Is Machine Learning v Domain expertise the wrong question?
James Taylor writes:
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.
I think the stronger point, the one that James closes with, is decision management needs machine learning and domain expertise, together.
And we find our choices of approaches justified by the results, “as we see them.” What more could you ask for?