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Jon Evans
Works at HappyFunCorp
Attended University of Waterloo
Lives in Berkeley
830 followers|148,479 views
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Jon Evans

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Travel post: north and south in West Africa.
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Jon Evans

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I am reasonably pleased with this photo I took today (in Saint-Louis, Senegal) but, as ever, annoyed that G+ only allows you one "link" to photos hosted on another site, whereas you can attach multiple photos hosted here (and they're shown much larger in the stream.)
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Jon Evans

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I haven't had time to write a review of The Second Machine Age, the new book by +Andrew McAfee and +Erik Brynjolfsson, but I just want to comment real quick on something that's stuck in my mind ever since I read the book, but it seems to have been completely skipped over in all other discussion I've seen anywhere about the book, perhaps because it's too "mathy" for most people to discuss. But seems hugely significant.

And that is, that labor income distribution in the industrial age (or First Machine Age as they call it) follows a normal (or Gaussian) distribution -- a bell curve, while in the information age (or Second Machine Age, as they call it), it follows a power law curve.

Actually in the industrial age it follows a log-normal distribution -- I know there are smart people here and someone would correct me if I didn't get that detail correct, but it doesn't matter for the basic point. A log-normal distribution is a bell curve that leans to one side (because there's a logarithm function figuring into its shape).

Anyway, let's use an example. Let's say the average wage in some industry is $10/hour. Nice round number, maybe enough to live on but not in Silicon Valley. With a normal distribution, this would mean most people earn $10, with fewer and fewer people earning more or less the farther you go from $10. With a power-law distribution, however, the majority of people would earn $0.01/hour, with a handful of people earning hundreds of millions or even billions -- such high numbers that the average still comes out to $10. So in both scenarios, the average income is $10, but the distribution is completely different.

What McAfee and Brynjolfsson are saying is that the industrial revolution naturally produces the normal distribution (ok, technically log-normal), and the information revolution (or Second Machine Age) naturally produces the power-law distribution. They say even for jobs where you wouldn't expect it -- service jobs where you'd expect everyone to be paid about the same -- you'll still see it because the effect propagates through the economy, through the networks of monetary exchange.

Illustrative pictures:

Normal distribution:
http://www.mathsisfun.com/data/images/normal-distribution-2.gif

Log-normal distribution:
http://3.bp.blogspot.com/_sFr6_ysAa7M/TKk2b_XvvhI/AAAAAAAAqFI/IwxbjX8q3K0/s400/4291_fig5.jpg

Power-law distribution:
http://en.wikipedia.org/wiki/File:Long_tail.svg
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Jon Evans

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Of course, there's also Peter Watts's theory: sentience - or, at least, consciousness - isn't a requisite for intelligence, it's just a bug 
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I remember hearing a lecture by this weird biologist in Berkley, T. McKenna who theorized self-consciousness is just a side-effect - like a mental appendix!
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“Utopian society.” Morgan Stanley!
HAHAHA!
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Pretend, for a moment, that you were programming a website that auto-generated sensationalistic headlines. What kinds of words would you plug into it? “Teen?” “Satanic?” “Serial killer?” The name of some kind of tech company? (Trust me on this one; headlines that include the word “Google,” “Apple,” or “Facebook” get tons of hits). On Sunday, nobody needed a fake headline generator to come up with a story that included all these phrases. After all, Miranda Barbour basically handed the story to them.
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Dear G+: I am torn between visiting Bolivia/Chile or Senegal/Gambia for my next international sojourn. Thoughts?
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People
In his circles
273 people
Have him in circles
830 people
James Clayton's profile photo
Work
Occupation
Novelist, journalist, software engineer
Skills
Telling lies for money, telling truths for money, writing software, finding cheap flights.
Employment
  • HappyFunCorp
    software engineer, 2010 - present
  • TechCrunch
    columnist, 2010 - present
  • Xtreme Labs
    software engineer, 2010 - 2011
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
Berkeley
Previously
Toronto, Canada - Waterloo, Canada - Ottawa - Montreal - New York City - San Francisco - London - Paris - Los Angeles
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Story
Tagline
Novelist, journalist, TechCrunch columnist, software engineer.
Introduction
Mostly I write stuff.
Bragging rights
See rezendi.com.
Education
  • University of Waterloo
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Gender
Male