Information vs. Knowledge: Understanding Deming's Theory
Telling information apart from knowledge through W. Edwards Deming's Theory of Knowledge — prediction, theory, and the rooster who thought he raised the sun.
Today, I want to share some insights from a YouTube video I recently watched to help clearly distinguish between Information and Knowledge. The video explains this concept beautifully using W. Edwards Deming's "Theory of Knowledge."
Information
Every day, we receive a massive amount of information to help us make decisions. Information is essentially data with context — the who, what, when, where, and why.
We constantly gather this information through daily conversations, meetings, and planning sessions. However, as the video points out, while information can sometimes help us build knowledge, it does not always guarantee it.
Knowledge
Understanding and accepting the relationship between cause and effect can be defined as a Theory. We can separate Information and Knowledge using two main distinctions:
- Prediction: Knowledge allows us to predict the future. For example, knowing that if you drop an object from your hand, it will fall to the ground — that is knowledge.
- Foundation in Theory: Knowledge is built entirely upon theory. Taking the previous example, the "effect" of the object falling is caused by the "theory" of Earth's gravity.
Because of this dependency, if the underlying theory is proven wrong, the entire body of knowledge must change along with it.
To illustrate this, let's look at Edwards Deming's famous example of the rooster:
A rooster believes that his morning crowing causes the sun to rise. Based on this established "knowledge," he faithfully crows every single morning. One day, however, he fails to crow — yet the sun rises anyway. At that exact moment, his foundational theory is shattered, and he gains a new understanding: he cannot control the sunrise.
System
In any system, the ability to predict the future is paramount. Therefore, just like knowledge, systems must also be built upon theories.
According to Deming, the most critical factors for the continuous improvement of knowledge and systems are the "unknowns" and the "unknowables." By definition, we cannot obtain any concrete information or data for these variables.
Because of this, while an existing system can continue to function smoothly as long as its underlying theory holds true, we must continuously evaluate and question our theories to ensure they remain valid.
— Ponya