This is a challenge of logic. Four double-sided cards, one for a number and one for a letter, have been provided to you. “If a card has a vowel on one side, it has an even number on the other side,” is the test you are instructed to perform. As dealt, the cards said “E, K, 2, 3.” Which one would you pick?
Should you, like myself, have chosen E and 2, you should read May Contain Lies: How Stories, Statistics, and Studies Exploit Our Biases—and What We Can Do About It by Alex Edmans. While supporting the rule, answers E and 2 don’t question its veracity. The right answer is to turn E and 3, which both support the positive and refute the negative.
Alternatively, as the London Business School finance professor states elsewhere in his book: “But growing in knowledge and improving decision-making isn’t just about guarding against misinformation—it’s also about positively obtaining information.”
Edmans wants to increase our level of scepticism by assisting us in comprehending and analysing the evidence that is presented to us. He demonstrates to us how data has historically been distorted and how false information has been used to launch initiatives. He writes, “Data is just a collection of facts.” “Data that enables you to differentiate between hypotheses—to validate yours and rule out alternatives—is evidence.”
His examples are not limited to just one area. He describes how, after the release of Malcolm Gladwell’s book Outliers, which made the claim that you could become an expert at anything if you put 10,000 hours into it, parents started forcing instruments on young children. He found that the truth is nuanced. Some tales are more intimate. After contacting Edmans and requesting measurements demonstrating that more diversified businesses had higher financial returns, the investor left him in favour of a rival who was prepared to twist the truth while Edmans wasn’t.
In an effort to refute books and articles that attempt to neatly sew a story around the prosperous life of a corporate mogul like Steve Jobs, he simultaneously delivers a rallying call for reason. He thinks we must learn to recognise these kinds of untrue statements before we come across them.
According to Edmans, there are two opposing accounts of Apple’s success that are similar in that they both feed into confirmation bias, exploit black-and-white thinking, and offer a compelling story. In addition to targeting TED talks and journalists, Edmans emphasises that “we forget the basic scientific method when we’re told a compelling story.” She also predicts the rise of “factual” communication on TikTok, where users can add facts at random to fit a preconceived narrative and become viral.
According to the author, he has experienced such spin firsthand. He appeared before the committee and provided a thorough, well-researched document to a UK parliamentary enquiry into wage inequality. However, his evidence was twisted to say the reverse of what he had stated in his final report.
He makes a strong argument. However, it also indicates Edmans’ reluctance to prioritise narrative over data. He uses a “Ladder of Misinference” in its stead. The diagram illustrates how decisions can go wrong, with the seemingly solid rungs from “statement” to “evidence” really being subject to debate.
Fortunately, his book is a page-turner for the first two thirds. Because too many people will select the incorrect cards, the appendix, which is described as “a checklist for smarter thinking,” should also be required reading.
