Now, everything is connected, but this is not primarily about persistent research misconceptions such as statistical significance. Instead it is about (inherently) interpretable ML versus (misleading with some nonzero frequency) explanatory ML that I previously blogged on just over a year ago. That was when I first become aware of work by Cynthia Rudin (Duke) …