AI scientists in previous decades would have concluded that to do so, a general intelligence would have been needed But that was not the case at all - Watson is blatantly not a general intelligence. Big data and clever algorithms were all that were needed
Hindsight is a wonderful thing - at the time, it was probably completely reasonable to imagine that a general AI would be the only way to solve that problem. As Arthur C Clarke said: “Any sufficiently advanced technology is indistinguishable from magic.”
This is perhaps a little extreme in this instance, but as techniques and narrow AI solvers move into more areas and complete a large number of specific tasks, the ‘General AI’ line will become a moving target as it has in the past.
A robot can pick up a ball and throw it to Fred who is wearing a red jacket - 20 years ago that would have been truly amazing (and it still is), but as you say - it is simply a bunch of algorithms and data.
Possibly the only way to measure General AI (at least among AI researchers) would be to give it NO data, and let it go from there.
I'm not sure that's really fair; humans start with various predispositions which probably amount to some meaningful data by birth (I don't think it's much of a stretch to posit this, plenty of other animals which are born more developed certainly seem to start with a significant amount of hard coded data, so it seems reasonable to suppose that humans would have some,) and we count humans as general intelligences.
Thinking aloud:
Humans are examples of general intelligence - the only example we're sure of. Some humans have various degrees of autism (low level versions are quite common in the circles I've moved in), impairing their social skills. Mild autists nevertheless remain general intelligences, capable of demonstrating strong cross domain optimisation. Psychology is full of other examples of mental pathologies that impair certain skills, but nevertheless leave their sufferers as full fledged general intelligences. This general intelligence is not enough, however, to solve their impairments.
Watson triumphed on Jeopardy. AI scientists in previous decades would have concluded that to do so, a general intelligence would have been needed. But that was not the case at all - Watson is blatantly not a general intelligence. Big data and clever algorithms were all that were needed. Computers are demonstrating more and more skills, besting humans in more and more domains - but still no sign of general intelligence. I've recently developed the suspicion that the Turing test (comparing AI with a standard human) could get passed by a narrow AI finely tuned to that task.
The general thread is that the link between narrow skills and general intelligence may not be as clear as we sometimes think. It may be that narrow skills are sufficiently diverse and unique that a mid-level general intelligence may not be able to develop them to a large extent. Or, put another way, an above-human social intelligence may not be able to control a robot body or do decent image recognition. A super-intelligence likely could: ultimately, general intelligence includes the specific skills. But his "ultimately" may take a long time to come.
So the questions I'm wondering about are: