A warning can change lives before its evidence has been checked. A confident AI answer can become a decision before anyone has examined how it was produced. Beyond True or False explores how people and institutions can assess information responsibly when knowledge is incomplete and intelligent systems influence what we see. Drawing on documented crises and research into anomaly detection and automated fact-checking, Dimitrios Ioannidis examines the distance between a statistical signal and a justified conclusion. The book connects machine learning with questions about language, platform visibility, human oversight, manufactured evidence, and the right to challenge a consequential judgment. It explores how automated tools can support careful inquiry while keeping their limitations visible. For readers interested in AI, misinformation, and digital trust, this book asks what is known, what remains uncertain, and what evidence would justify acting.