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I get your point, but you're making my head spin here from the sea-sickness involved in being asked to acknowledge that all viewpoints are equally valid. Peopl
by bravura 4y ago
I get your point, but you're making my head spin here from the sea-sickness involved in being asked to acknowledge that all viewpoints are equally valid.
People care about human-like intelligence. That's the point. We also care about trading and physics. But when we talk about the specific question of human-like intelligence (and not other kinds of intelligence), the human reality is the appropriate substrate. Acknowledging, of course, that for non-human intelligence there might be other substrates and also acknowledging that non-human intelligence can be valuable to people.
But let me take your argument to the extreme.
In classical machine learning theory, there's a proof of the value of bias. Bias plays a crucial role in guiding the learning process. If all hypotheses are considered equally possible, learning becomes infeasible due to the lack of any preference or constraint on the hypothesis space. Bias, in this context, refers to the inherent assumptions a learning algorithm makes about the data's underlying structure. Introducing some bias into the model allows it to favor certain types of solutions, thus narrowing down the hypothesis space and making learning feasible.
The logical extreme of your argument---if I understand it correctly---is that all machine learners are equally valuable. For example, an AI that learns a domain that is completely removed from all human values and thus we would be completely agnostic to and ignorant of, ipso facto, because it does not pertain or relate to us at all. In which case, who cares? By "who", I mean people. No one. By construction.
[edit: I'll give an example here. Let's say I randomly pick a corpus of images that are pure noise. I induce an algorithm to model that noise. That model will learn something valid but in a domain completely divorced from anything with human impact.]
So if we can acknowledge that some forms of learning are more important, merely by virtue of the fact that humans have preference, then perhaps we can perhaps wend our way back to agreeing that human-like intelligence is one valuable kind of intelligence, in addition to other valuable forms of intelligence like trading or board games.
We can play the game all day of "everything is subjective" and "up is down and black is white", but at the end of the day, for human beings, it's night.
- IIAOPSW 4y agoThe "general" in "general intelligence" is when you can hack together a picture of other domains by stitching together objects in your own domain. Our reasoning system only evolved to talk about 3 physical space dimensions and 1 time dimension and Newtonian physics and euclidean geometry. Things like trades and ownership and train lines aren't basic objects in our domain and the abstract rules governing their relations are completely unlike those rules of object properties like heavy and bright and loud. Can an intelligence stuck in a different substrate also come up with abstractions and generalize its intelligence? Maybe >The logical extreme of your argument---if I understand it correctly---is that all machine learners are equally valuable. That's not quite it. My argument is that general intelligence can in principle be grounded in the semantics of pretty much any baseline of objects and relations. The specific base line properties such as size, shape, color etc is orthogonal to the property of intelligence. We don't need to give the machine familiar sensory input for general intelligence, and general intelligence would not imply that it can do well at conversation in our domain (merely that it can talk about our domain in a very contorted way if it had to). I'll admit if the goal is to make an intelligence "in our image" then sensory modalities will get us there faster. It will also lead people to erroneously believe that the key ingredient to general intelligence is physical grounding in our reality. My counter example to that belief is general intelligence embedded in a pure language model, which is perfectly recognizable as "in our image" AGI just so long as you stick to topics like transit lines and chess and whatever else can be grounded in words alone.
- bravura 4y agoThe definition of „general intelligence“ as chess, transit routing, and pure language, is not a commonplace interpretation of this term of art. But with that interpretation in mind, I see your point.
- IIAOPSW 4y agoIt can still be "general" outside of those areas, it will just be prone to mistakes of common sense. So to rephrase it all tersely: Sensory grounding isn't needed for general intelligence or for computers to be capable of "understanding" (as per the title), but it is needed for that intelligence to have what we consider common sense. But I'm glad I got my point made. Great talk.