3 ms·

> The reason that I know "The cup is in my hand" is not because P("The cup is in my hand"|HistoricalTexts) > P(not "The cup is in my hand"|HistoricalTexts) I m

> The reason that I know "The cup is in my hand" is not because P("The cup is in my hand"|HistoricalTexts) > P(not "The cup is in my hand"|HistoricalTexts) I mostly agree with your points, but I still disagree with this premise. Humans (and other animals) absolutely are statistical reasoning machines. They're just advanced ones which can process more than "text" - they're multi-modal. As a super dumb-simple set of examples: Think about the origin of the phrase "Cargo Cult" and similar religious activities - people will absolutely draw conclusions about the world based on their learned observations. Intellectual "reasoning" (science!) really just relies on more probabilities or correlations. The reason you know the cup is in your hand is because P("I see a cup and a hand"|HistoryOfEyesight) + P("I feel a cylinder shape"|HistoryOfTactileFeeling) + .... > P(Inverse). You can pretend it's because humans are intelligent beings with deep reasoning skills (not trying to challenge your smarts here!), but humans learn through trial and error just like a NN with reinforcement learning. Close your eyes and ask a person to randomly place either a cup from your kitchen in your hand or a different object. You can probably tell which one is it is. Why? Because you have learned what it feels like, and learned countless examples of cups that are different, from years of passive practice. Thats basically deep learning.

mjburgess 3y ago
I mean something specific by "statistics": modelling frequency associations in static ensembles of data. Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). That animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt. It's a failure of ecological salience mechanisms in regulating the "experimental learning" that animals engage in. Eg., with the cargo cults the reason they adopted that view was because their society had a "big man" value system based on material acquisition and western waring powers seemed Very Big and so were humiliating. In order to retain their status they adopted (apparently irrational) theories of how the world worked (gods, etc). From the outside this process might seem statistical, but it's the opposite. Their value system made material wealth have a different causal salience which was useful in their original ecology (a small island with small resources), but it went haywire when faced with the whole world. Eventually these mechanisms update with this new information, or the tribe dies off -- but what's going wrong here is that the very very non-statistical learning ends up describable that way. This is indeed, why we should be very concerned about people skinner-boxing themsleves with LLMs
- data_maan 3y ago
  > Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). That animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt. RL is doing just this, simulating an environment. And we can have an agent "learn" in that environment. I think tying learning to a body is too restrictive. The You strongly rely on the assumption that "something else" generates the statistics we observe, but scientifically, there exists little evidence whether that "something else" exists (see eg the Bayesian brain).
  - mjburgess 3y ago
    You need some way of inducing distributions in reality, ie., making the ice cube. If you're just subject to time-varying, random, stochastic, perceptual distributions you have no way of estimating the properties of the data generating process (reality). You need to be the one in control of the distribution in order to study it: this is the lesson of the whole history of science as an experimental discipline.
    - drdeca 3y ago
      What about astronomy and cosmology?
- vineyardmike 3y ago
  > Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). The "experiment" of life is what defines the statical values! Experimentation is just learning what the statistical output of something is. If I hand you a few dice, you'd probably be able to guess the statistical probability of every number for given roll. Because you've learned that through years of observation building a mental model. If I hand you a weighted die, suddenly your mental model is gone, and you can re-learn experimentally by rolling it a bunch. How can you explain experimental learning except "statistically"? > they adopted (apparently irrational) theories of how the world worked (gods, etc) They can be wrong without being irrational. Building an airport doesn't make planes show up, but planes won't show up without an airport. If you're an island nation with little understanding of the global geopolitical environment of WWII, you'd have no idea why planes started showing up on your island, but they keep showing up, and only at an airport. It seems rational to assume they'd continue showing up to airports. > that animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt What is it if not statistical? Also skinner boxes are, in a way, perfectly rational. There's no way to understand the environment, and if pushing a button feeds you, then rationally you should push the button when hungry. Humans like to think we're smart because we've invented deductive reasoning, and we quote "correlation is not causation" that we're not just earning to predict the world around us from past experiences.

mjburgess 3y ago

I mean something specific by "statistics": modelling frequency associations in static ensembles of data. Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). That animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt. It's a failure of ecological salience mechanisms in regulating the "experimental learning" that animals engage in. Eg., with the cargo cults the reason they adopted that view was because their society had a "big man" value system based on material acquisition and western waring powers seemed Very Big and so were humiliating. In order to retain their status they adopted (apparently irrational) theories of how the world worked (gods, etc). From the outside this process might seem statistical, but it's the opposite. Their value system made material wealth have a different causal salience which was useful in their original ecology (a small island with small resources), but it went haywire when faced with the whole world. Eventually these mechanisms update with this new information, or the tribe dies off -- but what's going wrong here is that the very very non-statistical learning ends up describable that way. This is indeed, why we should be very concerned about people skinner-boxing themsleves with LLMs

data_maan 3y ago
> Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). That animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt. RL is doing just this, simulating an environment. And we can have an agent "learn" in that environment. I think tying learning to a body is too restrictive. The You strongly rely on the assumption that "something else" generates the statistics we observe, but scientifically, there exists little evidence whether that "something else" exists (see eg the Bayesian brain).
- mjburgess 3y ago
  You need some way of inducing distributions in reality, ie., making the ice cube. If you're just subject to time-varying, random, stochastic, perceptual distributions you have no way of estimating the properties of the data generating process (reality). You need to be the one in control of the distribution in order to study it: this is the lesson of the whole history of science as an experimental discipline.
  - drdeca 3y ago
    What about astronomy and cosmology?
vineyardmike 3y ago
> Having a body which changes over time that interacts with a world that changes over time makes animal learning not statistical (call it, say, experimental). The "experiment" of life is what defines the statical values! Experimentation is just learning what the statistical output of something is. If I hand you a few dice, you'd probably be able to guess the statistical probability of every number for given roll. Because you've learned that through years of observation building a mental model. If I hand you a weighted die, suddenly your mental model is gone, and you can re-learn experimentally by rolling it a bunch. How can you explain experimental learning except "statistically"? > they adopted (apparently irrational) theories of how the world worked (gods, etc) They can be wrong without being irrational. Building an airport doesn't make planes show up, but planes won't show up without an airport. If you're an island nation with little understanding of the global geopolitical environment of WWII, you'd have no idea why planes started showing up on your island, but they keep showing up, and only at an airport. It seems rational to assume they'd continue showing up to airports. > that animals fall into skinner-box irrational behaviour can be modelled as a kind of statistical learning, but it actually isnt What is it if not statistical? Also skinner boxes are, in a way, perfectly rational. There's no way to understand the environment, and if pushing a button feeds you, then rationally you should push the button when hungry. Humans like to think we're smart because we've invented deductive reasoning, and we quote "correlation is not causation" that we're not just earning to predict the world around us from past experiences.