I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can answer reading comprehension questions" would be more correct?
We test whether a human have "basic reading comprehension" by asking them reading comprehension questions. If they answer the questions successfully, then we assume that they have this "reading comprehension" skill. Therefore, if an AI can answer these questions, then it must also have "reading comprehension".
Maybe these "reading comprehension questions" don't actually test reading comprehension, just pattern matching and sentence parsing. In which case, we shouldn't be asking these questions to anyone (human or AI). So what we need are new questions.
We test human "reading comprehension" with the assumption that humans have an underlying world model.
This is starkly different from a machine whose only ability is information retrieval -- this program (and more advanced versions e.g Freebase) parse and restructure text to be more retrievable. But there is no comprehension because there is no world model.
You wouldn't call parsing a google search query "reading comprehension."
But if a computer is able to do the same thing as a human does (answer a simple question with pattern recognition and sentence parsing), then the internal mechanism of how a computer does it seems like mere trivia/jargon rather than anything fundamentally important to intelligence. A computer may have reading comprehension without having it in exactly the same way that a human does.
But it's true that we do have a underlying world model by which we understand passages. And that world model is pretty essential if we are to answer more complicated questions. So since it's pretty clear computers can handle the "informational retrieval" side of reading, we should now be focused on generating a "world model" based on text.
the internal mechanism of how a computer does it seems like
mere trivia/jargon rather than anything fundamentally
important to intelligence. A computer may have reading
comprehension without having it in exactly the same way that
a human does.
Yes, it is trivia what we decide to call it, and computers may someday have "intelligence" or "sentience" without having it in the same way that we do. However I think mechanically structuring data and building a querying tool over that cannot be considered "intelligence" or "comprehension" in the sense we seem to speak of here.
since it's pretty clear computers can handle the
"informational retrieval" side of reading, we should now be
focused on generating a "world model" based on text.
Yes, that's what Google's working on with Knowledge Graph. It's quite good, it's integrated with search already.
Comments
We test whether a human have "basic reading comprehension" by asking them reading comprehension questions. If they answer the questions successfully, then we assume that they have this "reading comprehension" skill. Therefore, if an AI can answer these questions, then it must also have "reading comprehension".
Maybe these "reading comprehension questions" don't actually test reading comprehension, just pattern matching and sentence parsing. In which case, we shouldn't be asking these questions to anyone (human or AI). So what we need are new questions.
We test human "reading comprehension" with the assumption that humans have an underlying world model.
This is starkly different from a machine whose only ability is information retrieval -- this program (and more advanced versions e.g Freebase) parse and restructure text to be more retrievable. But there is no comprehension because there is no world model.
You wouldn't call parsing a google search query "reading comprehension."
But if a computer is able to do the same thing as a human does (answer a simple question with pattern recognition and sentence parsing), then the internal mechanism of how a computer does it seems like mere trivia/jargon rather than anything fundamentally important to intelligence. A computer may have reading comprehension without having it in exactly the same way that a human does.
But it's true that we do have a underlying world model by which we understand passages. And that world model is pretty essential if we are to answer more complicated questions. So since it's pretty clear computers can handle the "informational retrieval" side of reading, we should now be focused on generating a "world model" based on text.