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Say you have to enter a story to a computer. Now, the computer has to identify the philosophical concept on which the story is based, say:

  1. Was it a "self-fulfilling prophecy"?

  2. Was it an example of "Deadlock" or "Pinocchio paradox situation"?

  3. Was it an example of how rumours magnify? or something similar to a chain reaction process?

  4. Was it an example of "cognitive dissonance" of a person?

  5. Was it a story about "altruism"?

  6. Was it a story about a "misunderstanding" when a person did something "innovative" but it accidentally was innovated earlier so the person was "falsely accused" of "plagiarising"?

And so on.

Given that the story is not only a heavy rephrase of the pre-existing story; not only character names and identities are totally changed, but the context completely changed, the exact tasks they were doing are changed.

Can computers identify such "concepts" from stories? If yes, then what mechanism do they use?

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No. This is currently out of the scope for any language processing system. It requires a general understanding of abstract concepts which is not possible for machines at present.

In order to recognise a self-fulfilling prophecy, you first need to identify that something is a prophecy. So it needs to be something that expresses a possible future state, for which you need to identify what possible future states are; and then you need to see whether it is self-fulfilling. Conceptually this is far too complex to do.

You might get away for some of these with formal criteria (eg use of future tense for something describing a future state/event), but this is far too imprecise.

"Altruism" requires knowledge about typical expected behaviour; you would need to be able to identify motives behind people's actions, and then decide whether it was altruistic or not. This is just too complex for now (and the foreseeable future).

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    $\begingroup$ When one reviews cutting-edge AI narrative output, it's clear that the algorithms understand syntax (they can structure sentences and paragraphs, and write in various formats) and equally clear the algorithms have no semantic understanding of the content itself. $\endgroup$
    – DukeZhou
    Commented Jul 16, 2019 at 21:48
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    $\begingroup$ @DukeZhou Indeed -- structure is pretty much in hand, but the meaning (both semantic and pragmatic) of that structure is still far outside our grasp. $\endgroup$
    – Oliver Mason
    Commented Jul 17, 2019 at 8:28

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