Bloomsbury
EVERY day, we outsource decisions to the internet: should we stay at that hotel, eat at this restaurant, ride with that driver? We have become so accustomed to the large-scale insights afforded by tech, many of us wouldn鈥檛 buy so much as a toaster without first checking reviews online.
Their accessibility and apparent authority mean that to just roll the dice and pick an appliance is almost unthinkable 鈥� why wouldn鈥檛 you ask Google first?
And yet, when it comes to many more important decisions 鈥� like what we choose to study or who to marry 鈥� we often trust our gut. This, argues economist , is where we are going wrong. After all, following our instincts can lead us to act on subconscious bias or to keep following dead-end paths.
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As a former data scientist at Google, Stephens-Davidowitz was granted an overarching view of the questions we would rather put to a search engine than a friend, which he shared in his 2017 bestselling book, Everybody Lies. Now, he wants us to use the insights afforded by big data to inform life decisions such as who to marry and where to live. He calls it 鈥渟elf-help for data geeks鈥�.
In his new book Don鈥檛 Trust Your Gut: Using data instead of instinct to make better choices, Stephens-Davidowitz brings together 鈥渃redible answers to fundamental questions鈥� as revealed by vast online data sets, so we can apply them to be more successful and happier. 鈥淲hile we often think we know how to better ourselves, the numbers, it turns out, disagree,鈥� he writes.
Some findings are indeed counter-intuitive, such as the overstated advantage of youth in starting a business, or the popularity of people with non-natural hair colours or body piercings on dating platforms (suggesting you should aim to 鈥渂e an extreme version of yourself鈥�).
Others may be more in line with expectations: we routinely overestimate the pleasure of passive activities such as snacking and watching TV. Research by the London School of Economics found that even relaxing tends to make people feel less happy than anticipated. On the other hand, we underestimate the boost of running errands or visiting museums or libraries.
From work to relationships, Stephens-Davidowitz looks to the data for guidance and, where possible, tries it out for himself. In the 鈥淢akeover: Nerd edition鈥� chapter, he uses 鈥淎I plus rapid market research plus statistical analysis鈥� 鈥� putting more than 100 doctored images of himself to an online survey 鈥� to glean that people generally prefer him with glasses and a beard.
It is one example of where Stephens-Davidowitz sacrifices scientific rigour for a stunt, or puts forth a data-driven approach to life that is of limited practical application. Though entertaining and thought-provoking, Don鈥檛 Trust Your Gut is most persuasive as 鈥渟elf-help that actually works鈥� when it is puncturing myths about the importance of education and wealth, or tried-and-true sources of life satisfaction. Gratifyingly, the author suggests, these might be as simple as calling a friend, taking a walk near water or having sex.
He demonstrates, in broad strokes, what works best for most people, so that all of us might learn from their example. If you want to be happier day to day, for example, you might be better off making friends at work than pushing for a salary increase. Working with friends may be the 鈥渙ne way to truly make work tolerable 鈥� or even enjoyable鈥�.
But his somewhat utopian view of data 鈥� as a resource to be mined then applied, like painting by numbers 鈥� can be at odds with a world already transformed by it. Numbers may not lie, as Stephens-Davidowitz writes 鈥� but nor do they reveal the complete, complex picture, especially when they are controlled by corporate interests. When our behaviour is already being shaped by data in ways to which we aren鈥檛 privy, perhaps success isn鈥檛 always a matter of making the right decision.
And then how you feel about a decision can be just as relevant to your commitment to it as the favourable statistics backing it up. This he acknowledges in the book鈥檚 dedication, to his wife: 鈥淚f the data says that loving you is wrong, I don鈥檛 want to be right.鈥�
