By Helena Prins, Advisor, Learning + Teaching
I recently co-facilitated a course on AI in teaching and learning, and one thing was clear: most educators are trying to navigate the generative AI (GenAI) landscape without a map or even a compass.
Institutions are trying to catch up as GenAI tools keep evolving at a rapid pace. Often, guidance is vague or nonexistent. Yet GenAI is already embedded in our students’ lives and workflows. As educators, we’re expected to adapt quickly, integrate these tools, and model ethical and appropriate use. But many of us are still working through our own questions, especially around the ethical, social, and environmental implications of GenAI use.
In many sessions, we acknowledge these concerns, then quickly move on. “AI is here to stay,” we say. “We have no choice but to embrace it.”
But maybe we do have a choice. Or, at least, a different approach is possible.
What if we didn’t embrace AI so much as choose to explore it?
Like any exploration, we need tools to help us navigate. For me, that starts with a compass, my personal ethical framework, and a map, which is the contextual conversations and classroom strategies that ground this technology in our values, students’ lives, and societal impact.
The Compass: A Personal Ethical Framework
Brent de Waal, a fellow FLO Facilitator (2024), shared a personal ethical framework for using AI-generated images. I found it so resonant that I’ve since adapted it to guide all my GenAI use.
It’s a living framework, a tool to revisit as contexts shift. What makes it work is that it aligns with my values. To create your own ethical framework, you may consider some of these critical questions:
- Purpose – Why am I using AI instead of another tool?
- Originality – Am I leaning on the style or labour of another creator without consent?
- Impact – Could this reinforce stereotypes or cause harm?
- Message – What am I trying to communicate?
- Stakes – Is this a low-stakes draft or high-visibility output? What are the consequences of this project?
- Audience – Who will view this work and how might they interpret it?
Having a compass like this keeps my use of GenAI intentional and values-aligned, not just efficient or trendy. It also makes it easier for me to discuss my course decisions regarding AI use with students.
The Map: Conversations and Curricular Practices for Ethical Exploration
If our ethical framework is our compass, the map is made up of our conversations with students, colleagues, and ourselves, as well as the choices we make in our teaching.
In my experience, many educators feel underprepared to talk about GenAI with their students. These conversations don’t need to be complex or confrontational; they can begin with curiosity.
During a recent FLO Friday, Dr. Adina Gray suggested four simple entry points:
- Start by inviting students to share what they already know about AI.
- Ask them what excites or worries them.
- Walk through your syllabus together and co-develop a basic AI use policy.
- Share your own practices: how you’re experimenting and what you’re uncertain about. This transparency not only models responsible use, but can also build trust.
From there, deeper ethical conversations can emerge through curriculum. In my colleague Dr. Gwen Nguyen’s GenAI for Teaching and Learning Toolkit, she offers strategies for integrating ethical reflection into course design not as a standalone lecture, but as part of how we explore and use GenAI with students.
For example, you might invite students to co-create class policies around AI use or engage them in a structured debate around ethical dilemmas: “Should AI-written essays be allowed?” or “Is it okay to use AI to detect plagiarism?” These kinds of activities reveal the nuance and trade-offs we’re all navigating.
Ethical exploration can also happen through hands-on inquiry like identifying bias in AI-generated content or reflecting on how GenAI might disrupt learning, creativity, or relationships. Even journaling prompts can invite ongoing reflection and help students develop their own ethical compass alongside yours.
Ultimately, these practices help students see that ethical engagement with AI isn’t a checklist—it’s an evolving mindset. They reinforce that learning, like technology, is not neutral, and that it is shaped by the values we bring to it.
Final Thoughts
Where to begin?
Find your truenorth by reflecting on your personal ethical framework and use it to guide how and why you engage with GenAI. Then, start mapping a way forward through honest conversations and thoughtful integration into your teaching.
So, you don’t need to overhaul your whole course this summer! Maybe ask one new question. Try one tool. Have one reflective conversation. Let’s engage in “plus-one thinking” (Tobin & Behling, 2018, p.134). As Universal Design for Learning (UDL) scholar Thomas Tobin suggests, investigate or rethink one assignment, one concept, or one task in your course, add or change just one element, and build from there.
We’re all still finding our way through this shifting terrain, but we don’t have to do it in isolation or without intention. When we share our ethical frameworks and stay in conversation with our students, our peers, and ourselves, we begin to chart a path forward. Together, we can create space for thoughtful, values-aligned engagement with GenAI, one step, one question, one choice at a time. We’re not just teaching about technology; we’re shaping the culture of how we engage with it.
AI Disclosure Statement
- I submitted my written draft to ChatGPT and asked for suggestions on improvements for clarity and conciseness.
- I provided ChatGPT with URLs to create the APA reference list below.
The FLO MicroCourse: An Introduction to the GenAI Teaching and Learning Toolkit, designed by Dr. Gwen Nguyen, is an open education resource (OER) that is available for you to review, reuse, and adopt.
References
de Waal, B. (2024). Ethical considerations for AI image generation [MicroCourse]. BCcampus SCoPE.
Gray, A. (2024, May 24). Responsible AI use in the classroom: Starting conversations with students [Webinar]. BCcampus.
Nguyen, G. (2024). Teaching and learning with generative AI: An open education toolkit. BCcampus.
Tobin, T. J., & Behling, K. T. (2018). Reach everyone, teach everyone: Universal design for learning in higher education. West Virginia University Press.