovereignty. There is no provider-independent verification surface for what an AI is actually optimizing toward.

The framework. PAI-CD (Personal Authorial Intelligence — Constitutional Document) defines normative invariants — independently verifiable — that deployed AI systems must satisfy to protect Author cognitive sovereignty at the deployment layer. PAI-Kernel is the public reference implementation in Rust (Apache 2.0 / MIT dual-licensed code · CC BY 4.0 documentation).

Who should read further. Researchers exploring AI-alignment normative frameworks · engineers evaluating constitutional governance for deployed AI · auditors verifying provider compliance · adopters integrating PAI-CD-aligned governance into their AI systems · contributors to the open canonical corpus.

┌──────────────────────────────────────────────────────────┐
│                                                          │
│                           PAI                            │
│             Personal Authorial Intelligence              │
│                      (the concept)                       │
│                                                          │
│                            │                             │
│                            │ codified as                 │
│                            ▼                             │
│                                                          │
│                          PAI-CD                          │
│               PAI Constitutional Document                │
│                  (normative framework)                   │
│                                                          │
│                            │                             │
│                            │ implemented by              │
│                            ▼                             │
│                                                          │
│                      PAI-Kernel SDK                      │
│                 Reference implementation                 │
│              (Rust crates · dual-licensed)               │
│                                                          │
└──────────────────────────────────────────────────────────┘

ORCID iD DOI all versions

License (docs) License (code) GitHub release Crates.io

OpenSSF Scorecard CI CodeQL Fuzz

Personal Authorial Intelligence — Constitutional Framework

A normative layer for human-centric AI governance. Release v2.2.3 · 2026-04-28

Start here: QUICKSTART.md ⚡ - five-minute path to running daemon · NO setup required.

...or choose your path

If you are... Start here Time
An adopter evaluating PAI-CD for your AI system § Adopter Path ~30 min
A researcher interested in the constitutional framework § Researcher Path ~1 hour
An auditor verifying invariants and compliance § Auditor Path ~2 hours
A contributor wanting to propose changes § Contributor Path ~30 min
An engineer integrating PAI-Kernel runtime § Engineering Path ~1 hour

Adopter Path

Goal: evaluate fit · install · run a demo · understand scope.

  1. Read docs/RELEASE_NOTES_v2.2.3.md — what's in this release.
  2. Read docs/KNOWN_LIMITATIONS.md — what's NOT in this release.
  3. Follow docs/INSTALL.md — ~30 sec via install.sh (curl -fsSL https://paikernel.org/install.sh | sh) OR ~1 min via Homebrew binary.
  4. Run demo: pai_governance_daemon --version · explore /api/v1/health.
  5. Read corpus/PAI_Bill_of_Authorial_Rights.md — understand what's protected.

Continue further: § Engineering Path · § Researcher Path · SSRN paper.

Researcher Path

Goal: understand the framework's normative architecture · invariants · threat model.

  1. Read paper: PAI-CD: A Constitutional Framework for Authorial Sovereignty in Deployed AI SystemsDOI 10.2139/ssrn.6512218 · ~30 min.
  2. Read corpus/PAI_Constitutional_Document.md — ~15 min · six non-derogable invariants.
  3. Read corpus/PAI_Bill_of_Authorial_Rights.md — ~20 min · enforceable rights.
  4. Read corpus/Glossary.md — ~10 min · binding terminology.
  5. Browse corpus.paikernel.org — current rendered surface (legacy ReadMe.com hosting · sustained through v2.2.x window).

Continue further: § Auditor Path · cite the work · contact maintainer with research questions.

Auditor Path

Goal: verify invariants hold · review compliance evidence · independent assessment.

  1. Read corpus/PAI_Constitutional_Document.md — invariants enumerated.
  2. Review docs/sbom/sbom.json — CycloneDX 1.4 supply chain inventory.
  3. Review OpenSSF Scorecard — automated supply-chain scan.
  4. Review CI runs: github.com/PAI-Kernel/pai-kernel/actions.
  5. Verify GPG signature: git tag --verify v2.2.3.
  6. Audit compliance test results: cargo run -p pai_compliance --locked.

Continue further: contact maintainer with audit findings · file issues at github.com/PAI-Kernel/pai-kernel/issues.

Contributor Path

Goal: propose changes · understand contribution discipline · find where help is wanted.

  1. Read CONTRIBUTING.md — contribution model · amendment procedure.
  2. Read CODE_OF_CONDUCT.md — expected behavior.
  3. Read SECURITY.md — vulnerability disclosure procedure.
  4. Browse open issues: github.com/PAI-Kernel/pai-kernel/issues.
  5. Propose corpus changes via Amendment procedure (per Governance and Change Control).
  6. Propose code changes via PR.

Continue further: § Engineering Path for code-level orientation.

Engineering Path

Goal: integrate PAI-Kernel runtime · understand API surface · build adapter.

  1. Read docs/INSTALL.md § HTTP API surface.
  2. Browse published crates on crates.io.
  3. Read runtime/governance_daemon/ — axum-based HTTP service.
  4. Read crates/pai_api/ — core API types.
  5. Read crates/pai_witness/ — witness chain · audit log.
  6. Build with cargo build --workspace --locked.
  7. Run tests with cargo test --workspace --locked.

Continue further: § Auditor Path for verification approach · § Contributor Path if submitting changes.


The frozen v2.2 corpus snapshot is archived via DOI: https://doi.org/10.5281/zenodo.19151900


Document Status & Publication Model

PAI-CD v2.2 is a constitutional framework consisting of 10 normative documents, organized as a layered system.

The v2.2.3 release package contains:

  • Three foundational corpus documents (Layer 0) — constitutional invariants, authorial rights, binding terminology
  • Companion research paper (SSRN DOI 10.2139/ssrn.6512218)
  • Rust SDK v1.3.1 — 22 library crates + governance daemon binary + 5 runnable examples (T2/T3 authorization composition correctness fix relative to v1.3.0)
  • Install guide (docs/INSTALL.md) — cross-platform walkthrough
  • Release notes, known limitations, license, contribution policy, security policy, citation metadata

The remaining corpus layers (interpretation rules, threat modeling beyond Layer 0, protocol constraints, compliance logic, audit procedures, governance mechanisms, implementation mapping) exist in internal canonical development and will be released progressively in subsequent publications.

This repository is not a research paper.

It is a normative constitutional specification (Layer 0 infrastructure).

A companion research paper describing the problem space, threat model, invariant architecture, and system implications is published on SSRN:

"PAI-CD: A Constitutional Framework for Authorial Sovereignty in Deployed AI Systems" Mikhail Anatolievich Sergeev · Independent Researcher; PAI-Kernel Initiative · 2026 DOI: 10.2139/ssrn.6512218

The paper PDF is also included in this repository under papers/.


What This Is

PAI (Personal Authorial Intelligence) is a normative framework that ensures AI systems operate exclusively under the declared and verifiable authority of the human author they represent.

PAI defines the constitutional conditions required to preserve authorial sovereignty at the deployment layer of AI systems.

PAI-Kernel is the public normative layer of the PAI Constitutional Framework (PAI-CD) — a formal specification defining the constitutional principles, authorial rights, and governance invariants for Personal Authorial Intelligence systems.

The PAI Constitutional Framework (PAI-CD) is a structured corpus of normative documents establishing the governance model of PAI systems.

This repository contains the Public Edition — the Layer 0 release of the PAI-CD corpus.

PAI-CD is not a product. It is not a startup. It is a Layer 0 normative infrastructure — a constitutional substrate on which compliant implementations, governance bodies, and execution systems may be built.


Core Premise

Most AI governance discourse focuses on what AI systems should do.

PAI-CD focuses on something prior: who holds final authority, and what structural guarantees protect that authority from erosion — by providers, by optimization pressure, by infrastructure lock-in, or by cumulative drift.

The framework defines six non-derogable invariants:

Invariant What It Protects
Authorship Supremacy Final human authority over all consequential decisions
Cognitive Sovereignty Freedom from covert persuasion and behavioral shaping
Anti-Manipulation Prohibition on undeclared optimization objectives
Provider Independence Portability and governance reproducibility
Reversibility Reconstructability of all structural changes
Drift Immutability Protection against cumulative invariant erosion

These invariants are non-derogable — they cannot be suspended by emergency, majority vote, economic pressure, security update, or provider policy.

PAI-CD operates at Layer 0 — below models, providers, and application logic.


Public Edition — Document Index

This repository publishes three foundational documents:

Document Description
corpus/PAI_Constitutional_Document.md Invariants and interpretation rules
corpus/PAI_Bill_of_Authorial_Rights.md Enforceable Author rights
corpus/Glossary.md Binding terminology for PAI-CD v2.2

The full corpus (10 documents) includes implementation mapping, threat modeling, compliance verification, and governance control layers. The complete framework is maintained by the author and will be extended as the project develops. A consolidated multi-language documentation portal is planned for v2.3 (~late May / early June 2026).

Adopter-facing operational documentation

Start here: QUICKSTART.md — five-minute path to running daemon · NO setup required.

Document Audience Time
QUICKSTART.md New evaluators · «just run it» · root-level mirror of docs/quickstart.md 5 min
docs/quickstart.md Same content as QUICKSTART.md (root) · canonical docs/ location 5 min
docs/INSTALL.md Comprehensive install reference (6 methods) 30-60 min
docs/upgrade.md Existing adopters upgrading between releases 15 min
docs/api.md API integrators · 5 REST endpoints 15 min
docs/architecture.md Architects evaluating fit 30 min
docs/audit_checklist.md Independent auditors verifying release artifacts 1-2 hours
docs/SUPPORT.md Anyone needing help · channels + expectations 5 min
docs/KNOWN_LIMITATIONS.md Adopters checking scope before commitment 10 min
docs/RELEASE_NOTES_v2.2.3.md What's in v2.2.3 binary release 5 min
docs/RELEASE_NOTES_v2.2.3.1.md What's in main HEAD post-tag (doc improvements) 5 min
CHANGELOG.md Release history · semantic versioning 5 min
examples/README.md 5 reference example binaries explained 10 min
SECURITY.md Vulnerability reporting · PGP key 5 min

Interpretation Principle

Ambiguity resolves toward stronger invariant protection, minimal authority expansion, and maximum portability.

This principle applies to all documents in this repository and to any compliant implementation.


Status

Item Status
Constitutional Framework v2.2 corpus — Freeze Edition (March 2026)
Release package v2.2.3 — Stabilization Release (2026-04-28)
Distribution Invitation-only early adopter preview
Domain paikernel.org
Paper DOI 10.2139/ssrn.6512218
Governance Currently maintained by the primary author

Author: Mikhail Sergeev · independent researcher. Background: 12-year journey from a June 2014 manuscript to the present constitutional corpus · ORCID 0009-0001-6443-855X.

Note on versioning: The v2.2 corpus is a frozen, citationally-stable snapshot of the three foundational documents (March 2026). The v2.2.3 release package (2026-04-28) ships that corpus alongside SDK v1.3.2 (runtime configuration improvements: author key initialization moved from compile-time defaults to environment variables across daemon, compliance, and API paths; optional --demo flag for local testing), superseding v2.2.2. The research paper and adopter materials are unchanged. Future releases may introduce additional normative content; v2.2.2 and v2.2.3 each remain retrievable under their respective tags. For academic citation, see CITATION.cff.


License

This repository is dual-licensed between code and documentation:

  • Source code (Rust crates · binaries · scripts · CI workflows): Licensed under MIT OR Apache-2.0 (dual license · choose either at your discretion). See LICENSE-MIT and LICENSE-APACHE.

  • Documentation (PAI-CD framework normative texts · Constitutional Document · Bill of Authorial Rights · Glossary · this README's narrative sections): Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE-CC-BY-4.0.

You are free to share, adapt, and use this material — including in commercial products — provided you preserve copyright notices, give appropriate attribution to PAI-Kernel Initiative, and indicate if changes were made.

For a license summary and FAQ, see LICENSE. A detailed License FAQ is published progressively across v2.2.x releases.


Contributing

PAI-Kernel is in early formation. Community standards are published in this repository:

At this stage, the most valuable contributions are:

  • Careful reading and substantive critique of the normative layer
  • Identification of ambiguities that require clarification via Amendment
  • Academic or institutional engagement

Please open an Issue using the provided templates to begin a public discussion.


Contact

For institutional inquiries, academic collaboration, or governance discussion:
Open an Issue in this repository, reach out via paikernel.org, or email contact@paikernel.org.


PAI-Kernel is a public normative layer of PAI-CD. It is not affiliated with any AI provider.