AI Ethics
Responsible AI
for Africa
As Africa builds its sovereign AI capabilities, Harch Corp commits to the highest standards of fairness, transparency, and human oversight. Our AI Ethics framework ensures that every model we deploy serves humanity — never the other way around.
Principles
Five Core Principles
These principles are non-negotiable. They guide every AI project from research through deployment and monitoring.
Fairness & Non-Discrimination
Principle 1 of 5
We design AI systems that treat all individuals equitably, regardless of race, gender, ethnicity, language, or socioeconomic status. Our models are continuously tested for bias across protected attributes, with corrective action taken when disparities exceed defined thresholds.
All production models undergo fairness audits before deployment and quarterly thereafter.
Transparency & Explainability
Principle 2 of 5
We believe users and stakeholders deserve to understand how AI systems make decisions. We provide model cards, explainability reports, and decision audit trails for every AI system in production.
87% of production models have published explainability reports. Target: 100% by Q2 2026.
Privacy & Data Protection
Principle 3 of 5
AI systems must respect individual privacy and comply with data protection regulations. We apply privacy-by-design principles, minimize data collection, and implement differential privacy techniques where appropriate.
All AI training data is audited for compliance with Moroccan DPA and GDPR requirements.
Human Oversight & Accountability
Principle 4 of 5
Every AI system has defined human accountability. Critical decisions are never fully automated — humans remain in the loop for high-stakes outcomes, with clear escalation paths and override capabilities.
All high-impact AI systems have designated human oversight officers with veto authority.
Social Benefit & Safety
Principle 5 of 5
We build AI to serve humanity — never to harm, manipulate, or exploit. Every AI project at Harch Corp undergoes an ethical impact assessment, and we reserve the right to decline projects that conflict with our values.
Ethical impact assessments mandatory for all AI projects. Zero tolerance for harmful AI applications.
Fairness
Fairness & Bias Testing
We deploy a multi-layered approach to bias detection and mitigation. Our testing methodology covers pre-deployment audits, continuous monitoring, and external validation.
Pre-Deployment Fairness Audit
ActiveEvery AI model undergoes a comprehensive fairness audit before production deployment. We test across 12+ protected attributes using demographic parity, equalized odds, and calibration metrics.
Frequency
Before every deployment
Adversarial Bias Testing
ActiveRed-team style testing where adversarial inputs are designed to surface hidden biases. Includes stress testing with underrepresented demographic groups and edge cases.
Frequency
Quarterly
Continuous Monitoring
ActiveReal-time monitoring of model predictions for statistical drift and bias emergence. Automated alerts trigger when disparity metrics exceed defined thresholds.
Frequency
Continuous
Third-Party Bias Audit
ActiveAnnual independent bias audit by external AI ethics organizations. Findings are published in our transparency report with remediation plans.
Frequency
Annual
Community Feedback Integration
ActiveStructured channels for affected communities to report perceived bias or harm. Feedback is triaged by the AI Ethics Review Board within 48 hours.
Frequency
Ongoing
Transparency
Model Transparency & Explainability
Every AI model in production at Harch Corp is documented, auditable, and explainable. We publish model cards, data sheets, and explainability reports to enable informed oversight.
Model Cards
Every production AI model has a published model card documenting its intended use, training data composition, performance metrics, known limitations, and fairness evaluations.
Decision Audit Trails
Every automated decision is logged with the input features, model version, confidence score, and decision rationale. Audit trails retained for 7 years.
Data Sheets
Training datasets are documented with datasheets describing collection methodology, demographic representation, consent mechanisms, and known biases.
Explainability Reports
For high-stakes AI applications, we provide feature importance analysis, counterfactual explanations, and SHAP values to enable human understanding of model decisions.
Oversight
Human Oversight Framework
Not all AI decisions carry the same risk. Our three-tier oversight framework ensures the right level of human involvement based on the stakes and potential impact of each AI system.
Human-in-the-Loop
Level 1 Oversight
AI provides recommendations; humans make all final decisions. Required for high-stakes domains: healthcare, legal, financial inclusion, and hiring.
Example Applications
Credit decisioning, medical diagnosis support, recruitment screening
Human-on-the-Loop
Level 2 Oversight
AI makes decisions with human monitoring and intervention capability. Humans can override any automated decision. Alerts triggered for anomalous patterns.
Example Applications
Energy grid optimization, predictive maintenance, demand forecasting
Human-over-the-Loop
Level 3 Oversight
AI operates autonomously within defined boundaries. Humans set policies, review aggregate outcomes, and intervene when systemic issues are detected.
Example Applications
Network traffic routing, resource scheduling, environmental monitoring
Governance
AI Ethics Review Board
The AI Ethics Review Board is an independent governance body with the authority to halt, modify, or reject AI projects that do not meet our ethical standards. The board meets monthly and can convene emergency sessions for urgent matters.
Chair
Chief Ethics Officer
Overall accountability for AI ethics program governance and policy enforcement.
Vice Chair
Head of AI Research
Ensures ethical principles are integrated into research methodology and model development.
Member
Legal & Compliance Lead
Ensures AI systems comply with Moroccan DPA, GDPR, and emerging AI regulations.
Member
External Ethics Advisor
Independent academic providing external perspective on ethical considerations and best practices.
Member
Community Representative
Represents the interests of communities affected by Harch Corp AI deployments.
Member
Data Privacy Officer
Guards data protection rights and privacy-by-design implementation in AI systems.
Board Authority
The Review Board has the authority to halt any AI project, mandate changes, and refer ethical violations to the executive team.
23
Reviews (2025)
2
Projects Halted
5
Modified
Dashboard
Public AI Ethics Dashboard
Transparency requires measurement. Our public dashboard tracks key AI ethics metrics across fairness, transparency, oversight, safety, and privacy — updated quarterly.
0.94
Fairness
87%
Transparency
100%
Oversight
0 Incidents
Safety
99.2%
Privacy
Detailed Metrics — Q4 2025
| Category | Metric | Value | Threshold | Status |
|---|---|---|---|---|
| Fairness | Demographic Parity Difference | 0.032 | <0.05 | Pass |
| Fairness | Equalized Odds Difference | 0.028 | <0.05 | Pass |
| Fairness | Calibration Error | 0.015 | <0.03 | Pass |
| Transparency | Model Cards Published | 87% | >80% | Pass |
| Transparency | Data Sheets Published | 92% | >80% | Pass |
| Transparency | Explainability Reports | 74% | >70% | Pass |
| Oversight | High-Impact HITL Coverage | 100% | 100% | Pass |
| Oversight | Ethics Reviews Completed | 23/23 | 100% | Pass |
| Safety | Critical Bias Incidents | 0 | 0 | Pass |
| Safety | Harm Reports Received | 0 | 0 | Pass |
| Privacy | DPA Compliance Score | 99.2% | >95% | Pass |
| Privacy | Differential Privacy Applied | 68% | >50% | Pass |
Last updated: January 2026. Next update: April 2026.
AI Ethics Matters
We welcome feedback, concerns, and collaboration on AI ethics from researchers, communities, and partners. Responsible AI is a shared endeavor.