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1. You need data about self-driving cars in all conditions. This doesn’t mean that “error rate of self-driving vs error rate of human drivers” is the wrong comp
by throwaway894345 5y ago
1. You need data about self-driving cars in all conditions. This doesn’t mean that “error rate of self-driving vs error rate of human drivers” is the wrong comparison.
2. This is irrelevant. What matters is the error frequency and severity. Correlations will increase frequency, but if that frequency and severity is lower than that of human drivers, it’s still a win.
- Barrin92 5y agoit's not irrelevant because the number of cars on the road is so low. If we had tens of millions instead of a few hundred or thousand of these on the road, and you roll out an update that makes the car drive over small kids in green t-shirts then you have a big problem in a very short time. Correlated error is a big problem when combined with tail risk, which you simply cannot see right now due to how limited the use of the technology is.
- throwaway894345 5y agoError rates account for these concerns. Error rate isn’t “the total number of errors”, it’s “errors per mile driven by all self-driving cars” (hence “rate”). Yes, an update might spike the number of errors, but as long as the error rate (accounting for severity) remains lower than for human drivers it’s still a net benefit. And moreover, no one is going to release an update to every car at once.