New Orleans will use AI to answer 911 calls instead of a human

:sigh: Yet again, nobody reads the fucking article and it is VERY obvious from most of the comments. If you can’t be bothered, then don’t fucking comment.

If you had READ the article: They’re answering with the AI saying like “Are you calling about X?” If the callers says no, they are transferred to a human. If they ARE calling about an incident, then they can get updates and information about it.

Now, I grant that this is still not perfect, but the stated goal is humans spending less time talking to people reporting an incident already reported so they can actually talk to people needing help faster.

Assuming that works out, this is actually a good idea and an improvement.

Now, if you wanna be cynical about it, fine. But just read the damn article and be cynical about what’s actually happening, not about what you think from the headline, or all you end up looking like an ass.

I came into the comments to have a good discussion on the issue. I should have known better. I’m so irritated by the majority of comments that I lost interested in the topic itself, even though there’s at least one ofther comment I saw also pointing out what the article says. But no, the majority of you can’t be bothered, so screw this. And you bitch about reddit.

Holy shit, I’m actually surprised how bad the rest of the comments are… And the volume of them!

I’ll try to TL;DR it for the lemmings, with formatting that is (hopefully) easy to understand for even the most rotten of brains.

TL;DR

The problem

• Too many people are all calling 911 about the same emergency.

I’ll use this example scenario below: People keep driving past a burning car on a busy road, and many of them call 911. (This will continue to happen until an emergency responder arrives.)

Before implementing this tech

• 911 operators are all busy answering calls that are all reporting the same car fire
• Long 911 hold time for someone with an emergency unrelated to the car fire

After implementing this tech

Bot: "Are you calling about the car fire on Seventh Street?"

• If caller answers “yes”:
  • AI bot tells them that responders have already been dispatched
• If caller answers anything other than “yes”:
  • Transfer to the next available human dispatcher
  • Greatly reduced hold time thanks to automated triage

If the critical failure point is accurately classifying “yes” or “not yes,” even the dumbest^1 models could handle that – and I doubt they use the dumbest models for 911 triage.

Even if it’s not 100% perfect every time, this still sounds like a net positive.

• If caller answers “yes”:
• AI bot tells them that responders have already >been dispatched

So you’re gating whether or not a caller in an emergency gets to speak to a human based on the audio recognition of a robot?

Easy enough to make it so that if the bot doesn’t hear a yes or a no clearly it defaults to forwarding the call, but what happens when a person says no and the bot “hears” yes?

I believe I touched on that in my last sentence, but I can elaborate:

That will probably happen – neural networks are approximation algorithms. It’s a question of how often that happens.

What percentage of the calls get misclassified? And what’s the threshold percentage that would be needed for the triage bot to be a net positive?

It sounds like they have an idea of these numbers based on data collected from the non-emergency line, so it’s not like they’re just blindly jumping into this.

EDIT: I just realized that I did not actually answer your question of “what happens”…

I imagine the caller would just interrupt the AI’s answer (e.g. “No not that,” “HELP,” “Give me a human,” “FUCK!” etc.)? That seems like the natural thing to do.

To be clear: I don’t know anyone at Carbyne or OPCD. I can only offer speculation.

I don’t think there’s any net positive that would account for not answering an emergency call at all.

Can you really justify someone not being able to reach help at all in place of everyone being able to reach it albeit slower?

As a lifelong first responder, I couldn’t get behind something like this at all.

:sigh: Okay, I’ll try to break it down even more…

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.

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…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.