#verbalization

Thanks for the poll request, anonymous! Keep 'em coming, folks.

Aside from general system design failure apparent in this report, it is striking that the system spent long seconds trying to decide what exactly is sees in front (whether that be a pedestrian, bike, vehicle or whatever else) rather than making the only logical decision in these circumstances, which was to make sure not to hit it.

There are several reasons for it: first, people will often verbalize their decisions post factum. So a human will typically say: "I saw a cyclist therefore I veered to the left to avoid him". Huge amount of psychophysical literature will suggest a quite different explanation: a human saw something which was very quickly interpreted as a obstacle by fast perceptual loops of his nervous systems and he performed a rapid action to avoid it, long seconds later realizing what happened and providing a verbal explanation".

Because most of these things are not easily verbalizable, they are hard to measure, and consequently we don't optimize our machine learning systems on these aspects at all.