The original version of this story appeared in Quanta Magazine.
In the film OppenheimerNiels Bohr challenges the physicist early in his career:
Bohr: Algebra is like a score. The important thing is not “can you read music?” but “can you hear it?” Can you hear the music, Robert?
Oppenheimer: Yes, I can.
I can’t hear the algebra, but I feel the machine.
I felt the machine even before I touched a computer. In the 1970s, I waited for the arrival of my first computer, a Radio Shack TRS-80, imagining how it would work. I wrote some simple programs on paper and could feel how the machine (which I didn’t yet have) processed each step. It was almost a disappointment to finally write the program and get the result without experiencing the process going on inside it.
Even today, I don’t visualize or hear the machine, but it sings to me; I feel it humming, updating variables, looping, branching, searching, until it reaches its destination and provides an answer. To me, a program is not static code, it is the embodiment of a living creature that follows my instructions to a (hopefully) successful conclusion. I know computers don’t physically work this way, but that doesn’t stop my metaphorical machine.
Once you start thinking about computing, you start seeing it everywhere. Take, for example, sending a letter by post. It is placed in an envelope with an address and a stamp, put in a mailbox, and somehow ends up in the recipient’s mailbox. This is a computational process, a series of operations that move the letter from one place to another until it reaches its final destination. This sending process is not very different from email or any other type of data sent over the Internet. Seeing the world this way may seem strange, but as Friedrich Nietzsche is reported to have said, “Those who were seen dancing were considered mad by those who could not hear the music.”
This innate sense of a machine at work can lend computational perspective to almost any phenomenon, even one as seemingly inscrutable as the concept of randomness. Something seemingly random, such as the flip of a coin, can be completely described by a complex computational process that produces an unpredictable result of heads or tails. The outcome depends on a myriad of variables: the force, angle, and height of the flip; the weight, diameter, thickness, and mass distribution of the coin; air resistance; gravity; the hardness of the landing surface; and so on. The same is true of shuffling a deck of cards, rolling dice, or spinning a roulette wheel, or generating “random” numbers on a computer, which simply involves running a deliberately complicated function. None of these processes is truly random.
The idea goes back centuries. In 1814, in its Philosophical essay on probabilitiesPierre-Simon Laplace was the first to describe an intelligence, known today as Laplace’s demon, that could predict these outcomes:
