i R nerd.

I’ve decided that I’m going to get really good at using R. What is R, you might ask? R is a programming language for originally created for statistical analysis, and my interest in it means I’ve apparently come to terms with the fact that I’m the type of person that jocks gave wedgies and swirlies to in high school.

Why am I interested in R? Well, R is a programming language that will enable machine learning. I’m not talking about the robots-flipping-pancakes type of machine learning which — while cool — is not what comes to mind when thinking about statistics. Rather, the type of machine learning I’m talking about is where a user programs a computer to learn without being explicitly programmed to do so. Basically, machine learning is artificial intelligence that enables a computer to refine its own conclusions.

This may sound like the stuff of science fiction, but it’s not that far-fetched. Companies like Gartner predict that machine learning will hit mainstream adoption within 2–5 years. Now, they also say that it’s at the top of the hype cycle, so it will likely disappoint a whole lot of people before it starts to prove its value more broadly.

I’ve decided on learning R instead of some of the other programming languages out there (MatLab, SAS, etc.) for two primary reasons. First, it’s open-source, and I like that. Second, I already have a base level of understanding from a class I took in my MBA program at Portland State University. It was one of the classes that most MBA students dread the most, but I found it oddly enjoyable.

It’s exciting to think that computers could actually get good enough at analyzing data to start making pretty important recommendations and conclusions with limited human involvement. At the same time, it’s terrifying to think that this means the eventual automation of certain strategic analysis jobs out there. Actuarial science, business intelligence, strategic finance and other high-paying, high-skilled occupations could see a disruption from this type of programming.

I’ve worked in strategic finance for almost 10 years, and my job is basically to make data-driven recommendations that improve the profitability of the companies I’ve worked for. In the future, machine learning could allow me to set up a program to continuously analyze data and monitor the direction we’re heading. Today, my team will run an analysis and sporadically revisit it; when we refresh an old analysis, we’re using valuable time that could allow us to build something new. Machine learning could solve that problem.

So, I guess it’s a combination of fear and excitement that makes me want to leverage my financial knowledge as I build programs in R. If I do this thing, I’ll may automate my job away while I build something of permanent value. If I don’t, someone else will. Either way, the future is on its way and that means that change is inevitable.