AI in Education: Cheating, Learning, and Fair Assessment

AI tools are rapidly entering classrooms through students, teachers, and school policies. The tough question is not whether AI will be used, but what kinds of use support learning versus cross the line into misrepresentation.

Join us for an inviting, big-picture conversation where we’ll explore:

• What counts as cheating now?: Where’s the line between tutoring, editing, collaboration, and submitting AI work as your own?
• Evidence of mastery: What does a teacher or professor actually need to see to assess learning fairly?
• Equity and access: Do strict AI bans punish students with fewer resources, or protect those most at risk?
• Privacy and student data: What should schools require from AI tools (data retention, third-party access, transparency)?
• Better assessments: How can we redesign assignments (process notes, oral defense, in-class drafting) to reduce incentives to cheat without turning to surveillance?

Whether you’re a student, educator, parent, technologist, administrator, or simply curious, bring your questions and a scenario or assignment you’d like to stress-test together.