Graduate school is a blur. I’m 1/4 of the way through, which is a huge relief compared to a few weeks ago, and yet is pretty shocking compared to the fact that I got here so recently. I hardly have time to keep up with my weekly assignments (almost all of my work is done purely in an effort to satisfy the following day’s requirements), much less maintain a blog. But now I am halfway through my break, and amidst binge-MST3K sessions, I’ve decided to attempt some kind of a summary of my semester – both to record it and perhaps to shed some light on what actually happened…
I’m not sure what I expected MIT to be like, but it is unlike any place I’ve ever been. Getting around the campus is similar to getting around Boston and Cambridge – it just takes practice. There’s very little opportunity to employ intuition in finding your way around. You must start with the (complex, non-intuitive, but admittedly very organized) numbering system and go from there. In some ways, I suppose it’s like the human brain…a dense, overlapping, interconnected mess of hallways, classrooms, and labs. Schools span and share floors and corridors with no apparent regard for organizational strategy. That’s a result of the premium square footage cost, of course, but it also makes for an interesting forced integration of fields. There seems to be very little hierarchy or class structure (so to speak) with the sole exceptions being the few branches that do occupy dedicated buildings (of which I’ve visited the Media Lab and the Brain and Cognitive Sciences Building). The general population seems young, despite the fact that there are more graduate and doctoral students than undergraduate. And it is absolutely, unequivocally, unapologetically the biggest collection of nerds I’ve ever been (proud to call myself) a part of.
I took 5 full classes (actually 4.5, but the .5 had the workload of a full class) this semester, which was probably 1 too many. My only architecture (Course 4) classes were Inquiry into Computation and Design and Architecture Studies Colloquium – both required. (I’m ignoring Forum in Computation, the Computation group’s brief weekly hangout session.) I’m not counting Tangible Interfaces as an architecture class, as I’d argue that most Media Lab classes (Course MAS??) should probably be categorized more broadly as “design” in general. My other two classes were Artificial Intelligence (Course 6, Electrical Engineering and Computer Science) and Aspects of a Computational Theory of Intelligence (Course 9, Brain and Cognitive Sciences). I suppose my low ratio of architecture-to-non- classes could seem a little strange, but it speaks to what I came here to do: juxtapose multiple fields alongside architectural design in an exploration of creativity, technology, and computation, all situated at the heart of some of the most progressive research going on in each field.
And the semester was fantastic. Inquiry provided a fantastic overview of various computational strategies, histories, and theories. Colloquium, even while holding the title of everyone’s semester thorn, still brought in many good speakers and covered a diverse array of interesting topics. Tangible Interfaces was a good introduction to the Media Lab, if a bit of a letdown in terms of rigor and production. Artificial Intelligence was a blast, and an excellent first plunge into the world of AI at MIT. ACTI, probably the most straightforward “class” of the semester, was a fantastic menagerie of different current research going in the cognitive/neuroscience community.
My work consisted almost entirely of reading and writing. I’ve started a nice PDF collection weighing in at about 700MB, which I’ve tried (with some success…) to organize. I did a few fabrication projects, but all in all this is a very different way to do architecture school. Research is why I came back, though, so I don’t mind that this will probably define my time here. I do occasionally itch for a little hands-on work; hopefully I’ll find ways to satisfy that amidst all the literature.
Since the whole program only lasts four semesters, I’m already beginning to think about my thesis (in fact, I take a computation-specific thesis prep course in the spring). My thinking has evolved a lot over the course of the semester, though I admit I’m nowhere close to knowing what I’ll research. In many ways I feel pulled into the field of Artificial Intelligence – but I remain ever dubious of it. No matter what cutting-edge work I see, I still can’t shake the notion that there is something missing, something wrong, some fundamental assumption(s) that we’re relying on that might turn out to be a bit skewed. There is such a focus on “intelligence” and, I worry, not enough on all of its auxiliary forms: emotion, morality, judgment, humor, value. I see more “life” in the cybernetic experiments of the 50’s and 60’s (and my current favorite, YouTube’s great collection of useless box videos) than any of the robots being developed today. To predicate the development of AI on the notion that we are, fundamentally, logical beings is…well, one way to do it, I suppose. This, of course, pulls me into other fields – sociology, philosophy, anthropology – which I feel are essential for an accurate view of AI, if largely neglected due to modern society’s championing of specialization.
To be fair, my opinions change drastically depending on the week, day, hour….there is much to research about the topic before settling on a direction, and it’s thrilling to be studying at one of the epicenters of its development. Artificial Intelligence is a study of the brain as much as it is a study of machines, and that frontier is as unexplored and exciting as ever.*
In undergrad I researched playfulness and what it meant to be creative when working with machines – this semester, I tried to expound on that topic with a paper I wrote for AI. In it, I looked at the early definitions of intelligence augmentation (largely provided by the field of cybernetics), and attempted to explain why this relatively under-researched area might be making a comeback (and how it could relate to design). Amidst such a massive influx of writers, theories, and fields, it will be difficult to settle on one focused topic for a thesis – maybe a PhD isn’t such a crazy idea after all…
What else? Cambridge has been great. The cold weather was essentially a non-issue in November and December, as it didn’t really plummet permanently until the very end of the year. We’re still trying to map our way around the city (see MIT campus description, above) and find our favorite bars and restaurants, but with good friends new and old, a great apartment, and an amazing partner with whom to explore, I can safely say I’m living my dream right now.
*I’m afraid I must report that, contrary to what the media would have you believe, AI isn’t anywhere close to being achieved, the Singularity is NOT near, and our robot overlords will have to wait a bit before settling in. Sorry, folks.