I wasn't as convinced by the mathiness and speculation/explanation arguments as the others. Sure there may be a few examples of obfuscation via math, but most papers, in my view, don't do that. Adding the couple of math equations doesn't really hurt (it doesn't add anything either). I also interpret explanations in most deep learning papers as speculation, since short of rigorous experimentation or theory (not found in DL papers), there's no way to prove explanation is correct.

Comparatively, the other problems are orders of magnitude more important and troubling. Experiments which mislead people into thinking the technique matters more than the compute (like in OpenAI's Glow paper) and intentional anthropomorphization to get media coverage (OpenAI Dota bot's "cooperation and teamwork") are much more serious and could have used more attention in your paper. I think these are more serious because the former can fool even experts in the field, and the latter seriously misinforms the lay public on the topic of AI.

I'm glad you started this important conversation.