why do we perceive music?
There’s long been evidence that human brains have specific structures for perceiving, recognizing, and playing music, and even that people with “greater” abilities in these structures also have “greater” abilities in mathematics. If I remember correctly, we know this because certain people suffer from musicogenic epilepsy, experiencing varying degrees of epileptic seizures when listening to particular songs.
It’s not particularly surprising that are brains are specialized at this; our brains are specialized at a lot of other things that are important to people. But from an evolutionary perspective, why was music important for our survival? Specifically, why were people better able to process rhythm, rhyme, timbre and tone better able to survive? Perhaps these people were able to draw the attention of their peers, like a primitive form of fame, and this opened up other avenues for acquiring food and shelter. Or maybe they were better able to perceive the social meaning (and impending danger) of a competing tribes beats.
But where did all of this music come from? Presumably people needed to be able to perceive music before being able to play it. Or maybe the foundations of music perception, such as rhythm, were bootstrapped by other pattern matching perceptual systems, enabling people to mimic the rhythms with practice. I can see it now: the early homo sapien sitting at the edge of her cave entrance on a rock, waiting for the return of the hunting party. It’s pouring outside, and a lively pattern of drips drop down from the arch of the entrance, emerging from the orderly chaos of surface tension and gravity. Listening to this rhythm all afternoon, and hearing the pattern slow as the skies dried, that boar tooth in her hand must have become her mallet and the rock her marimba. I wonder what the hunting party thought when they returned home and she was teaching the kids how to tap stone. At least the kids were busy playing instead of whining about the lack of food.
what does it mean to communicate an idea
What is an idea? Is it something that compels one to act? Is it influence? Is it the atom of communication? I would like to think that in each of these sentences is an idea, some pattern of thought that I can convey with language. If this is the case, what is this sequence of sentences? Is it a means of making you think what I’m thinking? By transcribing these words, am I guiding your thought? And what enables this guidance? Must I translate these ideas to written word to steer your mind, or might I speak them for the same effect? Might I sketch them out with lines and arcs with a charcoal pencil and in doing so ask you these same questions? What is it I’m doing? How is it that by forming this prose I influence the actions of your mind? How is it that I transmit this pattern of thought from my mind to yours? Do we share the same mechanisms, the same structures in our brains? Does some conventional human physiology give idea life? What if your mind had a different architecture that mine? Would you be unable to conceive of the ideas I present here? Is this paragraph a program that you execute by reading and whose effect is to modify your mental state? And is its power not in its determinism, but in the imprecise predictability of your interpretation of it? Perhaps the variability in my readers’ understanding of these concepts serve as the mutative operator of their evolution. Perhaps if ideas live and die like organic forms, bias is the racism of their society, and objectivity their democracy. Let these ideas thrive; give them time to breathe. Consider for a moment your role in their survival and adaptation. Think.
on the role of empiricism in applied sciences
As originally conceived, empiricism was a way to test your theories and hypotheses against observations of the natural world. This approach to understanding reality was a revolution in the sciences, bringing a flood of scientific knowledge and technological advancements.
It’s not surprising then that in modern applied sciences, such as human-computer interaction and software engineering, empiricism plays a similar role in helping researchers understand the phenomena they work with. One major difference between “soft” sciences such as HCI and software engineering and “hard” sciences such as biology, chemistry, and physics, is that the phenomena they study are quite different in their permanence. Physicists study the inner workings of the laws of the universe; biologists study the form and function of processes in life. These are phenomena that change very slowly over time, which gives “hard” scientists time to hypothesize, theorize, reject, and synthesize.
In contrast, “soft” sciences study phenomena that are extremely quick to change, relative to the expansion of the universe and evolution on Earth. I might suggest some relationships between programming environment design and group work, only to have yet undiscovered and fundamental dimensions of these programming environments change under my nose. I might propose a theory about the causal relationships between programming paradigms and productivity, but in 20 years, someone could reinvent the programming language, possibly making my theories irrelevant. Worse yet, by relying on empirical data, which is extremely fickle and context-sensitive, I may not even confirm my hypotheses or theories before they have to be thrown out.
What’s the value of empiricism then, if it’s not fast enough to keep up with the pace of technological change? One argument might be that the objectivity that empiricism provides has a slight edge on our best intuitions, even in the short term. If I’m trying to decide what to name a particular field on a web form, am I better off with my personal biases, or small sample of data, however small or skewed? Probably with data. At least then, the design choice is defensible.
But I think there’s a better reason. What underlies these tradeoffs is the fact that many “soft” sciences are used more directly for design than the harder sciences. In all design, there is never enough data to provide an objective recommendation to every design decision. At best, the research might offer a clean delineation of the tradeoffs involved in general categories of decisions, but ultimately, it is the designer who must make the final decision, and they must make that decision with their intuition. When I design tools and notations, I might make a hundred design decisions a day, with only one backed up by empirical data.
Empiricism then, is best suited at arming the designer with the most objective and reliable intuition that data can provide. And that means that the most important part of empirical research to get right in the soft sciences is to have the designer get the data. That’s right: your programmers must observe the phenomena they will support. They must become experts in the domain. They must understand it with such detail that when faced with the smallest of programming decisions, they have an empirically grounded intuition about what will work and what will not, and a deep sense of the tradeoffs of their choice.
If we really need empiricism to cultivate intuition, what is the value of reporting empirical data? I don’t personally believe that reading a report of another researcher’s observations is nearly as enlightening. But what it can do is change what researchers look for and how they interpret their own observations. The role of the research community is to temper individual observations with a broader collection of data. This is how we generalize and validate our experiences, in the search for truth. We just have to make sure that in the process of seeking truth, we expose the designers and engineers who will be building our world to as much of reality as we can.
