I had a conversation with today about challenges in doing VUI design that are difficult and tedious to pay attention to. One of the biggest ones is interestingly is polarity. I was chatting with my friend Ann how colleagues had made a claim about good conversation design, and rather ironically used a word that literally meant the opposite of what was intended.
(The word “preempt” was used to mean “thoughtfully anticipate” instead of “prevent” or “replace with”.)
Ann pointed out that we knew what they meant, but I had to disagree in spirit, since we were talking about speech and text recognition system design.
Why it’s interesting
In human language, polarity can be expressed at probably any level. Like positive and negative numbers, within the systems we use, their effect on meaning is intuitive. This is how devices like irony can work without explanation.
Our interpretation of language, being more about intuitive meaning than literal meaning allows us to “get” the meaning even when the words used don’t actually mean what’s intended. What’s more, polarity implies the existence of its opposite.
If I say “on” for “off” it’s easier to forgive a detail when you get the gist. “Don’t forget to turn the lights on before you leave” makes sense pragmatically without correction to a human, but not, “Don’t forget to turn the lights blue before you leave.”
Why it matters
Neither of these would be understood correctly by a machine. NLP systems interpret meanings from the literal words. They only have what you said to go on.
Quite unintentionally, a pretty good case was made about why conversation design is hard to do at all, let alone well. Static models and intents are the source of meaning, which is derived from text, which makes things quite rigid.
It’s not fun, and even quite boring, for this kind of rigid attention to detail to be required in order for software work as intended. That might be why you can’t remember the last time you invited a bunch of conversation designers to a party.
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