Noise

How to measure the noise in our daily decisions?

Which is better - expert judgment or mechanical prediction using very simple models/rules? Surprisingly, the model of you beats you! Even a simple regression model based on your past decisions!

How to make rules/models even less noisy? How can rules/models become more biased sometimes?

Why don’t people always use models (if they are so good) and still rely on their bad judgment?

When do we not need models?

Interesting to learn how your mind makes judgments. Two types of judgments: predictive and evaluative. How to measure errors from bias and noise. How to measure the cost of noise. And how to deal with catastrophic consequences.

Drilling down the noise to three components: system noise, level noise, and pattern noise. How to measure (and compensate) the noises. Occasional noise as a part of pattern noise. How to compensate occasional noise: wisdom-of-crowds effect, crowd-within-the-one effect, second answer effect, and dialectical bootstrapping tool.

How the group work influences the noise. Informational cascade and social pressure cascade. How to deal with them. The effect of group polarization.

Do you realize how seriously your organization is affected by bad decisions? There are two types of errors in human judgments: Bias and Noise. Bias is a very widely recognized problem, and you definitely heard about it. Noise is not so widely recognized. Yet, it affects MANY decisions in ALL the industries.

There is a huge Noise in government decisions. There is a huge Noise in commercial companies.

Noise can be made visible and can be reduced. It is harder to measure the noise in unique singular decisions, but it is still there and it still can be reduced.