Uncertainty

In 1948, Claude Shannon was working at Bell Telephone Labs and published a paper called “A Mathematical Theory of Communication.”¹ ⊕ ¹ A few years later, when he turned it into a book, he renamed it “The Mathematical Theory of Communication,” and honestly, I love that for him. Reach for the stars, king.

This paper came out of his work in cryptography during the second world war, and focused on how to encode messages you want to transmit. They’re working so hard at explaining what “noise” is in this context, because this paper is where the concept of “noise” as something that interferes with communication happens.  

In mathematical information theory as begun by Shannon, information is the opposite of noise. If noise is that which obscures the message and increases uncertainty, information is the thing which decreases. A corresponding relative increase in information would require a decrease in noise. 

When you bring it back to this, Galbraith’s argument is almost tautological. If information is that which decreases uncertainty, then uncertain contexts will require more information.

Coming from an LIS background, it’s not so much that this feels wrong to me, it’s undoubtedly correct in its context, but it also feels incomplete. It imparts a certain mathematical smoothness to the world that doesn’t quite do it for me. I think it’s telling that it was developed to think about telephone wires and I’m more interested in humans.

References

Han, Byung-Chul. 2020. The Disappearance of Rituals: A Topology of the Present. Polity Press. Han argues that symbols stand still while information exists by circulating. p. 13