In his dotage, my old man (a chemistry Ph.D) used to say, as he slowly stirred his martini with a crooked finger, “the more we know, the less we know.”
As systems become increasingly complex because we overcome old technological hurdles, they also become more unpredictable.
One recent example is report that NHTSA and the NASA Engineering and Safety Center (NESC) published regarding unintended acceleration of Toyota automobiles. Michael Barr has an excellent report on it. In short, NASA said it couldn’t rule in but couldn’t rule out software problems as a culprit in the unintended acceleration problem.
And Stanford, via its Facebook page, has described how engineers are addressing the "aeroelastic flutter" problem, a complicated, unpredictable phenomenon. (P.S. don't watch this video if you happen to be on a plane with WiFi).
The more complex the software (and hardware), the harder it is to model and find corner cases. We seem to be falling behind in assessing the known unknowns and we’re completely in the dark about how to approach unknown unknowns.
We race up the abstraction ladder to try to keep our arms around design complexity, but that creates other issues. I attended the annual meeting of college engineering departments recently in Phoenix and one questioner from industry stood before a panel of academics shaking his head. It’s great to turn out really smart kids who know theory and can deal with abstraction, but if they struggle with basic engineering concepts, companies need to train (or retrain, perhaps) them.
How are we going to get better at anticipating the unknown unknowns? It is formal methods? It is impossible?