Artificial intelligence can retrieve, combine, explain and apply enormous quantities of information. But when fluent output can also be false, what does it mean to know something? When Information Looks Like Knowledge examines the widening gap between access to answers and the human ability to judge whether those answers are true. G B Edlin explores hallucination, evidence, belief, retrieval, tacit knowledge, embodied experience and automation bias, showing why a system that sounds certain may not be a knower that can stand behind its claims. Clear, balanced and written for general readers, this book considers: - why fluency is often mistaken for truth - how evidence differs from plausible information - the limits of retrieval and statistical prediction - what tacit and embodied knowledge contribute - how automation bias weakens verification - practical habits for preserving judgment and responsibility Neither anti-technology nor uncritically optimistic, When Information Looks Like Knowledge offers a durable framework for using generative AI without confusing a library that contains answers with a person who understands them. This is Book 2 of The Borrowed Mind, a twelve-volume series about AI, human ability and the future of what we are.
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