Suppose that someone got an AI program working so that it was able to learn a rudimentary natural language. There is no reason why that program should be expected to understand everything. That would not make sense. Imagining that this program had only learned a little, it would not be able to disambiguate every phrase that might be thrown at it. So the test that it should be able to disambiguate anything is not a valid test. A qualified test then, is, after it was given some instruction in different subjects where some common word and words were used in different ways, could it 'understand' these different uses of the words as they pertain to the different subject domains? This qualified test would be difficult for most children but the ability to follow a discussion using terms that the child had learned should turn up some confirmatory evidence that the child had learned something about that subject. And with more practice the child would become better skilled at disambiguating the phrases that it had been taught. This kind of testing then can stand as the disambiguation test for innovative language-based AI projects in our age. Jim Bromer
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