My Take
PUBLISHED : Saturday, 10 November, 2012, 12:00am
UPDATED : Saturday, 10 November, 2012, 12:55am

The algorithm of life is a powerful thing

BIO

Alex Lo is a senior writer at the South China Morning Post. He writes editorials and the daily “My Take” column on page 2. He also edits the weekly science and technology page in Sunday Morning Post.
 

My wife thinks George Clooney has universal appeal. But according to the data-mining quants who helped propel Barack Obama back into the White House, the liberal film star and Obama supporter is most attractive to women aged between 40 and 49 on the west coast of the United States.

This is the level of specificity that US pollsters and campaign managers now muster to give their candidates a decisive edge. The presidential election may have been the most mathematical and data-driven in history. Welcome to 21st-century electioneering.

How to raise money and promote voter turnout in swing states, where and when to place TV ads, which supporting celebrities to deploy and what events they should appear in - all these and countless other campaign decisions were subjected not just to hunches and guesswork, but computer models and simulations.

Political campaigning is becoming rocket science. This was foreshadowed by high-frequency trading in the stock market, which involves the mining of large amounts of financial and geopolitical data.

Love it or hate it, America often shows the world what the future has in store. In time, the same data-driven electioneering will spread around the world, its algorithmic techniques borrowed not only by other democracies but authoritarian regimes as well. For what government wouldn't want that magical power to model the behaviour of its citizens and predict their responses?

And it's not just governments. Our likes and dislikes, habits and aversions, they are all data to be dissected and analysed to help companies determine who we are and what we want - to better sell us their products and services.

Marketing, public relations, governing, investing and the social sciences will all converge in big data. Of course, the old warnings apply: garbage in, garbage out. You still need skills to identify the right signals from the noise. Even then, the data only tells us how, not why.

But the best data guys today are much more sophisticated than their predecessors who first dreamed of "a grand unified theory of the social sciences".

We must not underestimate their ability to resolve these basic, almost philosophical issues - and in doing so, transform our lives, for better or worse.

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