While I do agree that false positive and false negative are better names, they do have one shortcoming in comparison: Classical statistics suffers from the inf

While I do agree that false positive and false negative are better names, they do have one shortcoming in comparison: Classical statistics suffers from the inference problem, where instead of "tested positive for presence" you have to say "tested negative for absence". So a type I error is a false negative as much as it is false positive, which can get confusing.