The GIGO Principle in Machine Learning
And its implications for PMs, designers, salespeople and data scientists
Garbage-In-Garbage-Out is the idea that the output of an algorithm, or any computer function for that matter, is only as good as the quality of the input that it receives.
The principle underlying GIGO is essential when it comes to the real world deployment of algorithms. And with the increasing usage of ML in everything from public-facing APIs to the underlying services that power public-facing applications, awareness and assimilation of this principle is as important now as it has ever been.
