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There is the old quote that we've all seen: "On two occasions I have been asked, 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right a

by jerf 5y ago

There is the old quote that we've all seen: "On two occasions I have been asked, 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question." - Charles Babbage I will say, I have some good news for the late great Charles Babbage. For the most part, people now do indeed understand that if you put small amounts of wrong figures into a machine, the wrong answers will come out. If nothing else, pocket calculators and math class have given them the direct experience of this. However, it seems that people still expect that if you put gigabytes or petabytes worth of wrong figures into a machine that somehow the right answer will pop out. Ah well. The road never ends, you know.

d1sxeyes 5y ago
> However, it seems that people still expect that if you put gigabytes or petabytes worth of wrong figures into a machine that somehow the right answer will pop out. The interesting fact is that if you put in lots of correct figures, and only one, slightly wrong figure, then the answer may be correct to an acceptable degree. For example, take 100 values, all exactly one, and find the mean. You'll find 1. If you take 99 values of exactly one and one value of two, the mean of your sample will be 1.01, which is close enough to still be useful. In some interpretations, it may even be rounded to 1, meaning that in some circumstances, incorrect figures can indeed sometimes lead to correct answers. Or if you're trying to find out what adding 1 and 4 gives you, but accidentally you add 2 and 3, you get the correct answer despite incorrect inputs. I think people are assuming that if you put gigabytes or petabytes worth of data into a machine, the number of 'wrong figures' will be lost as noise.
- paulmd 5y ago
  the problem is that for medical coding, this translates to "a small number of procedures will be coded wrong", and that's not a meaningfully better situation than "a small number of procedures can't be coded", and in fact is probably worse. So you need a reasonably high confidence threshold, and really in most cases you probably want to have a human manually review the problem (or questionable) cases.

by jerf 5y ago

d1sxeyes 5y ago

> However, it seems that people still expect that if you put gigabytes or petabytes worth of wrong figures into a machine that somehow the right answer will pop out. The interesting fact is that if you put in lots of correct figures, and only one, slightly wrong figure, then the answer may be correct to an acceptable degree. For example, take 100 values, all exactly one, and find the mean. You'll find 1. If you take 99 values of exactly one and one value of two, the mean of your sample will be 1.01, which is close enough to still be useful. In some interpretations, it may even be rounded to 1, meaning that in some circumstances, incorrect figures can indeed sometimes lead to correct answers. Or if you're trying to find out what adding 1 and 4 gives you, but accidentally you add 2 and 3, you get the correct answer despite incorrect inputs. I think people are assuming that if you put gigabytes or petabytes worth of data into a machine, the number of 'wrong figures' will be lost as noise.

paulmd 5y ago
the problem is that for medical coding, this translates to "a small number of procedures will be coded wrong", and that's not a meaningfully better situation than "a small number of procedures can't be coded", and in fact is probably worse. So you need a reasonably high confidence threshold, and really in most cases you probably want to have a human manually review the problem (or questionable) cases.