Artificial Intelligence is a rather pernicious label to attach to a very mixed bunch of activities, and one could argue that the sooner we forget it the better. It would be disastrous to conclude that AI was a Bad Thing and should not be supported, and it would be disastrous to conclude that it was a Good Thing and should have privileged access to the money tap. The former would tend to penalise well-based efforts to make computers do complicated things which had not been programmed before, and the latter would be a great waste of resources. AI does not refer to anything definite enough to have a coherent policy about in this way.---Dr. R. M. Needham, in a commentary on the Lighthill Report and the Sutherland Reply, 1973
43 years later...
There is already strong demand for engineers and scientists working on artificial intelligence in many of the fields you mention, and many more. But expertise in making real-time systems for controlling trains doesn't make you know anything about robotics. Analyzing human behavior to detect crime has virtually nothing in common with self-driving cars (beyond CS/pattern recognition building blocks). There is never going to be demand for someone with a broad sense of all these areas without any deep expertise, and there is never going to be someone with 300 PhDs who can work in all of them. TL;DR -- AI is not a branch, it's a tree. --Matthew Read, in a comment on Area 51 Stackexchange, 2016
AI is a label that is applied to a "very mixed bunch of activities". The only unifying feature between all those activities is the fact that they deal with machines in some fashion, but since there are so many ways to use a machine, the field's output may seem rather incoherent and incongruent. It does seem to make more sense for the AI field to collapse entirely, and instead be replaced by a multitude of specialized fields that don't really interact with one another. Sir James Lighthill appeared to have supported this sort of approach within his 1973 report on the state of artificial intelligence research.
Yet, today, this Artificial Intelligence SE exist, and we still talk of AI as a unified, coherent field of study. Why did this happen? Why did AI survive, despite its "big tent" nature?