This article is an excerpt from the Shortform book guide to "Everybody Lies" by Seth Stephens-Davidowitz. Shortform has the world's best summaries and analyses of books you should be reading.
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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’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‘s big data facts that will surprise you.
Everybody Lies’s Insights and Curiosities
Everybody Lies is full of strange, interesting, and disturbing insights into human nature. Throughout the book, Stephens-Davidowitz’s arguments focus on the logical core of big data—but there are still juicy tidbits about big data in Everybody Lies. Given how important (and fun) those tidbits are to the book as a whole, we’d be remiss not to share a few of the more interesting details. For instance:
1) Conventional wisdom holds that most professional basketball players come from poor inner-city backgrounds—but, for black players, in particular, being born in a wealthy county doubles the chances of reaching the NBA. 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).
2) According to textual analysis, American newspapers on average are more liberal than conservative—not because the papers themselves have a political agenda, but because they shape their content to appeal to the political biases of their audiences.
3) Women are twice as likely as men to search for porn that features violence against women.
4) Violent movies reduce the rate of violent crimes.
5) Super Bowl ads are so effective that companies are underpaying for them. The ad’s impact is strongest in the markets whose teams play in the game.
The Humanity of Data Analytics
It’s also worth ending on facts like these because, while they might seem trivial, they remind us of the human interest at the core of Everybody Lies. As Stephens-Davidowitz points out, data isn’t valuable in and of itself—its value lies in its potential to advance human ends. Ultimately, it’s not about any specific technique or technology or even about big data per se; it’s about how new information—and new ways of working with information—can 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.
If we review the trends in data science since Everybody Lies’ 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:
1) The fields of AI and machine learning have moved away from ever-larger data sets in favor of techniques like transfer learning, in which machines are programmed to learn new but related tasks 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.
2) Similarly, developers have found that AI works best when it’s trained not just by large datasets, but also by human expertise. This approach not only improves the AI but also leads to a helpful division of labor as computers tackle routine tasks and humans only step in to solve more difficult problems.
3) Many companies have started pursuing data democratization—a 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 Everybody Lies. 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.
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Here's what you'll find in our full Everybody Lies summary :
- How people confess their darkest secrets to Google search
- How this "big data" can be used in lieu of voluntary surveys
- The unethical uses and limitations of big data