Everybody Lies
Ratings60
Average rating3.8
15
Ratings60
Average rating3.8
Foreword by Steven Pinker Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions. By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable. Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women? Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.
Reviews with the most likes.
The upshot of this book is not that big data is the holy grail. Rather, the recurring theme in all of Stephens-Davidowitz's interesting examples is just that most self-reporting is awful.
I'm still skeptical about the big data revolution–and this book doesn't really focus on implicit bias in analysis of large data sets–but the conventional research methods of social sciences are amusingly torn to pieces (much like advertising ROI was absolutely shredded in the digital age where measurement was no longer entirely by gut).
It was touch and go with this book. I was halfway into it and ready to put it aside, funny curiosities about what people search on Google or what Facebook data says about us simply doesn't cut if for me anymore. I think Yuval Noah Harari set the bar too high in Homo Deus, by covering most interesting findings big data has to offer in an elegant and concise manner.
However, the second half of the book covers a bit more of human behaviour, data misrepresentations and the extent to which big data can be applied. I found that to be unique and informative enough to do some research on my own.
Although Big Data is no longer considered to be the new kid on the block, it is still very important (Google and Facebook are definitely making a hefty profit out of it), but the sooner fields like psychology, sociology, anthropology are going to embrace it, the better for us as human beings.
Turns out the google searchbar is the only place where we don't lie to ourselves or others. That's where we reveal our strangest fears, hidden prejudices and kinkiest wishes. Data scientist can wrangle that data to learn how racist we truly are, how sexist we raise our children and how much sex we're truly having. The book contains a lot of examples demonstrating how big data and data analysis methods now enable us to see connections and correlations where previously we were just blind guessing. It helps to pick the winning racehorse, reveals that good students have promising futures no matter which school they attend, and shows that violent movies help lower the crime rates on opening weekends.
So, all in all lots of interesting anecdotes, a lot of them on the juicy side, mixed with occasionally slightly inappropriate jokes. The book could have used a little less of the author trying to insert himself. Also, some of his analogies were just wrong (no, the grandma is not big-data).
3.5
