Back To The Computer Stone Age

Back To The Computer Stone Age

According to Charles Kenny in Bloomberg BusinessWeek (20 June 2013), the Internet is quite a big disappointment–because it “failed to generate much in the way of economic growth.”

While on one hand, the author seems to see the impact that the Internet has had–“it sparks uprisings, makes shopping easier, help people find their soul mates, and enables government to collect troves of useful data on potential terrorists;” on the other hand, he pooh-poohs all this and says it hasn’t generated prosperity.

And in a sense, don’t the facts seem to support Kenny: GDP is still in the 2-3% range, labor productivity growth is even lower, and unemployment is still elevated at over 7%?

The problem is that the author is making false correlations between our economic conditions and the rise of the Internet, which already Jack Welch pronounced in 2000 as “the single most important event in the U.S. economy since the industrial revolution.”

Kenny seems to think that not only aren’t there that many economic benefits to the Internet, but whatever there is we basically squander by becoming Facebook and Youtube junkies.

It’s a shame that Bloomberg BusinessWeek decided to publish such a ridiculous article as its “Opening Remarks,” blaming the failure of the Internet for economic challenges that have been brewing for decades–with high-levels of debt, low levels of savings, hefty entitlement programs based on empty national trust funds, the global outsourcing of our manufacturing base, elevated political polarization in Washington, and various economic jolts based on runaway technology, real estate, and commodity bubbles.

It’s concerning that the author, someone with a masters in International Economics, wouldn’t address, let alone mention, any of these other critical factors affecting our national economy–just the Internet!

Kenny adds insult to injury in his diatribe, when he says that the Internet’s “biggest impact” is the delivery of “a form of entertainment more addictive than watching reruns of Friends.”

Maybe that’s the biggest impact for him, but I think most of us could no longer live seriously without the Internet–whether in how we keep in touch, share, collaborate, inform, innovate, compute, buy and sell, and even entertain (yes, were entitled to some downtime as well).

Maybe some would like to forget all the benefits of technology and send us back to the Stone Age before computing, but I have a feeling that not only would our economy be a lot worse than it is now, but so would we. 🙂

(Source Photo: Andy Blumenthal)

Big Data, Correlation Or Causation?

Big Data, Correlation Or Causation?

Gordon Crovitz wrote about Big Data in the Wall Street Journal (25 March 2013) this week.

He cites from a book called “Big Data: A Revolution That Will Transform How We Live, Work, and Think,” an interesting notion that in processing the massive amounts of data we are capturing today, society will “shed some of its obsession for causality in exchange for simple correlation.”

The idea is that in the effort to speed decision processing and making, we will to some extent, or to a great extent, not have the time and resources for the scientific method to actually determine why something is happening, but instead will settle for knowing what is happening–through the massive data pouring in.

While seeing the trends in the data is a big step ahead of just being overwhelmed and possibly drowning in data and not knowing what to make of it, it is still important that we validate what we think we are seeing but scientifically testing it and determining if there is a real reason for what is going on.

Correlating loads of data can make for interesting conclusions like when Google Flu predicts outbreaks (before the CDC) by reaming through millions of searches for things like cough medicine, but correlations can be spurious when for example, a new cough medicine comes out and people are just looking up information about it–hence, no real outbreak of the flu. (Maybe not the best example, but you get the point).

Also, just knowing that something is happening like an epidemic, global warming, flight delays or whatever, is helpful in situational awareness, but without knowing why it’s happening (i.e. the root cause) how can we really address the issues to fix it?

It is good to know if data is pointing us to a new reality, then at least we can take some action(s) to prevent ourselves from getting sick or having to wait endlessly in the airport, but if we want to cure the disease or fix the airlines then we have to go deeper, find out the cause, and attack it–to make it right.

Correlation is good for a quick reaction, but correlation is necessary for long-term prevention and improvement.

Computing resources can be used not just to sift through petabytes of data points (e.g. to come up with neighborhood crime statistics), but to actually help test various causal factors (e.g. socio-economic conditions, community investment, law enforcement efforts, etc.) by processing the results of true scientific testing with proper controls, analysis, and drawn conclusions.