Is big data the guide to making better life decisions? Can millions of data points on behavior replace your own intuition?<\/p>\n\n\n\n
In his book Don’t Trust Your Gut<\/a>: Using Data to Get What You Really Want in Life<\/em>, Seth Stephens-Davidowitz shows how big data can provide scientific answers about which life choices lead to better outcomes. He argues that you should rely on data rather than your intuition.<\/p>\n\n\n\n Keep reading to discover how numbers, not narratives or instincts, can help you make smarter choices.<\/p>\n\n\n\n\n\n\n\n The normal state of human existence is to stumble blindly through life, making it up as we go along. From time to time, we turn to experts\u2014philosophers, spiritual teachers, business leaders, and self-help gurus\u2014for guidance on how to live our lives. While people have found all these paths useful to some degree, the overall results can be decidedly mixed. Clearly, no one\u2019s figured out the formula to a happy, well-lived life. But what if all our technological progress<\/a> has inadvertently created a tool to do just that?<\/p>\n\n\n\n In Don\u2019t Trust Your Gut: Using Data to Get What You Really Want in Life<\/em><\/a>, a book published in 2022, Seth Stephens-Davidowitz argues that, with the advent of \u201cbig data\u201d\u2014the vast amount of information now available on human behavior\u2014we can scientifically analyze the outcomes of millions of people\u2019s life decisions. Doing so gives us definitive answers to which of the many choices we make have the most impact on our careers, our love lives, and our happiness. Stephens-Davidowitz says that, instead of merely using big data to decide which ads to show customers or which videos to suggest on streaming platforms, we can use this information to make more informed decisions in our lives.<\/p>\n\n\n\n A self-proclaimed \u201cdata nerd,\u201d Stephens-Davidowitz has degrees in philosophy and economics, has analyzed data for Google, and is the author of 2017\u2019s Everybody Lies<\/em><\/a>, which explains how search engine data reveals truths about human behavior. Whereas that book focused on big data\u2019s unexpected insights, Don\u2019t Trust Your Gut<\/em> was inspired by Michael Lewis\u2019s Moneyball<\/em><\/a> (2003), which is about how the baseball team, the Oakland A\u2019s, used data analysis to improve their performance. Stephens-Davidowitz suggests that the same strategy can be used by everyday people to improve their lives.<\/p>\n\n\n\n In this overview of the book Don\u2019t Trust Your Gut: Using Data to Get What You Really Want in Life<\/em>, we\u2019ll explain the benefits of big data\u2014how it can guide us and how it reveals that some decisions don\u2019t really matter. We\u2019ll lay out Stephens-Davidowitz\u2019s case that making choices based on data can help improve your romantic life, your chances of success in your career, your effectiveness as a parent, and your overall happiness.<\/p>\n\n\n\n The title\u2014\u201cdon\u2019t trust your gut\u201d\u2014speaks directly to Stephens-Davidowitz\u2019s basic premise: namely, that hard data is a better guide to making decisions than human intuition.<\/strong> Let\u2019s look at the reasoning behind this statement, where the data we might turn to comes from, and what that data says about the role of deliberate decision-making<\/a> versus chance.<\/p>\n\n\n\n Stephens-Davidowitz\u2019s case against intuition is twofold. First he points out that the human mind is riddled with cognitive biases<\/a> and misleading mental shortcuts<\/a>.<\/strong> We can\u2019t help it\u2014these errors spring from the mental shorthand our brains use to quickly process information, making \u201ccommon sense\u201d on the individual level and \u201cconventional wisdom\u201d when applied to society at large. And we\u2019re not always wrong\u2014but Stephens-Davidowitz proposes that common sense<\/a> is wrong often enough<\/em> that we shouldn\u2019t fully trust it if we have a better option.<\/p>\n\n\n\n In addition to our untrustworthy instincts, we also frequently fall victim to misleading narratives. The most common trend that Stephens-Davidowitz points to is that society fixates on extraordinary stories to the point that they\u2019re not seen as outliers.<\/strong> For example, consider the age-old clich\u00e9 of the Hollywood star who\u2019s \u201cdiscovered\u201d by chance while waiting tables in an LA restaurant. Such stories draw attention<\/a> because they\u2019re unusual. But, because we hear them more often than the more common experience of persistence and rejection, we begin to think of the \u201cone-in-a-million\u201d rise to Hollywood fame as the rule, not the exception.<\/p>\n\n\n\n If commonplace narratives can\u2019t be trusted, where can we turn for accurate information? For individuals, there\u2019s no quick and easy answer. But Stephens-Davidowitz says that, for data scientists studying the human condition, smartphones are a goldmine.<\/strong> Using anonymized smartphone usage statistics, combined with census and tax return data, modern researchers can use analytics to measure and correlate aspects of human behavior to an unprecedented degree. Data scientists can use trends in internet searches, app usage, online commerce, and travel patterns to determine which choices people make have the greatest positive and negative outcomes.<\/p>\n\n\n\n While statistics highlight the relative importance of various life decisions, Stephens-Davidowitz says big data also illustrates how random chance plays a role in achieving success.<\/strong> For instance, consider the world of popular music. An artist might spend years writing songs, performing them in clubs, and sending tracks to record labels without being noticed by the world at large. Then, at random, someone creates a TikTok video using one of the artist\u2019s songs. Out of millions of clips, that video goes viral and the struggling musician is launched into stardom.<\/p>\n\n\n\n But does this mean that people who achieve success are just luckier than everyone else? Not so, says Stephens-Davidowitz. While individual luck is hard to measure, he points to data studies of the corporate world that reveal that the most successful businesses experience the same amount of good and bad luck as companies that don\u2019t perform as well. What this means is that luck is useful only if you take advantage of it.<\/strong> According to Stephens-Davidowitz, luck is fairly evenly distributed. All it does is create opportunities; it\u2019s up to you to grab them.<\/p>\n\n\n\n As we examine Stephens-Davidowitz\u2019s advice, keep in mind that none of the choices he highlights\u2014whether in your love life, your career, or elsewhere\u2014provide a guarantee of success. What he suggests is that making certain choices tips the odds in your favor.<\/strong> Therefore, like the struggling musician above, you can\u2019t take one chance in the hopes that you\u2019ll succeed. Whether you\u2019re going on dates, starting a business, or writing a hit single, you\u2019ll have to try again and again until your lucky break comes along. Statistically, the more times you roll the dice, the greater the odds that you\u2019ll eventually win.<\/p>\n\n\n\n The first aspect of life that Stephens-Davidowitz puts under the data microscope\u2014and one where the \u201ctry and try again\u201d rule clearly applies\u2014is the realm of romantic attraction, dating, and marriage. Information from online dating platforms paints a pretty clear picture of what people search for in romantic partners, some of which, such as personal appearance, are factors you can improve to raise your dating marketability. However, the attributes that make someone initially attractive don\u2019t carry any statistical weight when it comes to maintaining a lifelong relationship.<\/p>\n\n\n\n Stephens-Davidowitz summarizes online dating data thusly: Good looks are the most important factor, especially for women, while men\u2019s attractiveness also depends on income and career. <\/strong>Drilling deeper into the numbers, he finds that, when trying to find a date online:<\/p>\n\n\n\n According to Stephens-Davidowitz, dating data also reveals significant racial bias in the romantic marketplace.<\/strong> In general, the numbers show that people seek partners within their own racial demographic. However, even when people try to cross racial lines, the statistics clearly demonstrate the levels of prejudice baked into society at large. In short, white men sending messages online have the highest odds of any demographic group at getting a favorable response. Black women, on the other hand, get fewer responses than any other group, which Stephens-Davidowitz says severely limits their online dating options.<\/p>\n\n\n\n Not all of the factors listed above are things you can change to improve your luck at dating, but the most significant variable\u2014your appearance\u2014is something you can control. Several studies Stephens-Davidowitz cites show that physical appearance strongly affects how people perceive you in all aspects of life,<\/strong> not just romantically. Research on people\u2019s perceptions of faces makes it clear that we form opinions about strangers within an instant based on nothing more than how they look. However, similar studies also reveal that people respond differently to images of the same individual if the lighting is altered, if they have a different hairstyle, if they\u2019re wearing glasses, and a host of other factors. What matters, then, is finding the right look for you.<\/p>\n\n\n\n The problem is that most of us pick our \u201clook\u201d without being methodical about it. This is where Stephens-Davidowitz says you should adopt a data-driven approach to your appearance.<\/strong> For instance, you can take a picture of yourself and use an app to see what you\u2019d look like if you grew a mustache, wore different makeup, or changed your hairstyle. Then, instead of choosing what you \u201cfeel\u201d looks best, save images of all your potential styles and use them to get feedback. You might ask friends for their opinions. When Stephens-Davidowitz did this, he used online survey apps to poll strangers. In his case, he discovered that growing a beard and wearing glasses greatly improves the first impression he makes.<\/p>\n\n\n\n As much as the numbers tell us about how to attract a romantic partner, they also reveal what\u2019s perhaps more important\u2014the attributes that make potential partners attractive have no impact whatsoever on a relationship\u2019s long-term success.<\/strong> Stephens-Davidowitz says that study after study shows no correlation between what you look for in a relationship and whether that relationship will last. Therefore, the person your gut <\/em>says will make an ideal lifelong partner is nonsense. Judging solely by the criteria that the online dating studies measured, achieving a happy long-term relationship would seem to happen entirely at random\u2014but it doesn\u2019t.<\/p>\n\n\n\n When analyzing relationship longevity, what the data suggests is that we ask the wrong questions when seeking a life partner. According to Stephens-Davidowitz, the most important statistical factor in determining a relationship\u2019s success is <\/strong>your <\/em><\/strong>psychological state.<\/strong> If you\u2019re already happy with yourself, feel secure in your life, and look kindly toward others, you\u2019re four times more likely to be \u201clucky in love\u201d than someone who doesn\u2019t, even if they outscore you on all the traditional measures of attraction.<\/p>\n\n\n\n From all this data on romantic love, Stephens-Davidowitz draws the following conclusions:<\/p>\n\n\n\n There\u2019s no guarantee for romantic happiness, but Stephens-Davidowitz argues that taking the statistics of long-term love to heart can certainly improve your chances.<\/p>\n\n\n\n Just as hard data can give you the tools to be rational in your pursuit of love, it also acts as a guide to financial success<\/a>. According to Stephens-Davidowitz, researchers working with anonymized taxpayer data have determined that more than 80% of the richest people in the US are those who started a business.<\/strong> However the data also reveals that popular beliefs about entrepreneurship are wrong, that the road to wealth is long and boring, and that your odds of achieving runaway financial success are highly dependent on which field you enter.<\/p>\n\n\n\n Stephens-Davidowitz describes the popular myth of entrepreneurship this way: A brilliant young person drops out of college, starts a company in their parents\u2019 garage, invents some genius product that industry insiders would never dream of, and becomes an overnight millionaire. This rarely happens, but when it does, the media latches on to it and milks it for every ounce of drama it\u2019s worth.<\/strong> As a result, all we hear are stories of young, maverick business founders to the point that we believe they\u2019re whom we should emulate.<\/p>\n\n\n\n Despite the myth of the young entrepreneur, the data tells a different story. Stephens-Davidowitz writes that, after crunching the numbers on nearly three million entrepreneurs, two facts stand out:<\/p>\n\n\n\n 1. Your chances of being a successful business<\/a> founder increase with age.<\/strong> Tax data shows that the average person behind a successful new business venture is well into their 40s. The young, daring entrepreneurs of legend are outliers, not the norm.<\/p>\n\n\n\n 2. Your chances of success are double if you already have experience in your field.<\/strong> Like the value of youth, the premise that innovative business<\/a> plans only come from outside an industry is bunk. For the most part, to have a groundbreaking idea, you have to know and understand what\u2019s been tried before.<\/p>\n\n\n\n Therefore, Stephens-Davidowitz argues that big data\u2019s message is clear: To increase your odds of business success, spend the time to fully master your field before trying to start your own company.<\/strong> This may sound obvious, but the more exciting (if spurious) narrative of entrepreneurship has permeated the business world to the point that we now have to back up common sense with hard numbers.<\/p>\n\n\n\n In addition to discussing age and experience, Stephens-Davidowitz highlights studies showing that certain categories of businesses produce the most wealth for individual owners<\/strong>\u2014and unfortunately, they\u2019re not very glamorous. To increase your odds of becoming rich through your business, you\u2019ll want to focus on (in no particular order) car sales, market analysis, real estate, financial investing, and wholesale distribution. None of these are businesses that spark many people\u2019s ambitions when they\u2019re young. Nevertheless, these are the paths that statistically provide the most return on investment.<\/p>\n\n\n\n Beyond the numbers, Stephens-Davidowitz suggests that these profitable businesses share two things in common\u2014they\u2019re relatively immune to competitive price wars, and they\u2019re in industries that aren\u2019t monopolized by multinational giants.<\/strong> The reasons vary from industry to industry: Some are highly localized, some rely on specialized knowledge, and some have legal protections from competition. In each case, these businesses benefit from structural barriers that statistically decrease the odds of defeat by small-business Davids or corporate Goliaths. As much as you may dream of starting some other type of business that aligns with your passions, the data says that if you want wealth, this is the way to achieve it.<\/p>\n\n\n\n In addition to finding love and success, many people dream of starting a family. Yet, once they have children, many worry that they\u2019re doing too much or too little to raise them right. However, Stephens-Davidowitz says that statistical studies on parenting methods reveal something unexpected\u2014that most of the parenting choices people make have very little impact on their children\u2019s development.<\/strong> Nevertheless, there are two exceptions that do have a measurable impact on children\u2019s success as they grow up\u2014where you choose to raise them and, if they have athletic aspirations, which sports you help steer them to.<\/p>\n\n\n\n The idea that parenting styles are unimportant might be hard for many people to believe. Yet, Stephens-Davidowitz states that, when looking at statistically significant numbers of children, big data research supports the strength of genetics in the \u201cnature versus nurture\u201d debate.<\/strong> To differentiate between inborn and environmental factors, scientists study identical twins who grow up apart and families with multiple adopted children (who are genetically dissimilar but share the same upbringing). The numbers reveal that the decisions parents make\u2014from what to feed them, how much screen time they\u2019re allowed, to how strict you are about their grades\u2014have only a marginal impact on children\u2019s success in adult life.<\/p>\n\n\n\n However, the numbers reveal that one factor has an oversized effect on your children\u2019s development\u2014<\/strong>where they grow up<\/em><\/strong>. Not only does it matter what city you raise your child in, but researchers can now determine which individual neighborhoods are best for children. Of all the possible reasons, Stephens-Davidowitz argues that the most compelling is that, by choosing where your children are raised, you determine what adult role models<\/a> they\u2019re exposed to. For example, neighborhoods with many college graduates produce more children who go on to college. Some neighborhoods are better for low-income families\u2014for instance, if they provide role models who succeed despite their financial struggles and are active in their communities.<\/p>\n\n\n\n In short, Stephens-Davidowitz argues that, as long as you\u2019re making an honest effort as a parent, don\u2019t stress about your day-to-day decisions.<\/strong> However, if you\u2019re concerned about your children\u2019s upward mobility, visit the Opportunity Atlas<\/a>, which organizes neighborhood research into a guide to help you find where to best raise your children.<\/p>\n\n\n\n The other decision\u2014which children often make themselves\u2014that adults can nonetheless help to encourage is what sports they might choose to go into. Not all children aspire to be athletes. But, for those who do, Stephens-Davidowitz suggests that big data can help determine the most likely path to athletic success<\/a>.<\/strong> Once again, the question comes down to nature versus nurture\u2014or in this case, genetic predisposition versus the willingness to train and work hard. Does a person have to be a born athlete<\/a>, or can they learn to be one through effort? The statistical answer turns out to be \u201cit depends on the sport.\u201d<\/p>\n\n\n\n Stephens-Davidowitz points to research that tracks different siblings\u2019 athletic success. The numbers show that some sports require the right genes to reach the top, while others are open to anyone willing to learn.<\/strong> Basketball, running, and swimming favor certain genetic traits and body types that align with the mental skills needed for the game, whereas in baseball and football, the genetic factor is smaller. Studies of siblings who qualify for the Olympics reveal that diving, weightlifting, and horseback riding reward effort and training over natural talent more than any other sport. So, as a parent, if your child has aspirations but isn\u2019t \u201cbuilt\u201d for athletics, you might gently guide them to sports they might find more fulfilling.<\/p>\n\n\n\n But, what does it matter what sport a child goes into? Stephens-Davidowitz argues that professional aspirations notwithstanding, athletic scholarships open many doors to college education.<\/strong> If your child is willing to pursue such a path, a statistical analysis of college admissions<\/a> reveals which sports offer the greatest opportunities. The most popular sports are, of course, very competitive, and the average high school athlete\u2019s chances for a scholarship are low. However, several less obvious choices offer greater odds because the ratio of scholarships to applicants leans more heavily in a student\u2019s favor. These include gymnastics, fencing, and hockey for boys, and rowing, horseback riding, and rugby for girls.<\/p>\n\n\n\n So far, all the parts of life we\u2019ve covered\u2014love, success, and parenting\u2014reflect an even larger goal\u2014the desire to simply be happy. Once again, Stephens-Davidowitz argues that big data can offer a guide to happiness by correlating what people do and how they feel <\/strong>on a massive scale. He finds that certain behaviors tend to bring us down while others objectively improve our spirits, suggesting that the path to happiness isn\u2019t that complicated at all. <\/p>\n\n\n\n In this case, the data Stephens-Davidowitz refers to comes primarily from the Mappiness smartphone app<\/a>, which prompted millions of willing participants to record their daily activities as well as their emotional states. The result was a gigantic pool of information that data scientists have been able to mine so they can answer, scientifically, how to be happy<\/a>.<\/p>\n\n\n\n The reason we need data to tell us about happiness is that the human brain is notoriously bad at determining what will make us happy or not.<\/strong> Stephens-Davidowitz points to specific mental errors<\/a> discovered by psychologist Daniel Kahneman<\/a> that warp how we remember our emotions and thus how well we can predict them. The first is that our brains ignore how long an experience lasts, pleasant or otherwise. The other is known as the \u201cpeak-end rule,\u201d which states that, when we look back on an event, we judge whether we were happy or not by how we felt at the most intense moment and how we felt at the end. As a result, our memories are skewed, so we need to look at data collected during happy and unhappy times as they happen<\/em>.<\/p>\n\n\n\n What the numbers reveal is that we spend most of our time doing things that objectively make us unhappy,<\/strong> such as chores, driving to work, and worst of all, work itself. According to Stephens-Davidowitz, work ranks at the bottom<\/em> of the happiness scale, with nothing but illness listed as more unpleasant. For most of us, work is a necessity, and one might argue it leads to happiness later because of the money you earn. However, the research Stephens-Davidowitz cites is clear that money\u2019s effect on happiness is very slight\u2014you\u2019d have to increase your salary by a lot to increase your happiness even by a little.<\/p>\n\n\n\n Stephens-Davidowitz also explains that we\u2019re often wrong about what types of recreation make us happy.<\/strong> In the Mappiness data, \u201crelaxing\u201d pastimes such as watching television, playing video games, and reading books produced fewer feelings of enjoyment than expected. Meanwhile, scrolling through social media produces a decidedly negative <\/em>effect on happiness\u2014Stephens-Davidowitz references one study that showed that the best way to benefit from social media is to quit it. Doing so improves your emotional state in a way that\u2019s comparable to therapy.<\/p>\n\n\n\n Thankfully, there\u2019s good news to go along with the bad. Analysis of the Mappiness data as well as other studies concur that there are clear and relatively direct ways to improve your overall happiness. In general, what the top-ranked happiness-boosting activities have in common is that they involve being active in some way<\/strong>, rather than passive forms of recreation.<\/p>\n\n\n\nOverview of Don’t Trust Your Gut<\/em><\/h2>\n\n\n\n
The Power of Numbers<\/strong><\/h3>\n\n\n\n
The Role of Dumb Luck<\/strong><\/h4>\n\n\n\n
The Numbers on Love<\/strong><\/h3>\n\n\n\n
The Data of Attraction<\/strong><\/h4>\n\n\n\n
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Spruce Yourself Up\u2014Scientifically<\/h5>\n\n\n\n
The Math of \u201cHappy Ever After\u201d<\/strong><\/h4>\n\n\n\n
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The Numbers on Success<\/strong><\/h3>\n\n\n\n
The Real Entrepreneurs<\/strong><\/h4>\n\n\n\n
The Unromantic Side of Business<\/strong><\/h4>\n\n\n\n
The Numbers on Raising Children<\/strong><\/h3>\n\n\n\n
The Community Effect<\/strong><\/h4>\n\n\n\n
How to Pick a Sport<\/strong><\/h4>\n\n\n\n
The Numbers on Being Happy<\/strong><\/h3>\n\n\n\n
Why We\u2019re Miserable<\/strong><\/h4>\n\n\n\n
How to Have a Good Time<\/strong><\/h4>\n\n\n\n