Policies & Guidelines
Policies & guidelines
Generative Artificial Intelligence Task Force Report
On this page:
Senate policy | Guidelines | Administrative policy | Key gaps
TMU currently has several academic and administrative policies that are relevant to the governance of AI use. These include policies covering academic integrity, SRC integrity, course management, grade appeals, information technology use, cybersecurity, and privacy. The university has also developed guidelines for AI use, mainly in the areas of learning and teaching for undergraduate and graduate studies.
As the COU AI task force found,
“rather than introducing new policies, institutions are interpreting and adapting existing frameworks for AI-related issues.” 5
TMU has followed a similar course of action and we suggest that the university continue to modify and adapt existing policies rather than establish standalone AI policies. There is a need, however, for further guidelines on AI use, especially for administrative purposes. To support this work, an AI rubric should be established for academic and administrative policy reviews to help guide future policy updates.
| Document Name | Comments |
| Policy 51: Ethical Conduct for Research Involving Human Participants | The Policy may include additional considerations for data management, use, and storage, including additional details on a data management plan and data analysis pertaining to the use of AI tools. |
| Policy 60: Academic Integrity | Governs all matters of academic misconduct; recent revisions embedding specific language regarding AI in Appendix A, Sections 5.5 and 5.6. |
| Policy 118: Scholarly Research and Creative Activity (SRC) Integrity Policy | Policy recently updated, but may need some additional review to consider potential implications of AI. |
| Policy 162(a): Grade Reassessment and Grade Recalculation | Outlines the formal procedures for students to request a review of a course component grade or final grade calculation. May need updates to account for requests for grade appeal based on use of AI in assessment. |
| Policy 166: Course Management Policy | Provides the framework for course outlines, assessment, and the handling of missed tests/exams. Could potentially stipulate restrictions on use of AI for assessing students. |
| Policy 168: Grade and Standing Appeals | Sets out the principles and procedures governing formal appeals of academic standing and final grades after informal resolution options are exhausted. Grounds may have to be updated to account for use of AI to assess students. |
| Policy 170 (b): Graduate status, enrolment, and Evaluation Policy | The Policy might include language pertaining to requirements for master’s MRP, thesis, and PhD dissertation requirements, and to submission and deposit requirements for theses and dissertations. |
| Policy 171: Scholarly Research and Creative Activity (SRC) Intellectual Property Policy | New draft language to application and scope concerning AI to be added at a future date. |
| Document Name | Comments |
| CELT Principles and Guidelines on Generative Artificial Intelligence in Learning and Teaching at TMU | Guidance from the Centre for Excellence in Learning & Teaching (in collaboration with Senate Learning & Teaching Committee) for faculty and students on responsible and ethical GenAI use in the classroom. May need to be updated to include more information guiding instructor uses of GenAI. |
| YSGPS Guidance on the Use of GenAI in Graduate Studies | Specific direction for graduate students and supervisors on using Generative AI (GenAI) in research and academic milestones. May need to be updated to include more information guiding instructor uses of GenAI. |
| YSGPS Thesis, MRP, and Dissertation Submission Guidelines | The Policy might include language pertaining to requirements for master’s MRP, thesis, and PhD dissertation requirements, and to submission and deposit requirements for theses and dissertations. |
| Generative Artificial Intelligence and Research Integrity Module | Research integrity training for faculty specific to the application of AI technologies in SRC activities. |
| Information Classification Standard and Handling Guidelines | Defines the information classifications scheme and directs information custodians on appropriate protection of university information; |
| TMU Brand Standards and Style Guides | Governs communication, voice compliance, and visual representation; review for potential impacts of AI use on institutional reputation and brand. |
| Document Name | Comments |
| Acceptable Use of Information Technology Policy | Sets the rules for using university IT resources, including computers, networks, and software. Review for relevance to AI use. |
| Minimum Cybersecurity Controls | Defines the minimum security requirements for protecting university information systems and data. Review for relevance to AI use. |
| Information Protection Policy | Establishes how university information must be classified, handled, and protected based on sensitivity. Review for relevance to AI use. |
| Records Management Policy | Defines the requirements for the creation, maintenance, retention, and disposition of university records. Review for relevance to AI use. |
| Network and Server Security Management Policy | Focuses on the security standards and management of the university's network infrastructure and servers. Review for relevance to AI use. |
| Privacy and Access to Information Policy | Governs the collection, use, disclosure, and protection of personal information held by the university. Review for relevance to AI use. |
The task force identified key gaps in guidelines for AI use at the university:
- Specific guidance on instructor uses of AI including a focus on the assessment of student work and disclosure of use.
- Guidelines for the use of AI by researchers.
- Specific guidelines for administrative uses of AI for staff.
- Guidelines that address AI in graduate supervision.
- Protocols for disclosing AI use in research output.
- Specific guidelines for students on ethical and responsible use of AI with a focus on learning support.