I’ve been increasingly seeing people being prisoners of the moment. Whatever is happening now is the truth.
A great example of this is the NBA playoffs right now. After 3 games of the Eastern Conference files, people were ready to crown Jimmy Butler as one of the best 5 players in the league. Now through game 6, Jimmy is trash. In reality, Jimmy Butler is a great player with some limitations. With bayesian thinking, you can avoid some of this impulsive thinking.
Everyone is so dramatic about the moment. One day something is the greatest, the next day it is the worst. Bayesian thinking is updating beliefs based on observations to improve predictions.
Let’s dive into an example. Imagine you have a box with different types of fruits. You want to know the probability of picking an apple.
- Initial guess: Equal chance for each fruit (33%).
- Picked an apple: Increase probability of picking apples.
- Update belief: Adjust probabilities based on new information.
- Repeat: Keep updating belief after each pick.
As you can see, Bayesian thinking is a simple idea, but if applied properly it can help reduce rash thoughts.
The Bad in Bayes
Like anything else, Bayesian thinking has its downsides too. Firstly, the mathematical ideas behind Bayesian thinking can be a little too complex for some people. Furthermore, while Bayesian thinking is a mathematical concept, it’s also a subjective approach in terms of how much weight one assigns to new information. Lastly, if you underestimate the value of new information, it’s easy to attribute any issues to small sample sizes. I’m pro Bayesian thinking, but I wanted to provide both sides.
Wrap It Up
I’m not arguing that we should discount new information. I think we just need to be careful in how we weigh this new information. The next time you find yourself caught in this impulsive loop, stop and think about the significance of the new information.