Edited and curated by @philhagspiel
The meaningful is often buried in the meaningless.
“The signal is the truth. The noise is what distracts us from the truth.”
— Nate Silver
In a world flooded with information, separating the useful from the useless becomes a superpower.
Looking at business metrics, we want to filter actual customer behavior trends (signal) from the inevitable random variation around it (noise).
Consuming the news, we want to dissect true and meaningful world happenings (signal) from lies, exaggerated reports and misinterpretations of random events (noise).
When engaging with new ideas, we want to follow the ones that truly explain an aspect of the world (signal) and ignore the ones that are plausible but wrong (noise).
Whether in the physics of wave frequencies (tuning into a radio), in statistics (analyzing trends over time) or in everyday information media (understanding world events) — we almost always have to filter the meaningful information from the random variation and fluctuation around that information.
Signal vs. Noise is a term often used in science and engineering but also widely applicable to our lives at large. It describes how that which we are actually interested in can be buried in unwanted and often misleading data.
Before jumping to conclusions, asking yourself something like “is this a signal or just noise?”, or “where is the signal in all of this noise?” can focus your attention on what really matters as well as help you not fall prey to misleading information.
“Censorship no longer works by hiding information from you; censorship works by flooding you with immense amounts of misinformation, of irrelevant information.”
— Yuval N. Harari
A few further resources you might like if you find the above idea interesting:
- 📚 Nate Silver’s The Signal And The Noise
- 📚 Nassim Taleb’s Fooled By Randomness
- 📚 Hans Rosling’s Factfulness
- 🎥 RSA (YouTube): The Signal and the Noise — Nate Silver
- 📱 @visualizevalue on Instagram
- 📱 @naval Twitter
- 📝 Conceptually.org: Signal and Noise
- 📝 MindVault: Regression To The Mean
- 📝 MindVault: Correlation Isn’t Causation
- 📝 MindVault: The Plausibility Bias