Process Porn: Seeking the Thing Behind the Thing

Daniel Felsenfeld
Daniel Felsenfeld

  • READ an excerpt from David Cope’s Computer Models of Musical Creativity

    ***

    Time was, complexity was complicated. To state the historical case in a glib and tragically oversimplified fashion, after Wagner it seemed there was no way for music to go other than in the direction of high science—after all, since language was doing it (Wittgenstein), and art was doing it (Mondrian, among others), then certainly music should do it, too. From that point on, the image of the composer—especially in the Castalia1 of the academy’s cynosure—was not that of the Byronic hero waifishly using his art to keep the forces of his stormy emotional torrents at bay but rather that of the intellectual elite, the scientist in the lab pulling wings off butterflies and writing down columns of figures. Some post-Schoenbergian serialists even went so far as to believe that attending a concert ought to be strictly an in-crowd activity, with an over-prepared audience more redolent of a physics lecture or quantum mechanics seminar. To enjoy the concert, you had to have done your homework.

    Two clear memories of my own along these lines come to mind. The first occurred when I was an undergraduate, making my way through the mandatory course on Medieval music. The instructor (the brilliant Alejandro Planchart), in full declamatory mode, told us that we were not real musicians unless we read astrophysics textbooks in our spare time. The second, more salient, was when, some years later, I had the good fortune to study with the late Arthur Berger as a first-year graduate student. I availed myself of this chance to delve into the music of his friend Stravinsky, to write a slew of pieces utilizing the octatonic scale—after all, he was the one who invented that term. Not exclusive to his coining of one of the most important pieces of standard-issue nomenclature, Berger was one of the great explainers of the Russian master’s work, and this was a composer dear to my heart. For weeks I pored over my teacher’s watershed article in Perspectives of New Music, “Some Problems of Pitch Organization in the Music of Stravinsky.” It was tough going but I managed, only tripped up on one particular clause about octave division. When at one of our weekly lessons I asked him to explain the elusive concept to me, he could not. He simply did not understand what he had written, and explained that, in those days, when one was writing for the esteemed Perspectives one had to write incomprehensibly, as it was the order of the day. Clarity of presentation smacked of puerile simplicity. This stuff not only had to be smart, it had to seem smart.2

    One locus point of this musico-philosophical prose density—aside from the circle of heavyweights that formed around Pierre Boulez, whose morass of an article about The Rite of Spring has sent a shiver down many a student’s spine, mine included3—is and was the Massachusetts Institute of Technology, which lay a few miles from Berger’s dusty Cambridge home. The site of more than a few important advancements in the sciences, their musical offerings, mostly centered around electronic or spectral music (with little or no place afforded to neo-classicism, -romanticism, or minimalism), were always aimed at the smart set, and consequently their press published some truly harrowing—though important—texts. Books written for scholars by scholars, books that probably go largely unread, no matter how impressive or groundbreaking.

    Times change. In recent months, three books have rolled off this same press that take a friendlier tact: Computer Models of Musical Creativity by David Cope; Sweet Anticipation: Music and the Psychology of Expectation by David Huron; and Gareth Loy’s Musimathics: The Mathematical Foundations of Music, Volume One. These are, true to M.I.T. form, not for the less-than-hearty musical expeditionary, but what they do have in common is that they are similarly pitched not to the highest (to gather dust), not to the lowest (as any sort of introduction for the uninitiated layman), but to an honest place in the middle. In other words, the concepts are difficult and require wrestling, but the prose does not.

    Like any worthwhile analytical text, all three begin at the same point: a desire to explain music and all its attendant mysteries—why it works, why we love it, what makes it beautiful—using a specific route of intellectual understanding. But unlike many texts that aim to such heights, an immense foreknowledge of the topic is not presumed. If you are the sort of person inclined to explore music at a level where a heady theoretical text is something you might need, want, or enjoy, than these books pull few punches by way of sophistication, and are, in a moment of credible marketability, also user friendly. Not that any of them are easy beach reads, but, unlike many an academic tract, they are all intended to be read and understood.

    Most immediate and comprehensive is Huron’s book, which aims (quite elegantly) to reason out the whole notion of musical surprise. If the simplest definition of music—again, an oversimplification, so please hold your ire—is that it is a set of expectations which is either fulfilled or frustrated, Sweet Anticipation goes atavistic, seeking a deep understanding of the many complex ways these expectations come about. How does one set up possibilities on a human level? Partly by understanding what makes that human organism react—like trying to reason out why we cry, feel ecstasy, fall in love, and grieve. When, for example, he explains “surprise,” he veers from an anecdote about a sixth grade surprise party (he scared his teacher half to death, tremendously appealing) to an explanation of that phenomenon (two brain processes involving the thalamus, the amygdale, and the midbrain periaqueductal gray). He charts melody according to the statistical properties of its arch; explains how our brain’s imperfections actually help to create expectations and their subsequent resolutions (called heuristic listening, which is what happens when our brain fills in the likely next pitch, gesture, or contour, however inaccurately); and even goes into detail about how context—as in what people are wearing or where they are standing when the music is absorbed (a schema)—is everything. His aim is to get inside the perceptive process from multiple angles, and this he does with clarity, grace, and even humor, but he is ultimately humble before his topic, ever the philosopher before the tomb of mysteries. “My theory,” he writes, “does assume that music often evokes pleasure in listeners. But there is no requirement whatsoever that artists create works of art that evoke pleasure. Art has no predefined function, which means that it can be harnessed to serve any number of purposes—including no purpose at all. Sometimes art is successful because it educates us, inspires us, challenges us, disturbs us, or even insults us. But if art never offered any element of pleasure, it would cease to play much role in human affairs.” Nothing gnomic here, however; this is pure neuroscience and psychology, laid out in a way non-experts could understand.

    David Cope is a composer, and you can tell this from his book, Computer Models of Musical Creativity—and not just because it is riddled with examples from his own music. The process he wishes to explore and exploit is the creative process, and he does so by attacking it from the vantage point of one specific, vaguely sci-fi question: can a computer be programmed to create brilliant music, as good as that of any genius? It is a question that would not be out of place in the novels of Philip K. Dick or Richard Powers—the old seven-hundred-monkeys-typing-for-seven-hundred-years theory. Cope’s text is rife with examples of pieces “composed” by his computer program (given the cute and cuddly name Experiments in Musical Intelligence—oh for the days of Hal, one letter off from IBM), which he believes can not only be taught to compose music, but to compose music of genius. By trying to ferret out the ghost in the machine, however, his book has the opposite effect of making the ghost seem all the more ineffable because it cannot be quantified so easily—or, more to the point, that the very pursuit of quantification belies its capacity to be quantified. This is only my own opinion; you’d have to get this from between the lines, for Mr. Cope buys his argument completely. He is convinced that computers, if programmed by a great composer, can themselves be great composers, and has music, chess games, and charts to prove it. “Certainly music,” he writes, “is not ‘merely a puzzle or parlor game’ nor ‘complex ratiocinations’ good music. That does not mean, however, that great music cannot be created by computer programs. Interestingly, to say that humans cannot program computers to do what they themselves can do does not indicate that humans are superior, but rather that they are inferior—not competent enough to understand and replicate their own creative processes.”

    Whether this is creepy, progressive, or just plain pointless is entirely up to you, but you do not have to know how to teach Experiments in Musical Intelligence to come up with a convincing Stravinsky ballet score to follow Cope’s point, to read and understand (and possibly take umbrage with) his book.4 For better or for worse, his point is easily found in this clear, concise text. Like Huron’s work, the concepts are challenging, the explication crystalline and frill-free.

    Like Ferdinand Saussure’s epoch-making Course in General Lignuistics (the godfather of all semiotics texts), Gareth Loy’s Musimathics builds brilliantly from small, knowable nuggets and expands them into complicated arrays of thought and understanding. He states his raison d’etre straight out: “Mathematics can be as effortless as humming a tune, if you know the tune. But our culture does not prepare us for appreciation of mathematics as it does for appreciation of music. Though we start hearing music very early in life, the same cannot be said of mathematics, even though the two subjects are twins. This is a shame; to know music without knowing mathematics is like hearing a melody without its accompaniment.” Pure and simple, agree or no, this is take-no-prisoners thinking and solvent presentation. With a basic knowledge of music, a high-school level of mathematical competency, and a willingness to sweat over some difficult concepts, this book cleanly lays out how a musico-mathematician might come to understand the parallel disciplines in a concise and unfettered way. Plenty of texts exist about the relationship between the two subjects, but few make it so easy and compelling. In line with the first two books discussed, what is daunting is the understanding—the reading is pure and simple.

    All three of these books seek to exploit a particular sort of process in a provocative way—process porn. And all three of these books, agree with them or no—and I am totally with two out of three, but cannot go in for a computer being able to master the spark of creation—aim to explain how music works from a specific point of view. They take the processes of building, creativity, or perception—all things that lay behind the closed doors or drawn shades of the imagination, the subconscious, the turning of the earth—and show them naked and under hot lights, shining through in all their specificity. For those who aim to understand, books like these are a gift, helping us (without the usual linguistic hassle) to crack these sprawling concepts. After all, these ideas are hard enough, so why obfuscate them? It means a great deal to all of us that books like these (and that M.I.T. of all places is publishing them) aimed obviously at those in the know (or who want to be) don’t feel the need to muck around with an incomprehensible high-modernist presentation. So go and read without intimidation, as that is exactly what all three of these authors are hoping you will do.

    * * *

    1. If you don’t know the novel by Hesse called Madgister Ludi or The Glass Bead Game, to which I refer, run don’t walk to your local bookshop.

    2. Incidentally, as I was leaving that Friday night for an evening out with friends, my phone rang and it was Arthur. He’d figured it out after days of worry. He reminded me that, being one of the founding editors of the journal, he supposed he would have been entitled to write any way he liked. So why didn’t he, he asked?

    3. Though honestly, once you can actually figure out the measure numbers he is discussing (sometimes he speaks of a passage, other times of a whole section, and this is never clear) the article is a beautiful gift to anyone wishing to understand.

    4. He makes his case early on by citing commerce. Paintings generated by a fractal-based computer were, he says, selling at high rates, ergo the validity of same as art. Strong words from an algorithmic composer who makes, one hazards a guess, not much on his royalties.