The Luminous Prosperity Data Governance Addendum: Instrument 03 of the Luminous Governance Framework

The Luminous Prosperity Data Governance Addendum is Instrument 03 of the Luminous Governance Framework, an open-source constitutional architecture for organizations building consciousness technology. Where the User Rights Framework (Instrument 02) establishes ten non-negotiable entitlements, this Addendum specifies the operational machinery that delivers them: exactly what data may be collected, how it may be inferred upon, who owns it, how long it is stored, and how it is deleted. The instrument advances a four-tier data taxonomy ordered by intimacy rather than volume — interaction data, expressed data, inferred data, and derived aggregate data — and establishes inferred data as the most protected class on the argument that a machine-generated claim about a person's interior life is a categorically different object from a behavioral log: it exerts power independent of its accuracy, it decays in truth-value as the person develops, and it is generative, feeding back into the very self-understanding it purports to describe. Three original governance mechanisms are specified in auditable detail. First, the Inference Register: a binding requirement that every inference class the system can generate be enumerated in a public register — with inputs, framework of origin, confidence method, user-visible framing, and retention class — before it may run in production, with no undisclosed inference classes permitted under any research, beta, or enterprise exemption. Second, Temporal Sovereignty, the author's principal contribution: an engineering specification governing not whether a system may hold data about a person but the permissible age of the claim it makes about them right now, comprising eight named retention classes with maximum durations, a monotonic inference-decay schedule, a material-gap disclosure rule, a re-consent trigger, and an absolute prohibition on retroactive re-inference against archived data. Third, an honest deletion standard that declines to misrepresent the technical limits of removing an individual contribution from trained model weights, and specifies scheduled retraining and disclosed unlearning methods in place of a false guarantee. Enforcement is vested in a Data Stewardship Council with halt authority, a Governance Circle veto that the founder cannot revoke, and binding Ethics Review Triad findings. All provisions are non-waivable by commercial agreement. Every numeric threshold is marked as a proposed default subject to ratification. Released under GNU GPL v3.