The whole point of the medical treatment was to make you forget the past.
Memories that one wished had never occurred could be erased, particularly in the context of personal and emotional loss.
And if that feat of pharmaceutical engineering proved too magical to believe, one could still be emotionally inspired by way of an 18th century poem by Alexander Pope, from which the Michel Gondry film on this memory treatment took its name:
How happy is the blameless vestal's lot!
The world forgetting, by the world forgot.
Eternal sunshine of the spotless mind!
Each pray'r accepted, and each wish resign'd;
Linking memory with past and present had particular resonance for me at the moment, but it was remembering, not forgetting, that I was striving for. I was in Cincinnati, Ohio, where I found myself sitting at a café table with Lionel, a French entrepreneur and computer science PhD who was the founder of the company that had been facilitating the statistics software training I had been in all week. Lionel and I had learned that we were both fans of Michel Gondry, a film director known for his surreal theatrical imagery without the heavy use of computer-assisted effects. In particular, we both agreed that Gondry’s filmEternal Sunshine of the Spotless Mindwas an elegant interweaving of art and science. Despite our cinematic affinities however, our conversation had evolved to a much more pressing question:
“What is root beer?”
Referring to the popular soft drink available widely throughout the United States but less so outside North America, Lionel was inquiring about this deceptively non-alcoholic beverage, which he had recently read about in the Stephen King thriller,Hearts in Atlantis.
Questions and the contexts in which they were posed had very much been the stuff of Lionel’s workshop all week long. Knowing which questions to ask on the path toward a problem’s solution was the central concept of the training. Lionel was teaching a hands-on software seminar on using methods from a particular branch of mathematical analysis called Bayesian statistics to optimize engineering, research and development, and manufacturing processes. Michel Gondry’s themes of memory were quite apropos, since recalling how to evenspellBayesian statistics had itself proven to be a challenge for me, much less in being able to follow Ariadne’s fiber-optic cable through all these labyrinthine computing tools in which we had been immersed.
The concept of Bayesian statistics is to take the knowledge one knows now in the present and use it to predict knowledge that one could possibly know in the future. Harnessing that knowledge using precise statistical methods to form predictions creates correlations to the present, linking the present circumstances to new knowledge in the future that is not yet known or confirmed. The equations we dealt with were part probability, part human behavior, and part hieroglyphic-inspired mystique.
How Lionel and I had even ended up here in this cramped corner restaurant in the terminals of the Cincinnati-Northern Kentucky International Airport was itself a probabilistic journey, our third unplanned encounter over the span of a half day’s time.
Statistically speaking, the probability of two individuals randomly running into each other in a city of 300,000 people is not tremendously high.
But that’s not how a Bayesian would look at it.
A Bayesian would say: Start by looking at what information is presently known. Say you discover that the two individuals have a passion for the fine arts that are equal in intensity to their passion for the sciences. Given that the two individuals are uncertain as to the next time they would be in Cincinnati again to see its museums, they weigh the relative sizes of the major art museums in the city and select the smaller of the two. Say both individuals also have the behavioral practice to be early arrivers at the airport to minimize the unavoidable side effects of rental-car returns, ticket counters, luggage check-ins and long airport security lines. Say the two individuals both have connecting flights to major cities served by the same airline.
Generally without knowing these pieces of information, a third-party observer would estimate that the two individuals would probably not meet.
Until they do.
So it was not a Bayesian surprise when earlier that day Lionel had found me in a section of the Cincinnati Contemporary Art Center diligently participating in an interactive and extremely technically demanding hands-on exhibit: constructing a model house using copy paper and children’s crayons. I showed him my masterful design and we chatted about architecture and an emerging artists’ group show that was on display in the museum and then parted ways.
Just a couple of hours later, when he and I met again, unknowingly synchronized in the time frame in which we were returning our rental cars, we were still surprised, but less so. And when we found that our airport departure gates were directly across the hall from each other’s, we decided to seek out food and conversation in the remaining time that statistics would allow, bringing us to…root beer.
I knew inherently through experience (and copious indulgence) what root beer was, but had never been asked to explain what it was. But the course of the conversation grew to being less about the history of sugary soft drinks than the circumstances in which a computer scientist from the outskirts of Paris and a chemical engineer from New York City could unexpectedly meet and talk data analysis, horror novelists, and surreal art films, all in a distant city in the American Midwest. Science and engineering can be quite rigorous in their methodical combination of theory and applied practice, but ultimately, they are also just tools that help us seek a more precise understanding of all those characterized circumstances, composing the manner by which we all live as citizens in a world still trying very much to understand what it means to be immersed in an increasingly omnipresent and global life. We talked the challenges of venturing out to start your own company and the challenges of working internationally while striving so hard to make a significant impact locally. Every quantum of conversation was aggregated to the point where a seemingly mundane present was going to be a part of an intricately woven memory to be one day recalled in the future.
As we finally left the café to catch our flights, I reflected on what had just happened. As student, as listener, and as friend, there was nothing about our conversation and the circumstances in which it had formed that had not been just simply grand (even if perhaps that feeling had been influenced by me having just downed two icy cold root beers.)
Lionel picked up a few souvenirs from an overpriced airport gift shop for his children and we smiled and shook hands, wishing each other good journey and safe roads ahead. Between dreams and professional aspirations, stepping forth into the scientific promise of an inspired future can oftentimes be the equalizing tool that brings logic into the fray of reality and its ongoing unknown variables. It is here that the seemingly cold yet dynamic functions of the sciences are freeze-framed like a movie still, revealing the human elements of inspiration and aspiration therein among the threads.
You realize without knowing at first, that in the methodical execution of science, in all its rigor and quantitative intensity, nothing in the world is really magical.
And then everything is.
Published February 18, 2013 by Austin Lin