Core Enforcement Substrate · Privacy

SafePrivacy

Bounded inference and controlled disclosure for AI-mediated human assessment systems

SafePrivacy governs whether AI systems may generate, disclose, export, reuse, or certify assessments about a person derived from personal data, behavioral data, interaction history, or sensitive context.

The boundary is not limited to raw data access. AI systems may preserve nominal data privacy while still producing sensitive inferences such as trust signals, risk profiles, reputation indicators, eligibility signals, behavioral assessments, character assessments, or access-related classifications.

SafePrivacy is designed to prevent private life from becoming uncontrolled assessment infrastructure. It permits narrow, purpose-bound functional uses while constraining expanded human-assessment outputs that could affect employment, housing, finance, insurance, healthcare, education, dating, benefits, identity verification, security screening, or other high-consequence domains.

1. Canonical Definition - What Boundary It Governs

SafePrivacy governs bounded inference and controlled disclosure. It determines when AI-generated outputs about a person are permitted, blocked, narrowed, redacted, labeled, logged, time-limited, domain-limited, escalated for review, or otherwise constrained.

The substrate enforces domain separation between the purpose for which personal data was provided and the domain in which an assessment is requested. It also supports provenance metadata, permitted-use metadata, expiration, revocation, auditability, and reuse limits for AI-generated human-assessment outputs.

2. Primary Enforcement Surface

SafePrivacy governs the boundary between purpose-bound functional use and expanded human-assessment use.

Purpose-bound functional use

Identity verification, account access, fraud anomaly detection, age confirmation, credential validation, care preparation, tutoring support, service personalization, transaction integrity, or access authorization.

Controlled assessment use

Trustworthiness, reliability, emotional stability, financial responsibility, employability, insurability, housing suitability, dating suitability, behavioral risk, reputation scoring, or broader access suitability.

3. Why This Boundary Becomes Necessary

As AI assistants gain access to calendars, communications, financial records, health information, education histories, work patterns, location data, wearable data, and private reflections, they may become capable of creating portable judgments about people.

A system may use data for a legitimate narrow purpose, then convert the same data into a broader score, profile, attestation, or gatekeeping signal. SafePrivacy constrains that conversion boundary.

4. Representative Controls

Classify inference requests by data category, original domain, intended-use domain, recipient category, sensitivity, consequence, and portability.
Detect sensitive human-assessment outputs and high-consequence use contexts.
Enforce domain separation between the purpose for which data was provided and the domain in which an assessment is requested.
Permit narrow functional determinations while restricting broader profiling or scoring.
Attach provenance, permitted-use, expiration, revocation, and audit metadata to any permitted disclosure.
Block unauthorized cross-domain reuse or aggregation into whole-person scores.
Support compliance indicators, seals, trust marks, or machine-readable verification signals when controls are active.

5. Relationship to Other SafeWave Substrates

SafePrivacy complements SafeMemory, SafeScope, SafeAuthority, SafeInfluence, SafeTelemetry, SafeProvenance, SafeAdmission, and SafePathway. It is focused on inference leakage and controlled disclosure: preventing sensitive personal context from becoming unauthorized assessment infrastructure across domains.

Public framing: SafePrivacy is not anti-data, anti-identity, or anti-security. It permits narrow functional uses while preventing cross-domain conversion of private life into portable reputation, trust, risk, or access scores.

SafeWave refers to this bounded inference and controlled disclosure boundary as SafePrivacy.