From the archive · July 2, 2026
Order costs energy
Why does everything drift toward disorder unless something pushes back?
01 · Word
Entropy
noun
A measure of how disordered a system is: left alone it only ever rises, which is why heat spreads out, batteries run down, and any kind of order has to be paid for
Examples
A hot coffee cools to room temperature and never the reverse: entropy picks the direction.
Without maintenance the codebase's entropy climbed: every shortcut made the next change harder.
Origin
Coined in 1865 by the German physicist Rudolf Clausius, from the Greek tropē, “transformation,” deliberately built to sound like “energy.” Clausius wanted the two ideas paired: energy is what a system has, entropy is what it can no longer usefully do. In 1948 the mathematician Claude Shannon borrowed the word for messages, where a signal's entropy measures how much uncertainty it clears up.
02 · Idea
Entropy comes for the signal
A signal crossing a wire degrades like heat dissipating: noise creeps in, order leaks out. Telephone engineers fought the drift physically, spacing amplifying repeaters along the line to rebuild the signal before it drowned; every repeater is energy spent resisting entropy. Claude Shannon reframed the fight: measure the information in a message as its uncertainty (its entropy) and noise becomes a budget rather than a fate. His channel theorem proved that below a channel's capacity, error-correcting codes can make transmission almost perfectly reliable.
Shannon published “A Mathematical Theory of Communication” in the Bell System Technical Journal in 1948, drawing on decades of Bell's practical war with noisy long-distance lines. The paper defined information mathematically, named the “bit” as its unit, and founded information theory, the discipline underneath every phone call, file, and stream you use.
Noise does not forbid reliable communication. It only sets a speed limit, and codes can operate right up against it.
Order in a message, like order anywhere, is not free: it is engineered, paid for in redundancy and energy.
Limits and context
Shannon's entropy measures uncertainty, not meaning: a page of noise carries maximal Shannon information and says nothing. And the theorem promises good codes exist without handing them over; building codes that approach capacity took the field another half century.
The two entropies rhyme deliberately: both count disorder, and both charge for resisting it. Your phone spends real energy computing error corrections and boosting signal, all to hold a conversation together against the universal drift.
03 · Moment
The paper that counted information
Bell Telephone Laboratories, New Jersey; published in the Bell System Technical Journal, July and October 1948
In two installments of the Bell System Technical Journal in 1948, Claude Shannon, a 32-year-old mathematician at Bell Labs, published “A Mathematical Theory of Communication.” The paper defined the information in a source as its entropy, adopted the binary digit or “bit” (a name he credited to his colleague John Tukey) as its unit, and proved the theorems governing how much information any channel can carry through noise.
- Bell Labs
- 1948
- New unit
- The bit
- New field
- Information theory
The caveat
A famous anecdote holds that John von Neumann told Shannon to call his measure “entropy” because “no one knows what entropy really is, so in a debate you will always have the advantage.” The story is secondhand and Shannon's own accounts varied. The thermodynamic analogy in the paper stands on the mathematics either way.
Bell had fought the problem with hardware for decades, stringing the continent with repeaters to keep voices alive across the miles. The paper solved it by showing precisely what any communication system could and could not do. Nearly everything digital descends from it: compression, error correction, modems, CDs, deep-space links. Engineers rank it among the century's most consequential papers, the founding document of the information age.
Shannon took the physicists' word deliberately: his formula for information has the same form as Boltzmann's for thermodynamic entropy. Disorder in a gas and uncertainty in a message turned out to obey the same arithmetic.