Problem is, you are not alone on the road. And if somebody else does something really stupid, you can die as a consequence, without any chance to avoid it.
We are definitely not there yet, but I think of myself as a decent driver, and some assistant tools on high-end models are way better (just faster, probably) than me predicting stuff. For the first year this summer, I've driven a car that was quicker than I in an emergency break situation: while I started breaking, it depressed the pedal, and I was quite surprised, 'cause the car in front of me didn't begin breaking yet.
There's also the fact though, that if you're elderly you can't really avoid being a worse driver. I know particularly in rural areas where there's no public transportation, a lot of elderly people would accept an error rate higher than what their own driving used to be. It seems pretty tough for the rest of us to deny them access to a technology like that while it's in the interstitial stage.
If errors in any subsystem surface out to the car, well then okay. But it's not unlikely that the overall system would deal with an error in the image classifier.
Pay wall so I can’t read the article. But can someone comment on what 0.001% error means in real world scenarios?
To keep the maths easy, that’s 18 wrong frames/10min. So roughly 2/3 of a second.
If these images are spread out, maybe it’s fine. If it’s failing on certain types of images, then those images could be grouped and 2/3rds of a second is more than enough time for a serious failure.
Don't forget - the error might be reproduce-able. As in, it will error rarely, but at that one obstacle, with that one light config, it will error repeatedly and constantly.
AI related car accidents and deaths will have special places and dates, were they will repeat annually.
in my 20s you would need to bring the reckless back in.