FORTUNE — In the morning you wake up and check your Gmail, which is sorted for you courtesy of a proprietary Google (GOOG) bot. At lunchtime you read sports gossip on Deadspin, which deploys another set of proprietary algorithms to promote the most prolific commenters. After dinner you pick a movie from a menu of choices that a friendly Netflix (NFLX) algorithm queued up for you based on its record of your cinematic taste. Other algorithms help determine which streets we drive, the music we hear, and which way stocks move.
In short, algorithms are taking over our lives. An algorithm is simply a piece of software code that operates like a decision tree, considering multiple variables and then spitting out a decision or recommendation. (A bot is typically a collection of algorithms.) Without taking a step back, as Christopher Steiner does in Automate This: How Algorithms Came to Rule Our World, it’s hard to appreciate how fast and far algorithms have come in recent years, and what the consequences are for modern culture.
Steiner, a former Forbes writer, set out three years ago to explain how trading algorithms (which, in their simplest form, make buy/sell decisions based on various data inputs) had overtaken Wall Street. By that time, wildly complex trading bots had transformed financial markets. Steiner then decided to expand his reporting outside finance. The result is an encompassing tale of how industries as diverse as dating services, music and medicine all came to be ruled by machines.
There’s Savage Beast, a 1990s startup that paid hundreds of musicians to listen to songs and classify them according to some 400 musical attributes, including rhythm, tonality, and much more. Savage Beast tried without luck to sell its music recommendation service to music retailers like Tower Records and Best Buy (BBY). The company barely survived the 2000 dotcom bust and was on life support by 2005, when it started to produce music recommendations using algorithms instead of live musicians. Along the way, Savage Beast changed its name to Pandora (P). In 2011 it went public with a $3 billion valuation.
ELoyalty is another company whose story shows the power of algorithms. The customer management consultant deals in the stodgy business of advising call centers. ELoyalty’s algorithms scan a database of about two million speech patterns to classify callers by personality. As a result, sales and service reps can instantly tell if a customer is more emotional or more thought-driven, and tailor their pitches accordingly. Vodaphone (VOD) signed on to eLoyalty’s program, and afterward its operators knew if they were talking to an emotional customer who needed chummy gossip to get interested in upgrades, as opposed to more analytic clients who only wanted to hear about the value proposition. After adopting eLoyalty, Vodaphone’s sales upgrades increased by 8,600%.
Despite his wealth of case material, Steiner turns out to be an uncertain guide to this newfangled world. Because the book lacks a narrow focus on how algos are upending, say, Wall Street or the medical field, it tries to cover too many industries. As a result, some of the material feels stale. A chapter on the automation of musical taste, for instance, includes stories told in newspapers in the 1990s and early 2000s. Similarly, NASA’s personality-detecting system, which helped the space program pick teams of astronauts, was developed in the 1970s and 1980s.
I really wanted to fall in love with this book, for the new world of bots is at once alarming and engrossing. Increasingly, our world is being shaped by how Wall Street, Facebook (FB), Google, and Amazon (AMZN) deploy their algorithms. But while Steiner has written an exhaustive account of the bots powering our lives, the book lacks the characters and narrative to be a page-turner. Instead it feels like a book report that ran long.
The timing of Automate This (available Aug. 30) is both lucky and unlucky. Half of America is still talking about the fiasco at Knight Capital, where trading algorithms went haywire and caused the firm to lose several hundred million dollars overnight. Yet the Knight Capital story raises questions the book doesn’t answer. Knight’s algo issues only affected a few stocks. But if the health care industry eventually deploys bots to prescribe our medicines, for example, can we expect similar glitches? There’s a downside to this story that’s rarely been explored, and Steiner lets it pass.
Once bots move in, they don’t move out. Algorithms have brought efficiency, craftiness, and speed to nearly everything that humans have tasked them with. But as with most breakthrough innovations, they have experienced growing pains. Now that algorithms rule the world, the next story will be how their shortcomings might destroy it.
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