Statistically speaking, we are generally agnostic to which is a bigger problem,

Question

Statistically speaking, we are generally agnostic to which is a bigger problem, type I (false positive) errors or type II (false negative) errors. However, in certain circumstances it may be important to try and put more emphasis on avoiding one or the other. Can you think of an example of where you may want to try harder to avoid one type or another? Can you think of a policy; political, economic, social, or otherwise, that pushes people toward avoiding one type or another? What are the repercussions of such policies?

Explanation / Answer

solution=

In medicine, false negatives are dangerous. A person who receives a lab report saying "It isn't cancer" is now in an extremely dangerous position.
A false positive is emotionally hard, but the mistake is soon cleared up, and meanwhile, no harm has been done.

But not all lab reports are better as "false positive" than as "false negative."
For example, a false positive pregnancy test is devastating -- far more so than a false negative.
The mistake of a false negative will soon be corrected, but a false positive can make people do all kinds of things to address the "pregnancy that isn't."
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In safety testing (say, for the structural integrity of a component of a space rocket), a "false positive for 'damage is present' " is far better than a "false negative stating 'no damage.' "

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