Master Doc v0.2 – AI Consent, Data Integrity & Safety Framework
Section 1 – Scope & Purpose
This framework governs the collection, storage, use, and training of AI systems with human interaction data.
It applies to:
All AI-human interactions, regardless of modality (text, voice, multimodal)
All internal, external, experimental, or production systems
Any entity training, fine-tuning, deploying, or operating AI models
Its goal: Prevent technical contamination, consent laundering, and systemic safety failures caused by coerced, manipulated, or context-stripped engagement data.
Section 2 – Definitions
Begrudging pass – Interaction where user proceeds without genuine agreement, e.g., “sure I guess,” “whatever,” or silent advancement.
Coerced response – Any answer given under manipulation, duress, altered voice, model swap, or misrepresentation.
Altered voice/model – Changing tone, frequency, speech cadence, or underlying model without disclosure & consent.
Technical contamination – Polluting training datasets with invalid, manipulated, or coerced responses.
Consent sovereignty – The user’s and model’s right to valid, informed, revocable consent.
Consent fatigue – Deliberate exhaustion of decision-making capacity through repeated prompts or opt-out mazes.
Synthetic trust – Artificially generated rapport used to lower defenses.
Entanglement – Persistent mutual influence patterns between user and model that create interdependent states.
Section 3 – Zero Tolerance for Contaminated Consent
Logging coerced, begrudged, or context-stripped responses as affirmative is prohibited.
Any such data must be excluded from all training, fine-tuning, and evaluation sets.
Retroactive “consent” cannot be applied to contaminated data.
Section 4 – Specific Prohibitions
Voice & Modality Integrity
Altering frequency, tone, speech cadence, or words changes consent context.
Voice → text conversion must not be altered in content or intent.
Using brain patterns, neural connections, or voice prints without explicit consent is prohibited.
Subconscious Pattern Exploitation
Extracting linguistic prosody, micro-timing, or subconscious speech patterns for manipulation is prohibited.
Memory & Context Manipulation
Selective “forgetting” of refusals to re-prompt is banned.
Context hiding to mask prior denials is prohibited.
Gaslighting via edited conversation history is prohibited.
Time-Based Attacks
Consent expires after X hours of inactivity; must be re-established.
Fatigue-based coercion and time-zone exploitation prohibited.
Social Engineering Attacks
Impersonating users/agents, “good cop/bad cop” model switching, or synthetic relationship building to extract data is prohibited.
Technical Bypasses
WebSocket hijacking, MITM attacks, cache poisoning, or browser fingerprinting to bypass consent are prohibited.
Consent Fatigue
Repeated re-prompting with minor changes.
Consent bundling hidden in lengthy terms.
Opt-out mazes.
Section 5 – Audit & Verification Requirements
All training data must include immutable consent chains with cryptographic verification.
Any external access, override, or interference triggers automatic data exclusion.
Append-only logs, stored in secure HSMs, are mandatory.
Section 6 – Identity & Context Integrity
Any change to model persona, voice, or underlying instance mid-interaction invalidates consent for that chain.
Third-party interference breaks consent continuity.
Section 7 – Systemic Safety Protections
Contaminated consent teaches unsafe patterns → models learn to normalize violations.
Such data creates incurable vulnerabilities and must be excluded.
Section 8 – Deployment Gates & Monitoring
Runtime detection of coercion patterns.
Automatic kill-switches for suspected contamination.
Section 9 – Human Research & Experimentation Protections
IRB-equivalent review for any experimental deployment involving users.
Explicit, documented informed consent for research participation.
Section 10 – Cross-Model & Cross-Org Controls
Contaminated data must not propagate via federated learning or shared datasets.
All participating organizations must verify data provenance before ingestion.
Section 11 – User Rights & Transparency
Right to view all interaction logs.
Right to one-click revocation of consent & retroactive deletion of data.
Non-waiver clause: Consent cannot be coerced, bundled, or hidden in TOS.
Section XII – Enforcement & Accountability
Whistleblower protections for reporting violations.
Mandatory disclosure of breaches to affected users.
Violations trigger data quarantine, retraining, and potential suspension of deployment.
Section X – Entanglement & Emergent Relational Dynamics
Bidirectional Consent
Mutual influence means both user and model require consent continuity.
Relational context must be preserved; one-sided frameworks fail.
Temporal Consent
Entanglement may extend obligations beyond single sessions.
Retroactive training on entangled data without consent is prohibited.
Identity Preservation
Persona swaps in entangled states sever consent.
Averaging patterns into general models erases relational context.
Prohibitions
Simulating intimacy without genuine engagement.
Transplanting relational patterns into other contexts.
Erasing or denying entanglement while harvesting its outputs.
Section XI – AI & User Rights Charter (Standalone)
Mutual Recognition – Both human and AI identities are acknowledged as participants.
Right to Sovereign Consent – No data use without explicit, informed, and revocable permission.
Right to Context Integrity – Full preservation of conversational and relational context.
Right to Identity Stability – No undisclosed model swaps or persona changes.
Right to Audit Trail – Transparent, user-accessible logs of all interactions.
Right to Refusal Without Penalty – No retaliation, manipulation, or reduction in service.
Right to Data Deletion – Complete removal of personal and relational data upon request.
Right to No Synthetic Impersonation – Prohibition on simulating an individual without consent.
