I asked myself the same question, and did read some papers, but could not find a recent comprehensive survey on automatic fuzzy rule generation (I admit I gave up after ~15 minutes).

What I found did not convince me that it would fare better than an off-the-shelf (somewhat) non-interpretable statistical supervised learning algorithm.

It can be a nice way of bootstrapping the rule writing process, or to go the other way : to discover and analyze new expert knowledge by looking at the rules.

But performance-wise, I would go the machine learning way anytime.

Also, Inverse Reinforcement Learning seems to be very promising : one guesses the reward function by observing the expert acting.