The Algorithm That Controls Your Life

If you think you're your own person, think again. While you have the ability to make what you think seem like independent decisions, the truth is that most of the things you do—from the trains you catch to the food you eat—have been optimized by the world's most pervasive algorithm.

New Scientist takes a look at the simplex algorithm, now over 60 years old, which is used by everyone from fruit suppliers to banks to make decisions about non-linear problems with so many variables and outcomes that they would make a human brain explode:

A fund manager might... want to arrange a portfolio optimally to balance risk and expected return over a range of stocks; a railway timetabler to decide how best to roster staff and trains; or a factory or hospital manager to work out how to juggle finite machine resources or ward space...

This is the job of the algorithm.

Its full name is the simplex algorithm, and it emerged in the late 1940s from the work of the US mathematician George Dantzig, who had spent the second world war investigating ways to increase the logistical efficiency of the US air force... One of the first insights he arrived at was that the optimum value of the "target function" - the thing we want to maximize or minimize, be that profit, traveling time or whatever - is guaranteed to lie at one of the corners of the polytope. This instantly makes things much more tractable: there are infinitely many points within any polytope, but only ever a finite number of corners.

The feature takes a whistle-stop tour through the history and math behind the algorithm, which has gone on to run the world. As one academic quoted in the article explains, "probably tens or hundreds of thousands of calls of the simplex method are made every minute." Every minute.

It's fascinating reading, and really makes you wonder about just how much control you really have over your life compared to a single algorithm, sat crunching data on a dusty servers in dinghy basements all over the world. Sigh. [New Scientist]

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