No, I'm not talking about how best to set up the model. I'm saying that complicated neural network models have no track record of yielding reliable insights about social phenomena. They are untested. Any insights they supposedly provide must be verified by a human analyst checking the data to see if it really looks like the model says.
This isn't a new or surprising principle, and it also applies to much simpler models. Any scientist knows that, if you fit a line to data, you better plot the data with the line before you make any big claims about what that line tells you about the world, because the data underlying that fit could look lots of completely different ways with different implications [1]. These authors did the equivalent of fitting the line and telling us all about its formula and the big implications of the formula without ever plotting it with the data.
[1] https://en.m.wikipedia.org/wiki/Anscombe's_quartet