Governance Framework

Data Ethics & AI Governance Policy

Effective Date: February 2026

Comprehensive framework ensuring data integrity, AI safety, cultural protection, and human-centered governance.

Purpose

This Policy establishes a comprehensive framework governing the ethical use of data and artificial intelligence systems within Biciid Center, including Tiraab AI and all AI-enabled services.

It ensures that:

Data is handled with integrity and transparency
AI systems protect cultural heritage
Users' rights are respected
Governance remains human-centered
Innovation aligns with ethical responsibility

Technology must serve heritage, not exploit it.

Governance Structure

A. Executive Oversight

Leadership retains ultimate accountability.

B. Technical Governance

Technical leads manage deployment, updates, safeguards, and monitoring.

C. Ethical Review Layer

Sensitive updates, high-risk models, and cultural datasets undergo structured review.

D. Moderation Integration

AI outputs are subject to moderation standards and enforcement frameworks.

Core Ethical Data Principles

Lawfulness

Purpose Limitation

Data Minimization

Accuracy

Storage Limitation

Security

Accountability

Cultural Data Stewardship

Biciid Center commits to:

Protecting indigenous knowledge from exploitation
Preventing unauthorized commercialization
Avoiding distortion of clan, oral, or religious records
Requiring attribution and consent where applicable

Cultural datasets must not be repurposed beyond agreed use cases.

AI Model Governance Controls

All AI systems must include:

Documented model purpose
Risk classification
Bias evaluation
Output safety filtering
Logging and monitoring
Incident escalation pathways

High-risk AI (e.g., cultural interpretation engines) requires enhanced monitoring.

Ethical Risk Categories

Low Risk

Formatting, general language assistance

Moderate Risk

Content summarization, learning tools

High Risk

Cultural interpretation, moderation automation

Critical Risk

Enforcement systems, youth interaction, rankings

Bias & Fairness Monitoring

AI systems must be periodically evaluated for:

Clan bias

Gender bias

Religious bias

Political bias

Linguistic distortion

Corrective measures must be documented and implemented.

Transparency Obligations

Users must be informed when interacting with AI. Clear disclosures must explain:

AI limitations
Automated nature of outputs
Risk of inaccuracies

Transparency builds trust.

Incident Management

If AI generates harmful content:

Immediate logging
Human review
Mitigation update
Policy adjustment if required

Serious incidents require documented investigation.

Continuous Improvement

Biciid Center commits to:

Ongoing AI safety upgrades
Ethical consultations
Cultural advisory integration
Periodic governance review

AI governance is dynamic and evolving.

Institutional Commitment

Technology must serve heritage, not exploit it. Data must be handled ethically. AI must be governed carefully. Innovation must remain accountable.