Survivorship Bias

Survivorship bias is a cognitive bias that occurs when someone tries to make a decision based on past successes, while ignoring past failures. It is a specific type of selection bias.

Suppose you're trying to help the military decide how best to armour their planes for future bombing runs. They let you look over the planes that made it back, and you note that some areas get shot heavily, while other areas hardly get shot at all. So, you should increase the armour on the areas that get shot, right?

Wrong! These are the planes that got shot and survived. It stands to reason that on some planes, the areas where you don't see any damage did get shot, and they didn't survive. So those are the areas you reinforce. This was the brilliant deduction of Abraham Wald, a Hungarian-born Jewish statistician who fled Europe to work for the US military during World War II, which also goes to show you that you shouldn't try to kill your best thinkers.

 Other examples

Survivorship bias is also at play when considering the quality of artistic works throughout history. It's easy to look at Shakespeare and think that writers today are much less intelligent than they were in his day, but there were also plenty of writers of Shakespeare's day whose work wasn't as good, and so either didn't survive into the modern era or lacked the influence on Anglophone discourse that Shakespeare achieved.  Used in this way, survivorship bias can lead to nostalgia for an imagined glorious past.

Survivorship bias can obscure the effects of workplace exposure upon health problems. When new employees with prior exposure to, say, asbestos or silica are inappropriately combined with employees without prior exposure, the apparent exposure effect is reduced. Employees exposed at prior jobs become ill sooner than previously unexposed employees making exposure at the current employee appear negligible.