Policy presence
The University of Auckland has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Auckland, New Zealand
The University of Auckland
The University of Auckland is listed as QS 2026 rank 65. The University of Auckland has 7 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
The University of Auckland is listed as QS 2026 rank 65. The University of Auckland has 7 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.
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
The University of Auckland has 1 source-backed public claim for ai disclosure; deterministic analysis status: recommended.
Coursework
The University of Auckland has 5 source-backed public claims for coursework; deterministic analysis status: restricted.
Exams
The University of Auckland has 5 source-backed public claims for exams; deterministic analysis status: restricted.
Privacy and data entry
The University of Auckland has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.
Academic integrity
The University of Auckland has 3 source-backed public claims for academic integrity; deterministic analysis status: restricted.
Approved tools
The University of Auckland has 2 source-backed public claims for approved tools; deterministic analysis status: restricted.
Named AI services
The University of Auckland has 3 source-backed public claims for named ai services; deterministic analysis status: restricted.
Teaching guidance
The University of Auckland has 2 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
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.
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
Ai Tool Treatment
The University of Auckland's Assessment of Courses Procedures state that AI use in assessment tasks may only be restricted when the task is a controlled assessment, identified as Lane 1; AI may be used without restriction in other assessment tasks, identified as Lane 2.
Review: Agent reviewed
Normalized value: Two-lane assessment rule: AI restrictions only for controlled Lane 1 tasks; Lane 2 unrestricted
Original evidence
Evidence 1In accordance with the University's two-lane approach, the use of artificial intelligence (AI) in assessment tasks may only be restricted if the assessment task is a controlled assessment (lane 1). AI may be used without restriction in all other assessment tasks (lane 2).
Localized display only
The assessment procedure limits AI restrictions to controlled Lane 1 assessments and says AI may be used without restriction in Lane 2 tasks.
Teaching
The University of Auckland's Assessment of Courses Procedures require courses to use the two-lane nomenclature, including telling students which assessments align with Lane 1 or Lane 2, and require courses and programmes to implement the two-lane approach in assessment design by 2027.
Review: Agent reviewed
Normalized value: Courses must label assessment lanes and implement two-lane design by 2027
Original evidence
Evidence 1Courses must use nomenclature of the two-lane approach, including specifying to students which assessments align with lane 1 or lane 2. Courses and programmes will be required to implement the two-lane approach in assessment design by 2027.
Localized display only
Courses must identify Lane 1/Lane 2 assessments and implement the two-lane assessment approach by 2027.
Academic Integrity
The University of Auckland's student AI advice states that AI has no agency, treats the student prompting an AI tool as the author, and says students are ultimately responsible for work submitted for assessment.
Review: Agent reviewed
Normalized value: Student remains author/responsible party for AI-generated assessment work
Original evidence
Evidence 1The university takes the position that AI has no agency. What this means is that the student who is prompting the AI tool is to be treated as the author. As the author, each student is responsible for the work generated by the AI tool, and this may include expressly acknowledging the use of the tool.
Localized display only
The student AI advice treats the student prompting AI as the author and responsible for AI-generated work.
Academic Integrity
The University of Auckland's permitted-software assessment guideline says Gen-AI may not be permitted for assessment activities where the assessed skills overlap with functions performed by Gen-AI, and says use of non-permitted software may be considered a breach of academic integrity.
Review: Agent reviewed
Normalized value: Gen-AI may be disallowed where it overlaps assessed skills; non-permitted software may breach academic integrity
Original evidence
Evidence 1Generative AI (Gen-AI) may not be permitted for assessment activities where the skills assessed overlap with functions performed by Gen-AI. Use of software which is not permitted may be considered a breach of academic integrity and of the Student Academic Conduct Statute.
Localized display only
The guideline says Gen-AI may be non-permitted where it overlaps assessed skills, and non-permitted software use may breach academic integrity.
Ai Tool Treatment
The University of Auckland TeachWell two-lane assessment guidance says the University does not endorse third-party AI detection tools, citing unreliability, false positives, and possible student-data training risks.
Review: Agent reviewed
Normalized value: University does not endorse third-party AI detection tools
Original evidence
Evidence 1The University of Auckland does not endorse the use of third-party AI detection tools, as these may be unreliable, create false positives, and may use student data to train their models.
Localized display only
TeachWell states that the University does not endorse third-party AI detection tools.
Academic Integrity
Auckland Law School's student AI guidelines for taught courses state that using AI to generate, draft, or assist in creating content for graded assignments is prohibited unless the instructor explicitly permits it in writing.
Review: Agent reviewed
Normalized value: Faculty of Law default prohibition on AI-generated graded assignment content unless explicitly permitted
Original evidence
Evidence 1The use of AI to generate, draft, or assist in creating content for any graded assignment is prohibited, unless your instructor explicitly permits otherwise in writing (in your course outline or on Canvas).
Localized display only
Auckland Law School says AI-generated or AI-assisted content for graded assignments is prohibited unless the instructor explicitly permits it in writing.
Privacy
The University of Auckland's public TeachWell explainer for the AI Usage Standard says users should assess data against the University's data classification before submitting it to an AI tool, and says restricted data should not be used with AI chat services.
Review: Agent reviewed
Normalized value: AI use must account for University data classification; restricted data not for AI chat services
Original evidence
Evidence 1For example, it requires you to assess any data according to the University's data classification before you submit the data to an AI tool. The University has four data classifications: public, internal, sensitive, restricted. You should only use AI tools that are appropriate for the type of data you're working with.
Localized display only
The public AI Usage Standard explainer says data classification should be assessed before submitting data to AI tools.
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
Advice for students on using Artificial Intelligence
auckland.ac.nz
Assessment of Courses Procedures
auckland.ac.nz
Guidelines on permitted use of software in assessment activities
auckland.ac.nz
Learn about the University's AI Usage Standard
teachwell.auckland.ac.nz
Student guidelines for using Artificial Intelligence (AI) in taught courses
auckland.ac.nz
The use of AI tools in coursework
teachwell.auckland.ac.nz
Two-Lane Approach to assessment
teachwell.auckland.ac.nz
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.