This document discusses face mask detection. It begins by providing context about the scientific consensus shifting to strongly favor masks during the COVID-19 pandemic and data suggesting masks have helped curtail the spread of COVID-19 and other diseases. It then defines face mask detection as using machine learning algorithms to detect whether a person is wearing a mask or not, similar to face detection for security purposes. Finally, it provides examples of using face mask detection systems at offices to remind employees to wear a mask if they are not and an overview of how face detection algorithms work by searching for features like eyes, eyebrows, and nose.