By Amira Benjamin

With artificial intelligence (AI) disrupting academia, a new report from a Toronto Metropolitan University (TMU) task force aims to guide the university in adapting to the rapidly-developing technology.  

Published on Oct. 1, the report from the Leadership Task Force on generative AI highlights potential applications and risks of implementing AI throughout university administrative uses, educational supports, scholastic research and improving student experiences.

Thus far, the implementation of AI at the university has been at the discretion of departments, and, at the teaching level, individual instructors.

According to the university’s AI Resources webpage, instructors may integrate the use of generative AI into coursework, but are encouraged to refrain from marking assignments with the technology. 

According to the report, the task force consulted the TMU community, including an online survey that received 88 responses and five town halls which saw 129 registrants. 

The task force includes vice-provost academic and task force co-chair Sean Kheraj, vice-president research and innovation Steven Liss and Ted Rogers School of Management dean Cynthia Holmes.

Balancing teaching AI competencies with academic integrity

The task force suggests that generative AI tools can support student learning experiences, particularly as “collaborative learning partners” and “anonymous tutoring support.” The report also highlights the use for generative AI to improve accessibility, such as for the generation of alt-text for videos and images or AI-assisted notetaking.

The report outlined programs with “integrated AI competencies,” ranging from learning AI foundations throughout several undergraduate engineering courses to “explicit curriculum modifications made to address AI” within certain Image Arts film and photography courses, considering the societal contexts of AI in Liberal Studies.

It also makes room for concerns over academic integrity. The report notes the risk of students submitting AI-generated coursework and the possibility of “cognitive offloading…as a result of overreliance on AI tools.”

As previously reported by The Eyeopener, Hector Flores, the Toronto Metropolitan Students’ Union student issue and advocacy coordinator, reported that over a six-month period, 30 per cent of academic misconduct consultations the union held with students were over the alleged use of AI in coursework.

The task force’s report said using generative AI tools for student assessments is a “high risk activity,” and its authors “advise that the university continue to monitor the scholarship on…the effects of AI on learning and teaching.” 

Considerations of AI tools for research amid privacy and transparency concerns

The report found that generative AI could be applied for brainstorming, grant development, data collection and content creation. And with appropriate disclosure, generative AI can be used for tasks such as ideation, data analysis, data visualization and image generation.

It highlighted that AI tools “may also undermine [the grant development/review] process if researchers offload critical cognitive and analytical work to machine assistance.” The report cautions that some funding agencies or academic journals require AI disclosure or outright prohibit substantial use. 

The report also warned ongoing privacy concerns about public generative AI tools, as they “collect user input to further train [language learning models] and thus present significant data privacy risks.”

AI can enhance the student experience, but not in all areas

The task force highlighted how AI tools could improve student experience at TMU. Among them are, “enhanced staff productivity and effectiveness,” “better student preparations for workforce expectations regarding AI” and “improved access, inclusivity, and innovation in the learning environment.”

However, the report expressed hesitation with implementing AI tools for certain services, particularly mental health services, citing concerns over sharing private student information with outside parties. 

“In community consultations, there was optimism about the potential for adopting AI systems to improve student services, but many in the community saw a need to ensure that there is always a human touch in the services TMU provides to students,” the report stated.

Assisting with administrative tasks with human oversight

The report found that generative AI has potential to support administrative tasks, so long as space is made for human oversight to ensure “accuracy and maintenance of institutional reputation.”

The task force also expressed concern over potential cybersecurity vulnerabilities and data privacy risks in administrative and operational settings.

One challenge they noted was the threat of data leakage through new AI integrations within Google Workspace, which is used by university staff and students.

The task force also analyzed pre-existing Senate and administrative policies for potential revisions, with the report suggesting “AI adaptation can best be facilitated by updating existing policies rather than attempting to establish a single, standalone policy.”

The report also outlined gaps in AI-use guidelines concerning assessment of student work, administrative uses and “protocols for disclosing AI use in research output.”