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.
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.