I don’t think there’s any net positive that would account for not answering an emergency call at all.
Exactly. That’s what they want to solve.
TL;DR: Even when callers reach the triage bot, they can still reach a human much faster than without the triage bot.
Comparing again:
WITHOUT the triage tech:
NOBODY (or nothing) answers the call for a long while, because the caller is stuck in a very long queue of calls waiting to tell them about the same emergency
WITH the triage tech:
AI bot answers the call instantly and probably knows how to help because the call is probably about the same emergency that 95% of the other calls are about
so 95% less spam for the human operators to get through
If the call is NOT about the same thing as the others, the caller can simply say that (i.e., “no”), and they reach a human within, say, 5-10 seconds because the operators aren’t busy trying to get through the spam calls
They chose this tech because it has already proven to be a net positive on their non-emergency line.
Do you honestly think that nobody has thought about that and solved that problem already? Even with all the engineers involved, and after all the real-world testing, you’re the first to have considered that scenario?
Even consumer-grade products like ChatGPT can be interrupted while talking. We’re talking about an AI implementation, not some rigid set of if...else statements.
You talk as if they don’t already have customer facing implementations in effect, and that those all suck and don’t work worth shit. You also seem to think the “engineers” involved are custom doing anything and not just some sales person slapping a half baked product on every problem. When you get paid per deployed program, everything looks like a problem to solve with said program.
This is an issue of not having enough 911 dispatchers, due to the unwillingness to pay for them. The idea of putting in a chatbot, that can not even speed up diction let alone have any empathy is just wildly inappropriate in this situation. The fact is that these LLMs will (like in current deployments) most of the time have to pass the call to a person, drastically increasing time on the phone before action is taken. This is already seen in almost all LLM supported call centers, but a 911 dispatch is not a telecom company and more time on the phone is more death, injury and suffering.
You talk as if they don’t already have customer facing implementations in effect,
Mind pointing to where I talk like that? I knew these have already been used in other customer-facing environments before ever commenting, so I’m happy to try to clarify, if needed.
and that those all suck and don’t work worth shit.
Got any sources from within the last year? I ask for the last year because “AI” (LLMs and the overall ecosystem) has become much more capable over the last ~year (maybe a little less, but close enough).
I’ve already seen some reports that are older and, unsurprisingly, terrible. Those earlier generations of LLMs definitely don’t seem like they’d be up to the task – and some cities even had the balls to adopt this tech back in 2023 😬
This is an issue of not having enough 911 dispatchers
Correct, but it’s not like they can just go to the 911 dispatcher store and pick up some dispatchers. The widespread shortages have been a problem since before transformer-based LLMs even existed.
This triage system is a mitigation, not a solution. It makes the bad problem less bad – not solved. Maybe someday there will be enough dispatchers. Unfortunately, we have not reached that “someday” yet.
due to the unwillingness to pay for them.
Source? Not saying you’re wrong – I’m only aware of the shortage because I was friends with a dispatcher. I just never really looked into why there’s a shortage, and now I’m curious.
The idea of putting in a chatbot, that can not even speed up diction
The goal is not to speed up diction – that would be more like “vertical scaling,” or “scaling up.” AI a bad choice for scaling that way, in most cases. AI is much better for “horizontal scaling,” or “scaling out” – so like 20 bots concurrently answering 1 call each, not 1 bot trying to speed-run through 20 calls serially.
The fact is that these LLMs will (like in current deployments)
By “current deployments,” do you mean current 911 deployments, or just things like customer service lines? There’s a huge difference in product requirements between those two. If done the same, then yes, that would be an absolute disaster. That’s not what this is though.
most of the time have to pass the call to a person, drastically increasing time on the phone before action is taken.
Where is this information from? I thought the problem was the surge of calls going to the call center to report the same thing (for example, people calling 911 when driving past a burning car). When that happens, the AI agents actually don’t have to pass most calls to a person, because most calls are about the same emergency (e.g. the car fire example). Did I misunderstand this?
911 dispatch is not a telecom company and more time on the phone is more death, injury and suffering.
Exactly. This system reduces hold times by filtering out the spam about the car fire, freeing up some operators in the understaffed team to deal with more emergencies.
The AI system is obviously slower than a well-staffed team of operators who can handle the call volume surges, but faster than an understaffed team that has to get through the spam. Unfortunately, they’re faced with the latter, so they found a way to at least mitigate the problem a bit.
All of that is just not true, literally all of that huge wall of text. From the odd takes on somehow saying there is and is not examples of LLMs used in call centers that are complete shit (my example would be just to point to any AI agent call I have had to do in the last year) to the clear non understanding of how the speed of diction could be an issue shows that the wall of text you put up has zero substance. Almost as if wrote by chat GPT or the likes. The same issues in a call center for hotdog packaging and 911 will exist and saying “smart people” will handle one better then the other is one of if not the stupidest things I have seen in print.
Your odd hubris is why the world is going to shit. You are the direct reason why we live in interesting times.
All of that is just not true, literally all of that
Incorrect. For example, you really can’t go solve the 911 dispatcher shortage by getting more 911 dispatchers from the 911 dispatcher store, and I stand by that. If you can prove this wrong, please do.
huge wall of text
Apologies for replying to each of your points due to respecting you enough to assume you’re a worthwhile human instead of writing you off as a waste of time. It seems to have frustrated you to some degree…
I’m gonna do it again though.
From the odd takes on somehow saying there is and is not examples of LLMs used in call centers that are complete shit
Where did I say there are no shitty LLM implementations in call centers? I doubt you’ll answer this (you don’t seem to like backing up your claims), but I really am curious. That would not be consistent with my experience with call center LLM implementations at all. I don’t think I’ve ever had a good experience with them.
My shitty little self-hosted smarthome assistant that I slapped together outperforms most of them, and it’s an old, half-assed, neglected side project 😆. (Not much of an achievement when it only has to serve one user though.)
(my example would be just to point to any AI agent call I have had to do in the last year)
Was it a 911 triage agent? If not, then there’s not much of a comparison here. Very different implementations to serve very different purposes. A 911 triage agent should be designed for much simpler, narrower goals than some customer service agent.
to the clear non understanding of how the speed of diction could be an issue
If you’d like to explain it, I’m open to it.
the wall of text you put up has zero substance.
Speaking of that, I noticed that you haven’t answered a single one of the questions related to the substance of your last comment. I’m just curious – Can you? Surely there must be some substance behind your words if that’s something you value, yes?
The same issues in a call center for hotdog packaging and 911 will exist
“will exist”? Future tense? Was this meant to sound so speculative?
New Orleans is not the first city to adopt this 911 triage system. Why speculate when we already have the past and present?
If it helps, I can even point you to a spicy one as head start: If you go far back enough, you’ll find a death in Seattle related to an old LLM implementation in a 911 call center… or something like that. (It has been a while since I read it)
Your odd hubris
Ironic ;)
You are the direct reason why we live in interesting times.
Thanks, but I’m just a guy writing comments on the same network that you’re writing comments on. I may have worked on some AI tools, but nothing public-facing, and nothing really exciting. I’m mostly just a consumer of these “interesting times”… Maybe an indirect reason at best. Not more than a drop in the ocean.
Do you honestly think that nobody has thought about that and solved that problem already? Even with all the engineers involved, and after all the real-world testing,
That is the thought process of a child. If your defense of something with obvious issues is “Well I’m sure they know what they’re doing, because if they didn’t it would be bad”, I have some really, really bad news for you about the world.
If this was thought through by a capable adult, it would’t be implemented at all. The very fact that this solution is on the table is proof of the breakdown of rational thought. Or more likely, greased palms.
Your blind appeal to authority would hold more water if we haven’t already seen national adoption of AI products in emergency services that that have catastrophically failed to perform their basic functions, leading to real world harm. Audits of Flock cameras deployed in several cities found an error rate ranging from 33-70%. People are being arrested for things they didn’t do because the AI doesn’t work and nobody cares. People are being stalked because nobody thought of basic security controls.
We’re talking about an AI implementation, not some rigid set of if...elsestatements.
Even worse, we’re talking about an AI implementation of if…else statements. Regular if else statements are consistent. As soon as you throw AI into the mix they become unpredictable. You introduce a failure mode that didn’t exist before that can and will have real consequences.
So… you do assume that you’re the first to think of this problem, or…?
If you assume that your brain is somehow superior[1] to everyone involved in the R&D, engineering, data analysts/QC, etc., then this may come as a surprise to you: You’re not even the first Lemmy commenter to think of it.
Literally multiple people here already thought about that and commented before you did. They’re not the first either; the author of the article herself even thought about it.
This idea is among the most obvious potential problems that come to mind within seconds or minutes of just hearing about the concept. It’s not a dumb idea by any means (it’s completely valid), it’s just not a particularly smart or special one.
911 is not the first department in that city[2] to use this tech, and that city isn’t even the first to adopt it. It’s silly to assume that such an easy-to-solve problem hasn’t been addressed by now, or that it somehow has not yet happened in other deployments.
To be clear: I make no assumptions that your brain is not superior to theirs either – I couldn’t possibly know either way. AFAIK, I’ve never even met you nor them… But I think it would be a safe bet that you don’t know either. ↩︎
BTW, have you heard cajun accents? There’s no way this bridge hasn’t already been crossed during their 311 trials. ↩︎
As someone who worked in the industry, your trust is wildly misplaced. I guarantee someone has already said internally this will not work and was shushed by a sales manager.
And as far as “I am sure they tested accents” goes? HA they likely noted it was a mess and moved on. You think the goal is a functioning system, but it is not it is just to make the sale.
Why does it have to be AI? Why can’t it be “press 1 for the highway car fire on 42, press 2 to be transferred to an operator”? Surely that’s much less likely to fail?
Ah, right, I suppose it’s contextual. You would also have to read the comment that it’s responding to. To summarize: it might not have to be AI.
However, 911 is a bit too dynamic for your solution to be viable as-is. For example, “Hey Siri/Google, I can’t move my hands. Call 911.”
Your idea is probably a decent starting point for brainstorming a solution — it just needs more thought, research, testing, etc. And I wouldn’t be surprised if a similar product already exists. (I’d actually be surprised if it doesn’t already exist.)
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?
Yeah I just don’t buy that there is a case where any “net gain” here is justified. These are people’s lives that you’re playing with by reducing them to what amounts to a balance sheet in the name of saving money.
The idea that you would create the possibility of denying someone emergency care that didn’t exist before, no matter how improbable (probably not even that improbable, given the propensity even the most advanced frontier AI models have for getting things wrong or hallucinating entirely despite simple instructions) just to save 10-15 seconds on average for other callers is not only absurd on its face, but morally bankrupt. You can personally ignore it because you don’t live there and it’s not the lives of you or your family at stake. I think those who this system could fail would not be able to ignore a flaw like that when it happens to them, and the idea that their peril was “highly improbable” will not be of much comfort to them.
The problem is that there are staffing shortages. The solution is hiring more staff. Trying to cheat our way out by implementing a system prone to unmitigatable flaws that could have life-altering or even life ending consequences isn’t a solution, it’s dystopian.
:sigh: Okay, I’ll try to break it down even more…
Exactly. That’s what they want to solve.
TL;DR: Even when callers reach the triage bot, they can still reach a human much faster than without the triage bot.
Comparing again:
WITHOUT the triage tech:
WITH the triage tech:
They chose this tech because it has already proven to be a net positive on their non-emergency line.
None of that applies if a caller just can’t get through at all because the bot mistook “no” for “yes”
Do you honestly think that nobody has thought about that and solved that problem already? Even with all the engineers involved, and after all the real-world testing, you’re the first to have considered that scenario?
Even consumer-grade products like ChatGPT can be interrupted while talking. We’re talking about an AI implementation, not some rigid set of
if...elsestatements.You talk as if they don’t already have customer facing implementations in effect, and that those all suck and don’t work worth shit. You also seem to think the “engineers” involved are custom doing anything and not just some sales person slapping a half baked product on every problem. When you get paid per deployed program, everything looks like a problem to solve with said program.
This is an issue of not having enough 911 dispatchers, due to the unwillingness to pay for them. The idea of putting in a chatbot, that can not even speed up diction let alone have any empathy is just wildly inappropriate in this situation. The fact is that these LLMs will (like in current deployments) most of the time have to pass the call to a person, drastically increasing time on the phone before action is taken. This is already seen in almost all LLM supported call centers, but a 911 dispatch is not a telecom company and more time on the phone is more death, injury and suffering.
Mind pointing to where I talk like that? I knew these have already been used in other customer-facing environments before ever commenting, so I’m happy to try to clarify, if needed.
Got any sources from within the last year? I ask for the last year because “AI” (LLMs and the overall ecosystem) has become much more capable over the last ~year (maybe a little less, but close enough).
I’ve already seen some reports that are older and, unsurprisingly, terrible. Those earlier generations of LLMs definitely don’t seem like they’d be up to the task – and some cities even had the balls to adopt this tech back in 2023 😬
Correct, but it’s not like they can just go to the 911 dispatcher store and pick up some dispatchers. The widespread shortages have been a problem since before transformer-based LLMs even existed.
This triage system is a mitigation, not a solution. It makes the bad problem less bad – not solved. Maybe someday there will be enough dispatchers. Unfortunately, we have not reached that “someday” yet.
Source? Not saying you’re wrong – I’m only aware of the shortage because I was friends with a dispatcher. I just never really looked into why there’s a shortage, and now I’m curious.
The goal is not to speed up diction – that would be more like “vertical scaling,” or “scaling up.” AI a bad choice for scaling that way, in most cases. AI is much better for “horizontal scaling,” or “scaling out” – so like 20 bots concurrently answering 1 call each, not 1 bot trying to speed-run through 20 calls serially.
By “current deployments,” do you mean current 911 deployments, or just things like customer service lines? There’s a huge difference in product requirements between those two. If done the same, then yes, that would be an absolute disaster. That’s not what this is though.
Where is this information from? I thought the problem was the surge of calls going to the call center to report the same thing (for example, people calling 911 when driving past a burning car). When that happens, the AI agents actually don’t have to pass most calls to a person, because most calls are about the same emergency (e.g. the car fire example). Did I misunderstand this?
Exactly. This system reduces hold times by filtering out the spam about the car fire, freeing up some operators in the understaffed team to deal with more emergencies.
The AI system is obviously slower than a well-staffed team of operators who can handle the call volume surges, but faster than an understaffed team that has to get through the spam. Unfortunately, they’re faced with the latter, so they found a way to at least mitigate the problem a bit.
All of that is just not true, literally all of that huge wall of text. From the odd takes on somehow saying there is and is not examples of LLMs used in call centers that are complete shit (my example would be just to point to any AI agent call I have had to do in the last year) to the clear non understanding of how the speed of diction could be an issue shows that the wall of text you put up has zero substance. Almost as if wrote by chat GPT or the likes. The same issues in a call center for hotdog packaging and 911 will exist and saying “smart people” will handle one better then the other is one of if not the stupidest things I have seen in print.
Your odd hubris is why the world is going to shit. You are the direct reason why we live in interesting times.
Incorrect. For example, you really can’t go solve the 911 dispatcher shortage by getting more 911 dispatchers from the 911 dispatcher store, and I stand by that. If you can prove this wrong, please do.
Apologies for replying to each of your points due to respecting you enough to assume you’re a worthwhile human instead of writing you off as a waste of time. It seems to have frustrated you to some degree…
I’m gonna do it again though.
Where did I say there are no shitty LLM implementations in call centers? I doubt you’ll answer this (you don’t seem to like backing up your claims), but I really am curious. That would not be consistent with my experience with call center LLM implementations at all. I don’t think I’ve ever had a good experience with them.
My shitty little self-hosted smarthome assistant that I slapped together outperforms most of them, and it’s an old, half-assed, neglected side project 😆. (Not much of an achievement when it only has to serve one user though.)
Was it a 911 triage agent? If not, then there’s not much of a comparison here. Very different implementations to serve very different purposes. A 911 triage agent should be designed for much simpler, narrower goals than some customer service agent.
If you’d like to explain it, I’m open to it.
Speaking of that, I noticed that you haven’t answered a single one of the questions related to the substance of your last comment. I’m just curious – Can you? Surely there must be some substance behind your words if that’s something you value, yes?
“will exist”? Future tense? Was this meant to sound so speculative?
New Orleans is not the first city to adopt this 911 triage system. Why speculate when we already have the past and present?
If it helps, I can even point you to a spicy one as head start: If you go far back enough, you’ll find a death in Seattle related to an old LLM implementation in a 911 call center… or something like that. (It has been a while since I read it)
Ironic ;)
Thanks, but I’m just a guy writing comments on the same network that you’re writing comments on. I may have worked on some AI tools, but nothing public-facing, and nothing really exciting. I’m mostly just a consumer of these “interesting times”… Maybe an indirect reason at best. Not more than a drop in the ocean.
That is the thought process of a child. If your defense of something with obvious issues is “Well I’m sure they know what they’re doing, because if they didn’t it would be bad”, I have some really, really bad news for you about the world.
If this was thought through by a capable adult, it would’t be implemented at all. The very fact that this solution is on the table is proof of the breakdown of rational thought. Or more likely, greased palms.
Your blind appeal to authority would hold more water if we haven’t already seen national adoption of AI products in emergency services that that have catastrophically failed to perform their basic functions, leading to real world harm. Audits of Flock cameras deployed in several cities found an error rate ranging from 33-70%. People are being arrested for things they didn’t do because the AI doesn’t work and nobody cares. People are being stalked because nobody thought of basic security controls.
Even worse, we’re talking about an AI implementation of if…else statements. Regular if else statements are consistent. As soon as you throw AI into the mix they become unpredictable. You introduce a failure mode that didn’t exist before that can and will have real consequences.
Yeah it’s definitely better to not answer all those calls
So… you do assume that you’re the first to think of this problem, or…?
If you assume that your brain is somehow superior[1] to everyone involved in the R&D, engineering, data analysts/QC, etc., then this may come as a surprise to you: You’re not even the first Lemmy commenter to think of it.
Literally multiple people here already thought about that and commented before you did. They’re not the first either; the author of the article herself even thought about it.
This idea is among the most obvious potential problems that come to mind within seconds or minutes of just hearing about the concept. It’s not a dumb idea by any means (it’s completely valid), it’s just not a particularly smart or special one.
911 is not the first department in that city[2] to use this tech, and that city isn’t even the first to adopt it. It’s silly to assume that such an easy-to-solve problem hasn’t been addressed by now, or that it somehow has not yet happened in other deployments.
To be clear: I make no assumptions that your brain is not superior to theirs either – I couldn’t possibly know either way. AFAIK, I’ve never even met you nor them… But I think it would be a safe bet that you don’t know either. ↩︎
BTW, have you heard cajun accents? There’s no way this bridge hasn’t already been crossed during their 311 trials. ↩︎
As someone who worked in the industry, your trust is wildly misplaced. I guarantee someone has already said internally this will not work and was shushed by a sales manager.
And as far as “I am sure they tested accents” goes? HA they likely noted it was a mess and moved on. You think the goal is a functioning system, but it is not it is just to make the sale.
Why does it have to be AI? Why can’t it be “press 1 for the highway car fire on 42, press 2 to be transferred to an operator”? Surely that’s much less likely to fail?
https://infosec.pub/comment/23116617
That doesn’t answer my question at all?
Ah, right, I suppose it’s contextual. You would also have to read the comment that it’s responding to. To summarize: it might not have to be AI.
However, 911 is a bit too dynamic for your solution to be viable as-is. For example, “Hey Siri/Google, I can’t move my hands. Call 911.”
Your idea is probably a decent starting point for brainstorming a solution — it just needs more thought, research, testing, etc. And I wouldn’t be surprised if a similar product already exists. (I’d actually be surprised if it doesn’t already exist.)
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?
Yeah I just don’t buy that there is a case where any “net gain” here is justified. These are people’s lives that you’re playing with by reducing them to what amounts to a balance sheet in the name of saving money.
The idea that you would create the possibility of denying someone emergency care that didn’t exist before, no matter how improbable (probably not even that improbable, given the propensity even the most advanced frontier AI models have for getting things wrong or hallucinating entirely despite simple instructions) just to save 10-15 seconds on average for other callers is not only absurd on its face, but morally bankrupt. You can personally ignore it because you don’t live there and it’s not the lives of you or your family at stake. I think those who this system could fail would not be able to ignore a flaw like that when it happens to them, and the idea that their peril was “highly improbable” will not be of much comfort to them.
The problem is that there are staffing shortages. The solution is hiring more staff. Trying to cheat our way out by implementing a system prone to unmitigatable flaws that could have life-altering or even life ending consequences isn’t a solution, it’s dystopian.