Alex Pentland

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Alex Pentland got his start in Big Data, wearables and the quantified life while working with Canadian beavers four decades ago. From Maria Konnikova at the Verge:

“It all started with beavers. When Alex Pentland was three years into his undergraduate degree at the University of Michigan, in 1973, he worked part-time as a computer programmer for NASA’s Environmental Research Institute. One of his first tasks — part of a larger environmental-monitoring project — was to develop a method for counting Canadian beavers from outer space. There was just one problem: existing satellites were crude, and beavers are small. ‘What beavers do is they create ponds,’ he recalls of his eventual solution, ‘and you can count the number of beavers by the number of ponds. You’re watching the lifestyle, and you get an indirect measure.’

The beavers were soon accounted for, but Pentland’s fascination with the underlying methodology had taken root. Would it be possible, the 21-year-old wondered, to use the same approach to understand people and societies, or use sensors to unravel complex social behavior? And in so doing, could we find a way to improve our collective intelligence — to create, in a sense, a world that was more suited to human needs, where cities and businesses alike were developed using objective data to maximize our happiness and productivity?

Pentland would spend the next four decades exploring those very questions, finding ways to observe people and their patterns from a computer rather than outer space.”

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In the new Technology Review article “The Limits of Social Engineering,” Nicholas Carr looks at the potential and pitfalls of Big Data, which can tell us where things are going but can also bury the lead. In the piece, Carr references a 1969 Playboy interview with Marshall McLuhan, which was both really wrong and really right. The opening:

“In 1969, Playboy published a long, freewheeling interview with Marshall McLuhan in which the media theorist and sixties icon sketched a portrait of the future that was at once seductive and repellent. Noting the ability of digital computers to analyze data and communicate messages, he predicted that the machines eventually would be deployed to fine-tune society’s workings. ‘The computer can be used to direct a network of global thermostats to pattern life in ways that will optimize human awareness,’ he said. ‘Already, it’s technologically feasible to employ the computer to program societies in beneficial ways.’ He acknowledged that such centralized control raised the specter of ‘brainwashing, or far worse,’ but he stressed that ‘the programming of societies could actually be conducted quite constructively and humanistically.’

The interview appeared when computers were used mainly for arcane scientific and industrial number-crunching. To most readers at the time, McLuhan’s words must have sounded far-fetched, if not nutty. Now they seem prophetic. With smartphones ubiquitous, Facebook inescapable, and wearable computers like Google Glass emerging, society is gaining a digital sensing system. People’s location and behavior are being tracked as they go through their days, and the resulting information is being transmitted instantaneously to vast server farms. Once we write the algorithms needed to parse all that ‘big data,’ many sociologists and statisticians believe, we’ll be rewarded with a much deeper understanding of what makes society tick.

One of big data’s keenest advocates is Alex ‘Sandy’ Pentland, a data scientist who, as the director of MIT’s Human Dynamics Laboratory, has long used computers to study the behavior of businesses and other organizations. In his brief but ambitious new book, Social Physics, Pentland argues that our greatly expanded ability to gather behavioral data will allow scientists to develop ‘a causal theory of social structure’ and ultimately establish ‘a mathematical explanation for why society reacts as it does’ in all manner of circumstances. As the book’s title makes clear, Pentland thinks that the social world, no less than the material world, operates according to rules. There are ‘statistical regularities within human movement and communication,’ he writes, and once we fully understand those regularities, we’ll discover ‘the basic mechanisms of social interactions.'”

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Economist editors discuss how Big Data is changing human modeling, how it can be used to predict–even direct–group behavior, with MIT’s Alex Pentland, author of the new book, Social Physics. Watch six-minute video here.

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Esther Dyson has called for quantified communities, and others are working in the same direction. Computer scientist Sandy Pentland argues at Edge that Karl Marx and Adam Smith didn’t possess the proper information to be completely correct, but we now do:

“These Big Data issues are important, but there are bigger things afoot. As you move into a society driven by Big Data most of the ways we think about the world change in a rather dramatic way. For instance, Adam Smith and Karl Marx were wrong, or at least had only half the answers. Why? Because they talked about markets and classes, but those are aggregates. They’re averages.

While it may be useful to reason about the averages, social phenomena are really made up of millions of small transactions between individuals. There are patterns in those individual transactions that are not just averages, they’re the things that are responsible for the flash crash and the Arab spring. You need to get down into these new patterns, these micro-patterns, because they don’t just average out to the classical way of understanding society. We’re entering a new era of social physics, where it’s the details of all the particles—the you and me—that actually determine the outcome. 

Reasoning about markets and classes may get you half of the way there, but it’s this new capability of looking at the details, which is only possible through Big Data, that will give us the other 50 percent of the story. We can potentially design companies, organizations, and societies that are more fair, stable and efficient as we get to really understand human physics at this fine-grain scale. This new computational social science offers incredible possibilities.”

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