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It’s not “learning” anything though. Difference is causation vs correlation: If I learn how to boil water for example, there is close to 100% causation that he

It’s not “learning” anything though. Difference is causation vs correlation: If I learn how to boil water for example, there is close to 100% causation that heating water causes it to boil (notwithstanding we do not know everything about Physics, eg before we would say the earth is flat because we learnt it so, but that was incorrect, ie not everything we learn is true, it’s just a super high level of correlation) However if a machine learning model says the probability of water boiling is 99% after heating water, that is actually correlation. So I would distinguish it from learning In this example there’s not much different. But when you apply to more complex examples, the difference between causation and correlation become clearer

DubiousPusher 6y ago
You think people's ability to learn is really distinguished by an ability to discern causation and correlation? That does not comport with modern behavioral science.
- abhinav22 6y ago
  To some degree yes. For example, can the fields of mathematics and advanced physics or programming be studied to the degree they are with an understanding of causation? For some things, correlation can be sufficient, so I can see where you are coming from. As a better counterpoint: if we could not distinguish between causation and correlation, why is general AI so hard?
  - DubiousPusher 6y ago
    > can the fields of mathematics and advanced physics or programming be studied to the degree they are with an understanding of causation? Yes, pretty much. Newton's laws are a perfect example of something that establishes a correlation but are useful absent accurate causation. They did just fine until we needed something better. Einstein provided this but can we be so sure gravity as a result of curved space is "true" and not just a really good model? Perhaps the hunt for what quantum gravity will one day tell. > As a better counterpoint: if we could not distinguish between causation and correlation, why is general AI so hard? I think general AI is hard because for one it might be a fiction. For general AI to be real, we'd have to assume people posses "general intelligence". Or at the very least, were it beyond us, we'd have to assume we could tell if we had created it. What we are really trying to do with "general intelligence" is reproduce something that took 3.5 billion years of natural selection to design. We have only recently become capable of even creating machines with the kinds of part counts that biology comes with. Were we to produce "general intelligence" in the next thousand years I'd be surprised it came so easy.
    - abhinav22 6y ago
      I see where you are coming from and don’t disagree on many points. From a layman’s perspective, the causation vs correlation distinction I think works well still and I also think “machine learning” is a misrepresentation in its current use and limitations. But this is now getting into subjective opinion so it’s neither right or wrong. Nice talking to you on this topic :)
Yajirobe 6y ago
According to Hume neither the model nor you would know/see the causation. It would be correlation in both (an all other) cases

DubiousPusher 6y ago

You think people's ability to learn is really distinguished by an ability to discern causation and correlation? That does not comport with modern behavioral science.

abhinav22 6y ago
To some degree yes. For example, can the fields of mathematics and advanced physics or programming be studied to the degree they are with an understanding of causation? For some things, correlation can be sufficient, so I can see where you are coming from. As a better counterpoint: if we could not distinguish between causation and correlation, why is general AI so hard?
- DubiousPusher 6y ago
  > can the fields of mathematics and advanced physics or programming be studied to the degree they are with an understanding of causation? Yes, pretty much. Newton's laws are a perfect example of something that establishes a correlation but are useful absent accurate causation. They did just fine until we needed something better. Einstein provided this but can we be so sure gravity as a result of curved space is "true" and not just a really good model? Perhaps the hunt for what quantum gravity will one day tell. > As a better counterpoint: if we could not distinguish between causation and correlation, why is general AI so hard? I think general AI is hard because for one it might be a fiction. For general AI to be real, we'd have to assume people posses "general intelligence". Or at the very least, were it beyond us, we'd have to assume we could tell if we had created it. What we are really trying to do with "general intelligence" is reproduce something that took 3.5 billion years of natural selection to design. We have only recently become capable of even creating machines with the kinds of part counts that biology comes with. Were we to produce "general intelligence" in the next thousand years I'd be surprised it came so easy.
  - abhinav22 6y ago
    I see where you are coming from and don’t disagree on many points. From a layman’s perspective, the causation vs correlation distinction I think works well still and I also think “machine learning” is a misrepresentation in its current use and limitations. But this is now getting into subjective opinion so it’s neither right or wrong. Nice talking to you on this topic :)

Yajirobe 6y ago

According to Hume neither the model nor you would know/see the causation. It would be correlation in both (an all other) cases