A question for the author(s), at least one of whom is participating in the discussion (thanks!): Why try to lump together description, prediction, and prescription under the "normal" adjective?
Discussing AI is fraught. My claim: conflating those three under the "normal" label seems likely to backfire and lead to unnecessary confusion. Why not instead keep these separate?
My main objection is this: it locks in a narrative that tries to neatly fuse description, prediction, and prescription. I recoil at this; it feels like an unnecessary coupling. Better to remain fluid and not lock in a narrative. The field is changing so fast, making description by itself very challenging. Predictions should update on new information, including how we frame the problem and our evolving values.
A little bit about my POV in case it gives useful context: I've found the authors (Narayanan and Kapoor) to be quite level-headed and sane w.r.t. AI discussions, unlike many others. I'll mention Gary Marcus as one counterexample; I find it hard to pin Marcus down on the actual form of his arguments or concrete predictions. His pieces often feel like rants without a clear underlying logical backbone (at least in the year or so I've read his work).