AI isn’t replacing student work. It is replacing student struggle.
In an era when AI can write an essay, solve an equation, and generate a research summary in seconds, the most important question is no longer whether students can use AI — it’s whether they are thinking while they do it. This session reframes the AI-in-schools conversation away from detection and discipline toward something far more powerful: building the responsible use, critical thinking, and informed judgment that make students genuinely prepared for the world they are entering.
Drawing on the aiEDU AI Readiness Framework, participants will explore how AI bias shows up in classrooms, what it looks like to be a critical consumer of AI outputs, and how to design learning experiences that honor both human judgment and the tools that are here to stay.
By the end of this session, participants will be able to:
Identify at least two ways AI systems reflect bias and explain why this matters for classroom learning and student agency.
Recognize human cognitive biases — including confirmation bias and authority bias — that shape how students and teachers interact with AI outputs.
Apply a framework for evaluating student AI use that centers critical thinking and responsible judgment, not detection or compliance.
Redesign or adapt at least one existing task to support transparent, integrity-centered AI integration using a prompt rubric and transcript as the assessable artifact.
