Sydney, Australia

Macquarie University (Sydney, Australia)

Macquarie University (Sydney, Australia) is listed as QS 2026 rank =138. Macquarie University (Sydney, Australia) has 9 source-backed AI policy claim records from 7 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Macquarie University (Sydney, Australia) is listed as QS 2026 rank =138. Macquarie University (Sydney, Australia) has 9 source-backed AI policy claim records from 7 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 Macquarie University (Sydney, Australia) as an agent-reviewed AI policy record last checked on May 14, 2026 and last changed on May 14, 2026. The record contains 9 source-backed claims, including 9 reviewed claims, from 7 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/macquarie-university.json. The entity-level confidence is 97%. 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.

Claim coverage9 reviewedSource languageen, en-AUPublic JSON/api/public/v1/universities/macquarie-university.json

Policy signals in this record

  • Evidence includes Academic integrity claims.
  • Evidence includes AI tool treatment claims.
  • Evidence includes Research claims.
  • Evidence includes Security review claims.
  • Evidence includes Privacy claims.
  • Evidence includes Teaching claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims9Reviewed9Candidate0Official sources7

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 score100/100Coverage 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.

Teaching guidance

Macquarie University (Sydney, Australia) has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1

Security and procurement

Macquarie University (Sydney, Australia) has 1 source-backed public claim for security and procurement; deterministic analysis status: allowed.

AllowedMachine candidateConfidence80%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

9 reviewed evidence-backed public claim

Academic Integrity

Macquarie's Academic Integrity Policy treats unauthorised use of generative AI in an academic exercise as unacceptable academic conduct that may lead to an academic integrity breach allegation.

Review: Agent reviewedConfidence97%

Normalized value: unauthorised_genai_unacceptable_academic_conduct

Original evidence

Evidence 1
Unacceptable Academic Conduct may lead to an allegation of an academic integrity breach... Unauthorised use of generative artificial intelligence occurs when a student uses material produced by a generative artificial intelligence in an academic exercise, without authorisation and submits it as their own work.

Localized display only

Unauthorised GenAI use is explicitly listed as unacceptable academic conduct in the Academic Integrity Policy.

Ai Tool Treatment

Macquarie University's Responsible and Ethical Use of Artificial Intelligence Policy applies to staff, students, and affiliates across all uses of AI and sets eight principles for responsible and ethical AI use.

Review: Agent reviewedConfidence96%

Normalized value: ai_policy_applies_staff_students_affiliates_all_ai_uses_eight_principles

Original evidence

Evidence 1
This Policy outlines the principles that support the responsible and ethical use of Artificial Intelligence (AI) at Macquarie University. This Policy applies to all Staff, Students and Affiliates of the University, encompassing all uses of Artificial Intelligence (AI) by these groups.

Localized display only

The policy is university-wide for staff, students, and affiliates and covers all AI uses under responsible and ethical AI principles.

Research

Macquarie's research guidance says researchers must not use generative AI for peer review activities, substantive research-output content including HDR theses, or critical components of human ethics, animal ethics, or biosafety applications.

Review: Agent reviewedConfidence96%

Normalized value: research_genai_not_for_peer_review_substantive_outputs_critical_ethics_biosafety

Original evidence

Evidence 1
Researchers must not use Generative AI: to perform peer review activities; to generate substantive content of research outputs, including HDR theses; for writing the critical components of human ethics, animal ethics, or biosafety applications.

Localized display only

The research guidance sets explicit prohibited research uses for GenAI.

Academic Integrity

Macquarie student guidance categorises assessment tasks as Open or Observed: Open tasks allow generative AI with acknowledgement and student responsibility, while Observed tasks may restrict or prohibit AI use.

Review: Agent reviewedConfidence95%

Normalized value: assessment_open_or_observed_open_acknowledge_observed_restricted_or_prohibited

Original evidence

Evidence 1
Your assessment tasks will be categorised as either Open or Observed. Open assessments do not restrict the application of AI tools. However, it is expected that the use of AI is acknowledged in an appropriate manner... Observed tasks are either fully or partly observed or invigilated. AI use will either not be permitted or might be restricted in a particular way during the assessment.

Localized display only

Assessment AI permissions are task-specific: Open allows AI with acknowledgement; Observed may restrict or prohibit it.

Security Review

Macquarie's AI policy says University-provided AI tools and systems are subject to privacy, security, intellectual-property, intended-use, and risk-assessment controls.

Review: Agent reviewedConfidence94%

Normalized value: ai_tools_privacy_security_ip_intended_use_risk_assessment_controls

Original evidence

Evidence 1
The University will undertake regular assessments to ensure that the use of AI systems and tools does not compromise data security or intellectual property rights and complies with University policy. Users of AI tools and systems provided by the University must use these for their intended purpose... A risk assessment will be conducted by the Head of AI prior to the implementation of an AI system.

Localized display only

Macquarie links AI systems to security/IP checks, intended-use requirements, and risk assessment before implementation.

Privacy

Macquarie's research guidance says researchers using generative AI should mitigate sensitive-data risks, keep oversight and control, critically review outputs, and disclose or acknowledge generative AI use in research.

Review: Agent reviewedConfidence92%

Normalized value: research_genai_sensitive_data_risk_oversight_critical_review_disclosure

Original evidence

Evidence 1
Researchers must exercise care in the use of Generative AI in other aspects of their research and should... mitigate risks around the insecure storage or unauthorised re-use of sensitive data... exert oversight and control... carefully and critically review the output and results created by Generative AI... their use must be acknowledged and disclosed.

Localized display only

The research guidance requires careful controls around sensitive data, oversight, review, and disclosure of GenAI use.

Teaching

Macquarie student assessment guidance says Unit Guides are the definitive source for whether a task is Open or Observed, with iLearn providing more detailed assessment information.

Review: Agent reviewedConfidence90%

Normalized value: unit_guides_definitive_assessment_ai_information_ilearn_more_details

Original evidence

Evidence 1
Unit Guides are your definitive source for assessment information. Your unit guide will show you whether a task is Open or Observed. iLearn is typically where you'll find more comprehensive information about your assessments.

Localized display only

Students should use Unit Guides and iLearn to confirm assessment-specific AI permissions.

Academic Integrity

Macquarie Library referencing guidance says students who use generative AI in assessments should clearly state how they used it and fact-check AI responses against reliable sources.

Review: Agent reviewedConfidence88%

Normalized value: students_should_state_ai_use_and_fact_check_ai_responses

Original evidence

Evidence 1
If you use generative AI in your assessments, you should clearly state how you used it. Generative AI tools can produce inaccurate, biased, or outdated information and may collect personal data. Investigate each tool before using it and fact check all responses using reliable sources such as textbooks, peer reviewed articles, and reference works.

Localized display only

Students are told to disclose assessment AI use and verify AI outputs using reliable sources.

Ai Tool Treatment

Macquarie Library student guidance lists several MQ-accessible AI-enabled tools and tells students in AI-Open assessments to check AI output carefully and acknowledge AI use.

Review: Agent reviewedConfidence87%

Normalized value: library_lists_mq_accessible_ai_tools_ai_open_check_output_acknowledge_use

Original evidence

Evidence 1
Macquarie provides a suite of AI-enabled tools to support your learning... MQ Virtual Peer... MultiSearch Research Assistant... Web of Science Research Assistant... Studiosity... Microsoft Copilot... Adobe Express... Google Scholar Labs... While AI tools are permitted in OPEN assessment, you are responsible for the content of your assignment... Always check AI generated output carefully. Don't forget to acknowledge your use of AI.

Localized display only

The library guide frames listed tools as MQ-accessible learning supports and repeats responsibility, checking, and acknowledgement expectations.

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

7 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 14, 2026Last changedMay 14, 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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