Reply to thread

Message

<blockquote data-quote="pemerton" data-source="post: 9323781" data-attributes="member: 42582">[USER=6790260]@EzekielRaiden[/USER]A key feature of occasion sentences is anaphora - both anaphoric pronouns, and also anaphora-like constraints on the content of referring terms. In mainstream models these are handled by various sorts of quantification devices (including restricted domains of quantification to handle the anaphora-like constraints) - eg &quot;I have a dog. It is hairy. My couch gets covered in hair!&quot; The pronoun &quot;it&quot; refers to the dog that I have. And the noun hair in the final sentence is referring to dog hair, not hair in general - that's the restricted domain of quantification (or whatever other technical device you want to use - personally I don't accept quantification as a good analysis of reference, but I think that's by-the-by for present purposes).Let's suppose you can &quot;teach&quot; your AI model to parse these anaphoric elements - I don't know of any knock-down argument that this can't be done by way of generating probabilities of word-correlations based on inspection of millions or billions of sentences. (Gareth Evans and Donald Davidson have good arguments that it will require an interpretation manual rather than a Quinean or &quot;Chinese Room&quot; translation manual: but I don't know of any argument that what the AI is generating is necessarily the latter rather than the former.)My point is that even so, the AI has no access to evidence, because it has no access to the occasions on which occasion sentences are produced, which are in turn the pathways to ascertaining expertise when it comes to the production of eternal sentences.Thus, more semantically powerful/sophisticated AI won't solve the falsehood problem, as best I can tell. There needs to be a whole other input - namely, evidence as a constraint on the production of occasion sentences. Humans' embodiment in the world generates that constraint in our case. I have no idea what it would look like for an AI. (Though I'm sure there is writing on the issue - there always is!)</blockquote>

[QUOTE="pemerton, post: 9323781, member: 42582"] [USER=6790260]@EzekielRaiden[/USER] A key feature of occasion sentences is anaphora - both anaphoric pronouns, and also anaphora-like constraints on the content of referring terms. In mainstream models these are handled by various sorts of quantification devices (including restricted domains of quantification to handle the anaphora-like constraints) - eg "I have a dog. It is hairy. My couch gets covered in hair!" The pronoun "it" refers to [I]the dog that I have[/I]. And the noun [I]hair[/I] in the final sentence is referring to [I]dog hair[/I], not hair in general - that's the restricted domain of quantification (or whatever other technical device you want to use - personally I don't accept quantification as a good analysis of reference, but I think that's by-the-by for present purposes). Let's suppose you can "teach" your AI model to parse these anaphoric elements - I don't know of any knock-down argument that this can't be done by way of generating probabilities of word-correlations based on inspection of millions or billions of sentences. (Gareth Evans and Donald Davidson have good arguments that it will require an interpretation manual rather than a Quinean or "Chinese Room" translation manual: but I don't know of any argument that what the AI is generating is necessarily the latter rather than the former.) My point is that [I]even so[/I], the AI has no access to evidence, because it has no access to the occasions on which occasion sentences are produced, which are in turn the pathways to ascertaining expertise when it comes to the production of eternal sentences. Thus, more semantically powerful/sophisticated AI won't solve the falsehood problem, as best I can tell. There needs to be a whole other input - namely, evidence as a constraint on the production of occasion sentences. Humans' embodiment in the world generates that constraint in our case. I have no idea what it would look like for an AI. (Though I'm sure there is writing on the issue - there always is!) [/QUOTE]

Verification