Did you see the "Missing:
A big problem with English (natural language really) is that it doesn't come equipped with an explicit set of inference rules. Consequently, when someone uses natural language to communicate with an AI system, it's not really possible for that system to immediately connect the utterance to its store of knowledge. If only natural languages were like formal languages, which have proper inference and well-defined semantics. The thought that secretly they are was the intuition of Richard Montague*. But he was misguided.
Any AI natural language understanding system tries to transform the raw material of human language into something it can use, something more inferentially tractable. Usually that doesn't work too well, and even the latest statistical systems (which do well in surface-level speech-recognition and translation) show scant abilities to understand.
It's as well to remind ourselves just why natural languages are so unhelpful to AI designers. It's because they are a highly-optimised solution to a situated communications problem. Speech is a low-bandwidth, linear and slow channel for communicating time-critical thoughts. So speech is highly optimized to use every available constraint to speed up meaning transfer:
- volume, pitch, timbre and tone of voice
- shared and predictive knowledge of the conversational partner
- emotional cues
- physical gesturing and facial expressions
- environmental situation and context
Researchers are quite aware of this, of course. The topic area is called Pragmatics and it's hived off as a separate sub-discipline .. because it seems to require way too much modelling of the conversing agents in their specific environment, culture and history. In short, it's too hard.
But by abstracting away these additional constraints which channel and constrain meaning, we make the semantic understanding problem way too hard. Which is why we can't solve it.
A Google Translate system which mapped between a natural language and a formal language (with well-defined inference rules and semantics) would nevertheless be a boon to the designers of conversational AI systems, including chatbots. But Google doesn't have a corpus of First-Order Predicate Calculus sentences translationally-linked to English, so its deep learning systems can't crunch the data and add FOPC to its list of languages. Projects such as Cyc have attempted to do this stuff by hand .. with surprisingly little impact.
Again the way forward is embodied robotics and human baby conversational emulation.
* In a weird reprise of Alan Turing's fate, Wikipedia reports that Richard Montague 'died violently in his own home; the crime is unsolved to this day. Anita Feferman and Solomon Feferman argue that he usually went to bars "cruising" and bringing people home with him. On the day that he was murdered, he brought home several people "for some kind of soirée", but they instead robbed his house and strangled him.'
He was 40.