BLISS

I remember the late 1960’s when I went off to graduate school, all of my peers, all of us, we were there to measure something, lots of somethings then organize that information into tables, tables into graphs and then do a lot of math. In the end, we were supposed to learn something. If we were lucky, that something would be important to someone, somewhere; at least it would make sense and be factual. I was advised, by my advisor of course, “The only reason for you to be here is to learn to do research.” It would follow naturally, if you don’t know how, you can’t. All that talk about method would be just talk, like theoretical sky diving. Not only would you not be able to do credible research but neither would you be able to appreciate (critical review) the work of others. 

I shared an office with seven other graduate assistants. We shared one mechanical adding machine the size of a small foot locker. It had dozens of small windows with rotating dials; each dial with numbers 0 through 9. When you enter a problem and hit the big ‘Run’ lever it growled like a food processor gnawing its way through plywood. All of the dials would spin for 3 or 5 or 8 seconds and stop with an audible chime. The problem (equation) had been solved. In the large set of windows at the upper right, you could read the result. With a slide rule you could make some of your own calculations, pre set them on the operational dials and speed up the process. Some equations were long, requiring several operations and there were eight of us needing the machine. 

None of us were researching the same subject: some were the results of surveys, some were based on biometric data, others with performance levels. Regardless, we all struggled with the same kinds of obstacles. How do you find time to review related literature, to know everything you need to know before you can begin; how do you narrow the scope, control variables and determine the best tool and its best application? In the real world, dead ends are not only necessary but incredibly important. But for grad students, they are deadly. Standard deviation and statistical significance can be the answer to prayer or the fly in the ointment, all depending on where they lead and where you need to be. In the end it didn’t matter what we learned; all that mattered was we know how it works. It’s not as important where you land as you know how you got there. 

I live better now with two hearing aids, each one with more/better technology than the computers that got our astronauts to the moon and back. My grandchildren have at their fingertips, magical machines that text and tweet on command. But I doubt they will ever understand, even in principle, how energy from fossil fuels or water falling down hill reach the USB port on their smart phone. I doubt they will ever grasp how that energy is stored once it gets there. That disappoints me but it doesn’t come as a surprise. Evolution is not predicated on civilization, a higher standard of living or moral principles. They are side effects. Evolution is dedicated to only one purpose, a sustainable birth rate. To that end, it is like any other form of research; many dead ends. To think we can avoid that dead end is naive on our part. 

I’m afraid we are obsessed with “Forever” when we should be focused on “Now” - not tomorrow or later today but right now! I’m still hung up on E. O. Wilson’s observation: “The problem with humanity is that we have Paleolithic emotions, medieval institutions and God like technology.” In just the last half of my lifetime, we’ve come from graduate schools with mechanical adding machines to global tweeting, between people who can’t remember anything about the periodic table other than it was boring. How many cell phone junkies recall what happened at Runnymede or the significance of, “Let them eat cake”? If I frame my own observation it will certainly parallel a better one, made by someone who understands better then I; but it’s all I can do. “Ignorance is bliss but it’s no better than your last breath: it won't take you very far.”