> it might be great to have a human readable and tweakable solution (assuming you have the resources) but for something like recognising handwritten digits from images, not so much.

Agree, but with black-box I meant not something that is opaque to my grand-mother but partially opaque to engineers that implement MLP machine learning applications and the tech-lead that takes the decisions. The thing is that even research people (or maybe specially them) tend to positively bias things they do not completely understand (so I think, maybe its just me ;)). That is what I meant with black-box delusion. As you say only time will tell.

Regarding DBNs, again, the case of ASR uses DNNs which is to say big-fat MLPs. The model is handled as a DBN only for pre-training, and layer-wise pre-training does a similar job anyway.