I believe the argument is that the probability of misclassifying an arbitrary segment of speech as the very particular answer “yes” is sufficiently low (with reasonably trained, current models) that we may ignore it under practical circumstances.
I find the non-zero probability of misclassifying in a little disquieting, but I suppose one way of looking at it is that this will probably increase the expected value of lives saved; the very probable case (calls are correctly filtered and a smaller proportion is passed through, allowing operators to respond to more new emergencies) may save a lot of lives, whereas the very improbable case (something that is not “yes” is misclassified as such) may endanger a few.
One thing that would worry me about just looking at expected values is the possibility of bias against a particular group of people or emergency type, but to me that seems unlikely in this case.
Edit: it also just occurred to me that if you are woefully unfortunate, you can probably just call again if you accept the assumption that there is a high probability the answer is yes given the model classified it as such. It might be more or less random chance?
None of that applies if a caller just can’t get through at all because the bot mistook “no” for “yes”
I believe the argument is that the probability of misclassifying an arbitrary segment of speech as the very particular answer “yes” is sufficiently low (with reasonably trained, current models) that we may ignore it under practical circumstances.
I find the non-zero probability of misclassifying in a little disquieting, but I suppose one way of looking at it is that this will probably increase the expected value of lives saved; the very probable case (calls are correctly filtered and a smaller proportion is passed through, allowing operators to respond to more new emergencies) may save a lot of lives, whereas the very improbable case (something that is not “yes” is misclassified as such) may endanger a few.
One thing that would worry me about just looking at expected values is the possibility of bias against a particular group of people or emergency type, but to me that seems unlikely in this case.
Edit: it also just occurred to me that if you are woefully unfortunate, you can probably just call again if you accept the assumption that there is a high probability the answer is yes given the model classified it as such. It might be more or less random chance?