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File Size: 17468 KB
Print Length: 314 pages
Publisher: Dutton; Reprint edition (March 7, 2017)
Publication Date: March 7, 2017
Language: English
ASIN: B01MS89ER7
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I have read numerous books on this subject. Many of them have too many errors, focus on trivial considerations or arcane mathematical technicalities, and few cover the important subject of applying critical thinking not only to numbers but words (logic, reasoning protocol, etc.). Given that, this is one of the very best books on the topic I have read yet.I really liked the author splitting his subject in three main categories: 1) evaluating numbers; 2) evaluating words; 3) how the scientific method works. Each section covers its respective subject in a thorough and entertaining way.Within the evaluating numbers section the author covers all the ways in which visual quantitative data (graphs) can fool you. You really have to watch very carefully the scale of the X- and Y-axes to understand if someone is trying to trick you. The author does a good job of explaining the difference between correlation and causation (and how not to confuse the two). He also warns you not to confuse what is tested as statistically significant and yet can be immaterial (small differences pop up as statistically significant that have little bearing on the outcome when you have very large samples). The author also warns against extrapolating trends especially when you go outside the boundaries of the variable values you observed within the learning sample of your data set. The author covers well the various biases and errors that can affect sampling (participation bias, reporting bias, etc.). The chapter on probabilities is excellent with a well-defined differentiation between classic probabilities, frequentist probabilities, and Bayesian probabilities.Within the evaluating words section, the author warns about understanding the actual domain narrowness of experts. He does a good job of explaining the difference between incidence and prevalence rate. He provides a very good coverage on behavioral risk perception that is so detached from probabilistic thinking.Within the scientific method section, the author defines the different types of reasoning (deduction, induction, abduction). He also covers logic and logic notation. He also covers in greater detail Bayesian statistics. The latter is a subject that permeates every section of the book. And, he does a good job of explaining Bayes thanks to his four- quadrant framework that is really helpful in calculating the related Bayesian statistics.The author makes just one small error where he confuses R Square with R (correlation). R Square explains how much the variance in one variable can be explained by the other variable. Meanwhile, R simply tells you the strength and the direction of the relationship between those two variables. Also, remember R is often negative (so the explanation bit here not only is wrong but is divergent) meanwhile R Square can’t be negative by definition. This is a minor typo. I know the author knows that stuff. One math typo in a 250-page book is far better than most books on the subject.
I've seen some reviews lamenting that this isn't a book on the causes and nature of cognitive errors, and I agree that's a fascinating subject, but there are other books that address it.Weaponized Lies is, in essence, an entertaining beginning textbook on logic, fact checking, critical thinking, and information assessment. It makes every effort to teach these things and explain their importance in a concise and entertaining way, and, in terms of the lay audience, it seems to succeed admirably. Readers already familiar with these subjects may find it a bit slow, and those well versed in one or more of these areas may even be frustrated when the book doesn’t go further or even stray into areas it’s not actually designed to address.Daniel J. Levitin is a noted American/Canadian cognitive psychologist and neuroscientist. He’s also a musician, a record producer, and - of course - an author. He’s contributed to the Billboard Encyclopedia of Record Producers and edited Foundations of Cognitive Psychology: Core Readings, and written numerous academic articles and four bestsellers to date.The first two bestsellers were on music and the mind, which is not surprising, as Levitin is a noted expert in the field of music perception and cognition, but these books have a very broad footprint, touching on social behaviour, the development and evolution of language, and more. His third bestseller essentially seeks to explain how the brain works, how we perceive and think, and to teach how to do so more clearly and efficiently. Weaponized Lies seems to be a natural progression of this line of thought, addressing a cluster of cognitive issues that may, together, constitute most people’s greatest obstacle to effective thinking.In terms of scope, Weaponized Lies could be used as a secondary or possibly even primary textbook for a 100-level class on information analysis, critical thinking, and logic. While this isn’t a journal of groundbreaking research and theory, and there’s no invention of original academic thought in this book, it’s treatment of the various ways we infer or are led to erroneous “knowledge†are thorough, concise, and well illustrated.The fact that such a large percentage of Americans could benefit substantially by reading and comprehending Weaponized Lies is more a reflection of why this book is needed than of it’s startling academic originality - it’s most original contribution may well be the efforts undertaken to make the subject matter interesting to the lay reader.Though it occupies a “popular science†market niche, that Weaponized Lies was written by a serious academic is clearly evident in the supporting material supplied. The final forty pages of the book - fifteen percent of its volume - is an appendix on the application of Bayes’s rule, a glossary, notes on sources, acknowledgements, and an extensive index.The notes section is particularly extensive as well, at nineteen pages, separated by chapter and including discussion and expanded sources the author found after the main writing of the book. The sources for each statistic used in an illustration or example are cited, and in most cases, Levetin uses relevant, and interesting sources, such as the Department of Education, the Bureau of Labor Statistics, the Centers for Disease Control, the Congressional Budget Office, and census-dot-gov. He uses real-world stories from major news sources such as the New York Times, the L. A. Times, US News, the Washington Post, the Christian Science Monitor, and so on. He also cites numerous academic texts and popular science books, including (but in no way limited to) his own.While there’s little danger of bias in a factual text about the assessment of information, statistics, logic, and so on, Levitin actually addresses the biggest risk of bias in that area in a section titled “Belief Perseverance†which discusses confirmation bias, and the difficulty of objectively assessing and accepting new information that contradicts previously held beliefs. Simply being made aware of the ways we are subjected to falsehood, innocently and intentionally, doesn’t mean we can easily avoid and dismiss it. To do so, for most all people, requires vigilance and significant effort.Many people today feel a heightened desire or an unusually elevated need to be able to find the actual truth. Weaponized Lies doesn’t teach people to find the truth - that’s a broader process and skill set - but an important part of finding the truth is detecting and identifying untruth. I would certainly suggest this book to those seeking to strengthen their ability to spot errors and falsehoods in information, intentional and unintentional, from government information to comments of politicians and political pundits, from advertisements to documentaries to news, from to social media to blog posts to online video and podcasts.Readers may find themselves wishing for more discussion of why humans are so prone to accepting and even embracing false information - more on cognition and cognitive science and less on raw process, as the title might imply. The areas are touched on, but they’re easy to miss, because they’re incidental explanations appended to or enhancing a discussion of how to spot false information, or test it’s veracity. Rather than a full section on why and how the human mind is very prone to making a particular error of judgement, brief mention of that tendency is made to reinforce the need for vigilance.Put simply, this book would make a beneficial addition to almost anyone’s reading list. For those with an academic or autodidactic background in logic, fallacy, and critical thinking - and one needs only read one or two “debates†on social media to see that a huge number of people count themselves in this category - areas that explain topics particularly familiar to you may seem tedious, but other parts will be new, and even in those familiar areas, it’s difficult to think of any time in human history that provided greater impetus to brush up on logic, fact checking, critical thinking, and information assessment than the present.
For anyone about to start University this is a must have primer. Levitin writes in such an easy going way that you can see him smiling as he provides examples to explain hard ideas in a simple, clear manner. If you find stats and research methods confusing or daunting this is for you. At the same time, as consumer of information everyone of us should be acquainted with the ideas and insights Levitin provides. We would be less likely to fall for the poor analysis and down-right nonsense that characterizes so much of the information we consume today. Who knows... if we up our game, maybe journalists/pundits/bloggers will be forced to up theirs!
Thoughts on Levitin's Weaponized Lies & A Field Guide to Lies - Good reads on how statistics can deceiveWith great interest, I read Daniel Levitin's recent books "Weaponized Lies: How to Think Critically in the Post-Truth Era" and "A Field Guide to Lies: Critical Thinking in the Information Age." Both of these books give a good primer to deal with statistics, going over such things in detail such as Bayesian analysis in terms of a 2x2 table. Levitin also talks a bit about how people sort the truth by simply making false graphs with unlabeled axes or how there are more subtle aspects such as subtly changing the denominator (eg when talking about individuals versus families). Altogether I found these extremely useful reads. One thing that was a little troublesome to me was that they were fairly similar books. I think it does make sense for the author to repurpose his text into more current times where we talk about fake news and so forth but I still found the overlap between the two books disconcerting.
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