I was listening recently to some engineering graduates talking about their current research efforts. As I was forcibly immersed in the minutiae of opaque mathematics, the thought came to me that this was really difficult work for potentially small gains. But on the heels of that came another thought: These engineers were really skilled. I was greatly impressed by their depth of knowledge and facility with analysis. How did they learn so much in their few years of university training? After all, there is so much more to know now than there used to be, and every year it gets ever more overwhelming.
One explanation is that, as new knowledge accumulates, some old knowledge becomes irrelevant and falls off the knowledge stack. Almost all the college course work I took long ago is now useless in itself, although what remains is an engineering mind-set and a mathematical grounding. Perhaps every course should have a sell-by date. Indeed, in retrospect I now realize that a number of the courses I took were already well past their sell-by dates when I took them. I remember too when the technical library in the lab where I worked was shut down and all the books were offered free to the staff. Almost all of them went unclaimed; no one wanted them. The problem is that we never quite know when a particular course or book will become obsolete.
But the purging of obsolete knowledge is probably insufficient in itself to make room for the new stuff, as there seems to be an exponential increase in knowledge. The complexity of our work is always increasing, similar to the increase in entropy decreed by the second law of thermodynamics. For many decades we’ve been driven by Moore’s Law, which has urged us to embrace and exploit complexities that were unthinkable in previous decades. Even as Moore’s Law wanes, I feel sure that the general law of exponential increase will continue the trend.
New engineers often enter fields that have become well plowed, and so find themselves pushing against physical and theoretical limitations. The issues are complex, and the incremental gains may be small. I imagine an index of measurement—potential gain divided by complexity of required work. Normally, this index grows ever smaller, but fortunately new fields and new techniques open up periodically, and engineers rush in to take advantage. For example, I frequently hear about engineers employing machine learning in some new and creative way.
As the new engineers come out of school, they are also empowered by the continual rise of new tools. They work with networked computers, whose software embeds the knowledge and techniques of analysis and design accumulated by others. I remember when we used to wander down the halls asking other engineers how to solve some problem. Now we put our questions to the computer, and by doing so, ask all the other engineers and scientists of the networked world. You don’t have to know everything yourself, only how to ask the questions.
So the challenge is great, but these graduates are up to it. I’m thinking, however, that there must be some value in the experience of older engineers. But that is a subject for another time; this is a salute to the new guard. n
This article appears in the September 2019 print issue as “The Expiration Date of Knowledge.”