How to test software in the age of machine learning

Testing systems that don't always return the same answers require new approaches. This is especially true when testing systems whose responses adapt to what they have learned from previous transactions. Software testing, in theory, is a fairly straightforward activity. For every input, there should be a defined and known output. We enter values, make selections, or navigate an application and compare the actual result with the expected one.