How to prevent a neural network from choosing the 'easiest' solution
This is fairly common with scenarios like predicting fraud when overall cases of fraud are uncommon. The model will frequently just say "no fraud!" and be right a large percent of the time. You need to assign a penalty, cost, or weight so that output 1 isn't so easy. 

This article describes that further in a lot of detail:

https://blog.fineighbor.com/tensorflow-dealing-with-imbalanced-data-eb0108b10701