False positives and false negatives
There are two types of error that can occur with such things as laboratory tests, trials and predictions. A false positive is when there is no disease (or other condition) but the results come back as positive. For example, a positive test for AIDS or cancer, when the person was disease free, would be a false positive. Sometimes, when a disease is very rare, and/or when a test has a high rate of error, there may be more false positives than actual positives. A false negative is when there actually is a disease (or other condition) but the results come back as negative. A finding of no cancer, when there actually was cancer, would be a false negative. Both types of errors can be devastating; some people have been devastated when they were told that they had a disease when they actually did not, others have not gotten the timely treatment that they needed because their disease was not diagnosed.
These errors have important policy implications. In criminal trials, some would prefer to release 100 guilty people rather than convict one innocent person, minimizing the number of false positives. Others would rather send a few innocent people to jail, or even execution, in order to maximize the number of criminals who are convicted (minimal false negatives). Environmental activists want to minimize the number of false negatives, while industry supporters want to minimize the number of false positives. In debates, proponents often exaggerate the type of error that supports their case, while downplaying or ignoring the opposite type. For example, an opponent of the death penalty would emphasise the people who were executed or sentenced to death and later found to be innocent, while a death penalty proponent would talk about criminals who were released and then went on to commit more crimes.
These false results cannot be completely eliminated, but they can be reduced. People can demand a second opinion of their medical condition. They can work toward improving the judicial system, and insist that decisions are based on the best scientific information.
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Written by Jim Norton
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