With emerging digital tools at the time which made it possible to store & retrieve datasets that I was already interpreting in detail anyway.
Since it was programmable too, ended up using the memory to store the key points from many permutations of well-characterized raw training data, then running that against new datasets to give me advice on how to save time on the greatly reduced manual work remaining.
I like this as a descriptive phrase. ML won't be "intelligence" per se, but it can do repetitive tasks that otherwise required thought.