The Fair Witness was a job that Heinlein made up for Stranger in a Strange Land. Fair Witnesses were supposed to reliably report what they saw without judgement

The Fair Witness was a job that Heinlein made up for Stranger in a Strange Land. Fair Witnesses were supposed to reliably report what they saw without judgement - including their subjective judgement in their report. The example exchange is: "Is that house over there brown?" "It is brown on this side." Dall-E (and other ML systems) feel like fair witnesses for our cultural milieu. They basically find a series of weighted connections between every phrase we've thought to write down or say about all images and can blend between those weights on the fly. By any assessment it's an amazing feat - as is the feat to view their own work and modify it (though ofc it's from their coordinate system so one does expect it would work). In one sense - asking if the machine "understands" is beside the point. It does not need to 'understand' to be impressive (or even what people claim when they're not talking to Vice media or something). In another sense, even among humans, "understanding" is both a contested term and a height that we all agree we don't all reach all of the time. One can use ideas very successfully for many things without "understanding" them. Sometimes people will, like, turn this around and claim that: because humans don't always understand ideas when they use them, we should say that ML algorithms are doing a kind of understanding. I don't buy it - the map is not the territory. How ML algorithms interact with semantics is wholly unlike how humans interact with them (even though the learning patterns show a lot of structural similarity). Maybe we are glimpsing a whole new kind of intelligence that humans cannot approach - an element of Turing Machine Sentience - but it seems clear to me that "understanding" in the Human Sentience way (whatever that means) is not part of it.