(This post was written & published on April 1st, but no, it’s not some April Fools thing, it’s 100% sincere. I’m not gonna wait to publish it tomorrow or something just because today happens to be Annual Prank Day.)
I’ve been reflecting a lot recently on the relatively soft landing I had in leaving academia. Don’t get me wrong, it wasn’t what I’d call “a breeze” – I faced various obstacles, mostly relating to the timing of it all – but here I am, less than a year later, gainfully employed and happy.
And the truth is that there’s a HUGE component of luck involved.
One thing I learned in academia – though it’s a lesson I could have learned in countless other places – is that the people who end up well-placed (whatever that means in your neck of the woods; for me, at the time, it meant something like being tenured at a decent university) tend to downplay the role that luck has played in getting them where they are. This is a fairly common kind of cognitive bias, and we’re all afflicted by it, so I’m not attaching any kind of moral judgment to it. But I do think that because of this cognitive bias, it can1 help if people who have “made it” (again, whatever that means to you) are as upfront as they can manage to be about the role luck has played in their accomplishments.
So with that in mind…
The bit of luck that I’m referring to here is, specifically, the fact that I’m a programmer. I don’t just mean the common refrain that I “can code”. Many linguists these days can code, be it from the kind of R and/or Python stuff they need to know in order to do certain kinds of data analysis, the kind of Python and/or Perl stuff they need to know in order to build web-based experiment frontends, and so on and so forth. And I don’t say this to downplay that knowledge: the fact that people whose primary interests lie not in software development itself but elsewhere still need to learn some programming skills to accomplish what they want to do in their actual field is noteworthy and, whether you think it’s a good thing or a sign that the basic tools they’re interfacing with are poorly designed, it’s a fact of life for many scientists these days. That they rise to the challenge of learning some programming on the side while being full-time scholars is a testament to these people’s skill and versatility.
So when I draw a minor distinction between “can code” and being a programmer, I mean it only in the very narrow sense that I know enough, and have been programming for long enough, to get hired as a software engineer per se, as opposed to as someone whose focus is elsewhere (e.g. ontologist, data scientist, language engineer) but whose role also involves a healthy amount of coding.
Unlike the people I just mentioned, who picked up their programming skills while on the job doing something else(!), I picked up my programming skills in a completely different context. Simply put, I was a very socially awkward kid, with two working parents (and later on, only one parent), living in a city where you needed a ride to get from place to place. This meant lots of time spent at home. I could have done many different things with this time – I could have read books, made model airplanes, taught myself to juggle, taken up kite building. But what I actually did was turn on our old IBM PC, and teach myself to program. And over the next decade or so until I finished high school – notwithstanding a few periods in between when I didn’t have access to a computer – programming became my main hobby.
I didn’t choose this hobby for its “career potential”. For one thing, an eight year old doesn’t think in these terms. Also, I’m not sure it was even clear in the first half of the 1980s that the tech industry would be such a financial wellspring for so many people in the decades to come. (And if it was already clear by then, well, again, eight-year-old me certainly didn’t get the memo.) So when I say it was pure luck that I chose programming as a hobby, I really mean it.
And lucky it was: ten years later, as high school ended, I had a ready-made, fairly lucrative vocation in hand. (Mind you: at the time, most high schools – including mine – did not offer anything in the way of an education in computers. What we would now call STEM amounted back then to math, physics, chemistry, and biology. Full stop.) So began the first of my careers, which would carry me to the end of my 20s, at which point I “veered off” into linguistics and academia.
But it doesn’t stop there. Since old habits die hard, the hobby never really went away. Even during my many years in academic linguistics, I never really stopped dabbling in software on the side. This, despite the fact that my linguistic research was about as far away from software as you could realistically get: I was doing qualitative research and developing theories that were deliberately mentalist (in the Chomsky & Miller sense) and not implementationalist, and actively & consciously resisting the urge to “go computational” (or statistical) in my research. In fact, there’s probably a sense in which these research choices preserved my hobbyist passion for software, since during these years, programming was so completely separate from “work.”
This all meant that, when I finally made the decision to leave academia, I had a ready-made skillset to take to industry with me. To be honest, this is somewhat of an oversimplification, in that I had the knowledge but not the credentials (recent employment in software and/or professional certifications), so it did prove to be somewhat of an uphill battle to convince people to look past my somewhat paltry on-paper qualifications as a software engineer. But it was a challenge of persuasion, not a challenge of substance. And for that, I have the random, lucky choices of an eight year old to thank.
I say can help as opposed to is guaranteed to help because, like many things, one can go overboard here: if you send the message that absolutely everything is about luck, it can be demoralizing, and make people feel like they have absolutely no control over their lives, whereas the truth is usually somewhere in between these two extremes. (The extremes being a perfect meritocracy, on the one hand, and a system where luck is the only operative factor, on the other.) ↩