I don't think this article is correct - it's not right to say that customers don't want chatbots, it that customers don't want the chatbots of today.
> Instead, the reason people go to customer service is because of a question that’s so specific, or complicated, or gnarly in some respect, that there’s no way the app will have the answer: you need a human.
This is the thrust of the whole thing, and the problem it's not looking quite deep enough at what people want. People don't want a human - people want their problem solved.
A human is probably the best way to do that, but realistically, if you consider the role of a human in these situations, it's as an interface between the customer and an internal system. The human translates natural language into a series of actions in some computer program (or maybe multiple programs and also communication with other humans).
This is something that LLMs will inevitably be better than humans at. I just called my new health insurance company to get my member number. I spoke to a woman who first had to open up my account and spend some time looking at information. An LLM will do this instantly, and the aggregate time savings of this across all customer service calls will be enormous. That's on top of the fact that no one will wait on hold because all agents are busy.
She eventually realized she had to transfer me to another department. She gave me the direct phone number for that department then transferred me. Except instead of transferring me, she dropped the call. Then I called the direct number she gave me, and it was the department for cancer and complex medical claims. We've all had experiences like this.
Humans are not anywhere near perfect at this job. LLMs may not ever be perfect either, but they'll be better. A human at a call center either needs to be trained, which is costly and time consuming, or they need to be given rote instructions for all possible tasks. Neither of these make them particularly well-equipped for questions "so specific, or complicated, or gnarly."
Obviously this won't all happen overnight, but it's not tough to imagine that cases like Wendy's replacing their drive thru employees with chatbots can be successful in the immediate future. A Wendy's employee in that role just hears natural language and translates it to a series of button presses on a screen representing a very much finite number of possibilities. This is well within the capabilities of GPT-4. I think we'll see this more and more often for low-level customer service, with the chatbot passing the user off to a human for more complex things. The chatbot will move further and further up the stack of complexity until it's doing everything.