Garbage in, garbage out
In computer science, garbage in, garbage out (GIGO) is the concept that flawed, or nonsense input data produces nonsense output or "garbage". In the UK the term sometimes used is rubbish in, rubbish out (RIRO).
It was popular in the early days of computing, but applies even more today, when powerful computers can produce large amounts of erroneous data or information in a short time. The first use of the phrase has been dated to a November 10, 1957, syndicated newspaper article about US Army mathematicians and their work with early computers, in which an Army Specialist named William D. Mellin explained that computers cannot think for themselves, and that "sloppily programmed" inputs inevitably lead to incorrect outputs. The underlying principle was noted by the inventor of the first programmable computing device design:
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.
More recently, the Marine Accident Investigation Branch comes to a similar conclusion:
A loading computer is an effective and useful tool for the safe running of a ship. However, its output can only be as accurate as the information entered into it.
Decision-makers increasingly face computer-generated information and analyses that could be collected and analyzed in no other way. Precisely for that reason, going behind that output is out of the question, even if one has good cause to be suspicious. In short, the computer analysis becomes a credible references point although based on poor data.
The term can also be used as an explanation for the poor quality of a digitized audio or video file. Although digitizing can be the first step in cleaning up a signal, it does not, by itself, improve the quality. Defects in the original analog signal will be faithfully recorded, but might be identified and removed by a subsequent step by digital signal processing.
GIGO is commonly used to describe failures in human decision-making due to faulty, incomplete, or imprecise data. This sort of issue predates the computer age, but the term can still be applied.
Incorrect data can still permit statistical analysis. Although in statistics incorrect or inaccurate data can hamper proper analysis, it can still be handled. The classic a broken clock is right twice a day can be defined as less than fully correct by noting that certain time settings are only correct once per day at least once per year. By contrast, information that relays a count, even if the count is incorrect, the data's precision is accurate.
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