Daddy chill

Just as long as you acknowledge the proper parental relationship here, son.

lol :P

So, Lemmy really seems to love these two things:

• Getting angry at things
• Having their biases confirmed

If a headline feeds the hunger, why risk ruining that validation by reading the article?

Yeah, its not handling “my grandma is dying pls send emt” calls, but more “The concert hall is on fire” call #450.

That being said, I disagree with most applications of AI that prevent human interaction. Just because im the 40th person calling about a situation doesnt mean my call is useless, it means i might have new information on an evolving situation.

Still, it’s a sloppy headline designed for clicks or thumbs up. It would be more accurate if it was “AI is to initially screen calls….”

sensationalized headlines aren’t new. If anything they’re more important now than ever

You don’t need “ai” for this though. IVRs have been doing this for literal decades. Your average dialup ISP had a standard option for times of outages ffs.

Read the article. This system will get people killed in the name of efficiency. AI is nowhere near ready to route emergency calls.

What about callers that can’t talk or have accents. The only proper way is to have a human answer and then transfer to an AI, not the other way around. Perhaps decades from now when theses systems are much more reliable we could trust it to be the front line, but we are nowhere near this yet.

If you have something to say, please say it. All I see is someone bitching about not having a discussion.

Read the article.

What do you fucking think I did?

If you have something to say, please say it.

I fucking well did.

All I see is someone bitching about not having a discussion.

Try reading all of my fucking comment then.

What about

Depends on how they implement it. I would assume they’re bound to be ahead on you on this one because some callers also can’t say anything on the line because of danger, so they are aware of this issue. Since we don’t have concrete details, we’ll have to speculate on how they handle such things.

I won’t bother to speculate further with you because I know you won’t read it anyway.

No, I meant I read the article, sorry if that wasn’t clear. You were bitching about people not reading it, I did.

We don’t have to speculate, these same systems are being used as call agents and front line contacts for many industries now. Having dealt with these agents firsthand I can tell you they are extremely limited and pretty much garbage unless you have an issue that could easily be answered by looking at their web page.

There is no possible way to currently reduce the error rate, stop GIGO issues, audit the decision making process, stop hallucinations, etc. To even pretend these are ready for emergency situations is such a gross lack of discernment that I would consider it criminal in nature.

It is problematic to even provide the most basic service of screening of phone calls considering it could be costing previous time in an emergency. If it is a manpower issue then they should be fixing it there and not lookimg for a quick fix.

Also, you know it will not stop there. Their goal is triage so you know they are eventually moving towards far more than a simple public service emergency announcement. You will not be talking to a human in the future but a LLM that will kill people when it makes mistakes and won’t be held accountable.

No, I meant I read the article, sorry if that wasn’t clear.

LOL. English ambiguity strikes again. Sorry for the misfire, totally my fault. Thanks for the kind reply and patience with me <3

I do disagree that there’s no way to make it work pretty safe. Instead of defaulting to holding someone in the AI loop until they talk their way out of it, you can simply set it up to stay in the loop only if it’s sure it needs to continue, i.e. anything other than something it gets like “Oh, yes, that’s what I was calling about”, it should dump them to a human.

And we don’t know if they’ve set it up something like that or not. I humbly disagree that we know for sure they have not, no matter how other systems are configured.

And I also disagree that it will necessarily turn out poorly. It literally depends on how they do it. But that said, it is analgous to taking humans out of the driver’s seat in the car. At some point, it will be statistically ten times safer for automated driving to drive you than letting people drive. And when we get to that point, people will be up in arms that automated driving is killing people - when it is literally only a tenth of the previous rate of death. But we humans don’t like giving up that sort of control.

AI is new technology. I’m not totally behind them doing this, but I see the goal. And if they configure it correctly to fail-to-human rather than fail-to-AI-loop, I can see how this can save lives, not lose them. Of course if you’re right and they screw it up it could be worse. I guess we’ll see with time what they do and how it works.

But I firmly believe that trying to fight against all the tech is the wrong move. It’s like trying to fight to keep woodchoppers employed. The tech is there and much of what it is doing is inevitable. What we should be focused on is solving wealth inequality, solving our oligarch problem, solving the lack of social safety nets, living wages, our government working for all of us, not just bilionaires.

So you and I probably aren’t going to see eye to eye on this, but I can respect you better now that I know what you were saying better. :) Sorry to have flubbed that!

Pretty safe? I am sorry but if it is your life on the line or a loved one pretty safe is just not going to cut it. When the AI decides your dying grandmother isn’t priority because of a reason no one can explain or audit what then.This is a huge safety issue than you hand wave away because you are apparently enamored with AI.

I am trying to keep an open mind but replacing human thinking in emergency situations is not a reasonable application. You want a LLM model to triage your medical care with an unproven model that can and does make serious mistakes?

foley.com/…/stanford-study-finds-high-percentage-…

This is not speculation. These companies are selling snake oil at this point and you act as their carnival barker. I do think that decades in the future these systems will be ready for these challenges, but I am not insane enough to believe this roll out is anything other than a cash grab at this point.

I find your statement that humans don’t like giving up control very disturbing. We obviously do give up control for routine low level things like GPS everyday. This is not what your are alluding to though. You are advocating for giving up a higher level of control to an algorithm that can’t be held accountable.

Maybe you are ready for a world of half baked customer agents, managers, counselors, architects, artists, doctors, teachers, judges, emergency dispatchers, etc but I am not. Ceding our control to a corporatocracy of profit driven yes men is not going to end well.

I’ll keep it simple and based on the article in question:

Right now, people who need help are waiting longer to talk to an operator becauase operators field lots of calls about large incidents (or well-witnessed incidents).

That’s causing harm RIGHT NOW.

The theory is that if you offer callers a way to NOT TAKE UP OPERATOR TIME for incidents that are known, then the people who need help talk to an operator faster and get help faster.

That is what the article presents as what they’re doing.

Everything you are saying is pure speculation.

You may well be right. We’ll see.

There are plenty of ways to mitigate this problem which do not require a AI solution. I find it insulting that you think it is the best solution considering their is no evidence of its effectiveness. In fact, I have presented why there are many reasons for concern.

The willingness for government to invest in unproven technology rather than increase manpower or develop their own mass alert systems is dysfunctional to say the least. The fact that they often commit to these plans without consulting experts or asking for public comment is dishonest and corrupt.

I have already had to deal with multiple people suffering from AI psychosis so I am not the biggest fan. You say real harm and AI is already doing it everyday. I see your retreat to reductionisism but I don’t find it compelling in this instance. As I already alluded to, we know where this is going.

I find it insulting that you think it is the best solution

And I find you taking insult to be tiring.

And where did I say it was the best solution? Do not put words in my mouth

Go off an be unhappy in your little world of unhappiness.

If you have a chip on your shoulder that is fine. You have already demonstrated your bombastic behavior as well and shown the ability for reflection. I appreciate that. Cheers!

Ironic. Attempts to be clever. Oh well.

This is Lemmy and it says AI. Expect nobody to read and for panties to twist so hard their legs come off.

As I replied to a similar comment, in fairness - my panties came off as well. hehe (but for a valid reason, dammit! :slams fist on desk:)

I increasingly hate Lemmy for the way this seems to constantly happen on this topic and others. It’s like users are caricatures of opinions instead of people. Which, hey, maybe that’s prescient.

I think it’s an internet thing, not a Lemmy thing, to be honest.

I’m a voracious reader. I’m on Lemmy and basically not on reddit anymore because I want to have good discussions. And sometimes the discussions are pretty decent, but things like this put me off a bit.

It’s still a pretty decent platform overall. Although that might say more about the state of the internet at large than it does say good things about Lemmy. heh. But I’m still here. :)

It’s a human thing, above all else. If they wanted logical reasonable discussion, they should talk to robots. Except that’s the thing they hate

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.

I have to agree with you one hundred, /u/percent

:)

• 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.

how long could the queue be? If someone can’t wait 60 seconds for the queue, but can take the 8 seconds to ask if it’s about X incident. I do imagine it will be smart enough to check their approximate location before giving the prompt

: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”

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.

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.

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 yet to happen in other deployments.

[^1]: 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.

[^2]: 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?

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.)

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.

AI is absolutely not needed for this, and is only a liability.

They could say “press 1 if you are calling about X” or even “if you are calling about X, we are already aware of it. If not, you will be transferred to an operator in a moment”.

An automated system like this is easy to implement, easy to audit, and will fail in expected and managable ways.
AI is nondeterministic, and will fail randomly in very unexpected ways.

I (mostly) agree. I was just TL;DR’ing it for the shocking number of people who are commenting about things that are already addressed in the article that they didn’t bother reading.

I hesitate to agree with “absolutely” though. I don’t know enough about their situation to confidently have an opinion that strong[^1].

AI can be useful for some dynamic situations – and 911 call centers can get pretty “dynamic” at times.

Imagine a busy 911 call center. Clippy appears (wearing a firefighter uniform) on an operator’s screen with a message like “The last 4 calls were about the same car fire. There are currently 9 calls in the queue. Want me to triage?” It would take WAY less time for a busy operator to click “Yes” than it would to step away and go record some voice message, configure some automated thing, etc.

[^1]: I only ever knew one dispatcher personally, and even in her town (much lower population than New Orleans’), they were overworked.