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The problem of induction since Hume has been a massive ideological misdirection against the possibility of knowledge. We do not use induction. We use abduction.

The problem of induction since Hume has been a massive ideological misdirection against the possibility of knowledge. We do not use induction. We use abduction. We first posit a universal, and then each subsequent data point is taken to confirm or delimit the universal. With a clear counter-example, the universal is dropped. As soon as the child touches the fire once, the conclusion "fire is always dangerous" is reached. This is impart why all ML (etc.) approaches based on conditional probability break: they are subject to the problem of induction. You cannot do science with statistics: there is nothing in the data that generalises. The generality is the hypothetical properties of the data generating process itself. ie., the shadows on the wall of Plato's cave cannot be averaged to produce the vases on the outside. It is the properties of the vases (the universals) that produce the shadows -- there are an infinite number of possible shadows, and no statistical operation on any amount of them reverses to "clay pot"

ur-whale 3y ago
> You cannot do science with statistics The entire team at CERN would beg to differ. So would all of the field of cosmology. So would the entire medical profession, researchers and practitioners - although I do agree that calling medicine a science is a stretch. You reasoning may be sound, but as in the example you give of child and the fire, your theory has the minor problem that it doesn't fit reality.
- mjburgess 3y ago
  Some scientists use statistics, sure -- by "doing science" I mean directly explaining how the world works. The way that (actual,) scientists use statistics is to "choose between possible vases". Suppose we're in plato's cave: we notice strange shadows. We then build pots inside the cave to match those shadows. different pots produce indistinguishable ones; and some pots produce impossible shadows. Here we can statistically analyses all the shadow data to select the best possible pot model. You can see that we never get to certainty, because there's always a class of pots producing identical shadows. So we use stats + "theoretical virutes" to select the pot we think most likely. My point is that in this story stats was never used to build the pots. Such a thing is provably impossible. This is, essentially, the problem of induction. And it's why the ML approach to pot = "compression of the shadows" breaks. It only works if you never move around the cave, ie., are always sat in exactly the position that the "compressed shadow" looks identical to the real one.
  - mjan22640 3y ago
    The goal of science is to provide predictive models of the observed data. Explaining 'how the world works' is a bit too ambitious. You need to reach to religion for that.
    - mjburgess 3y ago
      I know of no such scientific model. Indeed, almost all of them do not predict observed data. Newton's universal law of gravitation didn't predict huge amounts of stuff in the solar system. Rather than say it's wrong, we supposed there were missing planets. All models i'm aware of "predict" in the sense that they make existence claims; they don't "predict" observations -- on the latter, they'd basically all 'wrong'. The body of science we call "gravity, space/time, etc." makes the following existence claims: there is a sun, earth, planets, there are forces, masses,; these have properties that give rise to interactions; etc. From this body of knowlege, most of what we can predict abotu the observable universe is wrong. simply because, ex hyp., we arent able to observe enough of it. The models here arent wrong, we just do not have enough data to match them to observations. The world really has forces,masses,planets,etc. and they interact such that F=GMm/r^2 subject to {some constraints}. But if we use that to predict where "everythign should be", nothing is in the right place. We're missing a lot of "Everythign". This "science predicts observations" is humean problem of induction BS. It's never been true; it's radically sceptical; and is a deeply broken model explaining how we know things. If we had to literally have models from observations to observations, knowledge would be impossible.
      - ur-whale 3y ago
        > I know of no such scientific model. Indeed, almost all of them do not predict observed data. Now you're being entirely unreasonable. How did NASA put people on the moon? How did we fly satellites to the outer reaches of the solar system using orbital sling effects? Clearly because the Newtownian model of gravity is entirely wrong. We only pulled it off by chance.
        mjburgess 3y ago
mellosouls 3y ago
The problem of induction since Hume has been a massive ideological misdirection against the possibility of knowledge. Hume's observations were shocking, precisely because they undermined the most foundational of our assumptions and they have never been satisfactorily countered since; the use here of "ideological" and "misdirection" then seems rather unfair to Hume (though I acknowledge your use of "since") - he flagged our own misdirection in the most un-ideological way imaginable.
- mjburgess 3y ago
  The last illusion sceptics are subject to is scepticism itself. The final illusion is that we are separated from the world. Without this premise, hume has nothing to say

ur-whale 3y ago

> You cannot do science with statistics The entire team at CERN would beg to differ. So would all of the field of cosmology. So would the entire medical profession, researchers and practitioners - although I do agree that calling medicine a science is a stretch. You reasoning may be sound, but as in the example you give of child and the fire, your theory has the minor problem that it doesn't fit reality.

mjburgess 3y ago
Some scientists use statistics, sure -- by "doing science" I mean directly explaining how the world works. The way that (actual,) scientists use statistics is to "choose between possible vases". Suppose we're in plato's cave: we notice strange shadows. We then build pots inside the cave to match those shadows. different pots produce indistinguishable ones; and some pots produce impossible shadows. Here we can statistically analyses all the shadow data to select the best possible pot model. You can see that we never get to certainty, because there's always a class of pots producing identical shadows. So we use stats + "theoretical virutes" to select the pot we think most likely. My point is that in this story stats was never used to build the pots. Such a thing is provably impossible. This is, essentially, the problem of induction. And it's why the ML approach to pot = "compression of the shadows" breaks. It only works if you never move around the cave, ie., are always sat in exactly the position that the "compressed shadow" looks identical to the real one.
- mjan22640 3y ago
  The goal of science is to provide predictive models of the observed data. Explaining 'how the world works' is a bit too ambitious. You need to reach to religion for that.
  - mjburgess 3y ago
    I know of no such scientific model. Indeed, almost all of them do not predict observed data. Newton's universal law of gravitation didn't predict huge amounts of stuff in the solar system. Rather than say it's wrong, we supposed there were missing planets. All models i'm aware of "predict" in the sense that they make existence claims; they don't "predict" observations -- on the latter, they'd basically all 'wrong'. The body of science we call "gravity, space/time, etc." makes the following existence claims: there is a sun, earth, planets, there are forces, masses,; these have properties that give rise to interactions; etc. From this body of knowlege, most of what we can predict abotu the observable universe is wrong. simply because, ex hyp., we arent able to observe enough of it. The models here arent wrong, we just do not have enough data to match them to observations. The world really has forces,masses,planets,etc. and they interact such that F=GMm/r^2 subject to {some constraints}. But if we use that to predict where "everythign should be", nothing is in the right place. We're missing a lot of "Everythign". This "science predicts observations" is humean problem of induction BS. It's never been true; it's radically sceptical; and is a deeply broken model explaining how we know things. If we had to literally have models from observations to observations, knowledge would be impossible.
    - ur-whale 3y ago
      > I know of no such scientific model. Indeed, almost all of them do not predict observed data. Now you're being entirely unreasonable. How did NASA put people on the moon? How did we fly satellites to the outer reaches of the solar system using orbital sling effects? Clearly because the Newtownian model of gravity is entirely wrong. We only pulled it off by chance.
      - mjburgess 3y ago

mellosouls 3y ago

The problem of induction since Hume has been a massive ideological misdirection against the possibility of knowledge. Hume's observations were shocking, precisely because they undermined the most foundational of our assumptions and they have never been satisfactorily countered since; the use here of "ideological" and "misdirection" then seems rather unfair to Hume (though I acknowledge your use of "since") - he flagged our own misdirection in the most un-ideological way imaginable.

mjburgess 3y ago
The last illusion sceptics are subject to is scepticism itself. The final illusion is that we are separated from the world. Without this premise, hume has nothing to say