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How about: In ordinary discourse we say that "the earth orbits the sun" – not that "the sun orbits the earth", and we feel very strongly about this distinction.

by nonbel 10y ago

How about: In ordinary discourse we say that "the earth orbits the sun" – not that "the sun orbits the earth", and we feel very strongly about this distinction. It just seems like discussion of "what causes what" is missing the point, just like the above argument. That one persisted for centuries (millenia?) until it was pointed out the answer is neither! It depends on your reference frame.

epistasis 10y ago
Causality is quite different from frame of reference. Lets return to your equation. r^2 = m1*m2/F is a statement of correlation that's valid to many digits, that also says that "these are all the variables that affect anything here." It allows for calculations of quantities by plugging in numbers. In combination with other equations, it allows extrapolitaion and physical thinking. But equations alone are not enough for a physicist to make progress on problems, they don't combine arbitrarily, they still use that famous "physical intuition" that turns out to involve a heck of a lot of causality that they talk about in the cafeteria but don't often write about. In the world outside of physics classrooms, most situations involve a huge number of variables interacting with each other, and the variables themselves are leaky abstractions. This means that the correlation of quantities does not go out to many digits, or even one digit. This does not make an equation a useful abstraction. People have developed probabilistic models that stand in for equations in these situations. Sure, it would nice to have an equation that modeled things like they do in the simple situations that Physics publishes on, but when the equations of physics are so weak that they can't even fold a protein, how are we going to use them to model the interaction of a potential drug with a protein? Equations are great, when they apply. By introducing simplifying assumptions, we can sometimes extend their utility into new domains, but at the cost of introducing fragility because of those simplifying assumptions. They allow for calculating new things with only a very few computations. But nearly every new field of science invents new math. One of the more recent inventions is causality. It works fantastic in those sciences that use experimental interventions. Simple algebraic equations do not.
- nonbel 10y ago
  Sorry, all these arguments seem like non-sequiturs to me. Physicists might pray together in the cafeteria to come up with good ideas. It doesn't mean God answered their prayers when they have one. Useful laws need not be exactly correct. You can keep adjusting to stay on course to account for the error due to any simplifications. Sure causality seems like it must be at least some kind of heuristic, that doesn't mean looking for causes is the best, or even a good, use of time.
  - epistasis 10y ago
    Well, your arguments seem equally non-sequiter to me. I spend a lot of time in the world of correlations, in biology. They're not so useful. It's much better to get a causation: a knob that when you turn it you get a response, rather than no response. If you can't see the utility of the two, then perhaps there's not much to discuss?
    - nonbel 10y ago
      >"Well, your arguments seem equally non-sequiter to me." Fair enough. >"I spend a lot of time in the world of correlations, in biology." I left that field. One reason was because I realized so much of my time was wasted after I attempted to attach numbers to things like "# of receptors required to fit the narrative". Sure "A causes B", but it must be for some reason totally different from what is usually proposed (and could probably be considered a boring experimental artifact). I just don't care if "A causes B". I want to know for "f(A) ~ B", what is f? >"It's much better to get a causation: a knob that when you turn it you get a response, rather than no response." Reminds me of this paper: "Biologists summarize their results with the help of all-too-well recognizable diagrams, in which a favorite protein is placed in the middle and connected to everything else with two-way arrows. Even if a diagram makes overall sense (Fig. 3a), it is usually useless for a quantitative analysis, which limits its predictive or investigative value to a very narrow range. The language used by biologists for verbal communications is not better and is not unlike that used by stock market analysts. Both are vague (e.g., a balance between pro- and anti-apoptotic bcl-2 proteins appears to control the cell viability, and seems to correlate in long-term with the ability to form tumors) and avoid clear predictions." https://bml.bioe.uic.edu/BML/Stuff/Stuff_files/biologist%20fix%20radio.pdf https://bml.bioe.uic.edu/BML/Stuff/Stuff_files/biologist%20f...
solipsism 10y ago
the answer is neither! It depends on your reference frame Someone is new to the idea of relativity. This is nonsense. The frame of reference describing the sun rotating around the earth is not inertial (https://en.wikipedia.org/wiki/Inertial_frame_of_reference https://en.wikipedia.org/wiki/Inertial_frame_of_reference) and thus does not follow the laws of physics we know and love. In short, "Nope, you cannot say the sun orbits the earth."
- drdeca 10y ago
  I thought that using a non-inertial reference frame just introduced a "fictitious force"? Is that not the case?
  - empath75 10y ago
    You're correct. The laws of physics get very strange in a stationary earth reference frame. Imagine the forces that would be whipping the distant stars around earth.
    - nonbel 10y ago
      Well, I've made a solar system simulator before. Nothing great, but it was sufficient to convince me that is just a matter of perspective. The "law of physics" used was: d = sqrt(dx^2 + dy^2 + dz^2) F = G*m1*m2/d^3 That would just be summed up over all the objects included in the system. However, when visualizing the results, I could set (0,0,0) wherever I wanted. I could put it at the solar system barycenter, I could put it at the center of the sun, I could put at at the center of the galaxy (this leads to interesting vortex-like trails...), or I could put it at the center of the earth. The easiest was actually to use the solar system barycenter on an arbitrary date.
jasonwatkinspdx 10y ago
I would encourage you to look into Judea Pearl's work. I'd suggest starting with the epilog of his book: http://bayes.cs.ucla.edu/BOOK-2K/causality2-epilogue.pdf http://bayes.cs.ucla.edu/BOOK-2K/causality2-epilogue.pdf to get the general idea. To be clear: Pearl is not just philosophizing. He provides a formalization that takes causality from being an ambiguous concept to being applied mathematics. The bulk of the book is not a light read, but the mathematics involved are relatively basic. And to be absolutely clear: Pearl won the Turing prize for his work. It is not simply handwaving or non sequiturs. The common online conversations about causality are several decades out of date with real academic work on the topic.
- nonbel 10y ago
  I read that last time I thought about this topic, and went over it again earlier when epistasis linked to it. The arguments against Russel's position really do not do anything for me. As mentioned elsewhere, they seem to be a bunch of non-sequiturs about what we are told growing up. Regarding the Turing prize, etc. That type of thing doesn't really convince me. What engineering feats or surprising predictions has Pearl's methodology lead to? When I look at what is successful in machine learning these days, it is RNNs, CNNS, gradient boosting, etc. Correlation-based methods seem to be king, at least for now.
  - jasonwatkinspdx 10y ago
    Have you run into bayes nets or probabilistic graphical models? Or read the old Bayesian Automated Taxi paper from the 90's that got people thinking about autonomous vehicles based on these concepts? Pearl's work is heavily used: https://scholar.google.com/scholar?cites=10996260119229499611 https://scholar.google.com/scholar?cites=1099626011922949961... The Russel quote you posted is in no way some sort of rebuttal of Pearl et all's work. They aren't even in the same ballpark. I don't intended that as a slight agains Russel who I'm generally fond of.

by nonbel 10y ago

epistasis 10y ago

Causality is quite different from frame of reference. Lets return to your equation. r^2 = m1*m2/F is a statement of correlation that's valid to many digits, that also says that "these are all the variables that affect anything here." It allows for calculations of quantities by plugging in numbers. In combination with other equations, it allows extrapolitaion and physical thinking. But equations alone are not enough for a physicist to make progress on problems, they don't combine arbitrarily, they still use that famous "physical intuition" that turns out to involve a heck of a lot of causality that they talk about in the cafeteria but don't often write about. In the world outside of physics classrooms, most situations involve a huge number of variables interacting with each other, and the variables themselves are leaky abstractions. This means that the correlation of quantities does not go out to many digits, or even one digit. This does not make an equation a useful abstraction. People have developed probabilistic models that stand in for equations in these situations. Sure, it would nice to have an equation that modeled things like they do in the simple situations that Physics publishes on, but when the equations of physics are so weak that they can't even fold a protein, how are we going to use them to model the interaction of a potential drug with a protein? Equations are great, when they apply. By introducing simplifying assumptions, we can sometimes extend their utility into new domains, but at the cost of introducing fragility because of those simplifying assumptions. They allow for calculating new things with only a very few computations. But nearly every new field of science invents new math. One of the more recent inventions is causality. It works fantastic in those sciences that use experimental interventions. Simple algebraic equations do not.

nonbel 10y ago
Sorry, all these arguments seem like non-sequiturs to me. Physicists might pray together in the cafeteria to come up with good ideas. It doesn't mean God answered their prayers when they have one. Useful laws need not be exactly correct. You can keep adjusting to stay on course to account for the error due to any simplifications. Sure causality seems like it must be at least some kind of heuristic, that doesn't mean looking for causes is the best, or even a good, use of time.
- epistasis 10y ago
  Well, your arguments seem equally non-sequiter to me. I spend a lot of time in the world of correlations, in biology. They're not so useful. It's much better to get a causation: a knob that when you turn it you get a response, rather than no response. If you can't see the utility of the two, then perhaps there's not much to discuss?
  - nonbel 10y ago
    >"Well, your arguments seem equally non-sequiter to me." Fair enough. >"I spend a lot of time in the world of correlations, in biology." I left that field. One reason was because I realized so much of my time was wasted after I attempted to attach numbers to things like "# of receptors required to fit the narrative". Sure "A causes B", but it must be for some reason totally different from what is usually proposed (and could probably be considered a boring experimental artifact). I just don't care if "A causes B". I want to know for "f(A) ~ B", what is f? >"It's much better to get a causation: a knob that when you turn it you get a response, rather than no response." Reminds me of this paper: "Biologists summarize their results with the help of all-too-well recognizable diagrams, in which a favorite protein is placed in the middle and connected to everything else with two-way arrows. Even if a diagram makes overall sense (Fig. 3a), it is usually useless for a quantitative analysis, which limits its predictive or investigative value to a very narrow range. The language used by biologists for verbal communications is not better and is not unlike that used by stock market analysts. Both are vague (e.g., a balance between pro- and anti-apoptotic bcl-2 proteins appears to control the cell viability, and seems to correlate in long-term with the ability to form tumors) and avoid clear predictions." https://bml.bioe.uic.edu/BML/Stuff/Stuff_files/biologist%20fix%20radio.pdf https://bml.bioe.uic.edu/BML/Stuff/Stuff_files/biologist%20f...

solipsism 10y ago

the answer is neither! It depends on your reference frame Someone is new to the idea of relativity. This is nonsense. The frame of reference describing the sun rotating around the earth is not inertial (https://en.wikipedia.org/wiki/Inertial_frame_of_reference https://en.wikipedia.org/wiki/Inertial_frame_of_reference) and thus does not follow the laws of physics we know and love. In short, "Nope, you cannot say the sun orbits the earth."

drdeca 10y ago
I thought that using a non-inertial reference frame just introduced a "fictitious force"? Is that not the case?
- empath75 10y ago
  You're correct. The laws of physics get very strange in a stationary earth reference frame. Imagine the forces that would be whipping the distant stars around earth.
  - nonbel 10y ago
    Well, I've made a solar system simulator before. Nothing great, but it was sufficient to convince me that is just a matter of perspective. The "law of physics" used was: d = sqrt(dx^2 + dy^2 + dz^2) F = G*m1*m2/d^3 That would just be summed up over all the objects included in the system. However, when visualizing the results, I could set (0,0,0) wherever I wanted. I could put it at the solar system barycenter, I could put it at the center of the sun, I could put at at the center of the galaxy (this leads to interesting vortex-like trails...), or I could put it at the center of the earth. The easiest was actually to use the solar system barycenter on an arbitrary date.

jasonwatkinspdx 10y ago

I would encourage you to look into Judea Pearl's work. I'd suggest starting with the epilog of his book: http://bayes.cs.ucla.edu/BOOK-2K/causality2-epilogue.pdf http://bayes.cs.ucla.edu/BOOK-2K/causality2-epilogue.pdf to get the general idea. To be clear: Pearl is not just philosophizing. He provides a formalization that takes causality from being an ambiguous concept to being applied mathematics. The bulk of the book is not a light read, but the mathematics involved are relatively basic. And to be absolutely clear: Pearl won the Turing prize for his work. It is not simply handwaving or non sequiturs. The common online conversations about causality are several decades out of date with real academic work on the topic.

nonbel 10y ago
I read that last time I thought about this topic, and went over it again earlier when epistasis linked to it. The arguments against Russel's position really do not do anything for me. As mentioned elsewhere, they seem to be a bunch of non-sequiturs about what we are told growing up. Regarding the Turing prize, etc. That type of thing doesn't really convince me. What engineering feats or surprising predictions has Pearl's methodology lead to? When I look at what is successful in machine learning these days, it is RNNs, CNNS, gradient boosting, etc. Correlation-based methods seem to be king, at least for now.
- jasonwatkinspdx 10y ago
  Have you run into bayes nets or probabilistic graphical models? Or read the old Bayesian Automated Taxi paper from the 90's that got people thinking about autonomous vehicles based on these concepts? Pearl's work is heavily used: https://scholar.google.com/scholar?cites=10996260119229499611 https://scholar.google.com/scholar?cites=1099626011922949961... The Russel quote you posted is in no way some sort of rebuttal of Pearl et all's work. They aren't even in the same ballpark. I don't intended that as a slight agains Russel who I'm generally fond of.