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Can Software Replace Human Intuition?

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If you’re 33 years old and have attended a few family Thanksgivings in a row without a date, the topic of mate choice is likely to arise. And just about everybody will have an opinion.

“Seth needs a crazy girl, like him,” my sister says.

“You’re crazy! He needs a normal girl to balance him out,” my brother says.

“Seth’s not crazy,” my mother says.

“You’re crazy! Of course Seth is crazy,” my father says.

All of a sudden, my shy, soft-spoken grandmother, quiet through the dinner, speaks. The loud, aggressive New York voices go silent, and all eyes focus on the small old lady with short yellow hair and still a trace of an Eastern European accent. “Seth, you need a nice girl. Not too pretty. Very smart. Good with people. Social, so you will do things. Sense of humor, because you have a good sense of humor.”

Why does this old woman’s advice command such attention and respect in my family? Well, my 88-year-old grandmother has seen more than everybody else at the table. She’s observed more marriages, many that worked and many that didn’t. And over the decades, she has catalogued the qualities that make for successful relationships. At that Thanksgiving table, for that question, my grandmother has access to the largest number of data points. My grandmother is Big Data.

Like it or not, data is playing an increasingly important role in all of our lives — and its role is going to get larger. Newspapers now have full sections devoted to data. Companies have teams with the exclusive task of analyzing their data. Investors give startups tens of millions of dollars if they can store more data. Even if you never learn how to run a regression or calculate a confidence interval, you are going to encounter a lot of data — in the pages you read, the business meetings you attend, the gossip you hear next to the watercoolers you drink from.

At its core, data science is about spotting patterns and predicting how one variable will affect another.

Many people are anxious over this development. They are intimidated by data, easily lost and confused in a world of numbers. They think that a quantitative understanding of the world is for a select few left-brained prodigies, not for them. As soon as they encounter numbers, they are ready to turn the page, end the meeting, or change the conversation.

But I have spent 10 years in the data analysis business and have been fortunate to work with many of the top people in the field. And one of the most important lessons I have learned is this: Good data science is less complicated than people think. The best data science, in fact, is surprisingly intuitive.

What makes data science intuitive? At its core, data science is about spotting patterns and predicting how one variable will affect another. People do this all the time.

 

This is an excerpt from an article that is featured in the January/February 2018 issue of The Saturday Evening Post. Subscribe to the magazine for more art, inspiring stories, fiction, humor, and features from our archives.

Seth Stephens-Davidowitz is a Harvard-trained economist, former Google data scientist, and author of The New York Times best-seller Everybody Lies (Dey Street Books, 2017).

From the book Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are by Seth Stephens-Davidowitz.
Copyright © 2017 by Seth Stephend-Davidowitz. reprinted by permisson of Dey Street Books, an imprint of Harper-Collins Publishers.

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