Today I find myself most interested by explainable AI, an area that my past interests and struggles all led me to. Work I've done interpreting results from machine learning, graphing associations and patterns in data, and struggling with the theory underlying machine learning. It leads to a simple conclusion, if a pattern is so complex that we need machine learning, then we need to find ways to communicate what the models learn. Something I think everyone can get on board with and a goal that inspires me to continue researching everyday.