PERMISSIONS · CONSENT · GOVERNANCE

Define exactly what your digital twin is allowed to do.

TwinAuthority explores the governance layer for personal AI: clear, human-controlled authority over what a digital twin may access, decide, spend, sign, disclose or delegate.

The concept

TwinAuthority

As personal AI becomes more capable, society will need a precise answer to one question: what is this twin actually authorized to do?

Scope

Define the exact boundaries of permitted action.

Consent

Tie sensitive actions to explicit human intent.

Revocation

Pause, restrict or withdraw authority.

Accountability

Keep consequential actions traceable and reviewable.

Intelligence is not the same as authority.
Long-horizon thesis

Built for what comes after today’s AI.

As personal AI becomes more capable, society will need a precise answer to one question: what is this twin actually authorized to do?

Independent concept initiative exploring possible future human–AI systems. This site does not claim to represent an established standard, regulated credential, government program or currently deployed platform.

Human-AI Person Stack · Framework v0.1

TwinAuthority

The permission framework that states which actions a personal AI may undertake, on whose behalf, under what conditions, for how long, and with what approval or audit requirements.

Why this concept exists

AI capability and delegated permission are different things. A highly capable system may receive almost no authority, while a simpler agent may receive narrow permission for a specific task. TwinAuthority makes those limits explicit.

Boundary

Authority should not be inferred from identity, memory depth or technical capability. Knowing a person well, holding a credential or having access to a tool does not by itself confer permission to act.

Role in the stack

TwinAuthority constrains PersonProxy and other active layers through scopes, budgets, durations, counterparties, approval thresholds and revocation rules. It is the framework’s boundary between capability and permission.

Seven-layer framework

The Human-AI Person Stack

Representation, identity, portability, delegated action, authority, human involvement and lifecycle stewardship are treated as separate questions so that no one layer silently grants another.

Public Discussion Draft · 1 October 2026. The Human-AI Person Stack Project is an independent conceptual project originated and authored by Joe Primus Kayau. It is not an adopted technical, legal or industry standard. External research and standards are acknowledged in the full framework paper; references do not imply ownership, endorsement or affiliation.
Domain acquisition · strategic partnerships

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Research, partnerships and long-term opportunities