Thursday, September 11, 2014

Beyond the Commodity

Back in 2005 I lamented the fact that students viewed computers as a commodity, a tool they use, like an automobile, but have no reason to understand how or why it works. In 2011 I noticed a change, that computers like IBM's Watson were starting to make computer science cool again.

Now we are in the midst of yet another major change, reflected in refound interest in high school computer science, and the huge enrollment growth in universities, particularly in non-majors taking upper-level CS courses. Jobs certainly drive much of this enrollment but for an important reason. Basic computer science principles and reasoning have become a critical tool in almost any business. Every large company tries to glean knowledge from data, deal with security and privacy challenges, and solves big optimization questions in an ever complex environment. I've been told that car companies will take as many Mechanical Engineering major with CS minors as Georgia Tech can produce. For what are cars today but computers on wheels.

We've been down this path before, and trends that seem to be with us forever die out leading to computer science disillusionment. Somehow this seems different, but we'll just have to wait and see.


  1. by 2007 you mean 2011.

  2. I think computers are always both commodity and means of production.

  3. So I think there are a couple of things happening here in industry (worked for facebook for a couple years and now at another big-ish tech company).

    1. For software engineering roles, in general companies still like recent grads to have CS degrees. If you showed up with an econ or ME degree and some CS coursework, I don't think you'd make it far in most software engineering interviews.

    2. For non-engineering roles, specifically "analyst" roles in marketing, sales, finance, etc there is a huge demand for some computational skills. Specifically, the ability to reason about data, manipulate data, and think algorithmically. A typical problem these days for a marketing analyst might be, "We did ad campaign X can you parse through the terabytes of logs to figure out the impact?" -- you probably can't answer this problem in MS Excel.

    3. Thanks to open-source and things like github, there is a democratization of technology tools and it's much much easier for less technical people to write some code. Lots of companies are trying to shift some of their "tech debt" work to analysts-but-not-engineers in other departments while still providing some oversight.