The so-called "scientific method" is, I think, rather poorly understood. For example, let us consider one of the best-known laws of nature, often simply referred to as the Law of Gravity:
Newton's Law of Universal Gravitation: Every object in the universe attracts every other object toward it with a force proportional to the product of their masses, divided by the square of the distance between their centers of mass.
Now here is a series of questions for you, which I often ask audiences when I give lectures on the philosophy of science:
- Do you believe Newton's Law of Universal Gravitation is true?
- If so, how sure are you that it is true?
- Why do you believe it, with that degree of certainty?
The most common answers to these questions are "yes", "very sure", and "because it has been extensively experimentally verified." Those answers sound reasonable to any child of the Enlightenment -- but I submit, on the contrary, that this set of answers has no objective basis whatsoever. To begin with, let us ask, how many confirming experiments do you think would have been done, to qualify as "extensive experimental verification." I would ask that you, the reader, actually pick a number as a rough, round guess.
Whatever number N you picked, I now challenge you state the rule of inference that allows you to conclude, from N uniform observations, that a given effect is always about from a given alleged cause. If you dust off your stats book and thumb through it, you will find no such rule of inference rule there. What you will find are principles that allow you to conclude from a certain number N of observations that with confidence c, the proportion of positive cases is z, where c < 1 and z < 1. But there is no finite number of observations that would justify, with any nonzero confidence, that any law held universally, without exception (that is, z can never be 1 for any finite number of observations, no matter how small the desired confidence c is, unless c = 0). . And isn't that exactly what laws of nature are supposed to do? For Pete's sake it is called the law of universal gravitation, and it begins with the universal quantifier every (both of which may have seemed pretty innocuous up until now).
Let me repeat myself for clarity: I am not saying that there is no statistical law that would allow you to conclude the law with absolute certainty; absolute certainty is not even on the table. I am saying that there is no statistical law that would justify belief in the law of universal gravitation with even one tenth of one percent of one percent confidence, based on any finite number of observations. My point is that the laws of the physical sciences -- laws like the Ideal gas laws, the laws of gravity, Ohm's law, etc. -- are not based on statistical reasoning and could never be based on statistical reasoning, if they are supposed, with any confidence whatsoever, to hold universally.
So, if the scientific method is not based on the laws of statistics, what is it based on? In fact it is based on the
Principle of Abductive Inference: Given general principle as a hypothesis, if we have tried to experimentally disprove the hypothesis, with no disconfirming experiments, then we may infer that it is likely to be true -- with confidence justified by the ingenuity and diligence that has been exercised in attempting to disprove it.
In layman's terms, if we have tried to find and/or manufacture counterexamples to a hypothesis, extensively and cleverly, and found none, then we should be surprised if we then find a counterexample by accident. That is the essence of the scientific method that underpins most of the corpus of the physical sciences. Note that it is not statistical in nature. The methods of statistics are very different, in that they rest on theorems that justify confidence in those methods, under assumptions corresponding to the premises of the theorems. There is no such theorem for the Principle of Abductive Inference -- nor will there ever be, because, in fact, for reasons I will explain below, it is a miracle that the scientific method works (if it works).
Why would it take a miracle for the scientific method to work? Remember that the confidence with which we are entitled to infer a natural law is a function of the capability and diligence we have exercised in trying to disprove it. Thus, to conclude a general law with some moderate degree of confidence (say, 75%), we must have done due diligence in trying to disprove it, to the degree necessary to justify that level confidence, given the complexity of the system under study. But what in the world entitles us to think that the source code of the universe is so neat and simple, and its human denizens so smart, that we are capable of the diligence that is due?
For an illuminating analogy, consider that software testing is a process of experimentation that is closely analogous to scientific experimentation. In the case of software testing, the hypothesis being tested -- the general law that we are attempting to disconfirm -- is that a given program satisfies its specification for all inputs. Now do you suppose that we could effectively debug Microsoft Office, or gain justified confidence in its correctness with respect to on item of its specification, by letting a weasel crawl around on the keyboard while the software is running, and observing the results? Of course not: the program is far too complex, its behavior too nuanced, and the weasel too dimwitted (no offense to weasels) for that. Now, do you expect the source code of the Universe itself to be simpler and friendlier to the human brain than the source code of MS Office is to the brain of a weasel? That would be a miraculous thing to expect, for the following reason: a priori, if the complexity of that source code could be arbitrarily large. It could be a googleplex lines of spaghetti code -- and that would be a infinitesimally small level of complexity, given the realm of possible complexities -- namely the right-hand side of the number line.
In this light, if the human brain is better equipped to discover the laws of nature than a weasel is to confidently establish the correctness an item in the spec of MS Office, it would be a stunning coincidence. That is looking at it from the side of the a priori expected complexity of the problem, compared to any finite being's ability to solve it. But there is another side to look from, which is the side of the distribution of intelligence levels of the potential problem-solvers themselves. Obviously, a paramecium, for example, is not equipped to discover the laws of physics. Nor is an octopus, nor a turtle, nor a panther, nor an orangutan. In the spectrum of natural intelligences we know of, it just so happens that there is exactly one kind of creature that just barely has the capacity to uncover the laws of nature. It is as if some cosmic Dungeon Master was optimizing the problem from both sides, by making the source code of the universe just simple enough that the smartest beings within it (that we know of) were just barely capable of solving the puzzle. That is just the goldilocks situation that good DM's try to achieve with their puzzles: not so hard they can't be solved, not so easy that the players can't take pride in solving them
There is a salient counterargument I must respond to. It might be argued that, while it is a priori unlikely that any finite being would be capable of profitably employing the scientific method in a randomly constructed universe, it might be claimed that in hindsight of the scientific method having worked for us in this particular universe, we are now entitled, a posteriori, to embrace the Principle of Abductive Inference as a reliable method. My response is that we have no objective reason whatsoever to believe the scientific method has worked in hindsight -- at least not for the purpose of discovering universal laws of nature! I will grant that we have had pretty good luck with science-based engineering in the tiny little spec of the universe observable to us. I will even grant that this justifies the continued use of engineering for practical purposes with relative confidence -- under the laws of statistics, so long as, say, one anomaly per hundred thousand hours of use is an acceptable risk. But this gives no objective reason whatsoever (again under the laws of statistics) to believe that any of the alleged "laws of nature" we talk about is actually a universal law. That is to say, if you believe, with even one percent confidence, that we ever have, or ever will, uncover a single line of the source code of the universe -- a single law of Nature that holds without exception -- then you, my friend, believe in miracles. There is no reason to expect the scientific method to work, and good reason to expect it not to work -- unless human mind was designed to be able to uncover and understand the laws of nature, by Someone who knew exactly how complex they are.
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Notes -
You evidently don't hang around LessWrong enough.
While Predictive Processing theory, which posits that human cognition is inherently Bayesian, has not been established to the extent it's nigh incontrovertible, it elegantly explains many otherwise baffling things about human cognition, including how it breaks when it comes to mental illnesses like depression, autism, OCD, and schizophrenia. I've linked to Scott on it before. I think it's more likely to be true than not, even if I can't say with a straight-face that it's gospel truth. It is almost certainly incomplete.
In other words, humans are being imperfect Bayesians all the time, and you don't need to explicitly whip out the formula on encountering evidence to get by, but in situations where the expected value of doing so in a rigorous fashion is worth it, you should. The rest of the time, evolution has got you covered.
Besides, the best, most accurate superforecasters and people like quants absolutely pull it out and do explicit work. In their case, the effort really is worth it. You can't beat them without doing the same.
I know quants do this, but I think it is a special case. Show me a hundred randomly selected people who are making predictions they suffer consequences for getting wrong, and are succeeding, I will show you maybe 10 (and I think that's generous) that are writing down priors and using Bayes rule. Medical research, for example, uses parametric stats overwhelmingly more than Bayes (remember all those p-values you were tripping over?), as do the physical sciences.
If the effective altruism (EA) crowd are in the habit of regularly writing down priors (not just "there exist cases"), then I must be mistaken in the spirit of my descriptive claim that nobody writes them down. On the other hand, I would not count EA as people who pay consequences of being wrong, or that is doing a demonstrably good job of anything. If they aren't doing controlled experiments (which would absolutely be possible in the domain of altruism), they are just navel gazing -- and making it look like something else by throwing numbers around. I have a low opinion of EA in the first place; in fact, in the few cases where I looked at the details of the quantitative reasoning on sites like LessWrong, it was so amateurish that I wasn't sure whether to laugh or cry. So an appeal to the authority if LessWrong doesn't cut much ice with me.
I should give an example of this. Here is an EA article on the benefits of mosquito nets from Givewell.org. It is one of their leading projects. (https://www.givewell.org/international/technical/programs/insecticide-treated-nets#How_cost-effective_is_it). At a glance, to an untrained eye, it looks like an impressive, rigorous study. To a trained eye the first thing that jumps out is that it is highly misleading. The talk about "averting deaths" would make an untrained reader think that they are counting the number of "lives saved". But this is not how experts think about "saving lives" and there is a good reason for it. Let's suppose that we take a certain child, that at 9 AM our project saves him from a fatal incident; at 10 Am another, at 11 AM another, but at noon he dies from exactly the peril our program is designed to prevent. Yay, we just averted 3 deaths! That is the stat that Givewell is showing you. Did we save three lives? no, we saved three hours of life.
This is the way anyone with a smidgeon of actuarial expertise thinks about "saving lives" -- in terms of saving days of life, not "averting deaths", and the Givewell and Lesswrong people either know that or ought to know it. If they don't know it, they are incompetent; and if they know it, then talking about "averting deaths" in their public facing literature is deliberately deceptive because it strongly suggests "saving lives", meaning whole lives, in the mind of the average reader. To be fair to givewell, their method of analyzing deaths averted apply to saving someone from malaria for a full year (not just an hour), but (1) that would not be apparent to a typical donor who is not versed in actuarial science, and (2) the fact remains that you could "avert the death" of the same person nine times while they still died of malaria (the peril the program is supposed to prevent) at the age of 10. The analysis and language around it is either incompetent or deceptive -- contrary to either one word or the other in the name of the endeavor, effective altruism.
That's not a cherry picked example; it was the first thing I saw in my first five minutes of investigating "effective altruism". It soured me and I didn't look much further, but maybe I'm mistaken. Maybe you can point me to some EA projects that are truly well reasoned, that are also on the top of the heap for the EA community.
I can't imagine you've spent any time in the EA community and never encountered the concept of the QALY. So yes, they do know it.
Either your being dishonest or you've hardly spent anytime reading anything they've written.
Or your wrong that:
That's your opinion. Mine is that anyone who can understand the rest of the article can understand the difference.
Oh. Ok then.
If you are an EA buff, I'd be happy if you'd share with me the case for one of their better, or best projects.
The thing is I'm not. I've just read Scott's posts regularly, and the occasional link from his subreddit, yet even I knew enough to know they understood the concept of a qaly.
And then by doing a two second google search for: "qaly" mosquito nets site:givewell.org I found this:
https://files.givewell.org/files/ExternalReviews/CompletedReviews/FIECON_AMF_CEM_Technical_Report_December_2017_FINAL.pdf
I have no idea how rigorous it is, but it at least seems the information you are looking for can be easily found if you put in a modicum of effort.
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I'm not an EA. I couldn't give less of a fuck about the moral valence of shrimp.
I don't make nearly as strong a claim as you like, so I'm not compelled to submit the arguments you desire. As I've said before, intelligent, functional humans are rational enough that explicit training in the "arts" of rationality, including Bayesian reasoning, provides little mundane value in everyday life to justify the added effort of engaging in it. The opportunity cost of doing so every day is simply not worth it, it's an arsenal best reserved for Big Ticket decisions, and even then, cultural wisdom and "common sense" are not terrible. You don't need a black belt from Yudkowsky's dojo to know not to finance a 2024 Dodge Charger at 30% APR or rack up credit card debt, or even to make sensible middle class decisions.
But the fact is that when you can justify it, such as in forecasting (financial or otherwise), you see the pros doing it. Hence it must be superior to fudging it, all the more so when the stakes are high. The existence of any alpha at that level is surprising enough.
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I'm skeptical of this. I think predictive processing theory posits a model with certain qualitative features that Bayesian updating would also have, but there are scads of non-Bayesian approaches that would also have those qualitative properties. They would only look Bayesian from the point of view of someone who doesn't know any other theories of belief updating. Does PPT posit a model that have the quantitative properties of Bayesian updating in particular, and experimentally validate those? That would be a very interesting find. If you know of a source I'd be curious to look at it.
I haven't looked into it in that much detail, but I genuinely find the elegance of its explanations in multiple, highly different cognitive disorders, to be hard to explain if it didn't have a kernel of truth.
But as I've admitted, it could be a just-so story or false pattern matching. I'm not that confident in it just yet.
If I see anything more convincing, I'll try and spread it around. For now, it's the domain of better psychiatrists, neurologists and researchers than me.
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