That data sets between a hundred or so Waymo cars and millions of human cars isn't even comparable.

Really? This whole thread is littered with people drawing statistical inferences from a single Uber accident.

You are actually the one doing bad math. In statistics, you start with a null hypothesis, which is represented by the status quo (in this case, autonomous vehicles aren't any better than humans in terms of crashing), and use the data to try and prove it wrong.

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'm not doing math at all, except to say that all the people saying "fatalities per mile" and pointing to the Uber accident are misusing math.

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.

If the internet proves anything, it's that a lot of people will say whatever it is they think totally for free.