That's exactly what gave rise to the first "AI Winter". People had to hard-code things. But with NN and esp. Deep Learning, they thought there's no need to write programs for pattern recognition anymore; the "AI" just learns it on its own.
That wishful thinking has turned out to be dangerous tho, as we have moved towards an ML-dominated world where we don't even know how the ML algorithms produce specific results.
Add that to their bizarre behavior (like this example with Siri) and you'll realize chances of another AI Winter are not low. If we have to develop solutions to many context problems one by one, that may reduce so much of the hype and interest in "AI". We'd be basically back to square one.
That wishful thinking has turned out to be dangerous tho, as we have moved towards an ML-dominated world where we don't even know how the ML algorithms produce specific results.
Add that to their bizarre behavior (like this example with Siri) and you'll realize chances of another AI Winter are not low. If we have to develop solutions to many context problems one by one, that may reduce so much of the hype and interest in "AI". We'd be basically back to square one.