World in Confusion How Scientists Persuade Each Other (and how we can benefit from their skills)

Sale price  $26.99 Regular price $29.99

World in Confusion How Scientists Persuade Each Other (and how we can benefit from their skills)

Sale price  $26.99 Regular price $29.99

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World in Confusion

How Scientists Persuade Each Other (and how we can benefit from their skills)

Miroslav Kubat

Social Science / General

We live in an age of information overload, where scientific discoveries compete for attention with superstition, pseudoscience, conspiracy theories, and misinformation. How can we tell the difference between reliable knowledge and seductive nonsense? In World in Confusion, readers are invited inside the intellectual toolkit of science to discover how scientists evaluate evidence, challenge assumptions, weigh competing explanations, and ultimately persuade one another. Through engaging stories drawn from history, science, and everyday life, the book reveals the principles behind falsifiability, burden of proof, statistical reasoning, the evaluation of evidence, and many other habits of mind that help separate truth from error. 

Avoiding abstract philosophy and technical jargon, the book shows science as a practical way of thinking that anyone can apply. It explores not only how scientific knowledge is created and tested, but also the institutions, incentives, and human shortcomings that shape research. Building on these foundations, the book examines superstition, conspiracy theories, ideological certainties, and some of history's most consequential collective mistakes through a scientific lens. The result is an accessible, thought-provoking guide to critical thinking and intellectual self-defense for anyone seeking clarity in a confusing world.

Miroslav Kubat has spent most of his career in the university environment, the last twenty years prior to his retirement as a professor of electrical and computer engineering at the University of Miami, Florida, U.S.A. As a scientist, he published scores of peer-reviewed scientific papers, and four books, including the standard textbook An Introduction to Machine Learning (Springer). As an educator, he always wondered how best to convey to his students the need to be convincing, the necessity to offer adequate evidence for each new statement or proposition. New ideas succeed only if they are accepted by the world. At the same time, he puzzled over why the public so often accepts nonsense at face value, while rejecting serious pieces of information. This book is the result of those thoughts.


Publication Date: 13 March 2027
Publisher: Springer Nature Switzerland
Imprint: Springer
ISBN-13: 9783032413635
Format: Paperback softback

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