May Contain Lies
How Stories, Statistics, and Studies Exploit Our Biases and What We Can Do About It
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May Contain Lies
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Narrated by:
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Alex Edmands
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By:
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Alex Edmans
About this listen
Our lives are minefields of misinformation. It ripples through our social media feeds, our daily headlines, and the pronouncements of politicians, executives, and authors. Stories, statistics, and studies are everywhere, allowing people to find evidence to support whatever position they want. Many of these sources are flawed, yet by playing on our emotions and preying on our biases, they can gain widespread acceptance, warp our views, and distort our decisions.
In this eye-opening book, renowned economist Alex Edmans teaches us how to separate fact from fiction. Using colorful examples—from a wellness guru's tragic but fabricated backstory to the blunders that led to the Deepwater Horizon disaster to the diet that ensnared millions yet hastened its founder's death—Edmans highlights the biases that cause us to mistake statements for facts, facts for data, data for evidence, and evidence for proof.
Armed with the knowledge of what to guard against, he then provides a practical guide to combat this tide of misinformation. Going beyond simply checking the facts and explaining individual statistics, Edmans explores the relationships between statistics—the science of cause and effect—ultimately training us to think smarter, sharper, and more critically.
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Story4.5 out of 5 stars 14
Many of us comply much more than we realize. How many times have you wanted to object, disagree, or opt out of something but ended up swallowing your words, shaking your head, and just going along? Analyzing cases ranging from corporate corruption and sexual abuse to everyday acquiescence at work, the doctor’s office, and in our personal lives, award-winning organizational psychologist Dr. Sunita Sah delves deep into why the pressure to comply is a corrosive and often invisible force in our society.
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5 out of 5 stars
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Impactful
- By Allison Fullhart on 05-01-25
By: Dr. Sunita Sah
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On the Edge
- The Art of Risking Everything
- By: Nate Silver
- Narrated by: Nate Silver
- Length: 15 hrs and 5 mins
- Unabridged
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Overall4 out of 5 stars 422
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Performance4 out of 5 stars 390
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Story4 out of 5 stars 390
In the bestselling The Signal and the Noise, Nate Silver showed how forecasting would define the age of Big Data. Now, in this timely and riveting new book, Silver investigates "The River," or those whose mastery of risk allows them to shape—and dominate—so much of modern life. These professional risk takers—poker players and hedge fund managers, crypto true-believers and blue-chip art collectors—can teach us much about navigating the uncertainty of the 21st century.
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5 out of 5 stars
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Fascinating report from a distant land
- By David Benjamin on 09-14-24
By: Nate Silver
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Everything Is Predictable
- How Bayesian Statistics Explain Our World
- By: Tom Chivers
- Narrated by: Tom Chivers
- Length: 8 hrs and 7 mins
- Unabridged
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Overall4.5 out of 5 stars 49
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Performance4.5 out of 5 stars 44
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Story4.5 out of 5 stars 44
At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything. But who was the man who lent his name to this theorem?
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1 out of 5 stars
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I was looking forward to this. What a disappointment.
- By Alessandro Fadini on 06-28-24
By: Tom Chivers
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The Alignment Problem
- Machine Learning and Human Values
- By: Brian Christian
- Narrated by: Brian Christian
- Length: 13 hrs and 33 mins
- Unabridged
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Overall4.5 out of 5 stars 886
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Performance4.5 out of 5 stars 719
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Story4.5 out of 5 stars 714
Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.
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5 out of 5 stars
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Required reading for any AI course
- By ehan ferguson on 11-16-20
By: Brian Christian
His own bias against women
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