But in this case, the outcome of interest is quite rare. Despite the high numbers of people dying in car related accidents each year, the number of accidents that occur for the total number of miles driven by US drivers is very small. So in order to draw inference about whether autonomous vehicles improve on that rate, you need a huge amount of miles driven by autonomous vehicles. None of the companies have really approached that level of testing, to say nothing of the fact that most of the miles driven so far aren't on similar, real world conditions that US drivers face, making any statistical conclusions even more difficult.
I don't believe the Uber accident applies, because it was caused by human error, not the driving automation. The emergency braking was deliberately disabled (it would have prevented the accident), the detection system was not programmed to inform the driver, and the driver was not paying attention. If the Uber accident is disregarded, then we're at 0 fatalities, or infinitely perfect automated driving. Which is, of course, BS. But it's as rational as the argument others are making.
Given the inadequate data set, I'm relying on inference, not experience.