What does it mean for a machine to “understand”?

> Then animals do not understand.

I am agnostic regarding that, as I don't think there is any evidence that they do not attempt to build models that are consistent representations of reality.

I am assuming, based on my own experience, they also have this "internal lightbulb" going on when they think they have built the correct model. But whether they are actually cognizant of it (self-aware), I have no idea. (I guess what I am saying is that understanding and self-awareness are two different things.)

Very good observation, although I'd say this is still just understanding at the micro-level. A lot of what is going on in communication between people depends just as much on what hasn't been said, what would normally be said in this situation, having an idea of what the situation is in the first place, what was said recently or the last time you interacted with this person (which could potentially be a very long time ago), etc. I do believe that a lot or all of this can be posed as CSPs though.

On my reading list is "The proper treatment of events", a book which "studies the semantics of tense and aspect" within a formal framework of constraint logic programming[1]. There is other similar work in this area, like "Good-enough parsing, Whenever possible interpretation:a constraint-based model of sentence comprehension"[2].

[1] http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.10.... [2] https://hal.archives-ouvertes.fr/hal-01907632/file/CSLP-Blac...

I think this is partly down to us humans defining "intelligence" as "like us".

We have a very specific set of evolved traits that define our understanding of the universe. A lot of that is social. So our "understanding" of the phrase "call Carol" includes a wide range of social cues about what that means, and your example is perfect: "call Carol" means that I want to talk to her, and that would be better done in person if possible, but that "if possible" has a more-or-less specific range of "if she's within earshot so I can yell for her", which is limited to the range of a human voice (but not the maximum range, like screaming, but just a normal yelling range). Which is less if the door is closed, or there's music playing, or Kevin is trying to nap in the other room. And not at all if we're in a library, or concert, or even a public space where yelling would draw attention. If "call Carol" has to include all of these to qualify for "understanding" then I think I know some people who fail at this test.

My go-to thought experiment on this is Dolphins. Dolphins are intelligent, have language, etc. But their understanding of the world must be so different. Trying to explain to a dolphin what "tripping someone up" means is going to be tricky. They may understand the words, but they'll never understand the concept.

We swim in a sea of social cues and non-verbal communication. We can program an AI to imitate more and more of this, and be aware of more of it, but it's like teaching dolphins about long-distance running. It's never going to come naturally. And they're never going to evolve that understanding naturally (like we do as children) because it's not in their nature. We anthropomophise our machines a lot, and we assume that they'll grow (like children) to grok all of our social cues eventually, because our only experience of similar situations is, well, children. But they're just machines, designed for a single purpose. They're never going to grok this. They're never going to be "like us" and really understand all the social ramifications of "call Carol". At some point I think we're going to have to accept this, and say that the machine understands the phrase "call Carol" enough. TFA draws the line at the machine calling Carol, and that seems reasonable.

> Speaking as a psychologist, I’m flabbergasted by claims that the decisions of algorithms are opaque while the decisions of people are transparent. I’ve spent half my life at it and I still have limited success understanding human decisions. - Jean-François Bonnefon’s tweet (as quoted in https://p.migdal.pl/2019/07/15/human-machine-learning-motiva...)

> Siri was waiting for a command and executed the best command that matched. Which is, make a phone call.

ISTM there's no more "understanding" involved in this than when I touch the Contacts icon on my screen, then "C", "A", "R", etc until Carol's entry is displayed, and then I touch the Phone icon to initiate a call.

The fact that the interface used was sound-waves that the device recognised as matching the keyword "call" and the contact-list entry "Carol", rather than my finger touching specific areas of the screen, may be a handy feature. Of course it's a triumph of signal processing, fuzzy recognition, etc. But there's no more "understanding" involved than in the touch-screen version of the action, or in typing a command and parameter into a terminal window.