Toronto, Canada

Toronto Metropolitan University (formerly Ryerson University)

Toronto Metropolitan University (formerly Ryerson University) has 8 source-backed AI policy claims from 3 official source attributions. Review state: agent reviewed; 8 reviewed claims. Last checked May 18, 2026.

Toronto Metropolitan University (formerly Ryerson University) AI policy short answer

v1 public contract

Toronto Metropolitan University (formerly Ryerson University) has 8 source-backed AI policy claims from 3 official source attributions, including 8 reviewed claims. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 18, 2026. Discovery context: Toronto Metropolitan University (formerly Ryerson University) is listed as QS 2026 rank 711-720.

Citation-ready summary

As of this public record, University AI Policy Tracker lists Toronto Metropolitan University (formerly Ryerson University) as an agent-reviewed AI policy record last checked on May 18, 2026 and last changed on May 18, 2026. The record contains 8 source-backed claims, including 8 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/toronto-metropolitan-university-formerly-ryerson-university.json. The entity-level confidence is 95%. 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 Academic integrity claims.
  • Evidence includes Privacy claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Teaching claims.
  • Evidence includes Security review claims.
  • Named AI services detected in public claims: Gemini.
  • 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.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims8Reviewed8Candidate0Official sources3

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.

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence79%

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

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.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Security and procurement

Toronto Metropolitan University (formerly Ryerson University) has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence78%Evidence1Sources1

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

8 reviewed evidence-backed public claim

Academic Integrity

TMU's Academic Integrity Office says students should assume that using AI to complete assessments is prohibited unless the instructor explicitly states otherwise.

Review: Agent reviewedConfidence95%

Normalized value: assessment_ai_use_prohibited_unless_instructor_states_otherwise

Original evidence

Evidence 1
Unless explicitly stated by the instructor, students should assume that using AI to complete assessments is prohibited.

Privacy

TMU's Google AI Tools Help Centre says only public or low-sensitivity information should be entered into TMU's Google AI tools, and sensitive or confidential information should not be used in prompts, uploads, or activities.

Review: Agent reviewedConfidence95%

Normalized value: google_ai_tools_public_or_low_sensitivity_only

Original evidence

Evidence 1
Only public or low-sensitivity information should be input to these tools. Sensitive and confidential information should never be used in prompts, uploaded files or other activities.

Ai Tool Treatment

TMU guidance states that, unless a course instructor explicitly communicates otherwise, GenAI use for coursework is not permitted.

Review: Agent reviewedConfidence94%

Normalized value: course_instructor_permission_required_by_default

Original evidence

Evidence 1
Unless explicitly communicated by the course instructor, the use of GenAI for coursework is not permitted

Academic Integrity

TMU's Academic Integrity Office identifies submitting work created in whole or in part by AI tools, unless expressly permitted by the faculty member or contract lecturer, as a Policy 60 misrepresentation issue.

Review: Agent reviewedConfidence94%

Normalized value: policy60_misrepresentation_ai_work_unless_permitted

Original evidence

Evidence 1
5.5. submitting work created in whole or in part by artificial intelligence tools unless expressly permitted by the Faculty/Contract Lecturer;

Privacy

TMU's GenAI learning and teaching guidance tells users not to submit anyone's personal information into GenAI models without consent or an ability to opt out.

Review: Agent reviewedConfidence93%

Normalized value: do_not_submit_personal_information_without_consent_or_opt_out

Original evidence

Evidence 1
Do not submit anyone’s personal information into GenAI models without consent or ability to opt out and be aware that, in many cases, material uploaded or entered into GenAI tools is used to train future models.

Ai Tool Treatment

TMU says the Gemini App and NotebookLM are available to TMU employees and students and that using a TMU account means activities will not be used to train Google's AI models.

Review: Agent reviewedConfidence93%

Normalized value: tmu_google_ai_tools_not_used_to_train_models_when_using_tmu_account

Original evidence

Evidence 1
Both tools are available to TMU employees and students... By using your TMU account, you can ensure that your data will not be used to train Google's AI models.

Teaching

TMU guidance says AI detectors are not currently endorsed and directs instructors with GenAI misuse concerns to the Academic Integrity Office for investigation recommendations.

Review: Agent reviewedConfidence93%

Normalized value: ai_detectors_not_currently_endorsed

Original evidence

Evidence 1
AI detectors are not currently endorsed by TMU. If you have concerns about unauthorized use of GenAI by students, contact the Academic Integrity Office for recommendations on how to investigate the concern.

Security Review

TMU states that privacy and AI impact assessments and a security risk assessment were conducted before releasing the Gemini App and NotebookLM at TMU.

Review: Agent reviewedConfidence92%

Normalized value: privacy_ai_impact_assessments_and_security_risk_assessment_conducted

Original evidence

Evidence 1
Prior to the release of the Gemini App and NotebookLM at TMU, we conducted privacy and AI impact assessments... and a security risk assessment with the Office of the Chief Information Security Officer.

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

3 source attribution

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.

Last checkedMay 18, 2026Last changedMay 18, 2026Open change log

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.

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