The Numerati: We’re All Just a Number
Mathematical modeling of humanity: Interview with Stephen Baker of BusinessWeek and the author of “The Numerati.”
By Peter Horner
Stephen Baker, a journalist who has written for BusinessWeek for more than 20 years, is a “words” guy, not a “numbers” guy, but Baker’s world took a quantitative turn in 2006 while he was researching a BW cover story entitled, appropriately enough, “Math Will Rock Your World.”
According to Baker, the defining moment came when he first interviewed Samer Takriti, a senior manager in the Mathematical Sciences Department at IBM’s Thomas Watson Research Laboratory near New York City. Takriti and his team were working on a project aimed at building a mathematical model of thousands of IBM consultants in order to inventory their skills and optimally deploy them.
“I said to myself, ‘Wow, if Takriti can do that with IBM employees, other mathematicians like him can no doubt figure out a way to do the same thing with other groups of people,’ ” Baker recalls.
As Baker ultimately reported, the concept of mathematical modeling of human behavior and decision-making – pioneered most famously by companies such as Amazon and Netflix – is reshaping not only the way the corporate world conducts its business, but also the very nature of that business, not to mention how we shop, vote, interact with our doctor and select our potential soul mates. Massive computing power combined with mountains of data – gleaned from every swipe of a credit card, click on a Web site or placing of a phone call – make it all possible and practical.
After chatting with Takriti, Baker had his cover story. He also had an idea for a book that would explore the mathematical modeling of humanity, a Wizard-of-Oz world in which analysts of all stripes – data miners and statisticians, operations researchers and management scientists, mathematicians and mad scientists, number-crunchers and nerds – work behind the curtain to predict with amazing accuracy what we will “buy” in just about any marketplace – from the voting booth to the grocery store to the doctor’s office.
Baker’s book, “The Numerati” (Baker’s word for all-of-above math wizards), was published earlier this year and immediately drew considerable attention from readers, reviewers and bloggers alike, many of whom jumped on the invasion-of-privacy angle and wondered if the numerati (the math whizzes, not the book) were some kind of math mafia or Big Brother out to control our lives through nefarious methods. One pundit called it “the ultimate revenge of the nerds.”
Should we be concerned that so many of our seemingly innocuous activities can be captured electronically, data-mined, analyzed and used to compile a profile of us and our wants, needs, preferences and desires, or do the benefits of better service through microtargeted marketing outweigh what we lose in privacy?
We put those and other questions to Baker in an interview in October held during the annual meeting of the Institute for Operations Research and the Management Sciences (INFORMS) in Washington, D.C. Baker was at the conference for a book-signing session. After a couple of hours of brisk book business, Baker sat down for the following chat.
As a journalist, you’ve been covering the business world for more than 20 years. In terms of business trends and developments, put in perspective the ability for tech-savvy companies to “mathematically model humanity.”
It is incredibly important and powerful and scalable. For the first time in history we can compare each one of us to a hundred million other people. We can compare each one of us in a number of different variables to millions of other people in very little time. It gives us the opportunity to understand a lot about ourselves and about other people and to create new services and industries that would not have been impossible before. It also revolutionizes existing industries that have traditional ways of understanding people. If you’re running a big, global corporation or a government, there’s no way you can afford to run it in the old analog style. You have to automate. The question is, do you automate it intelligently or not? Operations research and analytics is at the very heart of this new wave that humans have of organizing our affairs and communicating with each other.
What is the target audience for “The Numerati”?
Educated and curious people who are not experts in this field and want to understand how the world is changing. My wife, for example. She’s a college graduate, reads the New York Times, listens to NPR, cares about current affairs and is curious about the world, but she doesn’t know anything about computer science, much less analytics or operations research. That’s the target audience.
How about C-level executives? Do you think they know this stuff?
I don’t want to generalize about it, but I would imagine that many C-level executives do not know that much about these things, either. I read one of the books on the fall of Enron called “Conspiracy of Fools.” I am convinced from reading the book that Ken Lay, the CEO of Enron, had no idea what his numbers people were doing. He just trusted them to know what they were doing. It’s like he was thinking, ‘They’re cutting-edge, they’re so smart and boy am I lucky to have them.’ According to the book, Lay didn’t know what his own company was selling.
That sounds frighteningly similar to the events that led up to the great 2008 financial sector meltdown.
It would be interesting to see how much our political leaders know about economics and financial matters. I imagine there are some who have no idea what’s going on. A leader of one of the congressional committees, I believe it was the Commerce Committee, called the Internet “a series of tubes.”
In the book you write “the dramatic market convulsions of 2008 … stemmed from faulty models that glossed over the complexity – and risk – associated with real estate loans.” Care to elaborate?
I believe Alan Greenspan in congressional testimony mentioned that mathematical modeling had failed. I don’t know about the mathematics, but I do know based on what I’ve learned since then that much of it was built on extremely faulty data. These people know better than anybody about garbage in, garbage out. Some of the data included bundled bunches of extremely high-risk loans in mortgage packages that were considered solid – as good as money. If you have those assumptions going into the model, you could have the most brilliant mathematician in the world behind it and it’s going to be a failed model because the assumptions are totally wrong.
After a financial meltdown of this magnitude, people look around for someone or something to blame. Will mathematical modeling be the fall guy?
It’s not like there’s a non-math alternative that’s going to work, right? When you’re dealing with a global financial system, everything has to run on math because it’s the only way that you can scale it and capture all of the variables involved in it. It’s either good math or bad math, but it’s not going to cease being math. You’re not going to go back to some kind of buddy network where people are just tapping each other on the shoulder or having interviews in offices. I think what’s going to happen as a result of the meltdown is you might see some people try to turn off the automatic systems because they don’t trust them. They’ll try to go back to the old days when you actually met people and asked them about investments and loans and someone personally approved them. But that is so inefficient. Someone will say we can do 10 times the volume and make 10 times as much money if we automate the process, so it will get right back to the way it is now. It’s inevitable.
On a personal level, do you buy into “The Numerati” way of the world?
Look at everything that everyone around you does and how our world works. I trust myself to them every time I climb on an airplane, right? In so many aspects of the logistical world, there’s science that makes things work. Far be it for me to say that I don’t trust it, because I trust it when I eat food. I trust it when I make a cell phone call. It underlies so much in this world. Of course it works.
What about the privacy issues raised by “The Numerati”?
First of all, people don’t like the idea of other people looking into what they buy, so it’s important to make the point that these are machines flipping through our data at rocket speeds, not a bunch of people listening to our conversations and laughing at us. Secondly, a lot of people are concerned about privacy and justifiably so, but when given a choice between privacy and convenience, monetary savings and the promise of security, they usually opt to give up privacy in exchange for those things. They use a cell phone, they go through the EZ pass lane when driving to work, they buy the OnStar in GM cars, they use the supermarket discount cards, they do all kinds of Web surfing and don’t erase their cookies. Why? Because there’s all kinds of conveniences in this world, and customized service isn’t necessarily a bad thing. If Netflix knows what movies you like, you get better service. If your doctor knows which medicines work best for you, you’re a lot better off. So there are all kinds of benefits. Yes, we give up some of our privacy, but we’re no longer treated as some kind of herd animal as we were in the 1950s and 1960s.
Back to the financial meltdown. How is this working for guys in the business press? Is it a good story or a bad story?
It’s a fantastic story to cover as journalists. It’s got drama, it’s got massive implications, it changes day by day, it’s the kind of thing we live for. The only trouble is, it’s also pummeling the economy that sustains our business. We’re covering a storm that is battering us.
You’re a words person, not a math person. After researching and writing “The Numerati,” what’s your take on the numbers guys and gals now?
Because math is at the heart of so much of how the world works, it’s not going to cease being important just because problems come up that have math associated with them, like this financial mess. I want my kids to know more math. My kids are not on a calculus track. They are likely to be humanities majors in college like me, but I think understanding statistics and probability is really important. Taking courses in those areas is a good idea even if you are not on the astrophysics track. We should all understand probability; it will help make us smarter in so many ways and help us make better decisions every day of our lives. ?
Peter Horner (email@example.com) is the editor of Analytics and OR/MS Today, the magazine of membership of INFORMS.
The Numerati Stephen Baker, author of “The Numerati,” has written for BusinessWeek for more than 20 years.
From the introduction:
When I tell people about this book, they often say, “We’re just going to be numbers!”
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.
Excerpted from “The Numerati” by Stephen Baker, copyright © 2008. Reprinted with permission of Houghton Mifflin Harcourt Publishing. All rights reserved.