Yes, I say, but we've long been numbers. Think of the endless rows of workers threading together electronic cables in a Mexican assembly plant or the thousands of soldiers rushing into machine-gun fire at Verdun — even the bless-out crowd pushing through the turnstiles at a Grateful Dead concert. From management's point of view, all of us in these scenarios might as well be nameless and faceless. We're utterly interchangeable. Turning us into simple numbers was what happened in the industrial age. That was yesterday's story.

The Numerati have much more ambitious plans for us. Forget single digits. They want to calculate for each of us a huge and complex maze of numbers and equations. These are mathematical models. Scientists have been using them for decades to simulate everything from fleets of trucks to nuclear bombs. They build them from vast collections of data, with every piece representing a fact of a probability. Each model must reflect, in numbers, the physical truth: its size and weight, the characteristics of its metal and plastics, how it responds to changes in air pressure or heat. Complex models can have thousands, or even millions, of variables. And they must interact with one another mathematically just the way they do it the real world. Building them is painstaking work. And sometimes they flop. The dramatic market convulsions of 2008, for example, stemmed from faulty models that glossed over the complexity — and the risk — associated with real estate loans.

Despite such stumbles, today's Numerati are plowing forward with an eye on us. They're already stitching bits of our data into predictive models, and they're just getting warmed up. In the coming decade, each of us will spawn, often unwittingly, models of ourselves in nearly every walk of life. We'll be modeled as workers, patients, soldiers, lovers, shoppers and voters. In the early days, most of the models are still primitive, making us look like stick figures. The ultimate goal, though, is to build versions of humans that are just as complex as we are — each one unique. Add all of these efforts together, and we're witnessing (as well as experiencing) the mathematical modeling of humanity. It promises to be one of the great undertakings of the twenty-first century. It will grow in scope to include much of the physical world as mathematicians get their hands on new flows of data, from constellations of atmospheric sensors to the feeds from millions of security cameras. It's a parallel world that's taking shape, a laboratory for innovation and discovery composed of numbers, vectors and algorithms. And you and I are in the middle of it.

What will the Numerati learn about us as they turn us into dizzying combinations of numbers? First they need to find us. Say you're a potential SUV shopper in the northern suburbs of New York, or a churchgoing, antiabortion Democrat in Albuquerque, New Mexico, or a jazz-loving, Chianti-sipping Sagittarius looking for snuggles by the fireplace in Stockholm. Heaven help us; maybe you're eager to strap bombs to your waist and climb onto a bus. Whatever you are — and each of us is a lot of things — companies and governments want to identify and locate you. Consider this: Google grew to a multibillion-dollar sensation by helping us find the right Web page. How much more valuable will it be, in every conceivable industry, to find the right person? That information is worth fortunes, and the personal data we throw off draws countless paths straight to our door. Even if you hold back your name, it's a cinch to find you. A Carnegie Mellon University study recently showed that simply by disclosing gender, birth date and postal zip code, 87 percent of the people in the United Sates could be pinpointed by name.

The Numerati also want to alter our behavior. If we're shopping, they want us to buy more. At the workplace, they're out to boost our productivity. As patients, they want us healthier and cheaper. As companies such as IBM and Amazon roll out early models of us, they can predict our behavior and experiment with us. They can simulate changes in a store or an office and see how we would likely react. And they can attempt to calculate mathematically how to boost our performance. How would shoppers like you respond to a $100 rebate on top-of-the-line Nikon cameras? How much more productive would you be at the office if you had a $600 course on spreadsheets? How would your colleagues cope if the company eliminated their positions or folded them into operations in Bangalore? The Numerati will be placing our models in all kinds of scenarios. They'll see how we might respond to a new exercise regimen or job transfer to a distant division. We don't have to participate or even know that out mathematical ghosts are laboring night and day as lab rats. We'll receive the results of these studies — the optimum course — as helpful suggestions, prescriptions or marching orders.

The exploding world of data, we we'll see, is a giant laboratory of human behavior. It's a test bed for the social sciences, for economic behavior and psychology. Researchers at companies such as Microsoft and Yahoo are busy hiring scientists from fields as diverse as medicine and linguistics to help them grapple with the bits and our lives that are pouring in. These streams of digital data don't recognize ancient boundaries. They're defined by algorithms, not disciplines. They can easily cross-fertilize. This means that psychologists, economists, biologists and computer scientists can collaborate as never before, all of them sifting for answers throughout countless details of our lives. Jack Einhorn, the chief scientist at a New York media start-up called Inform Technologies, predicts that the great discoveries of the twenty-first century will come from finding patterns in vast archives of data. "The next Jonas Salk will be a mathematician," he says, "not a doctor."

From the first chapter, "Worker":


Back when [George] Dantzig was putting the final touches on his algorithm, IBM researchers were already preparing to apply operations research to their own business. They had the mother of all tests for it: IBM's massive supply chain. To build its renowned office machines (which didn't yet include commercial computers), IBM bought parts and raw materials from suppliers all over the world. Naturally, these were a major expense. If the company could use this new math to organize it all, the savings would drop straight to the bottom line.

The math worked. In fact, IBM was able to turn this particular know-how into a business. The company's experts helped other companies convert their own logistics into math and then optimize them. This is where the story turns inside out, a bit like that drawing by M.C. Escher, where the artist's hand is drawing itself. In the past couple of decades, IBM's focus moved from manufacturing to services. The company now sells more expertise than machinery. It unloaded its personal computer division to China's Lenovo in 2005, and IBM Global Services has grown into a $40 billion business. So if IBM's experts were to optimize their supply chain today, they would have to model and fine-tune themselves. That's precisely what [Samer] Takriti's team is busy doing.

Just think where this could lead. We've seen, with supply chains, how the company used itself as a laboratory. It mastered the process for itself and then sold the expertise to others. Now the company is modeling its workers. If this leads to big gains in productivity, do you think that expertise will remained locked up inside Big Blue? I don't. Imagine mathematical modelers arriving at the doors of your company one day either as a phalanx of blue-clad consultants or perhaps encoded in a piece of software. Their focus will be on you.

Click here to read the interview with Stephen Baker, author of "The Numerati."

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