It is often said that we have two (or more) decision making centers in the human body. Mainly, one is in the head and one is in the stomach, in the gut. There is a good case to be made that many of our decisions happen instinctively, intuitively, subconsciously, in advance and under the hood, and our brains come up with logical justifications after the fact and tell us what the decision was.<p>Given any model, a researcher usually doesn't just run it once and accept the output (unless they happen to agree with the output of the first run). If they get an "unexpected" result, they will either "reassess", meaning that they genuinely have learned something new, or "develop the model", re-tweaking the model structure and parameters until they get an "expected" output.<p>Most of the value in these data-driven exercises doesn't seem to be deciding between A and B. Any executive can do that (and ask the data scientists to justify the decisions after the fact, as others have said). It's in finding C, which you never even considered and takes you off in a new direction. For that to happen, the human mind and the organization behind it needs to be flexible. And this generation of generative AI certainly seems capable of providing or helping to reach novel insights. Or is it? How can we go off of the beaten track using a tool which is built on top of following the track as much as possible?<p>I like what you said down lower in your comments about looking at data, "Update your gut with an updated map of the state". That's a great description and I think it's exactly what you want from whatever data tool, AI or whatever.