Expert systems are not dead.
We use them at work for the diagnosis of mechanical parts rather than human bodies. We don't call them expert systems but they are exactly that. There is a database of potential failures, repairs and verifications, and it will suggest a troubleshooting procedure taking cost into account. It means that it may try unlikely causes first if they are easy to check. It also has simple learning capabilities.
The problem with expert systems is that it needs a curated and complete database. It is possible to do with mechanical parts as they are well specified and failure modes are well documented. The top-down approach comes naturally because that's how components in a mechanical system are designed. By comparison, human bodies are a complex mess.
As for ChatGPT, it is a pure product of technical advances. Neural networks are an old idea, they knew about the theory in the 60s, and we had implementations in the 80s. The problem is that with little data and limited computing power, they were little more than toys. They have been made practical in the last few years only because of the "rich internet" on one side and lots of powerful GPUs on the other. And the way I understand it, recent advances in deep learning technology is not really fundamental research, more like trying a bunch of stuff and see what sticks, again made possible by lots of data and computing power.