Sat, Jul 06, 2013 - Page 9 News List

How algorithms rule the world

The NSA revelations highlight the role sophisticated algorithms play in sifting through masses of data, but more surprising is their widespread use in our everyday lives — should we be more wary of their power?

By Leo Hickman  /  The Guardian, LONDON

“Algorithms are not yet writing pop music,” Steiner said.

He pauses, then laughs.

“Not that we know of, anyway. If I were a record company executive or pop artist, I wouldn’t tell anyone if I’d had a No. 1 written by an algorithm,” he said.

Steiner says we should not automatically see algorithms as a malign influence on our lives, but we should debate their ubiquity and their wide range of uses.

“We’re already halfway towards a world where algorithms run nearly everything. As their power intensifies, wealth will concentrate towards them. They will ensure the 1 percent to 99 percent divide gets larger. If you’re not part of the class attached to algorithms, then you will struggle. The reason why there is no popular outrage about Wall Street being run by algorithms is because most people don’t yet know or understand it,” Steiner said.

However, Steiner says we should welcome their use when they are used appropriately to aid and speed our lives.

“Retail algorithms don’t scare me,” he said. “I find it useful when Amazon tells me what I might like. In the US, we know we will not have enough GP [general practitioner] doctors in 15 years, as not enough are being trained, but algorithms can replace many of their tasks. Pharmacists are already seeing some of their prescribing tasks replaced by algorithms. Algorithms might actually start to create new, mundane jobs for humans. For example, algorithms will still need a human to collect blood and urine samples for them to analyze.”

There can be a fine line, though, between “good” and “bad” algorithms.

“I don’t find the NSA revelations particularly scary. At the moment, they just hold the data,” Steiner said. “Even the best data scientists would struggle to know what to do with all that data, but it’s the next step that we need to keep an eye on. They could really screw up someone’s life with a false prediction about what they might be up to.”

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