A ton of tasks. Call centers to start with (they already do[1]), with human fallback.

1: In my country, after ChatGPT launched last year, when you call customer support you are now prompted to “just say in a few words” what you want instead of going through tap-this-number menus (they exist as a fallback) and I believe the backend is an LLM. The user flow and voice recordings are still programmatically determined though, but I can easily see one streamlined model calling APIs and whatnot, handling it all.

Yea that's pretty cool too, I heard some restaurants are also doing a 100% voice LLM to take orders.

Transcription, specifically Whisper, is one of those ML models where the accuracy is basically on-par with humans. So, I really expect a lot more to come out of real time voice/LLM integrations.(the ChatGPT voice thing is a good glimpse, but very janky)

"A firm providing AI drive-thru tech to fast food chains actually relies on human workers to take orders 70% of the time": https://www.businessinsider.com/ai-drive-thru-tech-relies-on...

I speak English clearly. These things always tell me to repeat what I said. Never once has it ever worked for me. I want to throw my phone at the wall.

Also I think this has been around for longer than chatgpt. It is often accompanied by a fake keyboard clicking noise.

> I speak English clearly. These things always tell me to repeat what I said. Never once has it ever worked for me. I want to throw my phone at the wall

Now imagine how well it works for people with non-"native" accents (even for native, I'd guess that a good Scouse/Glaswegian/Kiwi accent might confuse the hell of those systems as well). It's a disaster and I hate those.

There's a general problem across the tech industry with replacing existing simple and reliable (in a sense of conveying the user's intention) interfaces like physical buttons with stuff that is supposedly "more natural" like speech recognition or swipe gestures that in practice has a much higher error rate.

See also: replacing physical buttons with convoluted swipe gestures on mobile devices in the never-ending quest to make screen as large as possible. When was this ever a user ask?

I feel sometimes like the present UX design is one large LLM-like hallucination.

Scan a menu, look for the different entrees, identify the most probable ingredients, determine health content. Then: allow people to search for food based allergies, food aversions, calories. Generate pictures of what the food might look like, display the pics next to the food to make it more likely a user will buy that food.

Until one of your customers' children eats a peanut that the AI didn't infer would be an ingredient, and dies.

Generating fake pictures also seems like it would be more ordinary false advertising.

also requires the resto or manufacturer to list all ingredients, and most already list potential allergens.

but yeah liability would scare me, esp. because without it you can put the liability squarely on the restaurant or in some cases the person ordering / asking / buying.

Similar to the sibling comment, helpdesk ticket routing.

The volume of helpdesk tickets large enterprises deal with is very easily and vastly underestimated. If you can even route 30% away from the central triage with 90+% accuracy and drop everything else back to the central triage... you suddenly safe 2 FTEs in that spot in some places. And increase customer satisfaction for most of those tickets because they get resolved faster.

Or, as much as people hate it, chatbots as a customer front. Yes, everyone here as an expert in a lot of tech has had terrible experiences with chatbots. Please mark your hate with the word "Lemon" in the comments. But decently implemented chatbots with a few systems behind them can resolve staggering amounts of simple problems from non-techies without human interaction from the company deploying them. It remains important to eventually escalate to humans - including the history from all of these interactions to avoid frustrations, sure.

Or, ticket/request preprocessing. Remember how spelling that 10 digit account number to a call center agent hard of hearing sucks? Those 4 retries because of you not using a better way to communicate that number also costs the company. Now, you can push a few of these retries into an AI system. If you mail them, an AI system can try to extract information like account numbers, intent, start of the problem, problem descriptions and such into dedicated fields to make the support agents faster.

Companies are certainly overdoing it at the moment, I'm not denying that. But a lot of the support/helpdesk pre-screening can be automated with current AI/ML capabilities very decently. Especially if you learn to recognize and navigate it.

The last company I worked at eventually became a Big Tech. In the beginning though, we used to ask all engineers to pair with customer service folks to deal with ticket triage. When we got a bit bigger, we used to have rotations where eng would pair with customer service folks. Being on the other side of that was very eye-opening for all eng. Many used to come in with the same bias that you see on this site, that how dare you be routed to some automated service and how inhumane the service is. On the other side you see competent CS agents absolutely swamped with low-level questions that were often literally answered in docs and FAQ pages. I think getting transformer-based triage models correct can unlock tons of value.

Hard agree - i've heard frankly staggering "per support ticket" costs from every company i've worked for, or has publicly talked about customer support costs. Think $3-6 dollar per customer support ticket.

A UK company, Octopus has been doing some interesting work on GenAI <> customer support, which is helped by their "Energy provider in a box" software called Kraken (https://octopusenergy.group/kraken-technologies), which gives a single unified view over their operations.

They even have support agent level of personalisation - i.e; the agent will talk in the tone of voice of a given agent via fine-tuning of their chat history.

You group tickets into root cause and the future projected cost will now fully fund fixing the issue. Most companies, however, look at customer support a cost center instead of valuable insight it is.

I taught customer service / software engineers to process tickets from the singular queue and eliminated routing. Worked surprisingly well.

I have yet to see a chatbot in a customer service function that isn't strictly worse than a button. Usually, the button is "request refund / return" for whatever reason. It's like captcha stuff, web site owner is too dumb (no offense) to figure out how to handle spam so they offload that task onto the customer.

Lemon

and this is why consumers lose a bunch of money, so corporations can save $3-6 per help desk ticket. then consumers get stuck in a bot interface and can never break out of it (speaking from personal experience)

Well, an old one is OCR, especially handwritten OCR. I'm doing genealogy. There is SO MUCH old handwritten material that is never transcribed, and which requires special expertise to read (old and exotic handwriting styles) and interpret (place names, writing conventions, abbreviations).

It doesn't have to be perfect. It's not as if the actual data in there is perfect. It just has to be in a form where I can search it, ideally with named entities mapped.

Quality - like deciphering the writing on scrolls buried in volcanic ash in Herculaneum - gets all the attention. But what I really want is quantity - I want to be able to search through those 5000 pages of 200 year old mildly damaged cadastral records in dense handwriting. I want to relieve the army of kind retirees who currently transcribe these sorts of documents one by one based on their own needs.

bruh what are the retirees supposed to do once you've automated their hobby