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Jaron Lanier: So it's a little bit like The Wizard of Oz. . . . We see the internet and we see some cloud service or some simulated personality or some algorithm that seems to be able to recommend music or dating partners or whatever, but it all is data that just comes from real people.  And the problem with pretending that there is some entity in the cloud other than the real people is . . . well, one problem is economic.  If we pretend the people aren't there, then the people don't get paid and all the power and clout cloud gradually accumulates in our tech company servers and maybe in some other kinds of servers like the ones that run hedge funds and all that.  And so far that's okay because the only people losing out are, like, musicians and artists and photographers and writers and who cares about them?  But eventually there are going to be self driving cars and there are going to be automated manufacturing processes and there are going to be all sorts of things like that, and at that point there just won't be much employment compared to what we're used to.

And so if we don't learn to acknowledge that real people are actually creating the value online, we're never going to learn how to create the information economy that can really create employment and self determination for people when the machines get really good.  So we're really screwing ourselves over by pretending that it's not us.  And this appeal of this fantasy of the artificial intelligence, this fantastic being that's doing all this work, is understandable because what a great thing.  It's almost like a Frankenstein thing.  We've created this life form, but it's phony.  It ultimately is all people.

So let's say you're using one of the services online that can translate between English and Spanish or some other language and it seems magical.  Here is this machine translating!  But what it really is, is a ton of examples taken from real people who did translations in the past all combined together and applied to the new situations that need to be translated.  So if we remember that it all came from real people all of the sudden in the future somebody might be able to make a living from being such a good translator that they generate a lot of examples for the so-called automated translation system of the future.

That's what the new economy has to turn into some day if it's not going to be something really creepy.  You know so we have to learn to acknowledge our own role.  We have to accept that the people are more important than the machines, not as a matter of hope, but as a matter of fact.

I do feel that in a world created by hackers those who can't hack are the underclass and even, I mean, no matter what you do today success amounts to a form of twiddly hacking whether you're running a hedge fund or if you're just clipping coupons to get by at the bottom of the economic spectrum.  Those who can deal with the sort of tweedly information management are the ones who make it.  The problem with suggesting that everybody learn to program is that the particular tools for learning to program change so much, and none of them are really that great, that if you treat it as just a craft you learn, like, if you just learn RUBY or Python or some particular thing, it doesn't necessarily mean anything in ten years.  What you really have to do is get to the deeper concepts behind it all.

So what I really wish is that there was general literacy in computer science, which is different than learning to program.  That, I think, would empower a lot of people because then you're sort of learning all the programming languages at once and you can learn to think like the people who made them up.  It's not that hard.  I don't think it's really all that technical, and I think most people could learn it.  That probably is as important as reading, writing and arithmetic, but unfortunately the way people approach it is in this very almost rote fashion of like learn to be able to program in this or that, and I don't know how much it really helps people in the long term.

Directed / Produced by
Jonathan Fowler & Elizabeth Rodd

 

More from the Big Idea for Monday, December 17 2012

Today's Big Idea: Man Versus Machine

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