A Framework for Human-Centred AI at UTS
Last year brought many opportunities for educators to think deeply about the arrival of generative AI in K-12 schools. At UTS, we listened to students and families. We invested in teachers’ AI literacy. We leveraged experts. We watched, and we learned.
What has become clear is that educational institutions that proactively build the capacity to learn and adapt will be far better positioned to serve their students than those that wait for certainty to act. The schools that are shaping conversations about AI and education are doing so now. UTS is well positioned to lead this work. Our academic reputation, the calibre of our teachers, our research orientation through the Eureka! Research Institute, our affiliation with the University of Toronto, and our partnership with the Ontario Institute for Studies in Education ensures it.
To navigate this transformative moment with clarity, our roadmap for the coming school year intersects with three core categories: Our Philosophy (what we value and defend), Our Position (the principles that hold us accountable), and Our Practice (how our commitments meet the realities of the classroom).
OUR PHILOSOPHY
The arrival of generative AI brings with it important ontological and epistemological questions: What is the essential work of schools in a world where AI exists? What does it mean to safeguard human cognition? How do we know students have learned? How do we prepare students to use AI ethically, artfully? At UTS, we’re fortunate to have a long history of academic excellence rooted in our mission to ignite the brightest minds to make a difference in the world. We know who we are, we know what a UTS education offers, and because of that, we’re prepared to explore these questions with curiosity and courage.
Generative AI is already reshaping the professional and academic landscapes our students will inherit. As routine tasks and automated outputs proliferate, the capabilities most valued by universities and employers like human judgment, synthesis, ethical reasoning, creativity, problem-solving, and collaboration, are precisely those most difficult to automate. The presence of AI does not diminish the importance of academic rigour at UTS; rather, it clarifies what rigour must produce.
OUR FOUNDATIONAL COMMITMENTS
- Human flourishing is the measure. Technological adoption is only valuable insofar as it deepens learning, strengthens wellbeing, and develops the whole person.
- Experimentation is necessary but must be responsible. Pilots will precede scaling; ethical safeguards are non-negotiable; student wellbeing is protected throughout.
- Uncertainty is acknowledged honestly. The School will not claim more certainty than the landscape warrants.
- Agility is a strategic capability. Building the institutional capacity to learn and adapt continuously is a long-term investment.
- UTS should lead, not follow. The school’s resources and reputation position it to shape educational conversations, not simply respond to them.
Every act in a school already takes a stance on the purpose of education. UTS acts with an immutable commitment to Anti-Racism, Equity, Diversity, and Inclusion (AEDI). AEDI is not an adjunct to our technology guidelines; it is the non-negotiable foundation that governs how we evaluate status, access, and power in digital spaces.
OUR POSITION
The challenges AI poses are not peripheral to the UTS mission: they go to its centre. The Strategic Plan commits UTS to drive excellence in teaching and learning, lead in the innovative and responsible use of evolving technologies, and prepare students to critically assess information, produce original thinking, and navigate complexity with ethical judgment. Each of those commitments is directly tested by the emergence of AI in education.
Emerging from discussions with students, families, teachers, and shaped by insights from education leaders and experts, these principles support the pillars of our Strategic Plan and ground future discussions–and decisions–about the use of AI at UTS.
Leading in Learning
Human judgment must be cultivated through a robust understanding of AI ethics. AI may support decision-making, but it will not replace the human responsibility for educational judgment and care. Decisions about the use of AI in teaching and learning will continue to rely on the professional expertise of educators in alignment with the school's commitments to academic excellence and AEDI.
Responsible experimentation with AI is encouraged. Exploration of AI tools should be guided by curiosity, critical reflection, and a commitment to learning from both successes and limitations. The process should be iterative, evidence-based, and responsive to feedback. Findings should be shared widely.
Inclusion by Design
Equity and access must drive policy and practice. AI use may create or deepen existing inequities in access, opportunity, or outcomes. All decisions regarding AI use must prioritize equitable access, bias awareness, and inclusive participation for all students, teachers, and staff.
Promoting AI literacy and ethics in students, teachers, and staff is paramount. Opportunities for students, teachers, and staff to understand, evaluate, and use AI effectively and responsibility builds AI literacy and skill. This includes a basic understanding of how AI works, assessing its output, and ethical decision-making around its use.
Belonging and Wellness
Relationship-building must remain a central function of the classroom. Learning is a social and relational process. Students learn best when they feel known, supported, challenged, and connected to their teachers and peers. AI should be used in ways that preserve and enhance opportunities for human connection, collaboration, and community-building rather than diminishing them.
Privacy and data stewardship are imperative. Careful attention to student and staff safety, privacy, data security, and responsible information stewardship with particular care for how data is collected, stored, used and protected is paramount.
Impact with Integrity
Academic integrity is non-negotiable. UTS remains deeply committed to honesty, original work, and personal accountability. The school recognizes the importance of communicating clear expectations around the use of AI by students for course work and assessments.
Sustainability and regeneration should frame decision-making. The use of AI should be considered within the broader environmental systems in which it operates. Decisions about AI use should account for resource consumption, energy demands, and long-term environmental consequences while also considering how AI might support regenerative practices.
Better Together
Communication and transparency matters. Open dialogue with the UTS community and consultation with expert guidance are beneficial as these conversations evolve. Thoughtful engagement from students and families is valued and encouraged.
OUR PRACTICE
AI is already impacting UTS classrooms. It is disrupting how students learn, how teachers assess, and how the boundaries of academic work are understood. Over the coming years, it will likely put sustained pressure on deeper questions about the purpose of schools and how they can remain human-centred in a world increasingly shaped by intelligent systems.
When we adopt tools uncritically, we risk narrowing the gap between technological capacity and educational wisdom by surrendering thoughtful pedagogy to efficiency. At UTS, innovation with AI must be bound by humanistic purpose. We refuse to trade the productive friction of deep learning for automated expediency. Educational wisdom demands that human cognitive agency, ethical reasoning, and relational growth remain at the center of every classroom experience.
Translating principles into practice requires moving beyond simple tool use or reactive policies. Drawing on human-centered frameworks, UTS organizes its operational commitments around three categories: AI ethics, AI literacy, and AI learning.
AI Ethics
Ethics is at the center of our engagement with AI. This means examining the broader systems in which these technologies operate, including environmental resource demands, global labour supply chains, and entrenched disparities in access and opportunity. It also means going beyond narrow, technocratic paradigms by honoring diverse, non-dominant epistemologies that prioritize collective stewardship, relational accountability, and long-term harmony over extraction and rapid consumption.
For both educators and students, cultivating ethical use of AI is an ongoing discipline of critical questioning: scrutinizing algorithmic bias, recognizing whose voices are amplified or erased, and evaluating whether the use of an AI tool expands human agency or subtly diminishes it. We don’t view ethical AI engagement as a set of static restrictions, but as an active component of student learning. We believe in teaching students how to evaluate AI output including algorithmic bias, data stewardship, intellectual property, and environmental impact. Educational values such as critical self-reflection, empathy, and original thought will always take precedence over technological expediency or the demonstration of technical proficiency.
Across CAIS schools in Ontario and independent schools internationally, institutions are investing in AI-related leadership capacity. This looks like dedicated leadership capacity in two complementary areas: present-day pedagogical and ethical guidance, and longer-range strategic positioning and partnership-building. Dr. Janet Kurusanather, PhD, has joined the UTS community as the Director of Learning, Ethics and AI. She will lead the strategic, ethical, and innovative integration of AI across the curriculum, supporting staff and students in developing future-ready learning, and positioning the school as a leader in human-centered, research-informed education. Dr. Kurusanather will be working in tandem with Matthew DeClerico, MSc, UTS teacher and Strategic Lead, Future Learning and Innovation. In this role, he will identify emerging opportunities and challenges, evaluate their relevance to UTS and assess their alignment with the school's academic program and strategic priorities.
AI Literacy
While AI guidelines set boundaries, AI literacies build capacity. A school community with high AI literacy relies on informed human judgment. AI literacy involves understanding how these systems work, how they exert influence, and how to maintain agency when interacting with them. This includes (1) understanding the mechanics, strengths, and technical limitations of probabilistic models, (2) evaluating how AI-generated text or media shapes narrative, tone, and persuasion, (3) recognizing bias, data privacy issues, and the socio-technical impacts of the technology, and (4) knowing when and why to integrate or deliberately restrict technology in the learning process.
AI literacy is a deep, critical understanding of how intelligent systems shape information, thought, and culture. It equips educators and students to see through the illusion of machine neutrality, recognizing these tools as probabilistic engines with inherent limitations. By building this level of critical discernment, we’re preparing our teachers and students to engage with emerging technologies intentionally and creatively.
In practice, this means that new approaches to teaching, assessment, or learning technology will be piloted before being scaled; that any pilots involving students will be communicated transparently to families; that outcomes will be evaluated rigorously; and that human oversight will be maintained throughout. The school will not make commitments until evidence warrants them.
It also means acknowledging honestly that we will not get everything right on the first attempt; however, what distinguishes thoughtful institutions is not the absence of errors but the quality of the frameworks they have built to catch them early, course correct quickly, and learn continuously. That is the standard UTS is committed to meeting.
AI Learning
The most immediate pressures involve academic integrity and assessment. Generative AI tools have made it possible for students to produce sophisticated written work with minimal effort, and conventional assessment models such as essays, take-home assignments, and research projects are under strain. At the same time, students arrive with vastly different levels of AI literacy, access, and judgment, creating new sources of inequity within school communities.
Effective educational responses to AI start with curriculum design, not software choice. If an activity or assignment can be completed with an automated prompt, and without student collaboration, the learning design needs refinement. This requires a shift from defensive monitoring (how do we prevent students from using AI?) to constructive evaluation (how do we know learning has occurred?).
We’re also observing a growing risk of cognitive offloading, where AI tools handle the heavy lifting of drafting, problem-solving, and synthesis, bypassing the effort required for deep, sustained learning. This dynamic creates a performance paradox: short-term task execution appears fluent, yet it can mask an underlying loss of intrinsic motivation, metacognitive awareness, and long-term skill retention. These challenges do not occur in a silo; they intersect directly with broader provincial realities, including persistent achievement gaps across Ontario education and widening disparities between students who possess strong self-regulation skills and those who do not. Unstructured AI use risks exacerbating these gaps.
To navigate these complex layers, UTS is actively pursuing internal research initiatives alongside our OISE partners. Through ongoing classroom pilots and reflective research, we are examining how students perceive and interact with these systems, measuring the cognitive impact of AI-assisted feedback, and identifying actionable strategies to leverage AI without sacrificing human agency or demonstrable intellectual growth.
The Year Ahead
No independent school, and no educational institution of any kind, currently has a definitive roadmap for navigating AI. Schools that claim otherwise should be regarded with skepticism. The honest position is one of informed uncertainty: the landscape is changing faster than planning cycles can accommodate, and the most credible institutional response is one grounded in humility, continuous learning, and disciplined adaptability rather than false confidence in any single predicted future.
We will not adopt an aggressive posture of rapid technological adoption, nor will we take a defensive posture of resistance to change. Both approaches carry significant risks. Instead, we’re introducing guidelines that safeguard the UTS culture of intellectual curiosity and integrity. We’re elevating 21st century learning skills like critical thinking, creativity, and problem solving. We’re opening more avenues for dialogue. We’re building AI literacy in our students, teachers, and families. We’re collaborating with experts, and we’re leading the way.
