I ask this out of genuine, burning curiosity, and mean no rudeness by this…
Did you read the article that the OP linked to?
I don’t mean to single you out with this question, I’m just confused after scrolling this far through sooo many similar comments. It almost feels as if I somehow ended up reading a different article from everyone else.
callers get automatically routed to an AI agent who asks if they are calling regarding the incident. If the answer is yes, then callers can receive information or updates, and if it’s no, then the callers are transferred to a human.
So if somebody calls and is completely out of his mind, what will AI do?
What if someone is obviously out of their mind and says yes? Random example, say someone has a stroke and has just barely figured out how to use the big red emergency call button on their phone screen. The AI asks if they are calling about blah blah emergency. Maybe the person only understands half of it, thinks they’re being asked if they’re calling about an emergency and say “yes”. Now they’re stuck having a form letter read to them by AI while their brain is dying. A person would catch something was up even if they said yes.
The article even notes this can be a problem without anything medical going on:
It’s also possible that AI agents handling 911 triage could fail to understand individuals with stronger accents and dialects, as well as differences in pitch and articulation. This is because AI is programmed with automatic speech recognition systems and, therefore, could potentialy be unreliable when presented with a speech unlike the ones used the AI is trained to recognize.
Responding to people having emergencies is too important a task to leave up to voice recognition slapped on top of an LLM.
Sure, usually, but compare like to like. If a human operator asked if the call was about an already known scenario and transferred people to an automated service if they said “yes”, then the same exact thing could happen.
You attemtped to craft a very specific scenario in which harm would result, when in reality it is wildly unlikely that someone would call in at that precise time and only respond with the word “yes”.
I gave a single example of one way that AI can miss a genuine emergency in a way that a human operator won’t. ‘Nobody will ever call 911 with a stroke and be confused’ isn’t a realistic defense of removing the best system we have of assessing information, the human brain.
I don’t know the concrete answer to your "what if,’ and I don’t think you or the author of the article do either. That would be a question for Carbyne.
I would speculate that there is an answer, and that neither you nor the author are the first to think of these problem scenarios. There’s design, engineering, and real-world testing involved.
I gave you the benefit of the doubt. If you’ve had lots of interactions with AI, I am not sure how you can think that anything with AI can work as expected, specially in complicated edge cases.
If you’ve had lots of interactions with AI, I am not sure how you can think that anything with AI can work as expected
That’s a very broad statement, and “AI fluency” is a broad spectrum. Having “lots of interactions with AI” isn’t an indicator of much at all – lots of end users use LLMs every day. They have “lots of interactions with AI”, but most of them have not developed/trained agent “skill” files, built agent workflows, developed harnesses, handed complex tasks to a “team” of agents (and refining them to perform reliably), etc. Anyone can have lots of interactions with AI without ever experimenting beyond the consumer-grade interfaces.
Asking if someone has had “lots of interactions with AI” says much more about the AI fluency of the person asking. A lot of “advanced” (using the term very loosely here) users/builders would know that your concern is an easy problem to solve. It might even be a decent sort of challenge to give an intern to build/train as one of their first few AI agent skills, since they already have a lot real-world data (from their 311 trials and other cities/orgs that also use this tech) to use for testing and iterating.
Yeah, I can just imagine how well a “AI” would deal with a situation like this when they can’t even operate a drive-thru properly.
I ask this out of genuine, burning curiosity, and mean no rudeness by this…
Did you read the article that the OP linked to?
I don’t mean to single you out with this question, I’m just confused after scrolling this far through sooo many similar comments. It almost feels as if I somehow ended up reading a different article from everyone else.
Did you read the article?
So if somebody calls and is completely out of his mind, what will AI do?
Is this a rhetorical question?
Just in case you wanted a real answer: The caller is obviously not saying “yes,” so transfer to human.
To be clear: I don’t know anyone at Carbyne or OPCD. I can only offer speculation. But I’m curious: What would you have guessed?
What if someone is obviously out of their mind and says yes? Random example, say someone has a stroke and has just barely figured out how to use the big red emergency call button on their phone screen. The AI asks if they are calling about blah blah emergency. Maybe the person only understands half of it, thinks they’re being asked if they’re calling about an emergency and say “yes”. Now they’re stuck having a form letter read to them by AI while their brain is dying. A person would catch something was up even if they said yes.
The article even notes this can be a problem without anything medical going on:
Responding to people having emergencies is too important a task to leave up to voice recognition slapped on top of an LLM.
Besides “because it supports the conclusion I want to arrive at”, what makes you believe this is true?
People having a stroke can’t carry on a conversation and seem normal.
Sure, usually, but compare like to like. If a human operator asked if the call was about an already known scenario and transferred people to an automated service if they said “yes”, then the same exact thing could happen.
You attemtped to craft a very specific scenario in which harm would result, when in reality it is wildly unlikely that someone would call in at that precise time and only respond with the word “yes”.
I can only speculate as to why you would do that.
I gave a single example of one way that AI can miss a genuine emergency in a way that a human operator won’t. ‘Nobody will ever call 911 with a stroke and be confused’ isn’t a realistic defense of removing the best system we have of assessing information, the human brain.
I don’t know the concrete answer to your "what if,’ and I don’t think you or the author of the article do either. That would be a question for Carbyne.
I would speculate that there is an answer, and that neither you nor the author are the first to think of these problem scenarios. There’s design, engineering, and real-world testing involved.
“Well I just trust they thought of it” isn’t good enough.
If you’re unsatisfied with my answer, then maybe consider asking them. I’m just a guy writing comments on Lemmy.
I guess you don’t have lots of interaction with AI yet?
Very incorrect. Why do you ask?
I gave you the benefit of the doubt. If you’ve had lots of interactions with AI, I am not sure how you can think that anything with AI can work as expected, specially in complicated edge cases.
That’s a very broad statement, and “AI fluency” is a broad spectrum. Having “lots of interactions with AI” isn’t an indicator of much at all – lots of end users use LLMs every day. They have “lots of interactions with AI”, but most of them have not developed/trained agent “skill” files, built agent workflows, developed harnesses, handed complex tasks to a “team” of agents (and refining them to perform reliably), etc. Anyone can have lots of interactions with AI without ever experimenting beyond the consumer-grade interfaces.
Asking if someone has had “lots of interactions with AI” says much more about the AI fluency of the person asking. A lot of “advanced” (using the term very loosely here) users/builders would know that your concern is an easy problem to solve. It might even be a decent sort of challenge to give an intern to build/train as one of their first few AI agent skills, since they already have a lot real-world data (from their 311 trials and other cities/orgs that also use this tech) to use for testing and iterating.