What sort of algorithm enjoys music?

Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more beautiful. Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and (since 1990) artificial systems.

Manfred said:

One proposal is that we form a vague (consistent with many possibilities) model of what the musician is likely to do next, and enjoy it when the model feels accurate.

Andrew Hickey said:

I suspect actually the opposite is true - that we enjoy it when our expectations are subverted, but in a way that makes sense after the fact, like a joke.

I'm not where I can give you more detail right now, but interestingly (and kind of maddeningly) these positions are both correct; current psychological models of responses to music include both prediction mechanisms which experience gratification when they are proven correct (Manfred) and other "imaginative" mechanisms which find it arousing when expected events are delayed or when unexpected events occur (Andrew). Obviously, the interplay between these opposed mechanisms accounts for much of the complexity of the human response to music. The current standard text in the field is David Huron's Sweet Anticipation: Music and the Psychology of Expectation (MIT 2006). This isn't my area, but I will be happy to provide more information when I can consult my references later, if this would be of general interest.

I have a LOT to say on this topic (as in sequence-of-front-page-posts-quantity); unfortunately I can't exactly say it right now because I'm at a conference this week.

For the moment, I'll just send out a general warning that the temptation to engage in fake explanations or greedy reductionism seems to be nigh-irresistible in this domain (at least among those who don't opt for outright mysterianism).

In particular, be extremely cautious about trying to do something like this without having studied music (to the point where e.g. you've at least heard of Schenker). Otherwise, chances are you simply won't have a rich enough concept-inventory to capture the subtleties involved.

In general, remember that value is complex.

"One proposal is that we form a vague (consistent with many possibilities) model of what the musician is likely to do next, and enjoy it when the model feels accurate."

I suspect actually the opposite is true - that we enjoy it when our expectations are subverted, but in a way that makes sense after the fact, like a joke. Certainly if one watches video of screaming girls at Beatles concerts (the rawest, most visceral musical appreciation I can think of) they tend to scream loudest at those parts where an unexpected chord change comes along...

If you are going to try to understand the brain, I humbly suggest that you try to understand one of the easiest-to-understand aspects, and the human response to music is not one of them.

More generally, try to understand an aspect where the attempt has high expected utility.

I suggest reading Hofstadter's work on "fluid analogies", imitation and translation. However out of vogue DH is now, his writing on these topics is itself very enjoyable and has led many smart people to fruitful meditations about AI.

Also, possibly relevant, Burton's "On being certain" which analyses the neural correlates of the feeling of knowing, and points out that there are adaptive reasons to wire this feeling to the pleasure centers.

I'm also curious how all these relate to favorite songs. Why is a piece of music that you've heard years and years ago still enjoyable? Or why listen to the same awesome new song half a dozen times in one day? You already know what the next note will be...

The question of how we have aesthetics is one of a handful of big, important, unsolved questions that need an answer before anybody tries making artificial intelligences. (I don't have an answer.)

I don't enjoy music.