One way we might choose to draw these distinctions is using the technical vocabulary that teachers have developed. Reasoning about something is more than mere Comprehension: it would be called Application, Analysis or Synthesis, depending on how the reasoning is used.
So would you say that GPT-2 has Comprehension of “recycling” but not Comprehension of “in favor of” and “against”, because it doesn’t show even the basic understand that the latter pair are opposites? I feel like even teachers’ technical vocabulary isn’t great here because it was developed with typical human cognitive development in mind, and AIs aren’t “growing up” the same way.
So would you say that GPT-2 has Comprehension of “recycling” but not Comprehension of “in favor of” and “against”, because it doesn’t show even the basic understand that the latter pair are opposites?
Something like that, yes. I would say that the concept “recycling” is correctly linked to “the environment” by an “improves” relation, and that it Comprehends “recycling” and “the environment” pretty well. But some texts say that the “improves” relation is positive, and some texts say it is negative (“doesn’t really improve”) and so GPT-2 holds both contradictory beliefs about the relation simultaneously. Unlike humans, it doesn’t try to maintain consistency in what it expresses, and doesn’t express uncertainty properly. So we see what looks like waffling between contradictory strongly held opinions in the same sentence or paragraph.
As for whether the vocabulary is appropriate for discussing such an inhuman contraption or whether it is too misleading to use, especially when talking to non-experts, I don’t really know. I’m trying to go beyond descriptions of GPT-2 “doesn’t understand what it is saying” and “understands what it is saying” to a more nuanced picture of what capabilities and internal conceptual structures are actually present and absent.
So would you say that GPT-2 has Comprehension of “recycling” but not Comprehension of “in favor of” and “against”, because it doesn’t show even the basic understand that the latter pair are opposites? I feel like even teachers’ technical vocabulary isn’t great here because it was developed with typical human cognitive development in mind, and AIs aren’t “growing up” the same way.
Something like that, yes. I would say that the concept “recycling” is correctly linked to “the environment” by an “improves” relation, and that it Comprehends “recycling” and “the environment” pretty well. But some texts say that the “improves” relation is positive, and some texts say it is negative (“doesn’t really improve”) and so GPT-2 holds both contradictory beliefs about the relation simultaneously. Unlike humans, it doesn’t try to maintain consistency in what it expresses, and doesn’t express uncertainty properly. So we see what looks like waffling between contradictory strongly held opinions in the same sentence or paragraph.
As for whether the vocabulary is appropriate for discussing such an inhuman contraption or whether it is too misleading to use, especially when talking to non-experts, I don’t really know. I’m trying to go beyond descriptions of GPT-2 “doesn’t understand what it is saying” and “understands what it is saying” to a more nuanced picture of what capabilities and internal conceptual structures are actually present and absent.