When the inputs are wrong, the outputs are wronger.
Here's a breakdown of why:
First Law: If an algorithmic thought process is based on incomplete or inaccurate data, it will produce incorrect results.
Second Law: If an algorithmic thought process is based on outdated or irrelevant data, it will produce results that are even worse.
Third Law: If an algorithmic thought process is based on the wrong assumptions, it will produce results that are completely, utterly, and fantastically wrong.
And so on.