AI Content Policy
Status: ✅ READY
ARTIFICIAL INTELLIGENCE USAGE & CONTENT GOVERNANCE
THANDI AI (PTY) LTD | Registration No: 2025/939429/07 | POPIA Reg: 2025-068149
Information Officer: Seelan Govender | hello@thandi.online
AI Ethics Officer: Seelan Govender (interim)
Version: 1.0 (Beta) | Effective Date: 21 December 2025
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1. PURPOSE & SCOPE
This policy governs the development, deployment, and usage of Artificial Intelligence systems within Thandi.ai, specifically for career guidance, educational recommendations, and student support services.
Applies to:
All AI models powering career recommendations
Natural language generation in reports
Chatbot interactions (future feature)
Image/text analysis capabilities
Automated decision-making systems
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2. AI SYSTEMS IN USE (BETA PHASE)
2.1 Career Matching Engine
Type: Supervised machine learning (random forest + gradient boosting)
Purpose: Match students to careers based on academic performance, interests, and labor market data
Training data: 50,000+ historical student records (anonymized), SAQA occupational database, DHET labor market surveys
2.2 University Admission Predictor
Type: Logistic regression + neural network
Purpose: Estimate probability of admission to specific programs
Training data: Historical admission data from 26 SA universities (2020-2024)
2.3 Bursary Eligibility Classifier
Type: Rule-based system + NLP
Purpose: Match students to bursary opportunities
Training data: 200+ bursary databases, NSFAS guidelines, corporate bursary criteria
2.4 Content Generation (Reports)
Type: Template-based generation with GPT-4 fine-tuning
Purpose: Create personalized career guidance reports
Training data: Career counseling best practices, educational psychology literature
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3. PLATFORM-SPECIFIC AI USAGE POLICIES
3.1 Student-Facing AI
Principles:
Empowerment, not replacement: AI supports human decision-making, does not replace counselors
Transparency: Students informed they're interacting with AI
Age-appropriate: Content tailored for 14-18 year old comprehension
Safety-first: No advice that could cause physical, emotional, or financial harm
Prohibited Uses:
❌ No medical/psychological diagnosis
❌ No financial advice beyond bursary identification
❌ No encouragement of risky or illegal activities
❌ No collection of sensitive data (sexual orientation, political views, religious beliefs)
❌ No creation of addictive engagement loops
3.2 School-Facing AI (Analytics Dashboard)
Principles:
Aggregated only: Individual student data never shown to schools
Anonymization minimum: 10+ students required for any school-level statistic
Purpose limitation: School data only for institutional planning, not student surveillance
Prohibited Uses:
❌ No individual student tracking by schools
❌ No teacher performance evaluation based on AI recommendations
❌ No automated disciplinary action based on predicted outcomes
❌ No sharing school data with third parties without explicit consent
3.3 Research & Development AI
Principles:
Anonymization: All research data stripped of identifiers
Consent: Opt-in required for research participation (separate from service consent)
Transparency: Publish research findings openly (where appropriate)
Prohibited Uses:
❌ No using student data to train general-purpose AI models
❌ No selling anonymized data to third-party AI companies
❌ No psychological experiments without IRB approval
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4. CONTENT GENERATION GUIDELINES
4.1 Report Content Standards
All AI-generated career reports must:
✅ Include:
Clear statement that recommendations are AI-generated and probabilistic
Confidence level indicators (e.g., "High confidence: 85% match")
Explicit verification requirements ("⚠️ Verify with university")
Multiple alternative pathways (not single recommendation)
Resources for human support (school counselor contact)
✅ Tone & Language:
Encouraging and supportive (not deterministic: "You WILL succeed")
Culturally sensitive (South African context-aware)
Age-appropriate reading level (Grade 9 comprehension minimum)
Gender-neutral career descriptions (unless specific program requirements exist)
Multi-language support (primary: English, secondary: isiZulu, Afrikaans in development)
❌ Avoid:
Definitive statements: "You are guaranteed admission"
Discouraging language: "You are not good enough for this career"
Gender stereotyping: "This career is better for boys/girls"
Socio-economic bias: Assuming financial resources beyond stated constraints
Racial or cultural assumptions: All recommendations based on merit and interest only
4.2 Bursary Content Accuracy
Verification Protocol:
All bursary information cross-checked against provider website (automated monthly)
Human verification of top 50 bursaries quarterly
"Last verified" date displayed on every bursary listing
User flagging system for outdated information
Non-inclusion Criteria:
Bursaries requiring payment to apply (likely scams)
Bursaries with opaque selection criteria (unfair practices)
Bursaries from unregistered organizations
Bursaries with discriminatory requirements (unless legally exempted, e.g., certain transformation bursaries)
4.3 Career Description Content
Source Standards:
SAQA occupational descriptions (authoritative)
DHET career guidance materials (government-endorsed)
O*NET database (international, adapted for SA context)
Industry body input (Engineering Council of SA, HPCSA, etc.)
Update Frequency:
Annual review of all career descriptions
Quarterly updates for high-growth sectors (tech, renewable energy)
Real-time updates for discontinued programs or qualifications
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5. AI BIAS MITIGATION MEASURES
5.1 Identified Bias Risks
Historical Bias Risk: Training data reflects historical inequalities in education system
Mitigation:
Oversampling: Augment training data with records from quintile 1-3 schools
Fairness constraints: Explicitly penalize model for disparate impact based on school type
Benchmarking: Test model performance across different school quintiles before deployment
Socio-economic Bias Risk: AI may favor careers requiring resources unavailable to low-income students
Mitigation:
Bursary integration: prominently display financial aid for high-cost pathways
Cost filtering: Allow students to filter careers by "low-cost entry"
Barrier flagging: Identify careers with expensive requirements (e.g., medical school fees)
Gender Bias Risk: Stereotypical career recommendations based on gender (if provided)
Mitigation:
Optional gender field: Not required for core recommendations
Blind testing: Evaluate model outputs with and without gender data
Gender-neutral language: All career descriptions reviewed for bias
Counter-stereotypical examples: Actively promote careers in non-traditional fields
Geographic Bias Risk: Bias toward urban, Western Cape/Gauteng opportunities
Mitigation:
Provincial filters: Students select home province for local opportunities
Rural opportunities: Highlight careers viable in rural areas (agriculture, teaching, telecommuting)
Distance learning: Include UNISA and other distance options prominently
Racial Bias Risk: Training data may reflect apartheid-era educational disparities
Mitigation:
Blind processing: AI does not consider race in core recommendation algorithms
Transformation bursary matching: Race considered ONLY for explicit transformation bursaries with consent
Equity audits: Quarterly bias audits across demographic groups
B-BBEE transparency: We are 100% black-owned, committed to transformation
5.2 Bias Testing & Auditing
Quarterly Bias Audits:
Disparate impact analysis: Compare recommendation distributions across school quintiles
Counterfactual testing: Same student profile, different school location/socio-economic status
Gender parity: Ensure recommendation variance by gender <5%
Rural/urban parity: No systematic preference for urban careers
External Auditing:
Annual third-party algorithmic audit (planned for 2026)
B-BBEE verification includes data transformation practices
Open to Information Regulator audits at any time
User Reporting:
"Bias Report" button in every recommendation
Anonymous flagging of potentially biased content
All reports reviewed within 5 business days
Pattern analysis of bias reports quarterly
5.3 Model Update & Retraining Policy
Retraining Frequency:
Major retrain: Annually with new admission cycle data
Minor updates: Quarterly for new programs/courses
Hotfixes: Immediate for identified bias issues
Data Drift Monitoring:
Track model performance metrics weekly
Alert if recommendation patterns shift significantly
Investigate any demographic group performance degradation
Version Control:
All model versions documented and archived
Ability to rollback to previous version if bias detected
A/B testing for major model changes (limited beta group first)
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6. ETHICAL AI PRINCIPLES
6.1 Human-Centered AI
Human in the loop: School counselors/parents must review critical recommendations
Override capability: Students/parents can manually adjust recommendations
Explanation requirement: All recommendations include reasoning ("Why this career?")
6.2 Beneficence
Student welfare: All features must demonstrably benefit students
Harm prevention: Proactive identification and mitigation of potential harms
Positive impact: Track downstream outcomes (university admission rates, student satisfaction)
6.3 Justice & Fairness
Equitable access: Free tier available for all South African students
No discrimination: Race, gender, disability, religion never used to deny opportunities
Affirmative action: Actively promote transformation bursaries and historically disadvantaged access programs
6.4 Transparency
Open source: Core recommendation algorithms will be open-sourced (post-beta)
Explainability: White-box models preferred over black-box where possible
Public documentation: This policy and model cards publicly available
6.5 Accountability
Named responsibility: Seelan Govender accountable for AI ethics
Impact assessments: Algorithmic impact assessments before major model changes
Stakeholder input: Student, parent, teacher advisory panels for major features
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7. PROHIBITED CONTENT & USE CASES
We will NOT generate or allow:
❌ Content promoting illegal activities (drug trafficking, fraud)
❌ Explicit sexual content or sexual career advice
❌ Hate speech or discriminatory content
❌ Violence or self-harm encouragement
❌ Medical diagnoses or treatment recommendations
❌ Financial investment advice (beyond bursary identification)
❌ Political campaigning or partisan content
❌ Religious proselytizing
❌ Content encouraging academic dishonesty
❌ Misinformation about COVID-19, vaccines, or public health
We will NOT permit AI use for:
❌ Surveillance of students or teachers
❌ Automated grading or disciplinary decisions
❌ Predicting student failure or "risk" scoring
❌ Commercial advertising targeting minors
❌ Creating behavioral profiles for third parties
❌ Law enforcement investigations
❌ Immigration decisions
❌ Credit scoring or financial services
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8. USER RESPONSIBILITIES
As a student/parent using Thandi.ai:
✅ Provide accurate information (garbage in, garbage out)
✅ Use AI recommendations as one input among many
✅ Consult with human counselors, teachers, parents
✅ Verify information independently
✅ Report suspicious or biased recommendations
✅ Understand AI limitations (not infallible)
As a school/educator:
✅ Ensure proper consent obtained
✅ Supervise appropriate use (not during unauthorized times)
✅ Teach AI literacy and critical thinking
✅ Do NOT use AI to replace professional counseling
✅ Protect student login credentials
✅ Report AI errors or biases promptly
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9. AI ACCIDENT & FAILURE RESPONSE
If AI produces harmful recommendation:
Immediate: User reports via "Flag Issue" button
Within 2 hours: AI recommendation disabled pending review
Within 24 hours: Human review by qualified counselor
Within 48 hours: Corrected recommendation issued if error confirmed
Within 7 days: Root cause analysis and model update if systematic issue
Communication: Affected user(s) notified with explanation
If AI bias detected:
Immediate investigation by AI Ethics Officer
Bias audit within 5 business days
Model adjustment if bias confirmed
User notification if recommendations may have been affected
Report to regulator if systematic discrimination occurred
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10. POLICY ENFORCEMENT
Monitoring:
Automated content filtering (profanity, hate speech detection)
Human review of flagged recommendations (daily during beta)
Monthly AI ethics committee review (Seelan Govender + external advisor)
Consequences of Violation:
User violations (attempting to misuse AI):
Warning for first minor offense
Suspension for repeated violations
Permanent ban for serious violations (hate speech, illegal activities)
System violations (AI produces prohibited content):
Immediate model update
Feature temporarily disabled
Root cause analysis
Public incident report if widespread
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11. POLICY UPDATES
Version history:
v1.0 (21 Dec 2025): Initial beta release
Update frequency: Quarterly review during beta, annually post-launch
Stakeholder input: Policy changes reviewed by student, parent, and teacher advisory panels
Notification: Material changes posted on thandi.online/legal with 14-day notice
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12. CONTACT & GOVERNANCE
AI Ethics Officer:
Seelan Govender (interim)
hello@thandi.online
0781298701
Responsibilities:
Oversee AI bias audits
Review flagged content
Approve major model changes
Liaise with Information Regulator on AI matters
Advisory Panel (Planned Q1 2026):
2 Student representatives (Grade 11-12)
2 Parent representatives
2 School counselor representatives
1 AI ethics academic
1 Disability rights advocate
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13. COMPLIANCE & STANDARDS
We commit to:
✅ POPIA compliance: All AI processing POPIA-compliant
✅ Ubuntu AI Principles: African-centered AI ethics framework
✅ UNESCO AI Ethics: Following UNESCO AI ethics recommendations
✅ South African AI Blueprint: Aligned with DTIC AI strategy
✅ IEEE Ethically Aligned Design: Technical standards for AI systems
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14. BETA-SPECIFIC LIMITATIONS
During beta (Dec 2025 - Feb 2026):
AI models have limited training data in some career fields
Bias testing is ongoing; not all metrics validated
Human review of recommendations not yet automated
Model explainability features under development
Limited language support (primarily English)
Post-beta improvements:
Expanded training data (5x increase)
Full bias audit completion
All recommendations human-validated
Full isiZulu and Afrikaans support
Enhanced explainability features
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15. ACKNOWLEDGMENT
By using Thandi.ai, you acknowledge:
AI is a tool, not a crystal ball
Recommendations contain uncertainty
Bias may exist despite our mitigation efforts
Human judgment is essential
You will verify all critical decisions independently
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Document Version: 1.0 Beta
Last Updated: 21 December 2025
Next Review: 21 March 2026 (post-beta)
THANDI AI (PTY) LTD
170 Innes Road, Morningside, Durban, Kwa-Zulu Natal, 4001
www.thandi.online | hello@thandi.online | 0781298701
B-BBEE Level 1 Contributor | 100% Black-Owned | POPIA Reg: 2025-068149