{"id":72996,"date":"2022-07-21T14:23:00","date_gmt":"2022-07-21T18:23:00","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=72996"},"modified":"2022-07-27T13:54:29","modified_gmt":"2022-07-27T17:54:29","slug":"everybody-lies-big-data","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/everybody-lies-big-data\/","title":{"rendered":"Everybody Lies: Big Data Interesting Facts"},"content":{"rendered":"\n<p>What are some interesting facts from <em>Everybody Lies<\/em>? What do these facts tell us about big data?<\/p>\n\n\n\n<p><em>Everybody Lies <\/em>draws on data scientist Seth Stephens-Davidowitz&#8217;s research using Google search results as well as data from PornHub, Wikipedia, and more. The book contains many surprising and fascinating findings from his research.<\/p>\n\n\n\n<p>Read more for <em>Everybody Lies<\/em>&#8216;s big data facts that will surprise you.<\/p>\n\n\n\n<!--more-->\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-everybody-lies-s-insights-and-curiosities\"><strong><em>Everybody Lies<\/em>\u2019s Insights and Curiosities<\/strong><\/h2>\n\n\n\n<p><em>Everybody Lies <\/em>is full of strange, interesting, and disturbing insights into human nature. Throughout the book, Stephens-Davidowitz\u2019s arguments focus on the logical core of big data\u2014but there are still juicy tidbits about big data in <em>Everybody Lies<\/em>. Given how important (and fun) those tidbits are to the book as a whole, we\u2019d be remiss not to share a few of the more interesting details. For instance:<\/p>\n\n\n\n<p>1) Conventional wisdom holds that most professional basketball players come from poor inner-city backgrounds\u2014but, for black players, in particular, <strong>being born in a wealthy county doubles the chances of reaching the NBA<\/strong>. Stephens-Davidowitz explains that a wealthier background means better nutrition (which translates to height) and better interpersonal skills (which help players navigate the pressures and politics of professional sports).&nbsp;<\/p>\n\n\n\n<p>2) According to textual analysis, American newspapers on average are more liberal than conservative\u2014not because the papers themselves have a political agenda, but because they shape their content to appeal to the political biases of their audiences.<\/p>\n\n\n\n<p>3) Women are twice as likely as men to search for porn that features violence against women.<\/p>\n\n\n\n<p>4) Violent movies reduce the rate of violent crimes.<\/p>\n\n\n\n<p>5) Super Bowl ads are so effective that companies are underpaying for them. The ad\u2019s impact is strongest in the markets whose teams play in the game.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The Humanity of Data Analytics<\/strong><\/h2>\n\n\n\n<p>It\u2019s also worth ending on facts like these because, while they might seem trivial, they remind us of the human interest at the core of <em>Everybody Lies<\/em>. As Stephens-Davidowitz points out, data isn\u2019t valuable in and of itself\u2014its value lies in its potential to advance human ends. Ultimately, it\u2019s not about any specific technique or technology or even about big data per se; it\u2019s about how new information\u2014and new ways of <em>working with<\/em> information\u2014can help us better understand ourselves and improve our lives. We can infer that Stephens-Davidowitz includes these fascinating insights, in part, to connect data with our humanity, and it previews where data has gone since.<\/p>\n\n\n\n<p>If we review the trends in data science since <em>Everybody Lies<\/em>\u2019 2017 publication, we see an increasing emphasis on combining data with human insight. In recent years, data scientists, technology professionals, and companies have emphasized more flexible and versatile data applications and better integration with human users. For example:<\/p>\n\n\n\n<p>1) The fields of AI and machine learning have moved away from ever-larger <a href=\"https:\/\/www.shortform.com\/blog\/multiple-data-sets\/\">data sets<\/a> in favor of techniques like transfer learning, in which <a href=\"https:\/\/www.scientificamerican.com\/article\/small-data-are-also-crucial-for-machine-learning\/\">machines are programmed to learn new but related tasks<\/a> based on things they already know. This approach allows researchers to use AI to study problems for which large data sets might not be available or practical.<\/p>\n\n\n\n<p>2) Similarly, developers have found that AI works best when it\u2019s trained not just by large datasets, but also by human expertise. This approach not only improves the AI but also leads to a <a href=\"https:\/\/hbr.org\/2020\/02\/small-data-can-play-a-big-role-in-ai\">helpful division of labor<\/a> as computers tackle <a href=\"https:\/\/www.shortform.com\/blog\/routine-tasks\/\">routine tasks<\/a> and humans only step in to solve more difficult problems.<\/p>\n\n\n\n<p>3) Many companies have started pursuing <a href=\"https:\/\/amplitude.com\/blog\/data-democratization\">data democratization<\/a>\u2014a practice of empowering everyone in the organization (not just specialized analysts) to understand, access, and work with data.As technology continues to evolve, the specifics will keep changing; as we can see, data research already looks different from what we find in <em>Everybody Lies<\/em>. But as society becomes increasingly driven by data, it only becomes more important to consider the underlying human potential (for good and harm) that Stephens-Davidowitz describes.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What are some interesting facts from Everybody Lies? What do these facts tell us about big data? Everybody Lies draws on data scientist Seth Stephens-Davidowitz&#8217;s research using Google search results as well as data from PornHub, Wikipedia, and more. The book contains many surprising and fascinating findings from his research. Read more for Everybody Lies&#8216;s big data facts that will surprise you.<\/p>\n","protected":false},"author":14,"featured_media":73271,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[40,160,25],"tags":[691],"class_list":["post-72996","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-books","category-science","category-statistics","tag-everybody-lies","","tg-column-two"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.3 (Yoast SEO v24.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Everybody Lies: Big Data Interesting Facts - Shortform Books<\/title>\n<meta name=\"description\" content=\"In Everybody Lies, big data is the main focus. 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