Think Again: The Power of Knowing What You Don't Know by Adam Grant (sad books to read txt) 📕

their original strategies and products. It was too easy to preach the virtues of their past decisions, prosecute the vices of alternative options, and politick by catering to advisers who favored the existing direction. The entrepreneurs who had been taught to think like scientists, in contrast, pivoted more than twice as often. When their hypotheses weren’t supported, they knew it was time to rethink their business models.

What’s surprising about these results is that we typically celebrate great entrepreneurs and leaders for being strong-minded and clear-sighted. They’re supposed to be paragons of conviction: decisive and certain. Yet evidence reveals that when business executives compete in tournaments to price products, the best strategists are actually slow and unsure. Like careful scientists, they take their time so they have the flexibility to change their minds. I’m beginning to think decisiveness is overrated . . . but I reserve the right to change my mind.

Just as you don’t have to be a professional scientist to reason like one, being a professional scientist doesn’t guarantee that someone will use the tools of their training. Scientists morph into preachers when they present their pet theories as gospel and treat thoughtful critiques as sacrilege. They veer into politician terrain when they allow their views to be swayed by popularity rather than accuracy. They enter prosecutor mode when they’re hell-bent on debunking and discrediting rather than discovering. After upending physics with his theories of relativity, Einstein opposed the quantum revolution: “To punish me for my contempt of authority, Fate has made me an authority myself.” Sometimes even great scientists need to think more like scientists.

Decades before becoming a smartphone pioneer, Mike Lazaridis was recognized as a science prodigy. In middle school, he made the local news for building a solar panel at the science fair and won an award for reading every science book in the public library. If you open his eighth-grade yearbook, you’ll see a cartoon showing Mike as a mad scientist, with bolts of lightning shooting out of his head.

When Mike created the BlackBerry, he was thinking like a scientist. Existing devices for wireless email featured a stylus that was too slow or a keyboard that was too small. People had to clunkily forward their work emails to their mobile device in-boxes, and they took forever to download. He started generating hypotheses and sent his team of engineers off to test them. What if people could hold the device in their hands and type with their thumbs rather than their fingers? What if there was a single mailbox synchronized across devices? What if messages could be relayed through a server and appear on the device only after they were decrypted?

As other companies followed BlackBerry’s lead, Mike would take their smartphones apart and study them. Nothing really impressed him until the summer of 2007, when he was stunned by the computing power inside the first iPhone. “They’ve put a Mac in this thing,” he said. What Mike did next might have been the beginning of the end for the BlackBerry. If the BlackBerry’s rise was due in large part to his success in scientific thinking as an engineer, its demise was in many ways the result of his failure in rethinking as a CEO.

As the iPhone skyrocketed onto the scene, Mike maintained his belief in the features that had made the BlackBerry a sensation in the past. He was confident that people wanted a wireless device for work emails and calls, not an entire computer in their pocket with apps for home entertainment. As early as 1997, one of his top engineers wanted to add an internet browser, but Mike told him to focus only on email. A decade later, Mike was still certain that a powerful internet browser would drain the battery and strain the bandwidth of wireless networks. He didn’t test the alternative hypotheses.

By 2008, the company’s valuation exceeded $70 billion, but the BlackBerry remained the company’s sole product, and it still lacked a reliable browser. In 2010, when his colleagues pitched a strategy to feature encrypted text messages, Mike was receptive but expressed concerns that allowing messages to be exchanged on competitors’ devices would render the BlackBerry obsolete. As his reservations gained traction within the firm, the company abandoned instant messaging, missing an opportunity that WhatsApp later seized for upwards of $19 billion. As gifted as Mike was at rethinking the design of electronic devices, he wasn’t willing to rethink the market for his baby. Intelligence was no cure—it might have been more of a curse.

THE SMARTER THEY ARE, THE HARDER THEY FAIL

Mental horsepower doesn’t guarantee mental dexterity. No matter how much brainpower you have, if you lack the motivation to change your mind, you’ll miss many occasions to think again. Research reveals that the higher you score on an IQ test, the more likely you are to fall for stereotypes, because you’re faster at recognizing patterns. And recent experiments suggest that the smarter you are, the more you might struggle to update your beliefs.

One study investigated whether being a math whiz makes you better at analyzing data. The answer is yes—if you’re told the data are about something bland, like a treatment for skin rashes. But what if the exact same data are labeled as focusing on an ideological issue that activates strong emotions—like gun laws in the United States?

Being a quant jock makes you more accurate in interpreting the results—as long as they support your beliefs. Yet if the empirical pattern clashes with your ideology, math prowess is no longer an asset; it actually becomes a liability. The better you are at crunching numbers, the more spectacularly you fail at analyzing patterns that contradict your views. If they were liberals, math geniuses did worse than their peers at evaluating evidence that gun bans failed. If they were conservatives, they did worse at assessing evidence that gun bans worked.

In psychology there are at least two biases that drive this pattern. One is confirmation bias: seeing what we expect to see.