Call center employees are pretty much as good as gone once the price comes down on GPT4. You can pretty easily give it a good prompt that allows it to answer very specific questions about your company, or interact with external APIs to schedule services, make changes based on the customer's requests, etc. Throw some Speech to Text and Text to Speech services in front and behind it, and voila you have an AI receptioni…
I think companies will try to eliminate call centers, and customers will treasure a good call center even more than they do today.
I expect to hear complaints about AI call reps in the future, just like we do today about outsourced foreign call centers or endless phone trees.
I am dreading the inevitable future day when I have to argue about a denied health insurance claim on the phone with a fucking robot prompted to make it as difficult as possible for me to win.
Slow down. Maybe a robot that learns from past calls is better than (1) a static robot flow or (2) a human following a script. Maybe you don't have to interact via voice call, but maybe text/email/chat is a shortcut. Maybe you don't have to wait 30 minutes for your turn in the queue, since it's all running in VMs anyhow.
"better" for whom? The key issue raised by the parent post is that from whatever sources the robot learns, we should expect it to be trained to use that data to make things better at achieving the goals of the robot owner which are different from - and often opposite to - the goals of the customer.
So yes, in comparison to a static robot flow or a human following a script, a robot that learns from past calls would be better... at maximizing the chances that the caller gives up in frustration while still having their insurance claim denied.
Most call centers aren’t about answering questions though. It’s more about putting the ability to make changes to your system behind a phone wall and an employees judgement. AI can still do that role but it’s nowhere as easy as a question answering bot.
Bingo. The biggest problem with implementing LLMs-as-call-center-agents, at least in contexts like insurance, is fraud. Even GPT-4 is just too easy to fool currently. Call center conversations are often adversarial, where the caller wants the agent to create a change to the system that is somehow fraudulent or to their benefit, and it's the agent's job to hold the line. You don't want a situation where people are cal…
This is why well architected systems will require the AI agent to do things through other services via well-defined APIs. First, it allows the business to limit the space with which the AI can interact with the rest of the business. Secondly, it allows the business to use good ol' fashioned AI, logical rules, etc that can prevent an AI agent from doing things that it shouldn't. Of course, there will be exceptions to the rules, the same as there are today, but it should drastically cut down the number of humans involved in the process, and when a human is required to intervene on the business' behalf the AI can summarize the entire conversation + the reasoning on the business side for not acquiescing to the customer's demands.
On the occasion I do editing for certain documents on behalf of non-native English speakers. This can take up to two hours per document ordinarily. ChatGPT reduced this to 15 minutes, and almost all of that is just proofreading the output, waiting for it to respond and copying and pasting.
Rewriting text to be more fluent or readable. For all the (many!) people who need to create documents in English but aren't native speakers, GPT-4 is quite effective at rephrasing a technically correct but un-idiomatic text into something that's much better.
Text translation is basically solved with DeepL, at least on the languages it supports, it's indistinguishable for my native language. This is not talked much right now but language learning will become a hobby at this point between the increasing quality of speech recognition, translation and speech synthesis.
No electronic solution can ever come close to having a real spoken conversation with another person. DeepL and other AI translators are great for text, though.
It can come close enough that if the choice is between an expensive live translator and a cheap (or free) voice-to-voice machine translation, then many people might prefer the latter.
I've got a thread going with ChatGPT about an app I'm building. It knows all of the libraries I'm using, and has seen the main App component, the Router and many of the key components. I'm asking it about every task I need to do, feature I need to implement, bug I need to fix. Basically rubber ducking with it and talking through everything I'm doing as if it were my coworker. It's reducing my time to solve problems b…
I'm seeing similar, chatgpt replacing a lot of external libraries and digging through the weeds to find the right endpoint. After all, why bother dealing with so many external libraries to get it done when you can just relay the core ones you must use and ask chatgpt to flesh out the rest in a way that suits your needs? Need a component to be gamepad accessible written in Vue? Ask and you'll receive. No more botherin…
If you're not using external libraries that are maintained by other people, how do you handle your code's maintainability in the long-term? Keep asking ChatGPT to fix it when things break?
Truthfully... what's most remarkable to me is it not saying, "just stfu, you idiot" after me asking it question after question about stuff i want to know more about.
There has been countless times where I'll read it's response of, "sure, here's..." and it just blows my mind that i have the ability to barrage something with questions and it won't get tired of me doing so.
Unlike 3.5, GPT-4 is competent at translation. Not just competent; it's better than most human translators. We might not want to leave it to its own devices yet , but there's a large number of novels that were never translated, or were only translated badly. Personally, I've been setting things up to have it translate a series of light novels from Japanese to English. Experiments through the chat interface show it's…
Text translation is basically solved with DeepL, at least on the languages it supports, it's indistinguishable for my native language. This is not talked much right now but language learning will become a hobby at this point between the increasing quality of speech recognition, translation and speech synthesis.
Translation is not solved with deepl at ll. Not with difficult language pairs (English/Chinese, English/Japanese, English/korean etc ). That's where LLMs shine. Far ahead.
Unlike 3.5, GPT-4 is competent at translation. Not just competent; it's better than most human translators. We might not want to leave it to its own devices yet , but there's a large number of novels that were never translated, or were only translated badly. Personally, I've been setting things up to have it translate a series of light novels from Japanese to English. Experiments through the chat interface show it's…
Do you have an example of this!?!! There's so many untranslated light novels I want to read but the ML translation has been historically terrible where it's not readable. Being able to translate light novels without a translator/scanlator would be huge.