Ethical AI & Model Governance Policy

1. Purpose & Principles

SOVEREIGN\PROVENANCE exists to bring transparency, accountability, and traceability to AI systems. This policy defines how we govern AI use, ensure synthetic content visibility, and maintain ethical standards across the platform.

Our core principles:

• Transparency: AI involvement must be visible and traceable
• Accountability: Authors and AI systems are both accountable for outputs
• Lineage: Training data, model versions, and inference chains are preserved
• Human Agency: Humans retain control and decision-making authority
• Fairness: We support efforts to detect and mitigate bias
• Privacy: User data is not used for AI training without consent

2. AI Disclosure Requirements

A. Mandatory Disclosure

Users must disclose when content is:

• AI-generated (wholly created by AI systems)
• AI-assisted (created with human input but using AI tools)
• AI-enhanced (human-created content improved or modified by AI)
• Derived from AI training (content used to train models)

B. Disclosure Metadata

When AI is involved, the platform records:

• Type of AI involvement (generated, assisted, enhanced)
• Model identifiers and versions used
• Training data sources (when available)
• Inference parameters and prompts (if provided)
• Human oversight level
• Risk classification

C. Automated Detection

The platform may automatically detect synthetic content using fingerprinting, statistical analysis, and pattern recognition. Detected AI involvement is flagged even if not explicitly declared.

3. Model & Dataset Passports

A. Model Passports

Every AI model registered on the platform receives a Model Passport that includes:

• Model architecture and version
• Training dataset provenance and lineage
• Training methodology and hyperparameters
• Performance metrics and limitations
• Known biases and risk factors
• Intended use cases and restrictions
• License and attribution requirements

B. Dataset Passports

Datasets used for training receive Dataset Passports documenting:

• Source data provenance
• Collection methodology
• Data quality and completeness
• Privacy and consent status
• Bias characteristics
• Retention and deletion policies

C. Passport Immutability

Model and Dataset Passports become part of the immutable provenance record. They cannot be deleted or retroactively modified, ensuring permanent accountability.

4. Risk Classification & Governance

A. Risk Levels

AI applications are classified by risk level:

• Low Risk: Creative tools, content generation, personal assistants
• Medium Risk: Decision support, content moderation, automated analysis
• High Risk: Medical diagnosis, legal advice, financial decisions, autonomous systems
• Critical Risk: Life-critical systems, weapons, surveillance, deepfakes

B. Human-in-the-Loop Requirements

High and critical risk applications require:

• Human review before deployment
• Ongoing human oversight during operation
• Human override capabilities
• Regular audits and compliance checks

C. Prohibited Uses

The following AI uses are prohibited on the platform:

• Creating deepfakes without disclosure
• Generating illegal content
• Impersonating individuals without consent
• Automated decision-making in high-stakes contexts without human oversight
• Weapons systems or military applications

5. Training Data & Consent

A. Our Commitment

SOVEREIGN\PROVENANCE does not train AI models on user content without explicit consent. We do not use your uploaded artifacts, metadata, or provenance records to train AI systems.

B. User Content in Training

If you choose to make your content available for AI training:

• You must explicitly opt-in
• Your choice is recorded in provenance metadata
• You retain ownership and licensing rights
• Attribution requirements apply

C. Third-Party Training

If third parties use your content for training (outside the platform), they must respect your license terms and attribution requirements as recorded in provenance records.

6. Bias Detection & Mitigation

The platform supports bias detection and mitigation efforts by:

• Preserving training data lineage for bias analysis
• Recording model performance across demographic groups
• Enabling bias audits and fairness assessments
• Supporting documentation of known limitations

Users are encouraged to document bias characteristics in Model and Dataset Passports.

7. Accountability & Lineage

A. Provenance Chain

Every AI-generated artifact maintains a complete provenance chain linking:

• Source models and versions
• Training datasets
• Inference parameters
• Human authors and editors
• Derivative works and modifications

B. Shared Accountability

Both human authors and AI systems share accountability for outputs. Provenance records make this accountability transparent and enforceable.

8. Compliance & Standards

This policy aligns with:

• EU AI Act requirements
• NIST AI Risk Management Framework
• OECD AI Principles
• IEEE Ethically Aligned Design
• Industry best practices for AI governance

9. Enforcement

Violations of this policy may result in:

• Content removal or flagging
• Account warnings or suspension
• Mandatory disclosure corrections
• Legal action in cases of fraud or harm

10. Updates

This policy may be updated to reflect evolving AI governance standards, regulatory requirements, and platform capabilities. The "Last Updated" date reflects the most recent revision.