- \n
- Access to AUT\u2019s \u2018trust assessments\u2019 of frequently used AI tools<\/li>\n\n\n\n
- Guidance on the sensitivity of different types of data <\/li>\n\n\n\n
- AUT\u2019s \u201cOur AI Future\u201d report, detailing AUT\u2019s overall approach to AI <\/li>\n\n\n\n
- A guide to best practice, with practical tips for getting the best from AI tools <\/li>\n\n\n\n
- Self-checklists, assessments, and sample text for recording and disclosing your AI usage <\/li>\n\n\n\n
- Links to relevant workshops <\/li>\n<\/ul>\n\n\n\n
- <\/ul>\n\n\n\n
- Researcher responsibility and authorship: <\/strong>you remain fully accountable for all outputs. <\/li>\n<\/ol>\n\n\n\n
- \n
- Data sensitivity and ethics compliance: <\/strong>choose your AI tools carefully (considering AUT’s trust assessments<\/a>), be cautious with what data you input<\/a>, and make sure you stay within your ethical approval.<\/li>\n<\/ol>\n\n\n\n
- \n
- Transparency<\/strong>: always disclose your use of AI, and when in doubt, over<\/em>-disclose. You can use AUT’s AI Declaration Template<\/strong> for this purpose (available from PG forms here<\/a>). <\/li>\n<\/ol>\n\n\n\n
- \n
- Publisher, funder, and examination policy compliance:<\/strong> comply with other parties’ guidance where relevant.<\/li>\n<\/ol>\n\n\n\n
- \n
- Respect for data sovereignty:<\/strong> be aware that data can be considered sensitive by different people, cultures, and communities; and consider whether your planned use of AI may put data sovereignty at risk.<\/li>\n<\/ol>\n\n\n\n
\n\n\n\nCan I use AI tool X to do task Y?<\/h4>\n\n\n\n
The annoying answer is: it depends<\/em>. <\/p>\n\n\n\n
‘Appropriate’ AI use can vary a lot depending on your discipline, the type of data you’re working with, and the specifics of your project, methodology\/methods, and research questions. That’s why you’ve really got to discuss any planned AI use with your supervisors to get project-specific advice. <\/p>\n\n\n\n
That being said, there are some ways you can check how appropriate your planned AI use could be. <\/p>\n\n\n\n
Check the trust assessment<\/a> on your tool of choice: <\/strong>AUT’s IT department trawls through the fine print on many AI tools to check how ‘trustworthy’ they are in terms of data privacy and security. Give preference to tools marked ‘high trust’ or ‘very high trust,’ and avoid tools marked ‘low trust’ or ‘no trust’. <\/p>\n\n\n\n
Check the sensitivity of your data<\/a>: <\/strong>Some types of data are more sensitive than others, and require a higher level of caution when using AI. See the examples of data sensitivity levels to assess how sensitive your data might be. <\/p>\n\n\n\n
Discuss with supervisors and advisors:<\/strong> Talk your plans and intentions through with your supervisors, and ensure any action is aligned with your ethics approval. You may also like to speak with specialist advisors – for example ethics advisors<\/a>, library research specialists<\/a>, cultural advisors, copyright librarians<\/a>, intellectual property specialists, etc. <\/p>\n\n\n\n
Disclose, disclose, disclose: <\/strong>Make sure you keep a live and up-to-date copy of the AI Declaration Template<\/strong> (available from PG forms here<\/a>) to document your use of AI – including the exact prompts you used and how you worked with any outputs. This should be submitted with your initial research proposal, Confirmation of Candidature document (for doctoral students), and upon submission for examination. <\/p>\n\n\n\n
\n\n\n\nLearn more about AI in research <\/h4>\n\n\n\n
Check out the suite of Library AI workshops<\/a> for research students; and\/or browse this detailed guide to best practice<\/a> for practical tips for getting the best from AI tools. <\/p>\n","protected":false},"excerpt":{"rendered":"
In case you missed the news last week, AUT has a whole lot of new AI resources for postgraduate research students! The new ‘AI in postgraduate research’ website collates all sorts of useful things, […]<\/p>\n","protected":false},"author":25632,"featured_media":11167,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[30,8],"tags":[266,252,46,129],"class_list":["post-11166","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-authentic","category-category-3","tag-ai","tag-artificial-intelligence","tag-aut","tag-online-resources"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/thesislink.aut.ac.nz\/wp-content\/uploads\/AI-concept-image-scaled.jpg?fit=2560%2C1440&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p83npQ-2U6","_links":{"self":[{"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/posts\/11166","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/users\/25632"}],"replies":[{"embeddable":true,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11166"}],"version-history":[{"count":2,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/posts\/11166\/revisions"}],"predecessor-version":[{"id":11169,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/posts\/11166\/revisions\/11169"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=\/wp\/v2\/media\/11167"}],"wp:attachment":[{"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11166"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11166"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thesislink.aut.ac.nz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
- Respect for data sovereignty:<\/strong> be aware that data can be considered sensitive by different people, cultures, and communities; and consider whether your planned use of AI may put data sovereignty at risk.<\/li>\n<\/ol>\n\n\n\n
- Publisher, funder, and examination policy compliance:<\/strong> comply with other parties’ guidance where relevant.<\/li>\n<\/ol>\n\n\n\n
- Transparency<\/strong>: always disclose your use of AI, and when in doubt, over<\/em>-disclose. You can use AUT’s AI Declaration Template<\/strong> for this purpose (available from PG forms here<\/a>). <\/li>\n<\/ol>\n\n\n\n
- Data sensitivity and ethics compliance: <\/strong>choose your AI tools carefully (considering AUT’s trust assessments<\/a>), be cautious with what data you input<\/a>, and make sure you stay within your ethical approval.<\/li>\n<\/ol>\n\n\n\n
- <\/ul>\n\n\n\n
- <\/ul>\n\n\n\n
Perhaps the most important thing on the website though, is AUT’s new \u201cGuidelines for the Ethical Use of Generative Artificial Intelligence in Research\u201d<\/strong><\/a>. This document cover key risks, mitigation strategies, and five key principles for working with AI in your research. It applies to all AUT staff and postgraduate students doing research. <\/p>\n\n\n\n
This is not the first time there has been guidance on using AI in your postgraduate research. You may be aware of the AI guidance in the Postgraduate Handbook<\/a> (p. 95-98 in the current edition). You can think of these two sets of guidance as working in tandem: the new guidelines for all AUT researchers, and the Postgraduate Handbook guidance giving specificity for postgraduate contexts. <\/p>\n\n\n\n
Want to know more? Read on!<\/p>\n\n\n
\n![\"\"](\"https:\/\/i0.wp.com\/thesislink.aut.ac.nz\/wp-content\/uploads\/AI-concept-image.jpg?resize=1024%2C576&ssl=1\")
<\/figure>\n<\/div>\n\n\n
\n\n\n\nOK, so what’s the TL;DR on the new guidelines?<\/h4>\n\n\n\n
If you are using AI in your research (even in ways that seem ‘minor’ or inconsequential) you should read both sets of guidance and ensure that your use is aligned with them. <\/p>\n\n\n\n
They five key principles in the new guidelines are:<\/p>\n\n\n\n
- \n
- Researcher responsibility and authorship: <\/strong>you remain fully accountable for all outputs. <\/li>\n<\/ol>\n\n\n\n