Generative Artificial Intelligence in Doctoral Research Guidelines

All doctoral candidates and doctoral supervisors at Waipapa Taumata Rau, University of Auckland.

To advise doctoral candidates, supervisors, confirmation of candidature committees, and doctoral examiners on the acceptable use of Generative Artificial Intelligence (GenAI) tools in doctoral research and assessment at the University.

These guidelines are intended to help stakeholders navigate the use of GenAI in relation to the University's wider regulatory environment. This includes the PhD Statute, doctoral policies and procedures, and wider policies including academic integrity, research integrity, human research ethics, privacy, copyright, intellectual property, and research data management policy, which should be consulted for further detail. Any use of GenAI tools should also comply with all applicable laws, regulations, and guidelines relevant to the research domain and associated data sources. This includes, for example, the Privacy Act 2020, NEAC standards, professional body guidelines, funder requirements, publisher requirements, and organisational policies.

The following principles should guide all use of GenAI in doctoral research.

Supporting Research Excellence

• GenAI tools, if used, should enhance scholarly inquiry, helping doctoral candidates conduct quality research while developing essential academic skills. These tools should support skill development, not replace it.
  
  
• Supervisor engagement in guiding and critiquing research and writing remains vital for developing researchers' intellectual growth and communication skills.

Research and Academic Integrity

• Doctoral candidates are responsible for ensuring their thesis, and all formally submitted work, represents their own original intellectual contribution, in accordance with the University’s academic and research integrity policies and guidelines.
  
  
• Candidates use of GenAI tools should not compromise the originality or integrity of their work or breach institutional policies and scholarly standards, including the principles of transparency, security and privacy outlined in this document.
  
  
• The use of GenAI tools in ways that contravene University policy may constitute an academic integrity breach, which can lead to reprimands, fines, suspension or expulsion under the Student Academic Conduct Statute.

Transparency and Accountability

• Candidates remain fully responsible for all submitted work and should be prepared to defend it comprehensively, including during confirmation review and examination.
  
  
• All use of GenAI tools must be acknowledged in writing, including within the thesis itself. Candidates should document what tools were used, for what purposes, and how outputs were verified. In many cases this will require methodological justification within the thesis.
  
  
• Where full details are not included in formal submissions of doctoral work (for example, where used only for editing of spelling, punctuation and grammar), candidates should retain evidence of drafts, prompts, raw outputs, and edited final versions of any substantive GenAI use for possible review by supervisors, confirmation panels, or examiners.
  
  
• Further guidance on the use of GenAI in thesis writing is contained within the Third Party Editing and Proofreading of Theses and Dissertations Guidelines and Authorship and Publication Guidelines

Data Security and Privacy

• GenAI tools must be used in ways that protect privacy and confidentiality, meet IT security standards, and minimise risks to individuals and research environments.
  
  
• Many GenAI platforms use inputs to train future models, potentially exposing confidential research data. Therefore, only University-approved platforms may be used when handling internal, sensitive or restricted data, as these provide enhanced data protection as required by the Data Classification Standard and Generative AI Usage Standard.
  
  
• Candidates must obtain appropriate approvals for handling sensitive and restricted data and address these issues in their research data management plan and thesis proposal for discussion during confirmation of candidature.
  
  
• Intended use or creation of GenAI tools in research involving human participants or their data must be detailed in Human Research Ethics applications.

Intellectual Property Protection

• Candidates must protect personal, University, and other stakeholders’ intellectual property interests when using GenAI tools.
  
  
• Sharing innovative ideas or methodologies, or novel data sets, with GenAI platforms may compromise intellectual property rights, potentially allowing others to access and use this information without attribution. Sharing copyrighted materials with GenAI platforms may breach copyright policy and legislation.
  
  
• Candidates should carefully consider these implications before uploading any research content to GenAI platforms.

Accuracy and Bias

• Candidates are responsible for using GenAI in ways that support equity and inclusion across diverse communities. GenAI-generated content can contain inaccuracies, biases, or misleading information.
  
  
• All GenAI outputs should be verified through independent sources and critically evaluated before incorporation into academic work.

Interests and Perspectives of Māori as Articulated in te Tiriti o Waitangi

• In accordance with the Research Data Management Policy, candidates should acknowledge and respect that Māori data, including mātauranga Māori and te reo Māori, are taonga that Māori have te Tiriti o Waitangi-afforded rights to govern and protect. In using GenAI tools, candidates should:
  • Respect Indigenous data sovereignty principles, including Māori and Pacific data sovereignty rights
  • Ensure GenAI tools used do not claim proprietary interest of Māori data, including mātauranga Māori and te reo Māori
  • Consider the sustainability implications of energy-intensive GenAI use, recognising obligations to protect te taiao (the environment) under te Tiriti o Waitangi

Supervisor Consultation and Concerns

• Before using any GenAI tools in their research or communications with supervisors, doctoral candidates and supervisors are expected to discuss whether GenAI can and should be used in the context of the candidate’s specific research project and candidature. This should be discussed as early as possible during candidature to ensure alignment of supervisor and candidate expectations.
  
  
• Any intended GenAI use should be explicitly approved by the supervisory team. The agreed approach should be documented in writing through meeting minutes or email correspondence and detailed in the candidate's full thesis proposal for discussion during confirmation of candidature. Discussions should continue, and approvals should be updated or amended as appropriate throughout candidature.
  
  
• Supervisors should not upload any portion of a candidate's thesis to any GenAI platform without the candidate’s knowledge. 
  
  
• Supervisors should not employ GenAI detection software when reviewing candidates’ writing. Supervisors who have concerns about inappropriate or undisclosed GenAI use should discuss this with their candidate, and in the first instance seek to guide them toward appropriate usage. Where concerns are substantial and/or continued despite explicit concerns or expectations having been discussed and documented, supervisors may consult with their Academic Head, an Academic Integrity Adviser and/or Associate Dean/Director Postgraduate Research and may raise a report in accordance with the Student Academic Conduct Statute.

Candidate Preparedness

• Candidates who have used GenAI tools should be prepared to demonstrate comprehensive understanding of their research during their confirmation of candidature review and oral examination. This includes the ability to:
  
  
  • Explain and justify research decisions and methodologies
  • Discuss cited sources in detail and place them within broader scholarly contexts
  • Articulate original contributions and their significance to the field
  • Describe how their work addresses identified gaps in existing literature
     
• Candidates must include a Declaration of GenAI Use with their full thesis proposal at the time of confirmation review and in their thesis submitted for examination, as is required under the Doctoral Confirmation of Candidature Policy and Procedures and Doctoral Thesis Policy and Procedures.
  
  
• Where GenAI use has compromised a candidate's deep engagement with their research, they may find themselves unable to respond satisfactorily to confirmation committee or examiner questions, potentially affecting their confirmation or examination outcome.

Examiner Guidelines

• To maintain the integrity and confidentiality of the examination process and protect the candidate’s intellectual property, thesis examiners should not:
  
  
  • Upload any portion of a candidate's thesis to any GenAI platform
  • Employ external GenAI detection software when assessing submissions
     
• Examiners who have concerns about inappropriate or undisclosed GenAI use should raise these in their examiner's report so the University can investigate.
  

Policy Hierarchy

• In relation to doctoral research, these doctoral-specific guidelines take precedence over any general University GenAI guidelines for staff, undergraduate coursework, assessment, or research.

The following definitions apply to this document:

Generative artificial intelligence (GenAI) has the meaning set out in the Generative Artificial Intelligence Usage Standard.

Doctoral candidates are students who are enrolled in, or under examination for doctoral degrees at the University.

Supervisor has the meaning set out in the Doctoral Supervision Policy and Procedures

University means Waipapa Taumata Rau, University of Auckland and includes all subsidiaries.

• PhD Statute
• Student Academic Conduct Statute
• Academic Integrity Policies & Guidelines
• Copyright Materials Policy
• Doctoral Confirmation of Candidature Policy and Procedures
• Doctoral Supervision Policy & Procedures
• Doctoral Thesis Policy and Procedures
• Ethics Review of Proposals Involving Human Participants Policy
• Intellectual Property Created by Staff and Students Policy
• IT Security Policy
• Privacy Policy
• Research Integrity Policy
• Research Data Management Policy
• Authorship and Publication Guidelines
• Third Parting Editing and Proofreading of Theses and Dissertations Guidelines
• Data classification standard
• Generative AI Usage Standard

Owned by: Pro Vice-Chancellor Global and Graduate Research
Content manager: Senior Manager, Researcher Development and Doctoral Experiences
Approved by: Graduate Research Committee
Date approved: March 2026
Next Review date: March 2027