But that's every time a human gets behind the wheel also.
It comes down to trust: do you trust a machine to get it right every time, or a human to get it right every time? I think people will answer differently based on their differing experiences with machines and people.
(... but to my money: when the machine malfunctions, we can crack open its black box, look at its analysis logs, find errors, and update every other clone of the machine to never make that mistake again. Can't do that with humans; for all the lessons we learn about road safety, we are trying inefficiently to imprint them on a new, naive crop of drivers every day).
Machines distribute accidents without bias. Individuals who are otherwise safe drivers could crash viciously if using self driving modes.
Sometimes you can develop intuition for what cars are being driven by bad human drivers and you can avoid them. Machines will appear to be driving just fine until suddenly they’re not, and this can happen very quickly.
Also, if you know a car is being driven by a human rather than a machine, you can use your empathy to anticipate what a human driver is going to do in a situation and prepare for that, where as a machine can behave suddenly and unpredictably, increasing your chances of engaging in an accident.
Keep these self driving vehicles in their own lanes.
Isn't that a good thing? Or are we assuming we have control over the other drivers who are bad drivers and will kill us when they wreck into us?
> Also, if you know a car is being driven by a human rather than a machine, you can use your empathy to anticipate what a human driver is going to do in a situation and prepare for that
People keep claiming this but I think it's a claim without sufficient evidence. I've watched humans go backwards up a one-way street. I've watched humans stop at three stop signs and miss the forth. I've watched humans drive perfectly up until the point they had a coronary. I suspect it's something people like to believe because they get to say "I avoided that idiot swerving on the highway; that kept me safe" and they miss the huge confirmation bias that they're really safe because they didn't get wiped out by the guy who had the heart attack and suddenly drifted into the oncoming traffic lane, leaving no time to react. It's an illusion-of-safety feeling that, ironically, comes from so many human drivers being erratic in non-immediately-dangerous ways, far more often than an automated vehicle is erratic at all.
We don't hear a lot about from the tens of thousands of drivers killed on the road every year failed to use empathy to avoid that crash, because they're dead. So we're missing a huge datapoint to evaluate the "humans can communicate with each other empathetically on the road so they're safer than sharing the road with automata" claim.
For me, it's more nuanced than this. Most mistakes that are made by human drivers around me make intuitive sense to me based on how they are driving. They are often somewhat predictable. In those cases, I can partially mitigate those ahead of time (not always - I've been broadsided where I didn't see the other car until the last moment). The wide adoption of cell phones required a significant update to my mental model, but you can spot things like lane drift, uneven speed, etc. that tell you to give space to someone because they are probably distracted. Both chemically-impaired and sleep-deprived drivers tend to give even more clues to stay clear.
I find predictions informed by observation much more difficult with automated driving systems. In many cases, such cars will appear to be driving perfectly, right up until a severe mistake is made. Instead of having observable clues, it requires an understanding of what sensor suite and what version of software is in which vehicle in order to understand the tendencies of that vehicle. Something we can't possibly keep up with, especially given that the developers of the machine learning models being deployed can't deeply characterize each deployment's failure modes.
Given all that, I feel more able to defend myself against human mistakes than automated mistakes.
