Policy presence
Queen's University at Kingston has 3 source-backed public claims for policy presence; deterministic analysis status: unclear.
Kingston, Canada
Queen's University at Kingston
Queen's University at Kingston is listed as QS 2026 rank =191. Queen's University at Kingston has 7 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Queen's University at Kingston is listed as QS 2026 rank =191. Queen's University at Kingston has 7 source-backed AI policy claim records from 6 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Queen's University at Kingston as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 7 source-backed claims, including 7 reviewed claims, from 6 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/queens-university-at-kingston.json. The entity-level confidence is 92%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Privacy claims.
- Evidence includes Security review claims.
- Evidence includes Teaching claims.
- Evidence includes Other policy claims.
- Evidence includes Academic integrity claims.
- Named AI services detected in public claims: Microsoft Copilot.
- Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
- Privacy, sensitive-data, or security language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Coursework
Queen's University at Kingston has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
Queen's University at Kingston has 3 source-backed public claims for exams; deterministic analysis status: conditionally_allowed.
Privacy and data entry
Queen's University at Kingston has 3 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
Queen's University at Kingston has 1 source-backed public claim for academic integrity; deterministic analysis status: conditionally_allowed.
Approved tools
Queen's University at Kingston has 2 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
Queen's University at Kingston has 2 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
Queen's University at Kingston has 3 source-backed public claims for teaching guidance; deterministic analysis status: recommended.
Research guidance
No source-backed public claim about research AI use is present in this profile.
The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.
Security and procurement
Queen's University at Kingston has 2 source-backed public claims for security and procurement; deterministic analysis status: restricted.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
7 reviewed evidence-backed public claim
Privacy
Queen's guidance directs users working with internal or confidential data to use only Queen's-approved AI tools such as LibreChat and Microsoft Copilot with Queen's single sign-on.
Review: Agent reviewed
Normalized value: internal-confidential-data-approved-ai-tools
Original evidence
Evidence 1If you are using internal or confidential data, use only Queen’s-approved AI tools like LibreChat and Microsoft Copilot with Queen’s single sign-on. If only general data is involved, external tools may be acceptable with caution.
Security Review
Queen's AI Applications page states that the university has conducted security and privacy assessments for generative AI software and uses those assessments to identify risks and inform use guidelines.
Review: Agent reviewed
Normalized value: ai-applications-security-privacy-assessed
Original evidence
Evidence 1To ensure the safe and appropriate use of generative AI software, the university has conducted a series of security and privacy assessments through the Security Assessment Process (SAP). These evaluations help identify potential risks, protect user privacy and institutional data, and inform appropriate use guidelines.
Teaching
Queen's common course policies state that course outlines will include a statement indicating whether generative AI tools are permitted in a course and under what conditions.
Review: Agent reviewed
Normalized value: course-outline-ai-permission-statement
Original evidence
Evidence 1Statement and Guidance for Generative Artificial Intelligence (AI) Tools Your course outline will include a statement indicating whether generative AI tools are permitted in your course and under what conditions. Review that statement carefully and speak with your instructor if you have questions.
Other
Queen's describes responsible generative AI use through five guiding principles for students, staff, and faculty, including checks for whether a use is prohibited, permitted, encouraged, or required.
Review: Agent reviewed
Normalized value: responsible-ai-guiding-principles
Original evidence
Evidence 1Queen’s promotes the responsible use of generative AI across our community and has defined five guiding principles to help students, staff, and faculty make informed, effective decisions about integrating it into their work. Each principle below includes quick self-assessment questions to help users judge whether a use is prohibited, permitted, encouraged, or required.
Teaching
Queen's CTL guidance says instructors should specify parameters for AI tool use in courses and advise on terms of use through a syllabus statement.
Review: Agent reviewed
Normalized value: instructors-specify-ai-use-parameters-syllabus
Original evidence
Evidence 1Provide students guidance: Instructors should specify the parameters for AI tool use in their courses and advise on terms of use via a syllabus statement. Academic integrity: Unauthorized use of generative AI is considered a departure from academic integrity.
Academic Integrity
Queen's Library Generative AI guide says unauthorized use of generative AI tools is considered a departure from academic integrity.
Review: Agent reviewed
Normalized value: unauthorized-generative-ai-departure-academic-integrity
Original evidence
Evidence 1As of July 2024: There is no overall ban on the use of generative AI tools. Instructors should provide students with specific parameters for AI use in the course syllabus. Unauthorized use of generative AI tools is considered a "departure from academic integrity."
Privacy
Queen's Library Generative AI privacy guide warns users not to assume that data input into an AI tool is private and confidential.
Review: Agent reviewed
Normalized value: do-not-assume-ai-input-private-confidential
Original evidence
Evidence 1Always read the terms of use or privacy statements of the AI tool you're using. Some AI tools will use your inputted data (and the associated output) to further train or audit their models. Do not assume that any data you input into an AI tool is private and confidential.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
6 source attribution
Academic Integrity - Generative AI
guides.library.queensu.ca
AI Applications
queensu.ca
Common Course Policies and Statements
queensu.ca
Guidelines for Your Course Outline
queensu.ca
Guiding principles for the responsible use of generative AI
queensu.ca
Privacy - Generative AI
guides.library.queensu.ca
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.