Aging engineers versus experienced engineers

There are growing complaints that Silicon Valley companies discriminate against middle-aged engineers. But it might not be just ageism, it might just be aggregation error.

Engineering comprises mainly two things: a body of knowledge and a problem-solving mindset. To be a good engineer one needs an up-to-date body of knowledge in the relevant field and a facility with different problem-solving approaches used in the field (and possibly outside it as well).

(For the moment let's leave aside the problem-solving mindset; its dynamics are complicated and very situation-dependent: while some engineers acquire and develop problem-solving skills with experience, other fossilize their thinking, for example due to organizational practices.)

As part of what I do is continuing education, I have observed the dynamics of the body of knowledge as engineers' careers progress.

• The largest group by far (sadly), makes little attempt to keep up-to-date with their field after formal education ends. In conversation, after a corporate training event, a member of this group told me that keeping up-to-date was "very nice in theory, but we don't have the time." All of us would like more time; but this person spent tens of hours per week watching TV. One of those hours per week spent updating their skill set would mean 52 hours per year, which would be more than enough (most of the participants in that event had fewer than 20h/year of training or study, and self-paced learning can be much more effective than group events.)

• Most of the remaining engineers realized their technical obsolescence would become a problem and were retooling themselves for a management job. The main problem with this attitude is that there will always be fewer management jobs than engineers who plan to go into management. Secondarily, firms have both partially replaced management jobs with consultancy engagements and started prioritizing management-trained applicants over engineers.

• A few engineers fell into a third category: those who keep up-to-date either because they realize the job implications of doing so or because they really love their engineering field. The problem, for those in this group, is that their small number makes them liable to be categorized into one of the other groups.

Placing ourselves in the position of Google, for example, the decision to consider a candidate who's been out of formal education for several years versus considering one that's just graduated --- even if Google believes that the energy of youth can be balanced by the temper of experience --- comes down to which of the three groups above the older candidate will fall into.

In the absence of good information, statistically the older candidate will be in the first group, in other words, aged, not experienced, a distinction that most of the engineers can but will not make (as it defeats their case).

(The younger candidate's type is irrelevant, because being fresh from school means an up-to-date skill set, at least for the near future.)

There are obviously many confounds: consider a choice between a newly minted computer engineer from Idaho State - Tubertown with no code to show (not even from school projects) versus a 45-year-old Caltech graduate class of '95 who has code on GitHub that is particularly relevant to the job, for example.

For the other engineers, who have been lax in their updating of skills, there's a solution: it's never too late to learn. And then: show, don't tell.

Intellectual counterfeit fashionistas and the corruption of STEM and analytics

I have acquaintances who say they like classical music but never listen to it and can't tell Bach from Brahms. While this is entertaining to classical music aficionados, a similar disconnect happens in STEM and business analytics, where it has serious consequences.

I've observed many people who are always saying how important science is, who can name several recent Nobel laureates in the sciences, but can't compute the kinetic energy of a 2-ton SUV going 65MPH (766kJ), or, ironically, can't explain what the research of those Nobel laureates was about.

I know people who are always talking about Big Data™ and "the" Management Information Revolution™ (yes, they think the current one is the only one), but cannot write Bayes's formula and think that standard deviation is the same as standard error.

These are the signs of the rise of the intellectual counterfeit fashionista (ICF). The ICF wants others to consider him or her an intellectual (that's the I), up to date on the latest hottest intellectual topic (that's the F), but is not willing to do the work and the learning necessary to understand that topic (that's the C).

No matter how infuriating or entertaining an ICF can be on a personal level, their rise is a problem -- chiefly because of their effect on education, the practice of technical professions, and the general perception of STEM and analytics in society.

Education: by trying to recruit proto-ICFs into STEM/analytics, teaching institutions end up having to water down their courses, since the ICFs don't want to do the work needed for real learning. This leads to lower quality education for every student, even the non-ICFs.

In the mid-to-long term, this creates a number of credentialed ignoramuses and gives rise to the strange situation where people who hire engineers say there's a dearth of them, while engineering associations say there's a glut. I guess it depends on how you define engineer, by skills or by credentials.

Professions: the obvious effect of ICFs is the rise in average incompetence. The more pernicious effect is the destructive nature of internal politics, which always increase in organizations with large numbers of people for which appearances and narratives are more important than observable realities and hard work.

I wish nerdiness became unfashionable again, so that the ICFs moved on to corrupt something else and left STEM and analytics alone.