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Scholars of decision-making offer clear advice to resolve this tension: focus on the process, not on the outcome of a single case.
The different errors add up; they do not cancel out.
More Simplicity: Robust and Beautiful Robyn Dawes was another member of the Eugene, Oregon, team of stars that studied judgment in the 1960s and 1970s. In 1974, Dawes achieved a breakthrough in the simplification of prediction tasks. His idea was surprising, almost heretical: instead of using multiple regression to determine the precise weight of each predictor, he proposed giving all the predictors equal weights. Dawes labeled the equal-weight formula an improper linear model. His surprising discovery was that these equal-weight models are about as accurate as “proper” regression models, and
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Simple rules that are merely sensible typically do better than human judgment.
noise, which is variability in judgments that should be identical. There
Definition of noise is the Delta between various decisions that should be identical.
Overconfidence is one of the best-documented cognitive biases. In particular, judgments of one’s ability to make precise predictions, even from limited information, are notoriously overconfident.
Pundits blessed with clear theories about how the world works were the most confident and the least accurate.
Tetlock’s findings suggest that detailed long-term predictions about specific events are simply impossible. The world is a messy place, where minor events can have large consequences. For example, consider the fact that at the instant of conception, there was an even chance that every significant figure in history (and also the insignificant ones) would be born with a different gender.
Unforeseeable events are bound to occur, and the consequences of these unforeseeable events are also unforeseeable. As a result, objective ignorance accumulates s...
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When a finding is described as “significant,” we should not conclude that the effect it describes is a strong one. It simply means that the finding is unlikely to be the product of chance alone. With a sufficiently large sample, a correlation can be at once very “significant” and too small to be worth discussing.
A few minutes of research would reveal that estimates of CEO turnover in US companies hover around 15% annually. This statistic suggests that the average incoming CEO has a roughly 72% probability of still being around after two years.
Good definition of noise
