> When a model is developed with more rigor, it can be openly critiqued.
Yes. And the models developed like this haven't solved the problems the current black box models have.
> we have models running across such massive datasets with so many degrees of freedom that we have no feasible way of isolating problems when we see or suspect certain conclusions are amiss. Instead, we throw more data at it or train the model around those edge cases.
There are ways being studied to check for sensitivity to parameters, biases, etc. But in the end, reality is difficult and there's no way of dealing with that, or "getting the right answer" every time
Yes. And the models developed like this haven't solved the problems the current black box models have.
> we have models running across such massive datasets with so many degrees of freedom that we have no feasible way of isolating problems when we see or suspect certain conclusions are amiss. Instead, we throw more data at it or train the model around those edge cases.
There are ways being studied to check for sensitivity to parameters, biases, etc. But in the end, reality is difficult and there's no way of dealing with that, or "getting the right answer" every time