One of the first things that got me really excited about music was programming drum machines. I liked being able to find and record any sound with the computer’s lo-fi mic, and use it as an instrument. Actually, I still have (and use) a lot of the sounds that I recorded in middle school. The software I used was a simple step sequencer. A step sequencer represents time as discrete, evenly spaced “steps,” rather than as a continuous flow. Rhythms programmed with step sequencers tend to feel very mechanical. The intensity, timbre, and duration of each sound is exactly the same. If a human were to copy the rhythm of a drum machine, there would naturally be small but perceptible differences between each sound.
While I was learning music, oscillating between programming electronic music and performing on acoustic instruments, I thought a lot about my relationship to technology. I started to think of the essence of technology and machines as regularity, and the essence of humans and nature is irregularity. So, continuing to use the same software, I developed strategies to humanize my rhythms. I started using irregular and mixed meters – having the length of patterns constantly changing, destabilizing pulse and expectation. I also started using higher resolution step sequencers. Rather than dividing time into 16 steps (the default), I used divisions of 32 or 64. While time was still discrete, it gave me the option to have a sound between the expected divisions of time. As I learned more about computers and digital audio, I figured out that even software that supposedly gave access to a continuous timeline was discrete. Rather than dividing 1 second into 4 divisions, it might be divided into 44100 divisions (depending on the tempo and sample rate, but you get the point). This further complicated my ideas about humans and machines. No matter what, working in a digital medium means that everything is discrete, but the perceptibility of these essences depends on resolution.
More recently, as I’ve become interested in algorithmic composition – the use of computers to aid in music-making decisions – my regular / irregular duality became even more complicated. I quickly found out how easy it is for computers to generate complete randomness, and how inhuman this feels. Humanness isn’t just irregularity, and it isn’t a pure essence. For an algorithm to come up with human-like sounds, it needs to incorporate some balance between randomness and rule following.
These ideas about balance and resolution have become core aesthetic principles for me, applying to every aspect of music, as well as how I think about technology in general, other art forms, nature, life, etc. In teaching a music technology class primarily focused on concrete skills, I think it is important to try to incorporate some of these abstract aesthetic principles. From my perspective as a composer rather than an engineer or a theorist, this is truer to what I have to offer students. While the explicit focus of each project is usually a particular skill, I hope to implicitly encourage students to explore some of these concepts I’ve discovered over the years. But how can I do this in a way that applies to all of their diverse interests, and doesn’t push students towards or away from any particular style?
Here are a few examples: When we talk about programming rhythm, I ask students to start quantized (rhythmically regular), and gradually give them ideas on how to incorporate irregularity. Each student comes up with different ways of balancing and organizing these forces. When we talk about choosing software, I explain the benefits of each program, but I also ask students how they approach individuality and expression in a world where so many people are working with the exact same tools. I ask them to think about technological determinism, and how the software influences their decisions and sounds. When we talk about digital audio (really fun stuff like file formats, sampling rate, and bit depth), we compare our everyday associations with the words “analog” (lo-fi, warmth) and “digital” (hi-fi, cold, clean) with an actual technical definition: continuous or discrete. They’re surprised when I say that typewriters are digital because they have a discrete number of possible characters, and have interesting arguments against this. One student said that yes, the characters are finite, but that the way a typewrite puts ink on a page and the alignment of each line is always a little bit different.
I try to encourage students to follow a similar path to mine, starting with concrete ideas and figuring out how they can become more conceptual and interdisciplinary. I ask them to think critically about the tools they use by structuring the class around creative projects and open ended questions. As I continue to develop this class and prepare to teach others, musical and else, I’ve been thinking about how to communicate knowledge to students. Often, we can’t really just present some ideas outright and have it be meaningful. Rather, we often have to help students find ideas on their own. I find it really useful to think about my own experience discovering these ideas, and how I’m trying to help guide others to do the same.