The "responsible adults" know that chasing perfection gets you nowhere fast. A part of growing up is learning to put up with "good enough".

A car that only fails in a road conditions edge case is good enough for the vast majority of cases. You accept that, and issue a manual override for when that edge case pops up. Then you add that edge case to your training sets. Then the issue never comes up again.

If you think that "flooded roadway" is a case that's handled gracefully by every human driver, and it's the AI that's uniquely prone to failure, I have news for you.

Multiple cities with uncommonly flooded roadways get surges of "water flood engine damage" cars at the repair shops in the wake of extreme weather events. Human drivers underestimate just how flooded a roadway is, try to push through it, and have their car choke, die, and float there, waiting for some good samarithan with a snorkel and a long rope to pull it out. Then someone gets to play the fun game of "is this ICE toast or will it run once you get the water out".

I'm not aware of any self-driving widely available ten years ago. I just took my Model Y over Highway 1 in California without requiring human intervention (other than when I chose to pull the car over).

Obviously when these things can become fully autonomous isn't absolutely clear, and there may always be some discomfort with a probability of failure without a human chain of responsibility.

But, given ten years ago this didn't exist at all for consumers, and it now more reliably does? It doesn't seem insane to think ten years from now, it might address more edge cases, and be safer and more effective.

Why would you look at the general trend and assert jettisoning the effort?

EDIT: It seems some of the tech started rolling out 2016; my mind mentally was thinking 2015. So maybe this started about a decade ago. Though still, the trajectory is a decade of these systems going from limited assists toward greater autonomy with demonstrable progress.

I was (I think the search bar will prove this out) a pretty committed skeptic of driverless cars, but I've come around on them in some use cases. I'm not optimistic about them on highways. But they solve some important problems in regional/local transit.

We're contemplating standing up an EV shuttle service in Oak Park. It will fail. As I understand it, we've piloted non-EV versions of a shuttle service; they failed. The problem is that in small local areas, the staffing for a useful transit service is too expensive; that's because "useful" imposes constraints about responsiveness, coverage, and most of all hours of service, which mean the service won't pencil out with the ridership it'll get.

An autonomous vehicle transit service in our muni would probably work fine; it's a strict grid system with very low speed limits (AVs will, in our area, be strictly better drivers than the median human drivers --- this isn't a statement about human fallibility so much as an observation about scofflawry in our area). And if the product existed, we could afford it, because we wouldn't be paying fully loaded headcount costs for 2+ shifts of drivers at epsilon levels of utilization.

For whatever it's worth, I don't really have "autonomous vehicles" and "LLMs" in the same bucket in my head. I'm bullish on both, but for very different reasons. It usually doesn't occur to me to think of Waymos as "AI", though, obviously, they are.

I will posit something that guides my own thinking about this; robotaxis will never drink and drive. I'll take whatever flavor of mistake they conjure over that. I can deal with stupidity, I cannot (and don't want to) deal with malice.

I actually took a waymo down North Ave (where one got stuck) a few weeks ago and it was very pleasant.

I'm pretty conservative about this stuff but the waymo is genuinely nice to ride in.

This is very much expected while the kinks are worked out. The reason Waymo is rolling out their vehicles in Atlanta in partnership with Uber is precisely for scenarios like this. Standard Uber service provides a backstop for when times when Waymos can't fulfill rides.

Motorcycling used to be one of my biggest hobbies.

I live in NYC now. Drivers here are some combination of utterly selfish and mindlessly distracted. You can't even trust them to stop at red lights. It gives me a huge amount of pause riding here.

"Cars are dangerous, necessary in many places, but often driven by irresponsible people" is a huge problem that needs solving. Waymo seems to have been doing a pretty fantastic job at it.

And even if they couldn't figure out how to route around floods, floods are rare. They're still a net benefit to society.

AI as commonly discussed is just pretty-general intelligence that is very economically valuable. Not AGI outside of the true believers.

And can we discuss AI drivers and AI LLMs in the same paragraph? One is a special application of trying to emulate a very particular human embodiment, with all the sensory challenges. The other is a brain in a vat. Both can fail and flourish independent of each other, or at least I see little overlap.

I’ve just been to Austin where self-driving cars are everywhere but found to my disappointment that they can’t do trips to the airport.

To your point, knowledge work, as a whole is a much larger and complex domain than self-driving.