Yes, but it's still misleading. As soon as someone says the words, "an AI", they have entered a narrative about the thing personified. The original subject is

Yes, but it's still misleading. As soon as someone says the words, "an AI", they have entered a narrative about the thing personified. The original subject is lost to an anthropomorphized facade. The adjective, "General" was originally meant as a classifier for quality, not category. That distinction is still present on the face of the word itself. An AGI is an AI that can compete with human intelligence. Adding "General" to the phrase, "Artificial General Intelligence" does nothing to define "Artificial" or "Intelligence". The distinction I just made is entirely based on symbolic meaning. Words are defined explicitly, and then put together. In this approach, the resulting meaning is independent of context: it's literal. Your distinction takes the opposite approach: an entire phrase - regardless of any symbolic definitions each word is known to have - is defined by the narrative it is surrounded with. In this approach, the resulting meaning is dependent on the context: it's literary. Large Language Models are famous for demonstrating the second approach: they implicitly model whatever patterns exist in a prompt's text, so that they can generate a "continuation" that follows those patterns, without ever needing a literal symbolic definition. This is exciting, because natural language - as the result of humans taking both literal and literary approaches - is ambiguous. The literal approach that traditional programming language parsers use is fundamentally limited to "context-free grammars", because ambiguity can only be resolved with literary context. The problem is that LLMs cannot be literal. They are only capable of inference, so they lose all of the functionally that symbolic definition would provide. The distinction I made earlier has the same limitation that parsers have: it ignores the surrounding narrative context that has evolved away from the original meaning: it's short-sighted. The distinction you made has the same limitation that LLMs have: it ignores the original symbolic meaning that is still present in each word: it's confidently imprecise. What matters is the result: By ignoring the literary context, the definition of "AI" is written in stone, and we lose the ability to talk around it. By ignoring the literal meaning, we imply "AI" tech is (by definition) capable of both literal and literary transformations. We can resolve both limitations by simply using new words. There is no need to say "AI" when "NLP" is more precise.