Huh, on the balance of things refusing to use such a system would cost a lot of lives.

You can bring in new safety features without having full self-driving. I think the safest option is to have human drivers, with the car always monitoring to avoid any serious accidents. People will still be attentive, since they are in full control, but you avoid just as many accidents as you would if the car was driving itself.

I agree. By establishing an "auto-pilot," you actually eliminate redundancy by putting the driver in a passive position. (No matter how many times you tell the driver to remain attentive)

The machine ought to be an error handler for specific failures of an active human driver (sudden braking of lead vehicle, lane straying, etc). This is the only way to get both machine and human to pay full attention. A person in a co-pilot role will struggle to react quickly enough to handle errors of the machine auto-pilot.

Yeah. This is what I always thought. If we could safe many lives with self-driving cars then we could safe many more with augmented humans.

Only if there weren't alternative systems that were just as good and also managed to avoid this problem. Which seems unlikely.

> Which seems unlikely.

No kidding.

https://www.cdc.gov/niosh/docs/2001-128/pdfs/2001-128.pdf?id...: The two most dangerous things in road work, accounting for half of all of the industry's fatalities, are industrial vehicles working on the site and passenger vehicles passing it.

So, yeah, you're right - there aren't any alternative systems that manage to avoid this problem. Even humans suck at it. And if even humans can't handle construction areas safely, how can you possibly expect computers to be perfect?

* It depends on why the humans are failing. You can design a computer to not speed and not get distracted.

* Hitting a worker is very different from hitting a truck.

* Many of those fatalities are not in clear daylight.

There are. Use two or three alternative AI implementations, which will watch each other. Kind of famous "Predator" algo, but for driving. If one will fail, second will pick up. If one makes mistakes, second will teach it.