False Positive

AI detection tools promise certainty in an uncertain world. With a few clicks, they claim to identify whether a piece of writing was created by a human or generated by artificial intelligence. For schools facing rising concerns about academic integrity, that promise is hard to resist.But what if the technology isn't as reliable as it claims?False Positive takes a clear, grounded look at the growing use of AI detection software in education and the unintended consequences that follow. Drawing on real-world scenarios, emerging research, and practical insight, this book explores how these systems work, where they fall short, and why even a small error rate can have serious consequences for students and educators alike.When a student's original work is flagged incorrectly, the impact goes beyond a simple misunderstanding. Trust is shaken. Confidence erodes. And in some cases, academic and professional futures are placed at risk.This book examines:How AI detection tools actually evaluate writingWhy false positives occur more often than many expectWhich students are most likely to be affected—and whyThe limitations of relying on probability as proofThe ethical and educational risks of automated judgmentRather than offering fear-based arguments, False Positive provides a balanced, accessible perspective for educators, administrators, students, and parents navigating this rapidly changing landscape.As artificial intelligence becomes more embedded in education, the question is no longer whether these tools will be used—but how.False Positive invites readers to think critically, ask better questions, and approach AI detection with the caution and care it demands—before trust in the classroom is quietly rewritten by code.