Have heard your argument on the false positives and unnecessary interventions many times.
It is not a good argument. In fact, it makes no sense. If you get a positive with an uncertainty in its accuracy, at the very least, the test is repeated. But even more, you can use the information from the investigation of the reason for the false positive to improve the tests in the first place. If we weren't humans and the uncertainty of the test is known then at the very very very least you could throw a dice to decide whether you discard or not the test result.
If more information leads to worse decisions it just means that the noise level introduced by the test is just too high. A way to reduce the noise is two amplify the signal, and a way to amplify the signal is to look for more information (other tests, other indirect measurements: i.e., look for B if A was positive, etc.).
It is not a good argument. In fact, it makes no sense. If you get a positive with an uncertainty in its accuracy, at the very least, the test is repeated. But even more, you can use the information from the investigation of the reason for the false positive to improve the tests in the first place. If we weren't humans and the uncertainty of the test is known then at the very very very least you could throw a dice to decide whether you discard or not the test result.
If more information leads to worse decisions it just means that the noise level introduced by the test is just too high. A way to reduce the noise is two amplify the signal, and a way to amplify the signal is to look for more information (other tests, other indirect measurements: i.e., look for B if A was positive, etc.).