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Comment by debaserab2 | Hacker News Reader

> Significantly economically impactful in some cases- obvious examples of call centers and first-line customer support.

Is it that obvious?

Yesterday I had a trivial but uncommon issue with my pharmacy. I reached out to them online - their chatbot was the only channel available. I tried, over the course of 20 minutes and 3 restarted sessions, to communicate an issue that a human would have been able to respond to in 30 seconds. Eventually I just gave up and got the prescription filled elsewhere.

No doubt this pharmacy saved money by cutting support staff. I just think it's easy to see these solutions and cost savings without bothering to look at how much of a frustrating experience it can be for a customer.

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It is very easy to measure costs associated with a customer.

It is nearly impossible to measure the customers lost.

And you may never return, which they’ll never know.

Unless all pharmacies go to automation, in which you're screwed.

And don't think it can't happen. Consolidation in to just a few companies us happening in huge numbers of industries.

That’s the killer, and it gets bad really fast once an industry “decides” on something. And people simply fall through the cracks.

Do you have any reason to believe that the Chatbot was GPT3.5 or GPT4 based?

I’d be surprised if something like a pharmacy managed to adopt a tech that quickly. In my experience non-tech industries often take quite a while to adopt.

How are you gonna answer things like pricing? Issue with pharmacies is the super complicated and super secretive pricing structure. A good UI can solve this if they want to drop the secrecy.

I have seen plenty of chatbots used by my IT company and 3rd party suppliers I deal with. They really just turn what used to be phone tree to something text based. Pretty basic keyword search and recipes from my experience - that I usually like to escape to a human as soon as I can. I welcome a proper conversational AI chatbot that actually gets stuff done.

Seems unlikely they would be trusting a system that so willingly makes up stuff to provide a customer with life-critical advice about medications

I don't think so, I assume it's some more dated ML approach -- my point is moreso that it's not obvious that it's a good solution for this problem yet.

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