> I would 100% take a machine that performs 30% better than a human or helps a human perform 30% better every time because it means fewer humans die on the road.
It's surprisingly hard to establish those parameters though, since (i) the more meaningful indicators of good performance (driver error fatalities) happen only every million or so miles, even less frequently once you've narrowed your pool down to errors made by sober drivers that weren't racing or attempting to driver in conditions unsuited to electronic assistance, so that's a lot of real world road use required to establish statistically significant evidence a machine is a 30% or so safe than a human driver (ii) complex software doesn't improve monotonically, so really you need that amount of testing per update to be confident that the next minor version of something "30% safer" hasn't introduced regression bugs which mean that it is now a bit worse than the average driver and (iii) performance in different road conditions is likely highly variable such that it might be both 30% better overall and 30x as likely to cause an accident if not disengaged in that particular circumstance.
To make a valid assessment of the overall safety impact, you'd also have to factor in that (iv) the worst drivers who skew the stats are the generally the ones least likely to buy it and (v) if it's fully autonomous driving, road use would increase substantially and whilst that may have other benefits the likely outcome from substantial increase in miles driven using tech that's only marginally better than a human is more humans dying on the road
And yet the total mileage driven by a huge variety of autonomous systems over research programmes dating back a decade is of the order of 20-30 million. This disparity obviously supports my point about the difficulty of establishing statistically significant evidence that a particular software update on a particular platform is less lethal than the human driver [in a given set of circumstances] based on events which are very rare on a per mile basis, particularly if the baseline performance gap isn't that large.
The fact that overall road use is so high that a sufficiently bad regression bug in sufficiently widely-deployed software could rack up a massive body count within hours obviously doesn't make the case for introducing something believed to only be a marginal improvement any stronger.
It's surprisingly hard to establish those parameters though, since (i) the more meaningful indicators of good performance (driver error fatalities) happen only every million or so miles, even less frequently once you've narrowed your pool down to errors made by sober drivers that weren't racing or attempting to driver in conditions unsuited to electronic assistance, so that's a lot of real world road use required to establish statistically significant evidence a machine is a 30% or so safe than a human driver (ii) complex software doesn't improve monotonically, so really you need that amount of testing per update to be confident that the next minor version of something "30% safer" hasn't introduced regression bugs which mean that it is now a bit worse than the average driver and (iii) performance in different road conditions is likely highly variable such that it might be both 30% better overall and 30x as likely to cause an accident if not disengaged in that particular circumstance.
To make a valid assessment of the overall safety impact, you'd also have to factor in that (iv) the worst drivers who skew the stats are the generally the ones least likely to buy it and (v) if it's fully autonomous driving, road use would increase substantially and whilst that may have other benefits the likely outcome from substantial increase in miles driven using tech that's only marginally better than a human is more humans dying on the road