I had a somewhat less than pleasant encounter with a teacher who taught one of those STEM (science, technology, engineering and mathematics) subjects at a local school in London. Upon learning that I worked in engineering, perhaps to sound agreeable, she interjected with an air of pride, not dissimilar to the kind of pride displayed by those people who are (worryingly) proud of paying taxes or not littering, “I always encourage my students to go into STEM related professions. At this, I snapped if a little bit. My immediate reaction was “Um. Why would you do that? These kids can and deserve to have a bright future. Why would you actively subject young fledgling hopeful things to a life of dispiritingly, perpetually oversupplied, anxiety-infested market?” Startled and stunned like a deer caught in the headlights, and unable to formulate a quick enough response to these verbal convulsions of insanity, she had no choice but to listen to my ensuing rant. Repeatedly.
In conjunction with a few other minor indiscretions, it turned out a few minutes later that she had had enough of this ‘nonsense’ (or overwhelming enlightenment, depending on point of view); she stood up and left the table.
We often hear about shortages in the science and engineering workforce both in the UK and the US (e.g. here, and here), but I I wonder if this is generally true at all and maybe the initiative is more about wage suppression; certainly I’ve not personally seen any evidence of skills shortage or hiring difficulties in my line of work. I won’t go into the details as there are articles available online that express this concern in a far more articulate manner (this and this), but from what I’ve read so far, at least this much is true – engineering graduates are more likely to be unemployed after graduation than average. Let that one sink in and if you’re thinking about having kids – first, don’t. If it’s too late for you and you’re already having one or have had one, make sure you keep them out of harm’s way – the STEM way.
I work in engineering. By now most of you know that. In fact a lot of people I came to know in the past few years are unfortunately from this field. I say ‘unfortunate’ for a good reason, not to be humorous but because people are made redundant on a regular basis in engineering. Where I work in particular, I’ve seen the number of workers go from circa 1000 to 250 in the space of less than 3 years. Indeed this is what preoccupied much of my mind this week; the impending ax to be sharpened and to be deployed, the direction of its swing, the amplitude of its oscillation, the dampening effect on the oscillation etc., to stretch the metaphor. So I wondered ‘why’ naturally, and after a number of discussions with colleagues, we all agreed that it was because of outsourcing of work to those so-called ‘high value centres’, the decline of the specific industry we work in, automation and the cyclical nature of the market we depend on etc. As true and obvious as that sounds, I wondered further, if there was more to the quagmire in which we currently find ourselves, than the immediately obvious reasons that brought us to that conclusion.
Then this week, I had a pleasant chance encounter with the concept of ‘survivorship bias’. It’s an easy enough concept to understand – whatever data we have, we have (easy access to) them because something survived or succeeded. For those that either didn’t survive or didn’t quite succeed, either we have no access to their data or they are ignored. The example that best illustrates this point is the study conducted by the ‘famous’ Hungarian/American statistician Abraham Wald, the ultimate aim of which was to minimise aircraft losses to anti-aircraft attacks. The available data-set for this study was from the aircraft that had returned from missions, and survived the damages like in the image below (not mine).
The obvious recommendation for reinforcement/extra armour would have been for the damaged areas. However, Wald, being quite a clever chap, reasoned that since the returned aircraft had survived despite the damages, there would be no good reason to provide extra armour in those areas. Inversely in the absence of any data from the aircraft that had not survived and never returned, it would make more sense to take chances with providing extra armour in the areas with no or little damage in the surviving aircraft as it was more reasonable to assume that those were the areas of damage that might have caused them to crash. The damages in the returning aircraft represented areas where a bomber could take a hit and still survive. Wald therefore made his recommendations based on this reasoning.
Back to my original engineering/redundancy problem. I agree that outsourcing and decline in the industry are two of the few reasons why there are so many redundancies in (construction-related) engineering as well as the fluctuating nature of the market. But it is also possible that back in the days of our parents’ generation, in the post-war economy, engineers were scarce and that engineering was one of the most stable and abundant work categories to be employed in. Having spotted those opportunities (readily available data) at the time, perhaps they promoted this line of work and encouraged the following generation to be engaged in this sector. Alas, with no access to the missing data set (i.e. future) they had perhaps fallen victim to the ‘survivorship bias’ and made the matters worse by over-crowding the engineering employment market with their ill-thought-through albeit well-intended encouragement.
All this is just a conjecture with inconsistent logical fallacies but worth a thought or two especially when it comes to recommending choices for the future based on the current reality and situations. In my opinion, there’s too much emphasis on STEM subjects at the moment especially in computer-related STEM subjects. You watch this space. In 20 years time, there could be overcrowding of coders and programmers. In any case, whatever you do, remember, all the data available to you isn’t all the data there is.
Have a fully comprehensive Friday; take Saturday and Sunday into account if you need to.