Creative types tend to think of themselves as doing work that is beyond the reach of automation. Computers can't parse nuance, the thinking goes, or summon the imaginative powers that are required of writers, artists, technological innovators and policy-makers. As it turns out, however, this flattering assumption is mistaken. Computers can be creative after all.
The more we understand about creativity, the more we are able to distill it into the language of algorithms—the "brains" behind computer programs. An algorithm takes a series of inputs and then, moving through its own decision tree, issues an output or an answer. The gears can be as simple as binary questions of yes/no—or they can be a series of complicated differential equations that draw on outside databases.
The point, ultimately, is that algorithms are fast, repeatable and easy to use at massive scale. They are already determining some of the music that reaches our ears, movies that reach the big screen, decisions regarding national security and even the kind of people we often reach on the phone.
Music would seem an unlikely entry point for algorithms, but they have arrived. In 2004, the New Zealander Ben Novak was just another guitar-strummer songwriter hoping to crack into music with a record deal. On a whim, he paid $50 to upload one of his songs to a website that claimed to have an algorithm capable of finding hits. The algorithm gave Mr. Novak's song a rare and lofty score, putting it on par with classics such as "Take it Easy" by the Eagles and Steppenwolf's "Born to Be Wild."
The algorithm belonged to Mike McCready, who connected Mr. Novak with a label. The single, "Turn Your Car Around," eventually landed near the top of the European charts. Mr. McCready now runs Music Xray, a three-year-old start-up seeking to democratize the music business. Comparing the structure of a song to tunes of the past, the algorithm grades it for hit potential. Mr. McCready's algorithm rightly predicted the success of Norah Jones and of the band Maroon 5 before they were major artists.
Still, the creative class won't bend easily to such challenges. The people who guard the gates of big music labels guffawed at the prospect of a hit-picking algorithm, but Music Xray has now secured recording deals for more than 5,000 artists. The music industry can no longer ignore the algorithm.
Movies, too, can be sorted quantitatively. Analyzing only the script, an algorithm from Epagogix, a risk-management firm that caters to the entertainment industry, predicts box office grosses. Epagogix broke into the business when a major studio allowed the firm to analyze script data for nine yet-to-be released films. In six of the nine cases, its predictions were spot-on. Algorithms have since become an essential tool in Hollywood.
As for the art of the written word, algorithms can already grade essays as well as the best human graders. Beyond assessment, original pieces of writing are being composed by algorithms belonging to Narrative Science, whose programs put together sports news stories complete with witty lead sentences and colorful vocabulary. The Big Ten Network uses Narrative Science's algorithms to post stories less than a second after a game ends. In one article detailing an Illinois-Indiana football game last fall, the algorithm wrote: "Illinois' (6-0) offense dominated, ripping off huge chunks of yardage."
As algorithms turn more of the subjective domain of human creativity into objective tasks, some observers worry about cultural homogeneity. Are we doomed to a future of uniform harmonies and standardized sentences? Hopefully not, but the advent of creative machines certainly will make it harder for humans to stand out. It may be that only distinct and exceptional talents—Nirvana, the Coen Brothers, Jonathan Franzen—will be able to defend our claims to creative superiority.
Algorithms also have invaded areas of our lives that might seem too personal for mere automation. We are all familiar with the words "this call may be recorded for quality or training purposes." Though that message may sometimes mean just what it says, it often means that an algorithm has been invited in for a listen.
Using only the words you say in a three-minute conversation, more than five million eavesdropping algorithms, created by a company called Mattersight, determine your personality type, what you want and how you might be most easily and quickly satisfied by the customer-service agent. The electronic psychological analysis divides people into six sorts of personalities. Steve Jobs, for instance, was a "reactions-based" person, someone who responds strongly to things: "I hate that!"
The next time you call, the algorithms, recognizing your phone number, will route you to an agent with a personality similar to your own, which results in calls that are half as long and reach happy resolutions 92% of the time, compared with 47% otherwise, according to an assessment of 1,500 customer service calls at Vodafone, the European telecom company.
Psyche-assessing bots are also playing for far higher stakes. In matters of national security, deciding how to handle new threats can be an inscrutable puzzle. To make informed decisions on these issues, the U.S. will spend more than $50 billion in 2012 on its spy and intelligence agencies. Much of this work involves predicting the behavior of capricious regimes. As it turns out, algorithms are often superior to humans at evaluating such situations.
For more than a decade, the CIA has been paying Bruce Bueno de Mesquita, a political-science professor at New York University and a senior fellow at the Hoover Institution, to build predictive algorithms based on the elaborate scenarios of game theory. His results—across more than 1,700 political and military predictions—have been correct twice as often as those of the CIA's own analysts, according to a declassified CIA report.
Mr. Bueno de Mesquita doesn't like to brag, but when he talks about what separates the assessments of game-theory algorithms from those of humans, he points out that top professionals, including Ivy League-educated intelligence analysts, tend to be obsessed with personal back stories and gossip that will have no effect on the future. Algorithms, he stresses, couldn't care less.