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GIGO, or " garbage in, garbage out," is a fundamental principle in computer science and data processing that states the quality of a system's output is determined by the quality of its input. If flawed, inaccurate, or incomplete data is entered into a system, the results or output will also be flawed, regardless of how well-designed the program or algorithm is.

How GIGO applies to computing

Data quality: The term serves as a warning that computers do not possess independent reasoning. They process data based on the instructions given. If the initial data is bad, the computer cannot produce a reliable result.

Algorithms: A perfect algorithm will still produce garbage output if the input data is of poor quality. This is particularly relevant today in fields like data science, artificial intelligence, and machine learning, where vast datasets are used to train models.

Incorrect data types: If a program is fed data in an unexpected format, such as a text editor trying to interpret a binary file, the output will be unintelligible or "garbage".

Automation errors: Problems like faulty sensors or data entry errors can introduce flawed information into automated systems, leading to bad decisions. For example, relying on outdated demographic data for a market analysis will likely lead to misguided business conclusions.