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664 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Steven Pinker, Seth Stephens-Davidowitz
3.82 AVERAGE
664 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Steven Pinker, Seth Stephens-Davidowitz
3.82 AVERAGE
When are we telling the truth? Economists, psychologists, sociologists and other social scientists are always trying to uncover truths about the (human) world. Up to now, they were able to collect data from sources like surveys - these sources are filled out by other humans, like us... and we lie. All the time.
However, there's at least one place - a sort of digital confessional - were we pour our heart and soul, were we place our deepest fears and desires: Google. Seth Stephens-Davidwitz explores the vast world of human behaviour, especially our recent digital footprint, to uncover new insights about our society.
From testing Freudian theories to predicting crime rates with movies, the book is a really fun read, with many quirky examples.
However, there's at least one place - a sort of digital confessional - were we pour our heart and soul, were we place our deepest fears and desires: Google. Seth Stephens-Davidwitz explores the vast world of human behaviour, especially our recent digital footprint, to uncover new insights about our society.
From testing Freudian theories to predicting crime rates with movies, the book is a really fun read, with many quirky examples.
Fascinating, educational read. Talks about with the development and progression of the digital age, we finally can learn more about the contents of people's thoughts or, in the words of the author "we can finally see through people's lies." A good example the author uses is how all the traditional polls during the 2016 presidential election did not predict the election of Donald Trump, however if people had turned to google searches, they would have been able to predict his victory and this is because people lie ... they lie to their friends, family, strangers, but they are truthful with google. Would definitely recommend as it introduces new data relevant in this modern, technological age on people, their reactions, thoughts, worries and of course, their google searches.
funny
informative
medium-paced
Interesting premise. Essentially argues that the algorithms used by Big Data reveal truths we hide from sometimes even ourselves. Caution for my high school friends. The author investigates some more “mature” sources of Internet data.
If the ideas of Noah Yuval Harari interest you, especially how the revolution in AI will affect individuals and society, here is a great introduction to the power that Big Data and the insights that can be gleaned from it. It is well written, given the complexity of the subject, and you'll be thinking about the various areas it covers for a long time. One of the more interesting things is that now, with Big Data, the so-called "soft sciences" such as psychology and sociology, for instance, can be put on a firmly quantitative footing. Without giving anything away, we've all heard the expression "Freudian slip". So is that something that is real or more of an insight into Freud's mind? Read the book to find out!
should've just wrote an extended new yorker article or some shit.
seriously.
seriously.
i guess, to use this example, what i'd expected is a breakdown on why knowing american men are gay is important. cast allusions to the way of life, to the economy, to the bias towards heterosexual nuclear families as fundamental to the functioning of capitalism as we know it. anything but "haha 4.8% of men in texas search for gay porn!! way higher than rhode island!! but facebook surveys say only 2% watch gay porn!!". though subsequently he does address this via his thesis statement: that google searches are a more honest way of obtaining data. women who suspect their husbands are gay (and of course, this only applies to closeted gay/bi/pan/what have you men) do sometimes google "how do i know my husband likes dick?".
what i do enjoy about this book is him introducing inventive ways of obtaining data. what do you look at vs. what do you don't? how do you avoid from making correlation/causation assumptions? he introduces a number of pitfalls (coin 372) that i've never heard of when it comes to data analysis, and that was fascinating. but he lets his """humorous personality""" (his words, not mine) eclipse the data side of this and it sucks. for example:
conclusion? this dude needs to get on more qual studies.
Spoiler
i'm beginning to think my issue is just reading books by white dudes, whose fundamental perspective in life is narrow as fuck and differs greatly from mine (also see: my take on what could b a phenom sf novel but is sadly impeded by white guyism) and that i should probably stop reading books authored by people like these. but you never know, do you? you never know if you'll end up with a pratchett or if you find yourself mid-way through a book about big data and google searches and having to read the line "How many American men are gay? This is a legendary question in sexuality research".seriously.
seriously.
i guess, to use this example, what i'd expected is a breakdown on why knowing american men are gay is important. cast allusions to the way of life, to the economy, to the bias towards heterosexual nuclear families as fundamental to the functioning of capitalism as we know it. anything but "haha 4.8% of men in texas search for gay porn!! way higher than rhode island!! but facebook surveys say only 2% watch gay porn!!". though subsequently he does address this via his thesis statement: that google searches are a more honest way of obtaining data. women who suspect their husbands are gay (and of course, this only applies to closeted gay/bi/pan/what have you men) do sometimes google "how do i know my husband likes dick?".
what i do enjoy about this book is him introducing inventive ways of obtaining data. what do you look at vs. what do you don't? how do you avoid from making correlation/causation assumptions? he introduces a number of pitfalls (coin 372) that i've never heard of when it comes to data analysis, and that was fascinating. but he lets his """humorous personality""" (his words, not mine) eclipse the data side of this and it sucks. for example:
Perhaps someone in the president’s office had read Soltas’s and my Times column, which discussed what had worked and what didn’t. For the content of this speech was noticeably different.
When people learn that I am a data scientist and a writer, they sometimes will share some fact or survey with me. I often find this data boring—static and lifeless. It has no story to tell. Likewise, friends have tried to get me to join them in reading novels and biographies. But these hold little interest for me as well. I always find myself asking, “Would that happen in other situations? What’s the more general principle?” Their stories feel small and unrepresentative.
conclusion? this dude needs to get on more qual studies.
Very interesting and illuminating. Definitely learned a lot reading this. We tend to(at least I did) think of "big data" as a privacy issue, and problem that the tech giants need to be reined in on. This book takes a (mostly) positive look at all the great things that big data can be used for that we don't normally think of. Not to make money, or sell it, but for psychological, behavioral, and scientific research as well.
informative
lighthearted
medium-paced
Note: I accessed a digital review copy of this book through Edelweiss.