Edexia AI Framework and Ethics Policy

1. Governance

Principles and Values
Edexia operates under the principles of fairness, transparency, accountability, safety, and human primacy. AI systems are designed to augment human judgment, not replace it. All models are developed and deployed with measurable commitments to accuracy and interpretability.

Roles and Responsibilities

• Developers: Ensure model behavior aligns with fairness and privacy standards.
• AI Researchers: Validate datasets for bias and documentation integrity.
• Operational Managers: Maintain compliance and risk monitoring.
• End Users (educators, assessors): Retain decision authority and responsibility for applying AI outputs.

Risk Management
Risks are classified as technical, ethical, or societal. Each model undergoes the foloin before deployment:

• Bias assessment using statistical parity metrics.
• Accuracy Benchmarks using standardised evaluation metrics.
• Security evaluation for model inversion and data exposure.

2. Design and Development

Human-Centered Design
Edexia systems are designed to empower educators. Interfaces are built for interpretability and correction, not blind acceptance. AI feedback must always remain editable and reversible.

Data Management
All data sources are governed by the principles of minimization, consent, and localization.

• Data used for training or evaluation is anonymized and audited.
• User data is never repurposed or shared externally.
• Dataset composition is continuously reviewed to maintain demographic and contextual balance.

Algorithmic Transparency and Explainability
Each AI output must be traceable to input data and decision logic. Models are documented through Model Cardsdetailing objectives, training data summaries, limitations, and confidence levels. All explanations are accessible in non-technical form to end users.

3. Testing and Deployment

Testing and Validation
Before release, every model must pass:

• Functional validation (accuracy, reliability).
• Ethical validation (bias tolerance, fairness impact).
• Stress testing (edge-case performance and safety).
  Results are documented and stored for audit.

Monitoring and Auditing
All live systems are continuously monitored for drift, bias recurrence, and security breaches. Quarterly audits verify compliance with internal and external standards. Non-conformance triggers immediate suspension and review.

Human Oversight
Human authority supersedes AI outputs at all stages. All automated assessments must allow override and feedback logging. Critical decisions—academic, employment, or disciplinary—require human verification.

4. Communication and Stakeholder Engagement

Transparency with Users
Users are informed about:

• Model purpose, data use, and boundaries.
• Known limitations and confidence intervals.
• Procedures for appeal or correction of AI outcomes.

All privacy terms and AI behaviors are disclosed in plain language.

Stakeholder Engagement
Edexia maintains structured consultation with educators, regulators, students, and ethicists. Policy revisions incorporate feedback from these groups. Cross-sector collaboration ensures alignment with emerging AI standards in education and assessment.

Summary
The Edexia AI Framework and Ethics Policy defines a closed-loop governance system: design informed by ethics, deployment bound by accountability, and monitoring guided by transparency. Every AI action must be explainable, correctable, and aligned with human educational purpose.

‍