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It's important to recognize that we've never successfully answered Hume's general skepticism about the existence of causality as something that is real outside

It's important to recognize that we've never successfully answered Hume's general skepticism about the existence of causality as something that is real outside of our own minds. So causality can't be positively confirmed to exist at all, let alone be detected and confirmed through statistics. Before you dismiss that is philosophical non-sense, causality is closely related to the "Arrow of Time" which is considered an unsolved problem in physics [0]. From what we've observed time appears to be the only asymmetric physical process, largely due to entropy (that is you can immediately tell if a video of a jar breaking is being played backwards because we don't expected a jar to "fall together"). There are Quantum processes, for example, that are time symmetric, that is playing a video of these processes would look the same reversed and forward. That said, as someone who does a lot of statistics, in practice what we do is model the causal process with a directed acyclic graph and see how well our models behave under causal assumptions. These work okay for answering practical questions about does A cause B. By controlling for correlating variables we can see the impact on what we believe to be a causal variable when we condition on these other correlating factors. Worth mention that nearly all of the work is done by linear models in practice. 0. https://en.wikipedia.org/wiki/Arrow_of_time https://en.wikipedia.org/wiki/Arrow_of_time

xpe 3y ago
The comment above refers to Hume's 'induction problem' [1]. > we've never successfully answered Hume's general skepticism about the existence of causality as something that is real outside of our own minds The quote seems to imply a strong consensus, but [1] disagrees. The phrasing "the existence of causality as something that is real outside of our own minds" sounds like philosophical idealism [2]. One can take that view without discussing causation at all, seems to me. Forgive the following blunt questions: how is philosophical idealism either (a) useful or (b) testable? To me, currently, it seems to be neither. Maybe I'm missing something? For those that get value from it, what are some practical take-aways you get out of thinking about Hume's 'problem of induction'? I'm very much into philosophy, but I admit I don't see a lot of utility in digging into this outside of historical purposes. It feels to me that the tools from inferential statistics combined with some deeper study on causation are far more useful and enlightening than trying to figure out the historical context around Hume's writing here. I'm glad other people do it, for sure, but what I've skimmed doesn't "grab" me. WRT causation, I often return to the idea of "no model is perfect, but some are useful". There are many times when we build useful models that -- when combined with proper experimentation -- very strongly indicate causation. The laws of physics, for example. As soon as people get involved, it gets messy. [1]: https://plato.stanford.edu/entries/induction-problem/ https://plato.stanford.edu/entries/induction-problem/ [2]: https://plato.stanford.edu/entries/idealism/ https://plato.stanford.edu/entries/idealism/
- brutusborn 3y ago
  I completely agree that looking at old epistemology isn't that useful; simply because more recent theorists will need to address the same issues, so generally refer to older theory within their work. If you want a deep understanding then you need to look at the source material, but as you mention this is mostly only interesting for gaining a historical perspective. Unfortunately many of the people who create introductory science courses seem to mostly only be aware of Popper, so most students are aware of the importance of falsifiability but not of its problems. I suspect this is because reading Kuhn, Lakatos and Feyerabend leaves one with an impression that science isn't an objective endeavour and this is an uncomfortable truth when start from a belief that science is some infallible rationalist project. Personally it transformed my view from "trust the science"(TM) to "question the science, always." Science isn't always science unfortunately.
brutusborn 3y ago
I don't think Hume's work suggests that causality isn't 'real' but that we can't prove causation using inductive methods. This isn't a problem unless our measure of 'truth' is proving some causal effect to be true. The solution is to pretend our models of causation are correct, run them and compare the results to observation. We never 'prove' the causal effect, but we judge its validity by how well it can predict future observations. In my view the 'real' problem we currently have is that we cannot test hypothesis in isolation (Duhem-Quine thesis). Thus we rely on heuristics like "scientific consensus" to judge whether the hypothesis that make up a field are gaining predictive power or not. The solution to all these problems is to use the Lakatosian Method of Scientific Research Programmes to track a field's progress over time. Anything less than this just devolves into Kuhnian paradigms, which is basically a popularity contest to determine 'valid' scientific methods. I think this 'real' problem can explain all the failures of modern science: the replication crisis, abuse of statistical methods, funding influencing results.

xpe 3y ago

The comment above refers to Hume's 'induction problem' [1]. > we've never successfully answered Hume's general skepticism about the existence of causality as something that is real outside of our own minds The quote seems to imply a strong consensus, but [1] disagrees. The phrasing "the existence of causality as something that is real outside of our own minds" sounds like philosophical idealism [2]. One can take that view without discussing causation at all, seems to me. Forgive the following blunt questions: how is philosophical idealism either (a) useful or (b) testable? To me, currently, it seems to be neither. Maybe I'm missing something? For those that get value from it, what are some practical take-aways you get out of thinking about Hume's 'problem of induction'? I'm very much into philosophy, but I admit I don't see a lot of utility in digging into this outside of historical purposes. It feels to me that the tools from inferential statistics combined with some deeper study on causation are far more useful and enlightening than trying to figure out the historical context around Hume's writing here. I'm glad other people do it, for sure, but what I've skimmed doesn't "grab" me. WRT causation, I often return to the idea of "no model is perfect, but some are useful". There are many times when we build useful models that -- when combined with proper experimentation -- very strongly indicate causation. The laws of physics, for example. As soon as people get involved, it gets messy. [1]: https://plato.stanford.edu/entries/induction-problem/ https://plato.stanford.edu/entries/induction-problem/ [2]: https://plato.stanford.edu/entries/idealism/ https://plato.stanford.edu/entries/idealism/

brutusborn 3y ago
I completely agree that looking at old epistemology isn't that useful; simply because more recent theorists will need to address the same issues, so generally refer to older theory within their work. If you want a deep understanding then you need to look at the source material, but as you mention this is mostly only interesting for gaining a historical perspective. Unfortunately many of the people who create introductory science courses seem to mostly only be aware of Popper, so most students are aware of the importance of falsifiability but not of its problems. I suspect this is because reading Kuhn, Lakatos and Feyerabend leaves one with an impression that science isn't an objective endeavour and this is an uncomfortable truth when start from a belief that science is some infallible rationalist project. Personally it transformed my view from "trust the science"(TM) to "question the science, always." Science isn't always science unfortunately.

brutusborn 3y ago

I don't think Hume's work suggests that causality isn't 'real' but that we can't prove causation using inductive methods. This isn't a problem unless our measure of 'truth' is proving some causal effect to be true. The solution is to pretend our models of causation are correct, run them and compare the results to observation. We never 'prove' the causal effect, but we judge its validity by how well it can predict future observations. In my view the 'real' problem we currently have is that we cannot test hypothesis in isolation (Duhem-Quine thesis). Thus we rely on heuristics like "scientific consensus" to judge whether the hypothesis that make up a field are gaining predictive power or not. The solution to all these problems is to use the Lakatosian Method of Scientific Research Programmes to track a field's progress over time. Anything less than this just devolves into Kuhnian paradigms, which is basically a popularity contest to determine 'valid' scientific methods. I think this 'real' problem can explain all the failures of modern science: the replication crisis, abuse of statistical methods, funding influencing results.