[IgorPartola]

I don’t work in this field so take the grain of salt first.

Quality of additional data matters. How often does a particular sensor give you false positives and false negatives? What do you do when sensor A contradicts sensor B?

“3.6 roentgen, not great, not terrible.”

[giveita]

You can say that about human hearing and balance. What if they conflict with visual? We are good at figuring it out.

[ben_w]

We throw up, an evolved response because that conflict is a symptom of poisonous plants messing with us.

[IgorPartola]

Humans can be confused in a number of ways. So can AI. The difference is that we know pretty well how humans get confused. AI gets confused in novel and interesting ways.

[giveita]

Does removing a sense help in that regard (for car driving?).

Probably comes down to lidar (and Ai) failure modes.

[IgorPartola]

I suspect it helps engineering the system. If you have 30 difference sensors, how do you design a system that accounts for seemingly random combinations of them disagreeing with an observation in real time if a priori you don’t know the weight of their observation in that particular situation? For humans for example you know that in most cases seeing something in a car is more important than smelling something. But what if one of your eyes sees a pedestrian and another sees a shadow of a bird?

Also don’t forget that as a human you can move your head any which way, and also draw on your past experiences driving in that area. “There is always an old man crossing the road at this intersection. There is a school nearby so there might be kids here at 3pm.” That stuff is not as accessible to a LIDAR.