Where is my mind bicycle?

The devil is in the details #

To quote IBM - every day we create 2.5 x 10e18 bytes of data1. What this number does, is it creates an image of incomprehensible amounts of stuff we create with the help of our digital tools. This number is even more awe inspiring when compared to all the data produced up to a certain time in our past2. Add to that the fact that we’re increasing our rate of “data creation”, and you have a strong case for growing productivity. Except for one thing…

We are not creating that data, just revealing and storing it as bits. This might seem just wordplay, but to me it exposes part of the reason why we haven’t seen comparable growth in tangible production. We are not really producing much at all, just transferring what we already have to bits, while using services such as facebook, youtube or most any other top sites/apps. As goes the saying - “If a tree falls in the forest and no one is around to heart it, does it make a sound?”, so too, it seams, our data, if it’s not digital, is it even there?

A 2010 Economist article on data3 gave the example of Wal-Mart collecting 2.5 x 10e15 bytes of data on the 1 million customers it serves each hour. If that data is not converted into bits, is it still there? Arguably yes, it’s just hard to draw a graph from it. Why is the distinction between created and transferred important?

As a society we’ve always had a stable source of making a living, I.e. agriculture. Until it all started changing in the 19th century and since then we’ve seen shift after shift, from agriculture to manufacturing, from manufacturing to services and now it seems we’re shifting again. But unlike our past shifts (a college degree isn’t mandatory to move from agriculture to manufacturing and, even more so, to services), there is only so much a digitally-non-productive person can do in the future and unless we want to see more inequality (stemming from the 100/10/1 rule authored by Fred Wilson4), we have to vastly improve/reinvent our digital tools.

What do I mean by real productivity? #

“What a computer is to me is it’s the most remarkable tool that we have ever come up with. It’s the equivalent of a bicycle for our minds.”

Steve Jobs5

This is the perfect example of a great tool; the bicycle, without a steep learning curve, introduces a 3 to 1 lever to a person’s locomotion6. And even though the leverage ratio is incredible in the physical world, what’s even more astounding is that you don’t need an education to wield such leverage. Any tool with similar attributes is no less than revolutionary. So in comparing these two, Jobs did set quite a high bar for the computer.

By many counts, it seemingly reached and exceeded that bar, and yet tangible metrics paint a different picture. The biggest of them - last time US GDP grew in excess of 10% was in 19787, right at the dawn of digital technology. There is even a group of economists that have questioned whether computers lived up to the great innovations of the past8. Yet that would be completely unfair to the computer, because it isn’t really a tool, it’s a platform for building and using tools. So it’s totally our collective fault that we haven’t invented comparable tools to the bicycle on this platform.

A good way to judge a tool’s utility would be to measure its leverage on our abilities that we are trying to enhance, and in this case that would be our abilities to learn, imagine, create, adapt, feel, improvise, have intuition. Why single out these? Well, everything else is being, or eventually will be, replaced by machines. Now, could you name any computer tools that give you at least 3 to 1 leverage to your creative/learning/imagining capacity? I find this to be a difficult exercise and yet this is what we need - exponential gains in these, so far, unreplicable human skills.

Why is this relevant? #

Imagine what happens when a relatively low margin industry is disrupted by a technological tsunami of change and efficiency. One good example of that, would be Google’s effect on the newspaper & magazine industry. And that is a loss of ~$30b in industry revenues per year from 2004 to 2011, while Google saw a gain of ~$35b9. But far more important is the 28-40%10 decrease in headcount of the newspaper industry, which works out more than a hundred thousand people unemployed and Google didn’t absorb them all (since it only had ~25,000 employees then). In fact it probably didn’t absorb any of them, because the list of laid-off newspaper CS people was probably very short.

It should be fairly easy to see that such job destruction could provoke people into opposing technological change. In fact we have a term for that - the Luddite fallacy, and the reason it’s a fallacy is because it’s never been representative of how things work in the real world. Until we started seeing persistently high unemployment. This is because some of these jobs are lost not just until the economy recovers (by many metrics it has recovered already17), but forever. The Google example above perfectly illustrates this.

And the improvements that Google introduced were basically just low hanging fruit. In a 2011 Economist article on the Luddite legacy, Martin Ford is quoted to have identified 50m jobs in America which could be performed by a piece of software11 and a large part of them being knowledge workers. As Marc Andreessen put it - software is eating the world12.

Naturally this looming danger is creating tension between the Have’s and the Have-not’s which is difficult not to notice. And one way out of this quandary is education, many would argue it’s the only way, since most good paying jobs of the future require digital literacy. So it is no wonder enrolment in the engineering and computer science programs is at a four year high13, even though it’s still ~20% of its peak this decade (14,185 students awarded bachelors degrees in 2003-0414). But if you think this is a viable way to bring on real change, compare that with the number of U-6 unemployed of 23,970,0001516 and you can begin to see the scale of the improvement we truly need.

Obviously this is a great opportunity, and these past two years there has been a wave of new education related companies formed, so the market is well aware of this. But I still get the feeling that we are not tackling the steep learning curve of digital literacy, and it seems that there is a much greater opportunity there. To overcome this, we need digital tools that can truly become the bicycles for our minds.

References #

  1. http://www-01.ibm.com/software/data/bigdata/
  2. http://techcrunch.com/2010/08/04/schmidt-data/
  3. http://www.economist.com/node/15557443
  4. http://www.avc.com/a_vc/2011/06/dont-forget-your-logged-out-users.html
  5. https://www.youtube.com/watch?v=ob_GX50Za6c
  6. http://en.m.wikipedia.org/wiki/Bicycle_performance#section_1
  7. http://www.tradingeconomics.com/united-states/gdp-growth
  8. http://en.wikipedia.org/wiki/Productivity_paradox
  9. http://www.theatlantic.com/business/archive/2012/12/the-scariest-thing-about-the-newspaper-business-isnt-prints-decline-its-digitals-growth/266482/
  10. http://www.ibtimes.com/newspaper-industry-shrinks-40-percent-decade-report-793706
  11. http://www.economist.com/blogs/babbage/2011/11/artificial-intelligence
  12. http://online.wsj.com/article/SB10001424053111903480904576512250915629460.html
  13. http://cra.org/govaffairs/blog/2012/04/undergrad-computer-science-enrollments-rise-for-fourth-straight-year-cra-taulbee-report/
  14. http://www.cio.com/article/192911/Smallest_Number_of_Students_in_a_Decade_Graduate_with_Computer_Science_Degrees_in_2007
  15. http://www.bls.gov/news.release/empsit.t15.htm
  16. http://research.stlouisfed.org/fred2/series/CLF16OV
  17. http://research.stlouisfed.org/fred2/series/GDP/

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