University AI Policy Tracker
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Québec, Canada

Université du Québec

Last checkedMay 21, 2026Last changedMay 21, 2026Review: Agent reviewedConfidence93%
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Record status

Policy statusReviewed evidence-backed recordReview: Agent reviewedClaim coverage5 reviewedEvidence-backed claims5Reviewed5Candidate0Official sources2Source languagefrPublic JSON/api/public/v1/universities/universite-du-quebec.json

Policy profile

Analysis JSONAnalysis review
Coverage score90/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence78%

AI disclosure

Université du Québec has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1
Claim claim-uq-ai-transparency

Privacy and data entry

Université du Québec has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence79%Evidence1Sources1
Claim claim-uq-ai-confidentiality

Approved tools

No source-backed public claim identifying approved or licensed AI tools is present in this profile.

The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Named AI services

Université du Québec has 1 source-backed public claim for named ai services; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence79%Evidence1Sources1
Claim claim-uq-ai-confidentiality

Teaching guidance

Université du Québec has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence78%Evidence1Sources1
Claim claim-uq-ai-human-responsibility

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

AI tools

Tools directory
Derived tool records0

No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.

Evidence-backed claims

5 reviewed evidence-backed public claim

Source Status

Université du Québec states that its Conseil des études adopted a network-level principles statement on responsible use of generative AI in formation and research.

Review: Agent reviewedConfidence93%

Normalized value: network_principles_statement_adopted

Last checked
May 21, 2026
Last changed
May 21, 2026

Original evidence

Evidence 1
Le Conseil des études de l’Université du Québec (UQ) a récemment adopté un énoncé de principes sur l’utilisation responsable de l’intelligence artificielle générative dans les activités de formation et de recherche.

Localized display only

The UQ Conseil des études adopted a principles statement on responsible generative AI use in formation and research.

Source language
Francais (fr)
Snapshot hash
00026a29a022d3001cb7ea2cd73f37971a471f4fecf22a1d8866958defd38be9
Retrieved
May 21, 2026
Evidence locator
Press release body, first paragraph

Privacy

Université du Québec's principles state that public generative AI prompts must not include confidential information or non-public personal information unless competent authorities expressly authorize it.

Review: Agent reviewedConfidence93%

Normalized value: no_confidential_or_non_public_personal_information_in_public_iag_prompts_without_authorization

Last checked
May 21, 2026
Last changed
May 21, 2026

Original evidence

Evidence 1
À moins d’une autorisation expresse des autorités compétentes, les requêtes faites à un système d’IAg public ne doivent pas comprendre d’informations confidentielles ou de renseignements personnels qui ne sont pas publiquement accessibles.

Localized display only

Unless expressly authorized by competent authorities, prompts to public generative AI systems must not include confidential information or non-public personal information.

Source language
Francais (fr)
Snapshot hash
0d3c96ac7aef169108e7cd4430212cb0adf85b8a2b87ee9ed1ff9d47001c8407
Retrieved
May 21, 2026
Evidence locator
PDF, Principes, Sécurité et confidentialité des informations

Teaching

Université du Québec's principles state that when generative AI is used in formation or research, the university member remains responsible for work quality and consequences, and AI must not replace human judgment and responsibility.

Review: Agent reviewedConfidence92%

Normalized value: human_responsibility_required_for_iag_use

Last checked
May 21, 2026
Last changed
May 21, 2026

Original evidence

Evidence 1
Lorsqu’il fait appel à l’intelligence artificielle générative dans le cadre de la formation ou de la recherche, l’universitaire demeure responsable de la qualité de son travail et imputable des conséquences de ses actions.

Localized display only

When generative AI is used for formation or research, the university member remains responsible for work quality and consequences.

Source language
Francais (fr)
Snapshot hash
0d3c96ac7aef169108e7cd4430212cb0adf85b8a2b87ee9ed1ff9d47001c8407
Retrieved
May 21, 2026
Evidence locator
PDF, Principes, Responsabilité humaine

Academic Integrity

Université du Québec's principles state that significant use of generative AI should be explicitly mentioned, including how and to what extent it was used.

Review: Agent reviewedConfidence91%

Normalized value: significant_iag_use_should_be_disclosed

Last checked
May 21, 2026
Last changed
May 21, 2026

Original evidence

Evidence 1
Toute utilisation significative de l'IAg doit être explicitement mentionnée, en précisant comment et dans quelle mesure elle a été utilisée.

Localized display only

Any significant use of generative AI should be explicitly mentioned, including how and to what extent it was used.

Source language
Francais (fr)
Snapshot hash
0d3c96ac7aef169108e7cd4430212cb0adf85b8a2b87ee9ed1ff9d47001c8407
Retrieved
May 21, 2026
Evidence locator
PDF, Principes, Transparence

Academic Integrity

Université du Québec's principles frame generative AI use in formation and research around intellectual integrity, critical and proportionate use, and understanding of AI's operation and risks.

Review: Agent reviewedConfidence90%

Normalized value: integrity_critical_proportionate_and_informed_iag_use

Last checked
May 21, 2026
Last changed
May 21, 2026

Original evidence

Evidence 1
Lorsqu’elle s’inscrit dans une démarche de formation, l’utilisation de l’IAg doit contribuer à l’atteinte de ses objectifs, ce qui suppose un alignement pédagogique soigneusement réfléchi ainsi qu’un usage critique et proportionné.

Localized display only

For formation, generative AI use should support objectives and involve carefully considered pedagogical alignment plus critical, proportionate use.

Source language
Francais (fr)
Snapshot hash
0d3c96ac7aef169108e7cd4430212cb0adf85b8a2b87ee9ed1ff9d47001c8407
Retrieved
May 21, 2026
Evidence locator
PDF, Principes, Intégrité

Original evidence

Evidence 2
L'utilisation de l’IAg dans les activités de formation et de recherche universitaires doit être fondée sur une compréhension adéquate de ses principes généraux de fonctionnement.

Localized display only

Use of generative AI in university formation and research should rest on adequate understanding of its general operating principles.

Source language
Francais (fr)
Snapshot hash
0d3c96ac7aef169108e7cd4430212cb0adf85b8a2b87ee9ed1ff9d47001c8407
Retrieved
May 21, 2026
Evidence locator
PDF, Principes, Usage éclairé

Candidate claims

0 machine or needs-review claim

Official sources

2 source attribution

Change log

Last checkedMay 21, 2026Last changedMay 21, 2026Open change log

Corrections

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