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Philosophy of Science 101: What is the problem of induction?

80 points by webmaven 3y ago

ivansavz 3y ago
That was a nice introduction to the concept of induction: the idea that patterns observed in our past experience will hold in the future. Since we're talking about induction as the basis of science, I'm surprised the concept of "falsification" wasn't mentioned, which has been the "workhorse" of most science during the past two hundred years. See https://en.wikipedia.org/wiki/Falsifiability https://en.wikipedia.org/wiki/Falsifiability Specifically in the context of classical statistics methods (frequentist statistics), the idea of using p-values for scientific discovery only makes sense as part of repeated studies (induction over multiple tests of a theory). It's easy for any one study to observe some pattern by chance (one black raven), but if repeated studies all show this pattern exists, then we kind of start to believe the pattern might be true. Bayesian statisticians don't use the falsification paradigm directly, but instead focus on estimation, and combining the evidence from multiple experiments to obtain "tighter bounds" on the estimated quantities of interest. The conceptual machinery is very different, but the idea of induction is still kind of present in the form of "more data reduces uncertainty".
- 10g1k 3y ago
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  - epups 3y ago
    The theory of gravity is easily falsifiable. If we identify an object that has a given mass and does not produce the expected gravitational attraction, we will have to review the theory. Your assessment is very harsh. Popper's framework is hugely influential in science.
    - commonlisp94 3y ago
      I disagree. The law of gravity is what you describe, masses attract, and is falsifiable. The theory, that masses are distorting and curving space to cause that effect, is very hard to falsify.
      - epups 3y ago
        What you are alluding to is a modern interpretation of the theory, one that arose from Einstein's postulation about the relationship between space and time. This interpretation produces novel, testable predictions which have been experimentally verified. As a small quibble, there is no such distinction between "laws" and "theories". In common language a theory may imply less certainty than a law, but in science this is not the case.
        10g1k 3y ago
        > " there is no such distinction between "laws" and "theories" Law: A simple relation of limited scope intended to describe a single phenomenon, for example Ohm's Law. Theory: A description or narrative of how and why, which may include laws, data, observations, etc.
        commonlisp94 3y ago
        > there is no such distinction between "laws" and "theories" There is according to the academic circles I participated in, although it wouldn't surprise me if most physicists you meet wouldn't know that.
        whelp_24 3y ago
        There is a difference. A law comes through observation, for example the laws of thermodynamics, there has not (really) been an observation of them being violated (macro-scale). There's not really a theory underpinning them, mathematically a infinite motion machine could work. But it has been observed that it hasn't and it appears that it can't be violated. That atoms make up all matter is a Theory, it's a model based on hypotheses that have been tested over and over. A different model could be created that may match better (like everything being made of fields and waves). Basically a theory is how, a law is what. [Yes i am aware that atoms don't necessarily conflict with waves]
  - adr1an 3y ago
    I'm a scientist and I feel like Philosophers of science have much to say about science, even more than scientist even. Specially on this grounds. What you said was correct, but it's a reduced vision. Why don't we add Kuhn and Lakatos to the mix? https://en.m.wikipedia.org/wiki/Research_program https://en.m.wikipedia.org/wiki/Research_program
  - deleted 3y ago
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  - commonlisp94 3y ago
    I think your exaggerating by saying it has nothing to do with science, even if most scientific thinking isn't focused on falsification. Theories are the explanatory part to explain why a law or correlation occurs. The law can be falsified, but I think you're right, that it's very hard to falsify the theory portion.
    - ukj 3y ago
      You don't falsify a theory - all theories are tautologies. They are true by definition. You falsify the predictions of a theory. When a new theory works better and explains/predicts more the old theory is said to be falsified.
      - deleted 3y ago
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  - ukj 3y ago
    Indeed, the first theory of gravity was proven wrong. Einstein's theory of general relativity falsified Newton's law of universal gravitation. If you want to take this even further (which is a leap that would certainly upset most people's sensibilities) - Einstein proved that gravity doesn't exist. What does exist is the curvature of spacetime which explains all the phenomena which we used to attribute to gravity. Einstein falsified gravity.
  - the-mitr 3y ago
    What people also tend to misunderstand that Popper and also logical positivists provided a normative picture of what science ought to be be, rather than what it is. This naive normative picture of the scientific method was (perhaps even now it is with many scientists) in vogue during the 1950-60s, for example look at Medawar's books who was heavily influenced by ideas of Popper. The very fact that scientists do not give up on their pet theories despite of contrary evidence is a good evidence against such simple views, which have an image of a scientist as someone without any human emotions and personal beliefs. Also associated are several ideas of science being value neutral and observations being theory agnostic which were foundational to these view points have been seriously challenged.
    - ukj 3y ago
      The idea that we ought to believe what's true is itself a normative picture of how humans should think rather than a descriptive picture of how humans do think. There's no scientific way around underdetermination, but there certainly are a number of philosophical ways around it. Starting with: I'll believe whatever the heck I want to believe. https://en.wikipedia.org/wiki/Underdetermination https://en.wikipedia.org/wiki/Underdetermination
  - dale_glass 3y ago
    > Popper said that for a theory to qualify as science, it must be capable of being proven wrong. For example, for the theory of gravity to be scientific and correct, there must be an experiment which can prove it wrong. Is there such an experiment? Has anyone proven the theory of gravity wrong? Is it therefore not scientific? I think you're misunderstanding it? The requirement isn't that there exists an experiment that proves gravity wrong, and has been performed in reality. The requirement is that for the theory you propose, there must be some conceivable scenario in which you decide your theory is incorrect. Eg, if you posit "All swans are white", when it's falsifiable. All you need is a black swan to show up. But there is no requirement for this to actually happen, there's no problem with every swan in the universe being white.
  - kazinator 3y ago
    Falsifiability means that a claim is presented with specifics that could be proven wrong in some universe, not that they have to be shown wrong in this one (which is absurd). You're hanging on to the wrong meaning of "falsify", like to falsify a passport. One example of something that is not falsifiable is a deductive argument. Deduction isn't science; it is logic. A deductive argument is true regardless of the truth values of its constituent propositions. So in the most literal sense of the world, a deductive argument is not falsifiable. Another example of non-falsifiability is verbal bunk that refers to poorly defined or undefined concepts. The claims are not specific enough that they can be investigated and found true or false. E.g. "The world didn't exist yesterday; it came into being moments ago, with everything in it, including all your memories, and all of civilization and its apparent historic record." Okay, great; by what means of investigation can you tell that this is right? If this claim were false, how would the investigation inform you? Claims about gravity are falsifiable if they are specific and testable. E.g. "If I release this rock, it will move toward the ground and come to rest" is falsifiable because in some imaginary world, it could happen that the rock instead flies up and away when released. The claim is specific: we can construe what kinds of events could be observed which would make it false, like that the opposite of what is predicted happens. If a proposition is falsifiable, and we are not able to find it false, then that gives us confidence that it may be right.
    - 10g1k 3y ago
      There have been smoke-filled blow-hards in academia for generations, such as Hegel, whose entire opus consisted of deliberately nonsensical word salad, and whose careers in income depended entirely on confusing people in such a way as to seem profound, with word salad intended to be impenetrable and non-specific so nobody could clearly point out the myriad ways they were full of crap. Schopenhauer had a good go at explaining it, if you're interested. Popper was one of those people. He was not a scientist. He never had anything to do with science. He was a sophist. He talked rings around people in such a way that they never knew what the hell he was talking about, but they assumed it must be profound and amazing. Karl Popper himself based his ideas about science not on actual science, but on the philosophies including Marxism and Freudian psychology. Karl Popper's own words: "A theory which is NOT REFUTABLE by any conceivable event is non-scientific." Therefore the theory of gravity is not a scientific theory because nobody has yet conceived of an event or experiment which refutes it. I realise this will cause a negative reflex among those who are addicted to internerding and have held tightly to the unfounded belief (picked up from other internerds) that "Science must be falsifiable!", but it's just not reality. It's just a little thing that people saw on Wikipedia, latched on to, and figured it was really significant and legitimate. But it's just Popper's nonsense. There are plenty of extensive criticisms of Popper's sophistry out there by actual scientists and philosophers. Feel free to read some. As for the scientific method, if you can't do a web search and find out what they actually is, well, nobody can help you.
- jmpeax 3y ago
  The benefit of the Bayesian approach is the need to explicitly state a prior distribution, in this case, you would need to state the prior probability that all ravens are black. This forces us to realise that induction does not prove anything, and reduces to the matter of having the evolutionarily-gifted skill of coming up with good priors.
  - staunton 3y ago
    > induction does not prove anything Another benefit of a Bayesian approach is that you stop trying to "prove" things.
    - ThomPete 3y ago
      Bayenism is great for things that doesn't require explanations it's horrible as a method for knowledge creation.
      - jmpeax 3y ago
        Bayesianism is the only reliable way of creating knowledge, as it is the direct application of the mathematics of probability. All frequentism can do is tell you how poorly your data fits an unrealistic straw-man model.
        ThomPete 3y ago
        Probability is not knowledge creation.
        jmpeax 3y ago
        Then you must reject all science, as the knowledge gained is based on probabilistic experiments.
        ThomPete 3y ago
        No science is based on explanations that are hard to vary (i.e. explain what they purport to without any competing explanations). We use scientific experimentations not to prove but to rule out alternative theories. I can explain why a given thing will act a certain way. I don't need probabilities for that. If I need probability it's because I am just guessing and nothing else. If I need them I am just dressing up guessing in fancy words. But I am just that.
- LukeShu 3y ago
  The concept of falsification was introduced by Karl Popper in 1934... not 200 years ago. Popper is a historically important philosopher of science, but under scrutiny much of his thinking doesn't actually match up with how science is done (now or historically), and his philosophy hasn't been the dominant philosophy of science since the 1960s (enter Thomas Kuhn and Paul Feyerabend and Imre Lakatos). Nonetheless, the idea that "science = falsification" permeates popular culture, and is even repeated by many scientists who think about their work, but don't as often think about how they think about their work.
  - andybak 3y ago
    Nevertheless falsification is surely the most coherent justification for scientific reasoning in the sense of "a philosophy professor has a gun to your head and demands that you justify your work as a method for approximating reality"?
    - greydius 3y ago
      As philosophy professors often do.
      - SiempreViernes 3y ago
        Rarely in practice, but I'd bet they frequently dream of it, not least when the snotty undergrads ask why they should even bother to study philosophy.
    - consilient 3y ago
      No, if anything falsificationism and scientific realism are in tension. From Popper's The Logic of Scientific Discovery: > I think that we shall have to get accustomed to the idea that we must not look upon science as a ‘body of knowledge’, but rather as a system of hypotheses; that is to say, as a system of guesses or anticipations which in principle cannot be justified, but with which we work as long as they stand up to tests, and of which we are never justified in saying that we know that they are ‘true’ or ‘more or less certain’ or even ‘probable’. The most common realist arguments are probably variations on the "miracle argument": our scientific practices work, and the only plausible explanation is that they have at least some ability to find the truth.
- adr1an 3y ago
  I wouldn't oppose Bayesian statistics to Falsificationism but to Frequentism.
- Tomte 3y ago
  Gelman (http://www.stat.columbia.edu/~gelman/research/published/philosophy_online4.pdf http://www.stat.columbia.edu/~gelman/research/published/phil...): "The classical or frequentist approach to statistics (in which inference is centered on significance testing), is associated with a philosophy in which science is deductive and follows Popper’s doctrine of falsification. In contrast, Bayesian inference is commonly associated with inductive reasoning and the idea that a model can be dethroned by a competing model but can never be directly falsified by a significance test. The purpose of this article is to break these associations, which I think are incorrect and have been detrimen- tal to statistical practice, in that they have steered falsificationists away from the very useful tools of Bayesian inference and have discouraged Bayesians from checking the fit of their models."
- cb321 3y ago
  To address your surprise, the article was attempting to focus on just induction while falsifiability is more the higher level https://en.wikipedia.org/wiki/Demarcation_problem https://en.wikipedia.org/wiki/Demarcation_problem , but admittedly, philosophy of science topics do overlap a lot.
- webmaven 3y ago
  > Since we're talking about induction as the basis of science, I'm surprised the concept of "falsification" wasn't mentioned, which has been the "workhorse" of most science during the past two hundred years. An article on the subject of falsifiability and Popper was also published on the site (and posted on HN by me within minutes of this one): https://news.ycombinator.com/item?id=36951476 https://news.ycombinator.com/item?id=36951476
- cal85 3y ago
  Important to distinguish Bayesian epistemology (the idea that knowledge comes from induction) from Bayesian techniques in statistics. Karl Popper’s epistemology (critical rationalism) refutes the former, but does not mind the latter. Popper would agree that Bayesian techniques are useful (and even powerful) tools in statistics and practical problem-solving. But he would say that Bayesian ideas are insufficient to understand how knowledge grows and progresses. From a critical rationalism viewpoint, knowledge grows through conjecture and refutation - the proposal and testing of new explanatory theories. Bayesian statistical approaches can be part of the toolkit to falsify those theories, but they can’t explain how they come about, so they aren’t adequate as an epistemology. Popper’s critical rationalism may not be entirely complete, but it seems far better as a starting point for explaining how we get knowledge (which is what an epistemological framework needs to do) than Bayesian ideas about measuring truth statistically. Major breakthroughs like relativity and quantum entanglement are evidence for this: they required conjectures that at first seemed at odds with what we had observed. Physicists had to follow rational theories down very strange paths before any empirical confirmation, eventually to create new explanations that allowed us to model and predict distant cosmological events that had previously appeared random to us. If anyone is interested in these ideas (which are still fairly new to me; sorry for anything I’m expressing poorly), I highly recommend reading The Beginning of Infinity. It is an exciting, wide-ranging study of Popper’s epistemology by the guy who ‘invented’ quantum computing. It also discusses the ‘many universes’ theory, which is fascinating.
- belter 3y ago
  Well that is not really what the article is about. It's more about the problem of induction itself, and the problems of its use as basis for both Science and Philosophical endeavors. The article only made a flimsy drive into the subject, and the Wikipedia article does a much better job. "Problem of induction" - https://en.wikipedia.org/wiki/Problem_of_induction https://en.wikipedia.org/wiki/Problem_of_induction "...First formulated by David Hume, the problem of induction questions our reasons for believing that the future will resemble the past, or more broadly it questions predictions about unobserved things based on previous observations. This inference from the observed to the unobserved is known as "inductive inferences", and Hume, while acknowledging that everyone does and must make such inferences, argued that there is no non-circular way to justify them, thereby undermining one of the Enlightenment pillars of rationality..."
mostlyevil 3y ago
"The truly great advances in our understanding of nature originated in a manner almost diametrically opposed to induction. The intuitive grasp of the essentials or a large complex of facts leads the scientist to the postulation of a hypothetical basic law, or several such basic laws. From the basic law (system of axioms) he derives his conclusion as completely as possible in a purely logically deductive manner." - Albert Einstein [0] [0] https://einsteinpapers.press.princeton.edu/vol7-trans/124 https://einsteinpapers.press.princeton.edu/vol7-trans/124
- silencethendang 3y ago
  It seems like Einstein was saying "there's no such thing as a theory-free fact," specifically in his case that observation itself is influenced by some pre-existing theory. Some deduction is involved. But this begs the question... where did *that* theory originate?
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- ramraj07 3y ago
  This was the fall of Einstein though. He refused to acknowledge that the world truly was incomprehensibly weird in the quantum realm and kept trying to find some intuitive workaround or another for decades. The world is a sadder place because his true unique mind could have propelled us to unimaginable leaps (unimaginable to us mere mortals) if he had taken his head out of his own ass and accepted the reality for what it is and try to find the next breakthrough.
bee_rider 3y ago
A theory can only ever be not yet shown to be false, right? It’s only a model really.
- abtinf 3y ago
  If you are a human who wrote that statement, you are a conscious being with free will. You know this to be true through your direct experience. It is not subject to debate or falsification, and it is not merely a model. Any attempt to debate this point is self-refuting.
  - wddkcs 3y ago
    Where do determinists fall on your self refuting cut off line.
    - abtinf 3y ago
      Determinism is totally incoherent and self-evidently false. There is no evidence for determinism available to you. The very concept of “evidence” requires free will. There are no stupid determinists; it takes a certain level of intelligence to become so disconnected from literal moment-to-moment lived experience. Edit: I erred in saying it is false; that is too generous. It is arbitrary.
      - commonlisp94 3y ago
        I don't think most philosophers would agree with you. One framing of determinism is that you can only choose from the options in your head, weighted by your preferences. Both your preferences and those options were acquired through your experience, so how can choose anything other than what your experience already influenced you to do? It's fine to disagree, but do you find that "incoherent" and "self-evidently false"?
        abtinf 3y ago
        If everything is the result of previous factors, and nothing could have turned out differently, what is the point of making any argument about anything at all? You are relying on my free will: that I will focus my mind, read your argument, incorporate my experience, judge its truth using my reasoning faculty, and choose. Without free will, reason is impotent. Philosophers can’t agree or disagree because they have no choice in the matter. Free will is not about being able to choose any random thing at all. That would be like saying I’m not a human because I can’t will myself into becoming a banana peel.
_0w8t 3y ago
The article has not mentioned Bayesian inference, which allows to make sound decisions under uncertainty. For example, in practice the raven problem is not to guess if all ravens are black but to predict the color of the next raven if that color affects a decision. From that perspective if one knows absolutely nothing about ravens and has seen a single black raven, then it is mathematically sound to guess that the next raven will be black, not white, and make a decision accordingly.
- zalyalov 3y ago
  What do you mean by sound? Mathematically sound means "there exists a model validating it", and of course it exists, but so what? If you mean you can bound the probability of error, then in your formulation you actually can't.
  - _0w8t 3y ago
    Bayesian inference is mathematically sound as it is based on a very generic postulates and allows to compare probabilities based in the current information and made a decision accordingly. With the proper approach the errors are automatically accounted for. I.e. if the errors are large, then one will see that probabilities are too close each other to make a sound decision. Still if one must made a decision, then one can just use the answer based on Bayesian reasoning. The problem in practice is that accounting for the existing information is hard with guessing of priors etc. But that is the problem of applicability of Bayesian inference, not the problem with the principle itself. I.e. Bayesian inference is a good answer to the philosophical problem of induction. It is sad that the article has not even touched on that subject.
mjburgess 3y ago
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.
lvncelot 3y ago
How does Bayesian reasoning fit into this? To go with the introductory example, having seen the sun go up ~ 11000 times in my lifetime can never prove that it will go up tomorrow, but every time it does go up, I adjust my priors for expecting the sun to go up the next day, and assign it a bit more likeliness.
- ozy 3y ago
  I think a discussion on induction is best done by splitting the resulting models in two: models based on statistics, and models based on (abstract/iconic) simulation. (Eg all swans are white vs all swans lay eggs.) Since our reality is "atoms and void", and since the sun and earth are huge configurations of atoms locked together in a stable pattern, the sun coming up tomorrow has nothing to do with statistics. And bayesian reasoning plays no role in our predictions or certainty. At least not directly. It does indirectly, by asking what perturbation, what intervention, can stop this from happening? And how likely are such events?
danbruc 3y ago
The raven paradox is not that mysterious in my opinion, observing non-black non-ravens is indeed support for all ravens being black. How do you check that all ravens are black? From the set of all objects in the universe you select all objects of type raven and then check for each one that it is black. Or you do it the other way around, you select all non-black objects and then check for each one that it is not of type raven. Same result. [1] The cardinality of the two sets - all ravens and all non-black objects - will however be vastly different and I would certainly much prefer manually checking the list of all ravens. I think it is this disparity that makes us intuitively dismissive of the idea that seeing green apples helps us in any way with the color of ravens. And we might maybe also have some bias in our way of thinking - do you first see that a thing is a apple and then that it is red, or do you first see that it is a red thing and then that it is an apple? Ad hoc I would say that color usually comes second especially as we can essentially paint any object in any color we like, for example a blue apple. Color seems to only be the primary attribute if one can not clearly identify something, than it becomes just a red thing in the distance. [1] Also note that in both variants we ignore black non-ravens, in the first variant because they are not ravens, in the second one because they are not non-black.
dangitnotagain 3y ago
The problem is not that Truth is impossible to find, rather that undeceiving the self is difficult. The Truth is a perturbation of Objective Reality (the state resolve of universal potential into manifest form in the moment of now); and the truth is a figment of mind. Integrity is the measure of consistency between. More mental models should factor in the unreliability of conceptual state in reference to external resolve.
prometheus76 3y ago
My favorite example of the problem of induction: by induction, a cow believes the farmer to be the cow's best friend and loyal supporter, because the farmer dutifully cares for the cow's needs right up until the last day of the cow's life.
- hackandthink 3y ago
  You believe by induction the farmer is the enemy of the cow.
  - prometheus76 3y ago
    I like beef more than I like cows.
ThomPete 3y ago
I am surprised no one have mentioned David Deutsch yet as he probably have the best critique of induction (and a much more useful alternative) than any other living person. He is also the father of quantum computation and his two books Fabric of Reality and Beginning of Infinity the most important books I have ever read. Here is an interview with him: https://josephnoelwalker.com/139-david-deutsch/ https://josephnoelwalker.com/139-david-deutsch/ And here is a short lecture he did: https://www.youtube.com/watch?v=cs2n7l7wJow&t https://www.youtube.com/watch?v=cs2n7l7wJow&t
- Supermancho 3y ago
  13 minutes in that "short lecture" and he's still droning on about how gamblers originated and promoted probability, which is a pointless narrative bordering on political. Sheesh.
  - ThomPete 3y ago
    Your reaction is typical. Now listen to the whole thing and see how he answers your (typical objections)
kaycebasques 3y ago
I just finished the Very Short Introduction on philosophy of science a couple weeks ago. It was quite good. It covers the induction problem and more. https://academic.oup.com/book/517 https://academic.oup.com/book/517
lo_zamoyski 3y ago
"The problem of Hume’s problem of induction" [0] [0] http://edwardfeser.blogspot.com/2017/04/the-problem-of-humes-problem-of.html http://edwardfeser.blogspot.com/2017/04/the-problem-of-humes...

80 points by webmaven 3y ago

That was a nice introduction to the concept of induction: the idea that patterns observed in our past experience will hold in the future. Since we're talking about induction as the basis of science, I'm surprised the concept of "falsification" wasn't mentioned, which has been the "workhorse" of most science during the past two hundred years. See https://en.wikipedia.org/wiki/Falsifiability https://en.wikipedia.org/wiki/Falsifiability Specifically in the context of classical statistics methods (frequentist statistics), the idea of using p-values for scientific discovery only makes sense as part of repeated studies (induction over multiple tests of a theory). It's easy for any one study to observe some pattern by chance (one black raven), but if repeated studies all show this pattern exists, then we kind of start to believe the pattern might be true. Bayesian statisticians don't use the falsification paradigm directly, but instead focus on estimation, and combining the evidence from multiple experiments to obtain "tighter bounds" on the estimated quantities of interest. The conceptual machinery is very different, but the idea of induction is still kind of present in the form of "more data reduces uncertainty".

10g1k 3y ago
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- epups 3y ago
  The theory of gravity is easily falsifiable. If we identify an object that has a given mass and does not produce the expected gravitational attraction, we will have to review the theory. Your assessment is very harsh. Popper's framework is hugely influential in science.
  - commonlisp94 3y ago
    I disagree. The law of gravity is what you describe, masses attract, and is falsifiable. The theory, that masses are distorting and curving space to cause that effect, is very hard to falsify.
    - epups 3y ago
      What you are alluding to is a modern interpretation of the theory, one that arose from Einstein's postulation about the relationship between space and time. This interpretation produces novel, testable predictions which have been experimentally verified. As a small quibble, there is no such distinction between "laws" and "theories". In common language a theory may imply less certainty than a law, but in science this is not the case.
      - 10g1k 3y ago
        > " there is no such distinction between "laws" and "theories" Law: A simple relation of limited scope intended to describe a single phenomenon, for example Ohm's Law. Theory: A description or narrative of how and why, which may include laws, data, observations, etc.
      - commonlisp94 3y ago
        > there is no such distinction between "laws" and "theories" There is according to the academic circles I participated in, although it wouldn't surprise me if most physicists you meet wouldn't know that.
      - whelp_24 3y ago
        There is a difference. A law comes through observation, for example the laws of thermodynamics, there has not (really) been an observation of them being violated (macro-scale). There's not really a theory underpinning them, mathematically a infinite motion machine could work. But it has been observed that it hasn't and it appears that it can't be violated. That atoms make up all matter is a Theory, it's a model based on hypotheses that have been tested over and over. A different model could be created that may match better (like everything being made of fields and waves). Basically a theory is how, a law is what. [Yes i am aware that atoms don't necessarily conflict with waves]
- adr1an 3y ago
  I'm a scientist and I feel like Philosophers of science have much to say about science, even more than scientist even. Specially on this grounds. What you said was correct, but it's a reduced vision. Why don't we add Kuhn and Lakatos to the mix? https://en.m.wikipedia.org/wiki/Research_program https://en.m.wikipedia.org/wiki/Research_program
- deleted 3y ago
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- commonlisp94 3y ago
  I think your exaggerating by saying it has nothing to do with science, even if most scientific thinking isn't focused on falsification. Theories are the explanatory part to explain why a law or correlation occurs. The law can be falsified, but I think you're right, that it's very hard to falsify the theory portion.
  - ukj 3y ago
    You don't falsify a theory - all theories are tautologies. They are true by definition. You falsify the predictions of a theory. When a new theory works better and explains/predicts more the old theory is said to be falsified.
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- ukj 3y ago
  Indeed, the first theory of gravity was proven wrong. Einstein's theory of general relativity falsified Newton's law of universal gravitation. If you want to take this even further (which is a leap that would certainly upset most people's sensibilities) - Einstein proved that gravity doesn't exist. What does exist is the curvature of spacetime which explains all the phenomena which we used to attribute to gravity. Einstein falsified gravity.
- the-mitr 3y ago
  What people also tend to misunderstand that Popper and also logical positivists provided a normative picture of what science ought to be be, rather than what it is. This naive normative picture of the scientific method was (perhaps even now it is with many scientists) in vogue during the 1950-60s, for example look at Medawar's books who was heavily influenced by ideas of Popper. The very fact that scientists do not give up on their pet theories despite of contrary evidence is a good evidence against such simple views, which have an image of a scientist as someone without any human emotions and personal beliefs. Also associated are several ideas of science being value neutral and observations being theory agnostic which were foundational to these view points have been seriously challenged.
  - ukj 3y ago
    The idea that we ought to believe what's true is itself a normative picture of how humans should think rather than a descriptive picture of how humans do think. There's no scientific way around underdetermination, but there certainly are a number of philosophical ways around it. Starting with: I'll believe whatever the heck I want to believe. https://en.wikipedia.org/wiki/Underdetermination https://en.wikipedia.org/wiki/Underdetermination
- dale_glass 3y ago
  > Popper said that for a theory to qualify as science, it must be capable of being proven wrong. For example, for the theory of gravity to be scientific and correct, there must be an experiment which can prove it wrong. Is there such an experiment? Has anyone proven the theory of gravity wrong? Is it therefore not scientific? I think you're misunderstanding it? The requirement isn't that there exists an experiment that proves gravity wrong, and has been performed in reality. The requirement is that for the theory you propose, there must be some conceivable scenario in which you decide your theory is incorrect. Eg, if you posit "All swans are white", when it's falsifiable. All you need is a black swan to show up. But there is no requirement for this to actually happen, there's no problem with every swan in the universe being white.
- kazinator 3y ago
  Falsifiability means that a claim is presented with specifics that could be proven wrong in some universe, not that they have to be shown wrong in this one (which is absurd). You're hanging on to the wrong meaning of "falsify", like to falsify a passport. One example of something that is not falsifiable is a deductive argument. Deduction isn't science; it is logic. A deductive argument is true regardless of the truth values of its constituent propositions. So in the most literal sense of the world, a deductive argument is not falsifiable. Another example of non-falsifiability is verbal bunk that refers to poorly defined or undefined concepts. The claims are not specific enough that they can be investigated and found true or false. E.g. "The world didn't exist yesterday; it came into being moments ago, with everything in it, including all your memories, and all of civilization and its apparent historic record." Okay, great; by what means of investigation can you tell that this is right? If this claim were false, how would the investigation inform you? Claims about gravity are falsifiable if they are specific and testable. E.g. "If I release this rock, it will move toward the ground and come to rest" is falsifiable because in some imaginary world, it could happen that the rock instead flies up and away when released. The claim is specific: we can construe what kinds of events could be observed which would make it false, like that the opposite of what is predicted happens. If a proposition is falsifiable, and we are not able to find it false, then that gives us confidence that it may be right.
  - 10g1k 3y ago
    There have been smoke-filled blow-hards in academia for generations, such as Hegel, whose entire opus consisted of deliberately nonsensical word salad, and whose careers in income depended entirely on confusing people in such a way as to seem profound, with word salad intended to be impenetrable and non-specific so nobody could clearly point out the myriad ways they were full of crap. Schopenhauer had a good go at explaining it, if you're interested. Popper was one of those people. He was not a scientist. He never had anything to do with science. He was a sophist. He talked rings around people in such a way that they never knew what the hell he was talking about, but they assumed it must be profound and amazing. Karl Popper himself based his ideas about science not on actual science, but on the philosophies including Marxism and Freudian psychology. Karl Popper's own words: "A theory which is NOT REFUTABLE by any conceivable event is non-scientific." Therefore the theory of gravity is not a scientific theory because nobody has yet conceived of an event or experiment which refutes it. I realise this will cause a negative reflex among those who are addicted to internerding and have held tightly to the unfounded belief (picked up from other internerds) that "Science must be falsifiable!", but it's just not reality. It's just a little thing that people saw on Wikipedia, latched on to, and figured it was really significant and legitimate. But it's just Popper's nonsense. There are plenty of extensive criticisms of Popper's sophistry out there by actual scientists and philosophers. Feel free to read some. As for the scientific method, if you can't do a web search and find out what they actually is, well, nobody can help you.
jmpeax 3y ago
The benefit of the Bayesian approach is the need to explicitly state a prior distribution, in this case, you would need to state the prior probability that all ravens are black. This forces us to realise that induction does not prove anything, and reduces to the matter of having the evolutionarily-gifted skill of coming up with good priors.
- staunton 3y ago
  > induction does not prove anything Another benefit of a Bayesian approach is that you stop trying to "prove" things.
  - ThomPete 3y ago
    Bayenism is great for things that doesn't require explanations it's horrible as a method for knowledge creation.
    - jmpeax 3y ago
      Bayesianism is the only reliable way of creating knowledge, as it is the direct application of the mathematics of probability. All frequentism can do is tell you how poorly your data fits an unrealistic straw-man model.
      - ThomPete 3y ago
        Probability is not knowledge creation.
        jmpeax 3y ago
        Then you must reject all science, as the knowledge gained is based on probabilistic experiments.
        ThomPete 3y ago
        No science is based on explanations that are hard to vary (i.e. explain what they purport to without any competing explanations). We use scientific experimentations not to prove but to rule out alternative theories. I can explain why a given thing will act a certain way. I don't need probabilities for that. If I need probability it's because I am just guessing and nothing else. If I need them I am just dressing up guessing in fancy words. But I am just that.
LukeShu 3y ago
The concept of falsification was introduced by Karl Popper in 1934... not 200 years ago. Popper is a historically important philosopher of science, but under scrutiny much of his thinking doesn't actually match up with how science is done (now or historically), and his philosophy hasn't been the dominant philosophy of science since the 1960s (enter Thomas Kuhn and Paul Feyerabend and Imre Lakatos). Nonetheless, the idea that "science = falsification" permeates popular culture, and is even repeated by many scientists who think about their work, but don't as often think about how they think about their work.
- andybak 3y ago
  Nevertheless falsification is surely the most coherent justification for scientific reasoning in the sense of "a philosophy professor has a gun to your head and demands that you justify your work as a method for approximating reality"?
  - greydius 3y ago
    As philosophy professors often do.
    - SiempreViernes 3y ago
      Rarely in practice, but I'd bet they frequently dream of it, not least when the snotty undergrads ask why they should even bother to study philosophy.
  - consilient 3y ago
    No, if anything falsificationism and scientific realism are in tension. From Popper's The Logic of Scientific Discovery: > I think that we shall have to get accustomed to the idea that we must not look upon science as a ‘body of knowledge’, but rather as a system of hypotheses; that is to say, as a system of guesses or anticipations which in principle cannot be justified, but with which we work as long as they stand up to tests, and of which we are never justified in saying that we know that they are ‘true’ or ‘more or less certain’ or even ‘probable’. The most common realist arguments are probably variations on the "miracle argument": our scientific practices work, and the only plausible explanation is that they have at least some ability to find the truth.
adr1an 3y ago
I wouldn't oppose Bayesian statistics to Falsificationism but to Frequentism.
Tomte 3y ago
Gelman (http://www.stat.columbia.edu/~gelman/research/published/philosophy_online4.pdf http://www.stat.columbia.edu/~gelman/research/published/phil...): "The classical or frequentist approach to statistics (in which inference is centered on significance testing), is associated with a philosophy in which science is deductive and follows Popper’s doctrine of falsification. In contrast, Bayesian inference is commonly associated with inductive reasoning and the idea that a model can be dethroned by a competing model but can never be directly falsified by a significance test. The purpose of this article is to break these associations, which I think are incorrect and have been detrimen- tal to statistical practice, in that they have steered falsificationists away from the very useful tools of Bayesian inference and have discouraged Bayesians from checking the fit of their models."
cb321 3y ago
To address your surprise, the article was attempting to focus on just induction while falsifiability is more the higher level https://en.wikipedia.org/wiki/Demarcation_problem https://en.wikipedia.org/wiki/Demarcation_problem , but admittedly, philosophy of science topics do overlap a lot.
webmaven 3y ago
> Since we're talking about induction as the basis of science, I'm surprised the concept of "falsification" wasn't mentioned, which has been the "workhorse" of most science during the past two hundred years. An article on the subject of falsifiability and Popper was also published on the site (and posted on HN by me within minutes of this one): https://news.ycombinator.com/item?id=36951476 https://news.ycombinator.com/item?id=36951476
cal85 3y ago
Important to distinguish Bayesian epistemology (the idea that knowledge comes from induction) from Bayesian techniques in statistics. Karl Popper’s epistemology (critical rationalism) refutes the former, but does not mind the latter. Popper would agree that Bayesian techniques are useful (and even powerful) tools in statistics and practical problem-solving. But he would say that Bayesian ideas are insufficient to understand how knowledge grows and progresses. From a critical rationalism viewpoint, knowledge grows through conjecture and refutation - the proposal and testing of new explanatory theories. Bayesian statistical approaches can be part of the toolkit to falsify those theories, but they can’t explain how they come about, so they aren’t adequate as an epistemology. Popper’s critical rationalism may not be entirely complete, but it seems far better as a starting point for explaining how we get knowledge (which is what an epistemological framework needs to do) than Bayesian ideas about measuring truth statistically. Major breakthroughs like relativity and quantum entanglement are evidence for this: they required conjectures that at first seemed at odds with what we had observed. Physicists had to follow rational theories down very strange paths before any empirical confirmation, eventually to create new explanations that allowed us to model and predict distant cosmological events that had previously appeared random to us. If anyone is interested in these ideas (which are still fairly new to me; sorry for anything I’m expressing poorly), I highly recommend reading The Beginning of Infinity. It is an exciting, wide-ranging study of Popper’s epistemology by the guy who ‘invented’ quantum computing. It also discusses the ‘many universes’ theory, which is fascinating.
belter 3y ago
Well that is not really what the article is about. It's more about the problem of induction itself, and the problems of its use as basis for both Science and Philosophical endeavors. The article only made a flimsy drive into the subject, and the Wikipedia article does a much better job. "Problem of induction" - https://en.wikipedia.org/wiki/Problem_of_induction https://en.wikipedia.org/wiki/Problem_of_induction "...First formulated by David Hume, the problem of induction questions our reasons for believing that the future will resemble the past, or more broadly it questions predictions about unobserved things based on previous observations. This inference from the observed to the unobserved is known as "inductive inferences", and Hume, while acknowledging that everyone does and must make such inferences, argued that there is no non-circular way to justify them, thereby undermining one of the Enlightenment pillars of rationality..."

mostlyevil 3y ago

"The truly great advances in our understanding of nature originated in a manner almost diametrically opposed to induction. The intuitive grasp of the essentials or a large complex of facts leads the scientist to the postulation of a hypothetical basic law, or several such basic laws. From the basic law (system of axioms) he derives his conclusion as completely as possible in a purely logically deductive manner." - Albert Einstein [0] [0] https://einsteinpapers.press.princeton.edu/vol7-trans/124 https://einsteinpapers.press.princeton.edu/vol7-trans/124

silencethendang 3y ago
It seems like Einstein was saying "there's no such thing as a theory-free fact," specifically in his case that observation itself is influenced by some pre-existing theory. Some deduction is involved. But this begs the question... where did *that* theory originate?
- deleted 3y ago
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ramraj07 3y ago
This was the fall of Einstein though. He refused to acknowledge that the world truly was incomprehensibly weird in the quantum realm and kept trying to find some intuitive workaround or another for decades. The world is a sadder place because his true unique mind could have propelled us to unimaginable leaps (unimaginable to us mere mortals) if he had taken his head out of his own ass and accepted the reality for what it is and try to find the next breakthrough.

bee_rider 3y ago

A theory can only ever be not yet shown to be false, right? It’s only a model really.

abtinf 3y ago
If you are a human who wrote that statement, you are a conscious being with free will. You know this to be true through your direct experience. It is not subject to debate or falsification, and it is not merely a model. Any attempt to debate this point is self-refuting.
- wddkcs 3y ago
  Where do determinists fall on your self refuting cut off line.
  - abtinf 3y ago
    Determinism is totally incoherent and self-evidently false. There is no evidence for determinism available to you. The very concept of “evidence” requires free will. There are no stupid determinists; it takes a certain level of intelligence to become so disconnected from literal moment-to-moment lived experience. Edit: I erred in saying it is false; that is too generous. It is arbitrary.
    - commonlisp94 3y ago
      I don't think most philosophers would agree with you. One framing of determinism is that you can only choose from the options in your head, weighted by your preferences. Both your preferences and those options were acquired through your experience, so how can choose anything other than what your experience already influenced you to do? It's fine to disagree, but do you find that "incoherent" and "self-evidently false"?
      - abtinf 3y ago
        If everything is the result of previous factors, and nothing could have turned out differently, what is the point of making any argument about anything at all? You are relying on my free will: that I will focus my mind, read your argument, incorporate my experience, judge its truth using my reasoning faculty, and choose. Without free will, reason is impotent. Philosophers can’t agree or disagree because they have no choice in the matter. Free will is not about being able to choose any random thing at all. That would be like saying I’m not a human because I can’t will myself into becoming a banana peel.

_0w8t 3y ago

The article has not mentioned Bayesian inference, which allows to make sound decisions under uncertainty. For example, in practice the raven problem is not to guess if all ravens are black but to predict the color of the next raven if that color affects a decision. From that perspective if one knows absolutely nothing about ravens and has seen a single black raven, then it is mathematically sound to guess that the next raven will be black, not white, and make a decision accordingly.

zalyalov 3y ago
What do you mean by sound? Mathematically sound means "there exists a model validating it", and of course it exists, but so what? If you mean you can bound the probability of error, then in your formulation you actually can't.
- _0w8t 3y ago
  Bayesian inference is mathematically sound as it is based on a very generic postulates and allows to compare probabilities based in the current information and made a decision accordingly. With the proper approach the errors are automatically accounted for. I.e. if the errors are large, then one will see that probabilities are too close each other to make a sound decision. Still if one must made a decision, then one can just use the answer based on Bayesian reasoning. The problem in practice is that accounting for the existing information is hard with guessing of priors etc. But that is the problem of applicability of Bayesian inference, not the problem with the principle itself. I.e. Bayesian inference is a good answer to the philosophical problem of induction. It is sad that the article has not even touched on that subject.

mjburgess 3y ago

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.

lvncelot 3y ago

How does Bayesian reasoning fit into this? To go with the introductory example, having seen the sun go up ~ 11000 times in my lifetime can never prove that it will go up tomorrow, but every time it does go up, I adjust my priors for expecting the sun to go up the next day, and assign it a bit more likeliness.

ozy 3y ago
I think a discussion on induction is best done by splitting the resulting models in two: models based on statistics, and models based on (abstract/iconic) simulation. (Eg all swans are white vs all swans lay eggs.) Since our reality is "atoms and void", and since the sun and earth are huge configurations of atoms locked together in a stable pattern, the sun coming up tomorrow has nothing to do with statistics. And bayesian reasoning plays no role in our predictions or certainty. At least not directly. It does indirectly, by asking what perturbation, what intervention, can stop this from happening? And how likely are such events?

danbruc 3y ago

The raven paradox is not that mysterious in my opinion, observing non-black non-ravens is indeed support for all ravens being black. How do you check that all ravens are black? From the set of all objects in the universe you select all objects of type raven and then check for each one that it is black. Or you do it the other way around, you select all non-black objects and then check for each one that it is not of type raven. Same result. [1] The cardinality of the two sets - all ravens and all non-black objects - will however be vastly different and I would certainly much prefer manually checking the list of all ravens. I think it is this disparity that makes us intuitively dismissive of the idea that seeing green apples helps us in any way with the color of ravens. And we might maybe also have some bias in our way of thinking - do you first see that a thing is a apple and then that it is red, or do you first see that it is a red thing and then that it is an apple? Ad hoc I would say that color usually comes second especially as we can essentially paint any object in any color we like, for example a blue apple. Color seems to only be the primary attribute if one can not clearly identify something, than it becomes just a red thing in the distance. [1] Also note that in both variants we ignore black non-ravens, in the first variant because they are not ravens, in the second one because they are not non-black.

dangitnotagain 3y ago

The problem is not that Truth is impossible to find, rather that undeceiving the self is difficult. The Truth is a perturbation of Objective Reality (the state resolve of universal potential into manifest form in the moment of now); and the truth is a figment of mind. Integrity is the measure of consistency between. More mental models should factor in the unreliability of conceptual state in reference to external resolve.

prometheus76 3y ago

My favorite example of the problem of induction: by induction, a cow believes the farmer to be the cow's best friend and loyal supporter, because the farmer dutifully cares for the cow's needs right up until the last day of the cow's life.

hackandthink 3y ago
You believe by induction the farmer is the enemy of the cow.
- prometheus76 3y ago
  I like beef more than I like cows.

ThomPete 3y ago

I am surprised no one have mentioned David Deutsch yet as he probably have the best critique of induction (and a much more useful alternative) than any other living person. He is also the father of quantum computation and his two books Fabric of Reality and Beginning of Infinity the most important books I have ever read. Here is an interview with him: https://josephnoelwalker.com/139-david-deutsch/ https://josephnoelwalker.com/139-david-deutsch/ And here is a short lecture he did: https://www.youtube.com/watch?v=cs2n7l7wJow&t https://www.youtube.com/watch?v=cs2n7l7wJow&t

Supermancho 3y ago
13 minutes in that "short lecture" and he's still droning on about how gamblers originated and promoted probability, which is a pointless narrative bordering on political. Sheesh.
- ThomPete 3y ago
  Your reaction is typical. Now listen to the whole thing and see how he answers your (typical objections)

kaycebasques 3y ago

I just finished the Very Short Introduction on philosophy of science a couple weeks ago. It was quite good. It covers the induction problem and more. https://academic.oup.com/book/517 https://academic.oup.com/book/517

lo_zamoyski 3y ago

"The problem of Hume’s problem of induction" [0] [0] http://edwardfeser.blogspot.com/2017/04/the-problem-of-humes-problem-of.html http://edwardfeser.blogspot.com/2017/04/the-problem-of-humes...