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When pop science sounds like mentalist carnival barkers

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What else to make of this, from New Scientist?:

A lot of problems in today’s world are too big for our brains. An algorithm that identifies how cause and effect are linked could lead us to better solutions

Finding solutions means doing what Newton did with gravity: asking the right questions, teasing out causes and effects, and so building an intellectual framework to explain the puzzle. But how do we do that with the sheer quantity of data sloshing around in today’s world? It’s this problem that has led some to think we need to think seriously about the way we think. Only by rebooting our powers of logic and going beyond what nature has hardwired into our brain can we hope to grapple with problems that are far bigger than any of us. It’s time to install Thinking 2.0.

For most of us, Thinking 1.0 is taxing enough. We humans love to sideline logic in favour of the easy answer. We might make life decisions based on … More.

To get our handy dandy Thinking 2.0 kit we must, of course, forward $$ to New Scientist. Hey, our thinking skills are probably okay if we decide not to forward money.

Thought experiment: What if we talked that way (“We represent Thinking 2.0”)? What would be a logical assumption about us?

If the same thing isn’t a logical assumption about New Scientist, the most likely reason is the cultural hold naturalism has on the sciences. People don’t even see this rubbish as abnormal if it defends naturalism.

People don’t even see this rubbish for what it is, if it defends naturalism.

See also: What has naturalism done for the sciences?

Neuroscience tried wholly embracing naturalism, but then the brain got away

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One Reply to “When pop science sounds like mentalist carnival barkers

  1. 1

    You know this is bass-ackwards of course. The only thing computers are good at is serial logic. Even when we program up “neural nets” we really don’t know what they are doing, only that they must be “trained” by looking at gobs of data. Humans, as Malcolm Gladwell reminds us in “Blink”, can render a snap judgment on 1/1000th the data and in 1/millionth the time and still come out ahead. It took, oh, 50 years of chess programs before a computer could beat a chess master. The number of options in chess grows like 15-30 per move, so looking 5 moves ahead is a (30)^5 problem. Most winning chess programs are “brute force” evaluation of all options. But humans don’t play chess that way.
    Japanese Go has more like 200 options per move, or (200)^5 for 5 moves ahead. Brute force just doesn’t work at all. Until recently, the best Go software was no better than a rank beginner.
    So the one thing that humans do so very much better than a computer is non-linear pattern recognition–eg thinking. Solving simultaneous linear equations is something computers are good at.

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