Off the Map: Why the Best Use of a Robotaxi Is Finding the Places Nobody Reviews
Popularity signals are useful. So is the inverse. A robotaxi that knows which neighbourhoods the algorithm ignores is the closest thing to having a local friend.
Every listicle about Tokyo covers the same fifteen places. The city has thousands. The gap between the two is where a well-designed recommendation layer actually earns its keep.
Inversion as a feature
The same data that tells you Shibuya is packed can tell you Yanaka is quiet. The same data that surfaces the queue at Ichiran can surface the empty counter at a shokudo two stations away. A robotaxi with an 'unpopular' button is more interesting than one with only a 'popular' one.
This is what the ticketing layer sees
Nobody else has this dataset. The operator that owns the transaction layer owns the discovery product.
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