All hail the prediction machines

Get ready for a time when computers know our world - and our future - better than we do.

One of my favorite Isaac Asimov stories, Franchise, imagines an election where computers are advanced enough to predict the preferences of an entire country based on just one voter's actions.

We're not quite there yet, but we might be heading in that direction. One of the biggest successes of the 2012 presidential elections was the work of statistician Nate Silver. His FiveThirtyEight blog, which used algorithms to assess hundreds of polls based on their historical accuracy, successfully predicted the results in 50 out of 50 states.

His analysis, like every political story, divides opinion. However, I believe his work highlights a bigger story about our future relationship with technology. It shows a vision of progress where there's a clear distinction between tasks that humans can handle and those better suited for machines and mathematics.

This shift is already happening. From automated Mars explorations and the use of unmanned drones for reconnaissance and remote missions to the analysis of probabilities and predictions, we focus on what we do best and leave the rest to machines. Some things have always been this way, but the story of human enhancement is now more closely linked to the story of human redundancy.

In Silver's case, those who might face immediate redundancy are the professional political pundits whose speculations fill the media during elections. They might be replaced by figures like Silver who offer diverse ideological perspectives. In the long term, replacing speculation with data-driven science could become the norm, transforming how we plan and predict political campaigns.

The Obama team's extensive behind-the-scenes data analysis is well known: "We ran the election 66,000 times every night," a senior official told Time magazine, describing their simulation of swing state votes. What's less clear, but far more important, is how much this contributed to their victory.

Crunching 'souls'

It's not just in politics that "big data" is having a disruptive effect. These mathematical models, supported by vast amounts of data, are increasingly used for everything from predicting hurricanes and diagnosing diseases to spotting economic trends and modeling human behavior.

All of this is starting to fulfill a long-held vision of what happens when large amounts of data and computing power intersect with humanity. Companies like Google have long believed that there's more to computational truth than wishful thinking, with ongoing research showing that computers can drive cars more competently than we can, and can work out what people are thinking without them going to the bother of typing, and deliver ever-more-targeted products and services.