Why 95% Accuracy Can Still Block Automation at Scale (Full Transcript)
[00:00:00] Speaker 1: I think of self-driving cars, like 95% accuracy of a self-driving car is actually like amazing, but it probably won't get legalized because that 5% error rate, even 1% error rate is just too big. If you're going to deploy these things just out on the street in New York city. Similarly, if you're going to automate a phone operator, you're the error tolerance you have is probably very low. And the cost to deploy something like that at scale is going to be very high. So you're very cost conscious. And so we're just thinking about all these dynamics all the time when we think about what to build for.
- In safety-critical domains, small error rates can still be unacceptable.
- Regulatory approval may hinge on extremely low failure probabilities, not just high average accuracy.
- Dense, real-world environments (e.g., NYC streets) amplify the consequences of errors.
- Customer-facing automation like phone operators also demands low error tolerance due to user impact.
- Scaling automation systems can be expensive, making cost-benefit trade-offs central to product decisions.