Solving the world's problems with geek power

Why, as a country, did we spend so much time, money, and life trying to rescue seven trapped miners in Utah, while that same money could have saved dozens or hundreds of lives around the world? Clive Thompson attempts to answer that question in this month's Wired:

I've been reading the fascinating work of Paul Slovic, a psychologist who runs the social-science think tank Decision Research. He studies a troubling paradox in human empathy: We'll usually race to help a single stranger in dire straits, while ignoring huge numbers of people in precisely the same plight. We'll donate thousands of dollars to bring a single African war orphan to the US for lifesaving surgery, but we don't offer much money or political pressure to stop widespread genocides in Rwanda or Darfur.

You could argue that we're simply callous, or hypocrites. But Slovic doesn't think so. The problem isn't a moral failing: It's a cognitive one. We're very good at processing the plight of tiny groups of people but horrible at conceptualizing the suffering of large ones.

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He suggests that Bill Gates attempts to tackle epidemic level problems in Africa because of his geek sensibilities. Thompson suggest that those involved in the details of IT are simply wired differently to process the sheer volume of human despair by looking at the numbers in a way that makes most people go numb.

Which brings me back to Gates. The guy is practically a social cripple, and at times he has seemed to lack human empathy. But he's also a geek, and geeks are incredibly good at thinking concretely about giant numbers. Their imagination can scale up and down the powers of 10 — mega, giga, tera, peta — because their jobs demand it.

So maybe that's why he is able to truly understand mass disease in Africa. We look at the huge numbers and go numb. Gates looks at them and runs the moral algorithm: Preventable death = bad; preventable death x 1 million people = 1 million times as bad.

It's a brief, but intriguing look at just what it may take to solve the big problems of the world.