Beyond tech: What does responsible AI mean in higher education?

Across classrooms, government and research spaces, AI is no longer theoretical. As artificial intelligence reshapes teaching and research worldwide, Manitoba’s public institutions are asking not just what AI can do, but how it should be used.  

Students are already engaging with it. Faculty are exploring and integrating it into their teaching and research. Leaders are shaping the policies and frameworks that guide its use. The challenge is not simply adoption; it is responsibility.

In Manitoba, that responsibility is being defined through a careful balance of innovation and integrity, access and equity, efficiency, and human connection.  

Leaders and experts addressed the topic of responsibility at a recent UM panel on the challenges and opportunities for generative AI in higher education, as part of the Teaching Symposium. The panel included Premier Wab Kinew, President Michael Benarroch and other Indigenous, provincial and institutional leaders.  

In classrooms, the impact of AI is immediate. Traditional assignments are becoming harder to evaluate as indicators of true student learning.

“The answer is found in process, not product,” says Christina Penner, Senior Instructor in the Department of Computer Science. She suggests that instructors must now engage more deeply with students to observe how their learning unfolds, rather than only grading the final result.  

“We learn when things are hard, when they go right and when they go wrong,” adds Dr. Heidi Marx, Dean of the Faculty of Arts. “AI can benefit some of our journey, but it shouldn’t be outsourcing that journey.”  

Students are also taking an active role in shaping these new norms.  Divya Sharma, an undergraduate student at UM, highlights that students are not just passive users.  

“It also requires a shift in how we engage with knowledge,” she says. “We should not be approaching AI with half-formed thoughts or vague inputs. The quality of what we receive is directly shaped by the quality of what we ask. That means students need to read more, think more, and develop informed perspectives.”  

Dr. Brenda Stoesz emphasizes the collaborative aspect of this approach and says it’s important to “learn how to learn.” Stoesz is Research Lead – Science of Teaching and Learning at The Centre for the Advancement of Teaching and Learning.  

“The GenAI of today will not be the GenAI of tomorrow,” she says. “Learning the specifics of any one or a few tools will not prepare you for the future. What prepares one best for the future is to experience and learn a range knowledge, skills, and ways of doing that could be applied and/or adapted for future contexts, contexts that we have yet to imagine.” 

UM President Dr. Michael Benarroch notes that while no one knows the answers at this point, “it’s important to learn from each other and talk openly about both opportunities and challenges.” 

He says, “We recognize that AI is not only impacting teaching and learning, but also our governance, infrastructure, workforce development, and community trust.”  

UM established its Committee on Artificial Intelligence in 2024 to assess opportunities and risks, and to develop institution‑specific guiding principles that align with UM values.  

Dr. Diane Hiebert-Murphy, Provost and Vice-President (Academic), notes that UM has AI Guiding Principles that have been endorsed by Senate. These include addressing principles for implementing AI systems that include human-centred approaches, accessibility and fairness, and environmental and sustainability practices.

Benarroch adds, “I believe we need to be more deliberate in assessing how we teach critical thinking, judgement, ethics, problem solving, and contextualized thinking. We’ve made adjustments in the past as other technologies have emerged and been adopted, and we can do it again.” 

He continues, “We really need to step back and ask if what we’re doing is the best long‑term solution, and The Centre for the Advancement of Teaching and Learning is facilitating a lot of important conversations to help us do that.”  

“AI is not a skill developer; it is a skill enhancer. It is not replacing our critical thinking skills, but it is reminding us how valuable it is to teach those skills in the best ways,” he emphasizes.  

As some point out, a conversation around AI begins not with possibility, but with power.  

“Data is territory,” says Indigenous futurist and researcher Keeta Gladue. “And so when I think about a voracious appetite, I think about land.”  

Her framing shifts the conversation: AI systems are not neutral tools; they are powered by energy and built on data; these systems are shaped by values, and capable of reproducing existing inequities. This is especially true in Manitoba, she says.

“It is not right that your stolen work has been taken by a company who decided your work would be [part of] their system and never asked for your consent,” Gladue adds.  

“In order to make sure that [this] wrong equates to change, there will need to be resistance.”  

For Gladue, Indigenous knowledge systems offer guidance for a just and sustainable future. “The elders that I work with do not have quarterly plans,” she says.

For Manitoba’s public leaders, the rise of AI is a question of governance and public trust.  

Manitoba Premier Wab Kinew emphasizes that AI decisions cannot be made in isolation from the province’s unique social and environmental context.  

“How do we mitigate the impacts on the land, the people who live off the land, wildlife, water, ice, the local climate?” he asks.  

“I don’t think we can divorce the question of Reconciliation with highly impacted communities and Indigenous nations, more generally, from any economic or social question in Manitoba.”  

A parallel responsibility, says Minister of Advanced Education and Training Renée Cable, is preparing a workforce that is tech-savvy but remains deeply human. She highlights the tension between automation and human capability: in an AI-driven economy, technical skills matter, but so do ethics and the ability to navigate complexity.  

“The humanities are more important than ever,” she says.  

“We need to make sure that our brains don’t atrophy while machines do the rest of the work.” 

The consensus is clear: the future of AI is not predetermined.

“AI is not inevitable,” Gladue says. “How it looks, what it’s used for, what it does, is being actively defined right now.”  

Through policy, pedagogy, and public dialogue, UM and the province are opting for a path that values responsibility over speed.  

Ultimately, this is more than a technological shift: It is a cultural one, shaping how knowledge is created and sustained for generations to come.  

“It should be messy,” Benarroch says.  

“It should be a good mess. Humans should be at the heart of it.”