Is Machine Learning v Domain Expertise the wrong question?

KDNuggets had an interesting poll this week in which readers expressed themselves as Skeptical of Machine Learning replacing Domain Expertise. This struck me not because I disagree but because I think it is in some ways the wrong question:

Any given decision is made based on a combination of information, know-how and pre-cursor decisions.
The know-how can be based on policy, regulation, expertise, best practices or analytic insight (such as machine learning).
Some decisions are heavily influenced by policy and regulation (deciding if a claim is complete and valid for instance) while others are more heavily influenced by the kind of machine learning insight common in analytics (deciding if the claim is fraudulent might be largely driven by a Neural Network that determines how “normal” the claim seems to be).
Some decisions are driven primarily by the results of pre-cursor or dependent decisions.
All require access to some set of information.

To ask if one kind of know-how will replace another seems to me, then, to be the wrong question. Better to ask if the balance between manually documented know-how and machine learning will change and, if so, where and why? We could also ask if there are really any decisions where machine learning or analytics cannot help at all (probably but only because the decision-makers don’t have access to data that would help or because they are obliged to follow a precise set of regulations/policies). Or we could ask if there were any decisions that only required know-how that can be derived automatically using machine-learning (probably not, most business decisions involved some policy and regulations that are fixed even if we can replace experience with machine learning).

Too many analytic professionals think that only the data speaks and that business rules are, as someone once said to me, “for people too stupid to analyze their data”. Similarly too many IT professionals think that everything can be reduced to business rules or to code using explicit analysis. The reality for most decisions is somewhere in between.

Not machine learning or domain expertise but machine learning AND domain expertise. Decision Management in other words.