Politique de gouvernance de l'IA de la Fondation WITS
Applicable à compter du 1er juillet 2026 · Dernière mise à jour le 27 mai 2026 · Version 1.0
La présente politique explique comment la Fondation WITS utilise l'intelligence artificielle (IA) dans ses produits et services, quelles données transitent par ces systèmes, où ces données sont traitées, et comment les enseignants et les établissements scolaires peuvent avoir confiance dans l'utilisation de l'IA pour soutenir l'enseignement en classe sans compromettre la vie privée des élèves ni la responsabilité pédagogique.
Ce document a été rédigé à l'intention des enseignants, des parents, des responsables d'établissement et des responsables des achats au niveau des académies. Il constitue également la référence incontournable sur laquelle les conseillers juridiques et les responsables de la protection des données peuvent s'appuyer pour évaluer la solution WITS en vue de son adoption.
1. Dans quels domaines WITS utilise-t-il l'IA ?
WITS utilise l'IA dans deux contextes spécifiques. Ces deux contextes sont limités, clairement délimités et peuvent faire l'objet d'un contrôle.
1.1 Le copilote éducateur IA (bêta)
Co-Pilot est un assistant basé sur l'intelligence artificielle qui génère des ébauches d'activités pédagogiques pour les enseignants mettant en œuvre le programme WITS. Il prend en compte le niveau scolaire, une stratégie WITS ou LEADS (telle que “ S'éloigner ” ou “ En discuter ”) et, éventuellement, une note contextuelle fournie par l'enseignant. Il renvoie un projet de plan de cours conforme à la pédagogie WITS.
Le Co-Pilote est actuellement disponible en version bêta supervisée dans 15 à 20 écoles qui ont choisi de participer. Il n'est pas disponible pour tous les abonnés, et le contenu généré est examiné par Amrita Singh (coordonnatrice du programme) avant que toute sortie ne soit référencée extérieurement.
1.2 La ligne d'assistance vocale
Lorsque des enseignants ou des membres du personnel scolaire appellent la ligne d'assistance WITS, les appels peuvent être pris en charge par un assistant vocal basé sur l'IA pour les demandes courantes (questions relatives au compte, rubriques de la FAQ, recherche de ressources). Les demandes plus complexes sont transférées à un membre de l'équipe ou enregistrées pour être examinées par un intervenant humain.
L'assistant vocal ne gère pas les données des étudiants et n'a pas accès aux comptes des abonnés au-delà de l'identification de l'appelant par son numéro de téléphone.
2. Ce que WITS ne fait pas en matière d'IA
Pour être clair sur les limites :
- WITS n'utilise pas l'IA pour évaluer, noter ou attribuer des notes aux élèves
- Le programme WITS n'utilise pas l'intelligence artificielle pour prendre des décisions concernant les élèves à titre individuel (orientation, mesures disciplinaires, classification comportementale, recommandations d'accompagnement).
- WITS n'utilise pas l'IA pour analyser les travaux ou les communications des élèves
- WITS n'utilise pas les données des élèves ni les enregistrements en classe pour entraîner ses modèles d'IA
- WITS ne partage pas les données des élèves avec les fournisseurs d'IA, quelle que soit la manière dont le système est utilisé.
- WITS n'utilise pas l'IA pour générer des communications destinées aux parents sans vérification humaine.
C'est voulu. Le Co-Pilote a pour but de réduire la charge de travail des éducateurs lors de la préparation des leçons. Il ne s'étend pas à l'évaluation ou à la notation des élèves.
3. Où les données sont traitées
3.1 L'architecture de Co-Pilot
Lorsqu'un éducateur soumet une demande de génération Co-Pilot, la demande suit le pipeline suivant :
- Le navigateur de l'enseignant envoie la requête (note, stratégie, remarque facultative) à lessons.wits.foundation, hébergé sur une infrastructure canadienne gérée par la Fondation WITS.
- Le service de routage WITS (LiteLLM) sélectionne le modèle d'IA approprié
- Le modèle renvoie le texte généré au service WITS
- Le service formate et renvoie le plan de leçon à l'éducateur
Pour la période bêta, les modèles d'IA sous-jacents utilisés sont :
| Modèle | Prestataire | Région | Utiliser |
|---|---|---|---|
| Azure OpenAI GPT-4o | Microsoft Azure | Canada Est (Toronto) | Génération primaire |
| Azure OpenAI GPT-5.5 | Microsoft Azure | Canada Est (Toronto) | Évaluation bêta |
Azure Canada East is a Microsoft region located in Toronto, Ontario. Data processed in this region remains in Canada and is subject to Canadian data residency commitments under Microsoft’s Azure Canada agreements.
WITS has the option to swap in a self-hosted model running on WITS infrastructure (NVIDIA Tesla T4 GPU located in British Columbia). When this is enabled, generation does not leave WITS-controlled hardware.
3.2 Voice support architecture
The voice support line uses Twilio for telephony, ElevenLabs for voice synthesis (US-based provider, no PII transmitted), and Azure OpenAI for natural language understanding (Canada East region). Call transcripts are stored in the Zammad helpdesk system, hosted on WITS infrastructure in Canada.
4. What data goes to AI systems
The Co-Pilot receives only:
- Grade level (a number 1-12 or “K”)
- WITS or LEADS strategy name (one of nine fixed values)
- Optional context note (free text, written by the educator)
The Co-Pilot does not receive:
- Student names, ages, or any identifying information
- Student academic records or behavioral data
- The educator’s name, school name, or district (these are passed only to log usage, not to the AI model itself)
- Any uploaded files, images, or attachments
- Any conversation history beyond the current request
If an educator types student-specific information into the optional context note, that data passes to the AI model. The Co-Pilot interface displays a clear warning before submission asking educators not to enter student-identifying details. Compliance with this warning is the educator’s professional responsibility.
5. Conservation des données
| Data type | Retention | Where stored |
|---|---|---|
| Co-Pilot input (grade, strategy, note) | 90 days for audit | PostgreSQL on CT104 (WITS infrastructure, Canada) |
| Co-Pilot output (generated lesson) | 90 days for audit; longer if saved to user’s library | PostgreSQL on CT104 |
| Co-Pilot per-user usage counts | 13 months for reporting | PostgreSQL on CT104 |
| Voice call transcripts | 90 days, then deleted | Zammad on CT208 (WITS infrastructure, Canada) |
| Voice call recordings | Not retained (real-time only) | Not stored |
| Model interaction logs at Azure | Microsoft’s policy (typically 30 days, redacted) | Azure Canada East |
After the retention period, data is permanently deleted from WITS systems. Microsoft Azure retention is governed by Microsoft’s own data processing terms, which WITS has reviewed and accepted under the Azure subscription agreement.
6. Révision humaine
The Co-Pilot is supervised throughout the beta period. Specifically:
- Pre-launch curation: lesson plans generated during the beta are reviewed by Amrita Singh before any are presented as recommended in the portal
- Per-school monitoring: beta cohort schools have a designated WITS contact who reviews aggregated usage and outputs monthly
- User reporting: every Co-Pilot output includes a “Report concern” link that emails program staff. Concerns are reviewed within 5 business days
- Override: educators are reminded that generated content is a draft and that pedagogical judgment remains with the educator
WITS does not currently make Co-Pilot outputs available in real time to non-beta subscribers. Expansion beyond the beta cohort requires sign-off from Andy Telfer and a re-review of this policy.
7. Bias, safety, and quality
7.1 Inappropriate content
The Co-Pilot uses Azure OpenAI’s content safety filters, which block generation of explicit violence, sexual content, hate speech, and self-harm content. These filters are not configurable by WITS. If a generation is blocked, the educator receives a generic “Please rephrase your request” message.
In addition, WITS has implemented topic guardrails that prevent the model from generating content outside its scope (such as legal advice, medical diagnosis, or political commentary).
7.2 Accuracy
Generated lesson plans are drafts. WITS does not represent that every generated plan is pedagogically appropriate without review. Educators are expected to read and adapt the output to their classroom context. The Co-Pilot interface includes a banner stating this expectation on every output.
7.3 Bias
AI models can reflect biases present in their training data. WITS acknowledges this and applies the following safeguards:
- The Co-Pilot has been instructed via system prompt to use inclusive, culturally responsive language
- Examples and references in generated content are drawn from WITS-approved literature and resources
- Indigenous content is flagged for human review before publication or recommendation
- Educators in the beta are surveyed quarterly on perceived bias in outputs
If bias issues are identified, WITS will adjust the system prompt and, if necessary, restrict the model from generating in affected categories until corrections are validated.
8. Droit de retrait et droits d'accès
8.1 For educators
Educators can opt out of Co-Pilot usage at any time. There is no penalty and no reduction in other WITS services. Opting out removes the user’s account from beta access and deletes all Co-Pilot interaction history within 30 days.
Educators may request a copy of their Co-Pilot generation history by emailing [email protected]. Requests are fulfilled within 30 days.
8.2 For schools and districts
A school principal or district administrator can request that all educators at their school or district be excluded from the Co-Pilot beta. Such requests are honored within 5 business days.
District procurement teams may request a technical and legal review session with WITS staff before adopting any AI-enabled feature. Contact [email protected] to schedule.
8.3 For parents
Parents who wish to inquire about AI use in their child’s WITS classroom should contact their school directly. WITS does not maintain a direct relationship with families.
9. Réponse aux incidents
If an AI-related incident occurs (data breach, unintended disclosure, prolonged unavailability, generation of harmful content despite safeguards), WITS commits to:
- Containing the incident within 24 hours of detection
- Notifying affected schools within 72 hours
- Providing a written incident report within 14 days
- Reporting to the Office of the Privacy Commissioner of Canada and provincial privacy regulators if personal information is implicated
The WITS incident response procedure is documented separately and reviewed annually.
10. Cadres de conformité
This policy aligns with the following Canadian and international frameworks:
- Personal Information Protection and Electronic Documents Act (PIPEDA)
- Personal Information Protection Act of British Columbia (PIPA BC)
- Canada’s Anti-Spam Legislation (CASL) for AI-generated email communications
- The Office of the Privacy Commissioner of Canada’s “Principles for responsible, trustworthy and privacy-protective generative AI technologies” (December 2023)
- The Treasury Board of Canada’s Directive on Automated Decision-Making (where applicable, noting that WITS does not currently make automated decisions about individuals)
WITS engages BLG (Borden Ladner Gervais LLP) for ongoing legal review of AI deployments and privacy compliance.
11. Modifications de cette politique
This policy is reviewed at minimum annually and whenever a substantive change is made to an AI system in WITS products. Changes are communicated to subscribers via email at least 30 days before taking effect.
Version history is maintained at the policy changelog.
12. Contact
| Topic | Contact |
|---|---|
| Privacy questions about this policy | [email protected] |
| Co-Pilot beta opt-out | [email protected] |
| District procurement review | [email protected] |
| Reporting an AI-related concern | [email protected] |
| General inquiries | [email protected] |
Annexe A : Glossaire
AI (Artificial Intelligence): software that performs tasks typically requiring human intelligence, such as language understanding or text generation. The AI systems WITS uses are based on large language models.
Beta: a limited, supervised release of a feature to a small group of users before general availability.
Co-Pilot: the WITS AI-powered lesson planning assistant.
LiteLLM: a software service that routes requests to different AI models. WITS uses LiteLLM to control which model handles which request and to maintain consistent logging and access control.
LLM (Large Language Model): an AI system trained on large volumes of text to generate human-like language. Examples used by WITS include Azure OpenAI GPT-4o.
PIPEDA / PIPA BC: Canadian and British Columbia privacy laws governing how organizations handle personal information.
System prompt: internal instructions given to an AI model that shape its behavior. The WITS Co-Pilot system prompt directs the model toward inclusive, age-appropriate, WITS-aligned content.
Appendix B: Technical reference for procurement reviewers
This section provides the technical depth a district CIO or privacy officer may need.
B.1 Data flow diagram
Educator browser
HTTPS POST {grade, strategy, note}
[lessons.wits.foundation - WITS infrastructure, BC, Canada]
Validates JWT (educator must be authenticated subscriber + beta opt-in)
Logs request to PostgreSQL CT104
HTTPS POST to LiteLLM proxy
[LiteLLM proxy - WITS infrastructure, BC, Canada]
Selects model by routing rule (default: Azure GPT-4o)
HTTPS POST to Azure OpenAI endpoint
[Azure OpenAI - Microsoft Canada East, Toronto, Ontario]
Processes request
Returns generated text
[LiteLLM proxy]
Returns response to lessons service
[lessons.wits.foundation]
Logs response, applies branding to lesson PDF
Returns to educator browser
B.2 Authentication and authorization
- Educator must hold an active WITS subscription
- Educator’s account must have beta-opt-in flag set
- Generation requests use a short-lived JWT issued by the WITS portal
- JWT contains user ID, school ID (NocoDB), and beta flag, signed with the WITS private key
- The CT119 service validates JWT signature and expiry before forwarding
B.3 Audit trail
Every generation request is recorded with:
- Timestamp (UTC)
- User ID (WordPress)
- School ID (NocoDB)
- Strategy and grade
- Hash of optional context note (not the note itself)
- Model selected
- Response time
- Token usage (input/output)
Audit data is queryable by program staff and reviewable in monthly compliance summaries.
B.4 Network and infrastructure
WITS infrastructure relevant to the Co-Pilot:
- CT119 (lessons.wits.foundation): FastAPI application, Python 3.12, runs on a Proxmox cluster in Burnaby, BC
- CT104 (PostgreSQL 17): database for audit logs, runs on the same cluster
- CT106 (LiteLLM proxy): model routing, runs on the same cluster
- CT110 (Ollama, optional): local model inference on NVIDIA T4 GPU, used if Azure becomes unavailable
All traffic between the educator browser and lessons.wits.foundation is TLS 1.2+ encrypted. All traffic between WITS services and Azure is TLS-encrypted. No data is transmitted unencrypted.