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Scientific models clearly represent a compression of measurement data? Scientific models aren't necessarily "causal" to begin with. They are functions that giv

Scientific models clearly represent a compression of measurement data? Scientific models aren't necessarily "causal" to begin with. They are functions that give predictions about measurements. It is these predictions that are tested against data, not the function's confabulated "causal" justifications. People learn from data not adhering to predictions. This difference from model functions can be compressed, if not random. This compression then might reflect in the form of modularization in justifications, which again is interpreted as causal relationships.

mjburgess 3y ago
> Scientific models clearly represent a compression of measurement data? Nope! No theory of heat is a compression of therometer readings; no theory of gravity, of orbits; no theory of atoms of spectra. No theories compress measurments! Such a thing is pure superstition. Heat is not the motion of thermometer fluid. > not the function's confabulated "causal" justifications. Nope! We construct an experiment by counter-factual analysis of its causal semantics; we do not simply test whether observable quantities match prior data. Arbitary associative models match arbitary amounts of prior data. This is the opposite of science. We test scientific models by creating new experiments; it isnt "the data" which matters here, but that the experiment is designed to test the causal assumptions of the model. If the experiment doesn't: control causes, identify novel measures with potential causes, etc. then any data collected is useless. This is why you need, you know: randomised controlled trials, microscopes, satellites, ... etc. "Data" in the ML sense does not matter. This is pure superstitious pseudoscience. Science is a process of creating data under experimental conditions designed to be counter-factual tests of theories. Science is about the data generating process (reality), not our measurements of it.
- Loquebantur 3y ago
  I'm sorry, but I think you misinterpret what compression is all about? Heat is a random process. That process has a non-random component though. The phenomenon is compressed by describing it as a random distribution of impulses around that mean, given by temperature. In effect, you construct an algorithm that translates model parameters to predicted measurements. Any algorithm can be described as a function. Your idea of how models are concluded by testing causal assumptions is cargo-cult science. It is only partially correct and vastly misleading. In particular, such testing isn't always possible even in principle. You have untestable properties and parts of models that are simply chosen in lieu of better alternatives. By restricting yourself to such simple-minded testing, you blind yourself to large parts of reality even. Many interesting topics have no way of completely controlling conditions for example. They are not arbitrarily repeatable either. Astronomy, economics, psychology, biology...the world is bigger than your approach can account for.
  - mjburgess 3y ago
    > In particular, such testing isn't always possible even in principle You're the one saying it's a compression of measurements. How do you think we build models without any then? If you are aware that we do. > Many interesting topics have no way of completely controlling conditions for example Yes, and in these cases, much of what's produced is pseudoscience. Much of psychology is just taking surveys and compressing them, that's why it's unreporducible trash. > The phenomenon is compressed by describing it as a random distribution of impulses around that mean 'The phenomenon' isnt something 'compressible'. Compression in this sense means only a condition on an equation describing an association. The science of heat includes a model of atoms, molecules, flow, motion, etc. None of which are "Equations" but semantics for interpreting equations. The equations, given a "merely associative" semantics, are useless. All the things we discovered exist are science; and all the ways they work. The very language you're using here is a product of scientific disocvery. There was nothing to "compress", and is never anything to "compress". The world behaves differently depending on how you measure it; there are an infinite number of measures for any given system; and no "compression" of them -- not even all of them -- is that system. A sphere is not it's shadow, nor even all its shadows. It's the cause of its shadow -- and processes properties that no model of its shadows possess.

mjburgess 3y ago

> Scientific models clearly represent a compression of measurement data? Nope! No theory of heat is a compression of therometer readings; no theory of gravity, of orbits; no theory of atoms of spectra. No theories compress measurments! Such a thing is pure superstition. Heat is not the motion of thermometer fluid. > not the function's confabulated "causal" justifications. Nope! We construct an experiment by counter-factual analysis of its causal semantics; we do not simply test whether observable quantities match prior data. Arbitary associative models match arbitary amounts of prior data. This is the opposite of science. We test scientific models by creating new experiments; it isnt "the data" which matters here, but that the experiment is designed to test the causal assumptions of the model. If the experiment doesn't: control causes, identify novel measures with potential causes, etc. then any data collected is useless. This is why you need, you know: randomised controlled trials, microscopes, satellites, ... etc. "Data" in the ML sense does not matter. This is pure superstitious pseudoscience. Science is a process of creating data under experimental conditions designed to be counter-factual tests of theories. Science is about the data generating process (reality), not our measurements of it.

Loquebantur 3y ago
I'm sorry, but I think you misinterpret what compression is all about? Heat is a random process. That process has a non-random component though. The phenomenon is compressed by describing it as a random distribution of impulses around that mean, given by temperature. In effect, you construct an algorithm that translates model parameters to predicted measurements. Any algorithm can be described as a function. Your idea of how models are concluded by testing causal assumptions is cargo-cult science. It is only partially correct and vastly misleading. In particular, such testing isn't always possible even in principle. You have untestable properties and parts of models that are simply chosen in lieu of better alternatives. By restricting yourself to such simple-minded testing, you blind yourself to large parts of reality even. Many interesting topics have no way of completely controlling conditions for example. They are not arbitrarily repeatable either. Astronomy, economics, psychology, biology...the world is bigger than your approach can account for.
- mjburgess 3y ago
  > In particular, such testing isn't always possible even in principle You're the one saying it's a compression of measurements. How do you think we build models without any then? If you are aware that we do. > Many interesting topics have no way of completely controlling conditions for example Yes, and in these cases, much of what's produced is pseudoscience. Much of psychology is just taking surveys and compressing them, that's why it's unreporducible trash. > The phenomenon is compressed by describing it as a random distribution of impulses around that mean 'The phenomenon' isnt something 'compressible'. Compression in this sense means only a condition on an equation describing an association. The science of heat includes a model of atoms, molecules, flow, motion, etc. None of which are "Equations" but semantics for interpreting equations. The equations, given a "merely associative" semantics, are useless. All the things we discovered exist are science; and all the ways they work. The very language you're using here is a product of scientific disocvery. There was nothing to "compress", and is never anything to "compress". The world behaves differently depending on how you measure it; there are an infinite number of measures for any given system; and no "compression" of them -- not even all of them -- is that system. A sphere is not it's shadow, nor even all its shadows. It's the cause of its shadow -- and processes properties that no model of its shadows possess.