Date: 2011-03-30
To: Am I excited?
Miles today: 0.0

As I sit on this Amtrak train heading slowly (or so it seems) down to Georgia, I think about the question that people have been asking me -- are you excited? -- and about something my brother said months ago, that those who go on the AT unprepared have the most fun. It seems like he might have been right, at least in the sense of anticipation. After months of planning, researching and buying gear, reading books and trail journals and watching movies about the trail, I feel less excitement now than I did a year ago when the idea and possibility for the trip first began to bloom. Which is not to say that I'm having second thoughts; I want to start my thru-hike now just as much as I did six months ago when I began telling people that it would happen. I just don't feel any special sense of giddiness or anticipation. Instead, I think about a talk I saw years ago about machine learning and the convergence of research on computerized simple neural network models and experimental research studying neuron clusters of live animals.The way computerized neural networks are used in machine learning and artificial intelligence, the talk explained, is by using a series of inputs that lead to states associated with some reward to build a weighted predictive model that refines itself as it gains experience. This is a useful mathematical technique for solving complex, often abstract problems without having to "understand" how they're being solved. The technique is inspired by our understanding of how the human brain -- and the brain of animals -- works. But what's interesting is that, as MRI resolution explodes and other medical research technology improves, our understanding of artificial intelligence and computer models is in turn being used to help us better understand the workings and behavior of the brain.Take an experiment where you give a place a drop of sugar water on the tongue of a monkey at regular intervals. Measure the right part of its brain carefully enough and you will notice that the monkey experiences pleasure shortly before it receives the sugar water, consistent with psychological studies on classical conditioning. If the expected sugar water does not appear, the monkey feels a corresponding disappointment, in a neurologically measurable sense. Now if you look at and measure that area of the brain you can match up the physical model with a the standard computer learning model, right down to the "weights" on the nodes of the network, and predict how the physical model will change in response to new inputs.I think about how this model relates to broader changes in human consciousness, and though it may only be true in a metaphorical sense, it helps me understand the mellowing of emotions that seems to come with age and experience. What delights us is not so much pleasurable and novel experiences themselves as much as the belief -- for some deep, neurological definition of "belief" -- that these experiences exist and that we will experience them. As our experiences grows and our accuracy at predicting outcomes and their likelihood improves (if not consciously, then at a lower level). Which means that in place of the giddy joys and crushing disappointments of youth, we are more likely to have those reactions diffused over time as longer periods of contentment or depression that, in addition to being more diffused by time, are also more likely to average each other out.So, am I excited? I was excited when I realized, when I first fully believed, that I was really going to stand on Springer Mountain and start walking north. Having accepted and grown used to that idea over the last several months, what I feel now is more of a calm sense of anticipation. And I envy, if only in a small way, those who are about to embark on the trail unprepared, whose models of what it has in store for them have not yet been built and who will experience unsuspectingly the full power of what it is to hike the trail. But, for all my reading and anticipation, I am probably more naive and unprepared than I could guess, and will likely get more than my fill of shock and surprise.