Gear-level models are expensive - often prohibitively expensive. Black-box approaches are usually much cheaper and faster. But black-box approaches rarely generalize - they're subject to Goodhart, need to be rebuilt when conditions change, don't identify unknown unknowns, and are hard to build on top of. Gears-level models, on the other hand, offer permanent, generalizable knowledge which can be applied to many problems in the future, even if conditions shift.