Don’t let the experts define science!

We know more than we can tell. We all know what a democracy is… We know that France, Canada, the USA, Japan… are democracies… Russia and China are not democracies. However, I have never seen a definition of “democracy” that fits the actual use of the term. One formal definition is “government by the people, exercised either directly or through elected representatives”. But, of course, both China and Russia have elected representatives. And they will certainly claim to be governments “by the people and for the people”.

Formal definitions are less useful than you think.

Science is another term that defies formal definitions.

The philosopher Karl Popper offered us the concept of falsifiability to distinguish scientific statements. Something is falsifiable if it could be proven false. For example, I can say that the Moon was constructed the god Zeus. Could I test this statement and prove it wrong? Probably not. Thus it is not a scientific statement.

Notice that falsifiability is entirely general and has nothing with the natural sciences. For example, I can tell you that the unemployment rate in the US will skyrocket to 20% in 2018. That’s a falsifiable prediction. What is not falsifiable is to say that “because we elected Donald Trump to the presidency, the unemployment rate will skyrocket…”.

So falsifiability is a useful ingredient of science… but it does not define science, not anymore that elections define democracy. For example, there are highly paid financial analysists whose job is to predict economic indicators for the coming years. Their predictions are thoroughly falsifiable, but we do not consider them to be scientists.

People often say that science relies on the so-called scientific method. You start with a hypothesis and then you try to falsify it. There is no denying that it does happen in science… but that’s not what scientists “do”. What most scientists do is to try things out, without a clearly stated hypothesis… then they look at the results… if they find something that they can’t explain… they design more experiments to try to deepen their understanding.

The major fault of the “scientific method” is that it assumes too much on the part of the scientists. A clearly stated hypothesis is often the end result, not the starting point.

Let me take an example. Maybe I think that coffee causes cancer. You’d think that it might serve as my hypothesis, but as stated it is not falsifiable. What do I mean by “cause cancer”? I certainly do not mean that drinking coffee will lead you to have a stomach cancer the next day. So I will start to collect statistics about coffee and cancer. Maybe I will setup experiments with mice that somehow drink coffee. Eventually, after years, I might end up with a hypothesis that others can try to falsify. Maybe.

So though the concept of falsifiability is central to the sciences, the scientific method is not.

Another relevant scholar was Thomas Kuhn. Kuhn believed that scientific truth is not an objective fact. We have a collection of beliefs that are proving useful and that are robust enough to fit the facts as we see them. So far so good… but then Kuhn added a dichotomy… there is “normal” science where people do boring stuff under the existing belief system… and then there is “revolutionary” science that seeks to replace the existing belief system.

So you had silly Newtonian physicists… and Einstein appeared, threw everything overboard and forced people to rethink their long-held assumptions. Kuhn’s view is compatible with the Heroic Theory of Scientific Development. Scientists collectively stumble in the dark until a hero comes in to save the day.

Kuhn’s revolutionary science makes a good story… but I don’t think that’s how science works. In retrospect, we can tell stories about what happened and how it happened… but that’s not nearly as useful as it sounds.

If really science followed two distinct models, then you’d be able to tell, as it happens, whether this scientist pursues “normal science” whereas this other scientist pursues “revolutionary science”. But life isn’t quite so simple.

You see… the reason the Heroic Theory of Scientific Development is false is that “ideas have people” (as opposed to people having ideas)… that is, ideas evolve and spread on their own… As long as the fertile ground is available, strong ideas thrive… and it is only in retrospect, in an illusionary manner, that we pin down when exactly an idea came to be.

Why did most scientific progress come from Europe and North America? It is not because white men are smarter. It is because of the European culture, maybe through Judeo-Christianity, created fertile ground for strong new ideas.

That Kuhn was wrong matters because… because if he were right then you could turn around science funding and simply identify the “revolutionary science” and support that instead of wasting time with “normal science”. But, of course, if there was some way to tell apart “normal science” from “revolutionary science”, we would know.

Let us take a recent computer science “breakthrough”: deep learning. Companies like Google use deep learning to translate documents, recognize the content of pictures, speech recognition and so forth. It is the fastest area of growth right now in computer science (or it must be). We have gone back in time and granted great scientists like Yann Lecun the label of “science revolutionary” because deep learning took hold of them some time ago. (And, to be clear, people like Lecun should be celebrated.) But what actually happened?

  • We have had the idea of neural networks since… nearly forever. Though I was far from anything having to do with machine learning, I kept ending up in conferences covering neural networks in the last few decades. The field has grown and there have been lots of interesting theoretical developments… But it can easily be qualified as a whole lot of “normal science”.
  • Our computing hardware and software are a lot better, a lot faster than they were 20 years ago. What would have required a supercomputer worth billions in the 1990s can fit on the desk of any software engineer today. How did we get there? Through a whole lot of “normal science” and “normal engineering”.
  • Companies like Google have a lot more data than any company ever had. It is hard to think clearly about it, but we are talking about orders of magnitude in difference. How did we get there? Again, lots of patient, “normal work”.

So the dichotomy between normal and revolutionary science is about as scientific as the study of history… which is to say, not at all.

If the subversion of beliefs is to be qualified as “revolutionary”, then we may as well give up on science. Science needs the freedom to put in question our beliefs at every step. If you are not constantly rethinking what you think you know, you are not doing science.

There is, however, a useful dichotomy between non-scientific and scientific work. Lots of government-supported scientists, including some celebrated ones, do work that should never be qualified as “science”. Also, most scientists are guilty, at one point or another, of being lacking in ambition. That is, they pursue work that has little chance of being proven useful. But I would not call it “normal science”, I would call it “boring science”.

Most science out there is boring. The interesting parts are done by a small minority of researchers. But ambitious science is not the same as Kuhn’s revolutionary science. There is no need to work on a paradigm shift. For example, you can be a cancer scientist. On paper, your goal is to cure cancer. You can take the easy path and study one of the millions of mechanisms that have some relevance to cancer. You can then publish an endless stream of papers. Or you can set yourself as a goal to actually cure cancers. And then you can aim for clinical trials and so forth.

Thankfully, if you know where to look, science is still super exciting. But it tends to happen only on a fertile ground… of which we have a limited supply.

What is fertile ground for science? Feynman described science as the belief in the ignorance of experts. What does it mean? It means that science can only thrive where experts can be questioned. Prior to the emergence of science (in Europe), truth was mostly whatever your ancestors and the highest figure of authority said it was. And that’s not a bad way to go about it. There is a lot of collected wisdom in your culture. But relying on your culture to determine truth is not science.

That’s why people who say that something is true because most scientists think it is true (e.g., with respect to climate change) have little understanding of what science really is. Scientific truth is not established by a vote among scientists. It does not matter how nice and popular your idea is… if it does not fit the facts on the ground, then it must be rejected. For example, biologists taught us that human beings have 24 chromosomes, up until the 1950s, even though it was visible that there were only 23.

If you live in a culture where questioning the established truth will get you in trouble, then you are not on a scientific fertile ground. So you need freedom (including freedom of speech).

Freedom of speech is a delicate thing, but an integral component of science. When we silence someone, it often only harms the few at first while it can greatly benefit the rich and the powerful. But if we could not stand up and speak up to contradict the authorities, we could not pursue science for long.

To sum it up: I don’t think we can define formally what science is. It is a useful cultural construct that emerged out of Europe. It entails falsifiable ideas, and people working in a culture where it is possible to question and subvert widely held beliefs.

9 thoughts on “Don’t let the experts define science!”

  1. First, thanks for responding. I value your perspective.

    So you start off by saying that we don’t have a great definition of “democracy,” meaning that it’s difficult to come up with a definition that includes what we want and also excludes what we want.

    That’s fine. I think Plato said the same thing about chairs. We all know what a chair is. But it’s difficult to come up with a definition that includes everything we would call a chair and excludes everything we would not call a chair.

    The same goes for science, and that’s fine.

    This all started off with your question of what is a “useful theory.”

    https://twitter.com/lemire/status/811277657467944960

    In your blog post on that topic, I believe you said that a “useful theory” makes you smarter. I think that my response to your Tweet is along the same lines:

    https://twitter.com/carlroberts_us/status/811368423301251072

    “Useful theories let you do things. They don’t have to be true.”

    This is just describing how science actually works on the actual ground.

    What do I mean?

    Well, I assume that some physicists study “electrons.” I assume that physicists spend very little time studying whether “electrons” actually exist. Electrons fit in our model of how reality works, but models change and are refined and are sometimes upended completely.

    http://nautil.us/issue/40/learning/-why-science-should-stay-clear-of-metaphysics

    The “problem” is that we all walk around saying that electrons are real.

    We don’t know that. So saying that electrons are real is pretty close to saying that Zeus created the moon.

    Electrons make sense based on our current model of the physical world, similar to how phlogiston made sense to chemists of the past.

    So is this a problem? In many ways, it’s not.

    We can do a lot of cool stuff with our current model of the physical world.

    First, however, we need to acknowledge that our model of the physical world lets us do useful things. It is not the physical world.

    It is a model.

    We don’t have direct access to whatever the physical world is because the only way that we can perceive the physical world is through our senses.

    Yada yada yada.

    So we have a model.

    Science that is carried out within the confines of this model is “Normal Science.”

    Let me ask you this: How many scientists will get funded who propose research outside of our current model of the physical world?

    Let’s use the well-worn example of helio-centric versus geo-centric models of the solar system.

    Copernicus wasn’t the first guy to say that the Earth revolves around the Sun. He was just the first guy anyone really listened to, though, because the “scientific community” was more willing to consider the idea.

    So I think your view that Kuhn is advocating a “Heroic” model of science is flawed. Nobody listens to the “heroes” until they are ready to hear them.

    On that note, few people want to be a hero because heroes are often crushed by the establishment.

    Check this out: http://mobile.nytimes.com/blogs/well/2016/04/13/a-decades-old-study-rediscovered-challenges-advice-on-saturated-fat/

    So maybe scientists are trying things out, they find some strange results, and they just shrug and move on.

    Now, let’s get to revolutionary science.

    “Revolutionary Science” happens when someone is pushing our model of the physical world closer to “reality” by creating a model that is fundamentally different than the one it is trying to replace.

    So to use your Newton and Einstein example, it’s not that all of the scientists are in the dark until someone saves them. It’s that all of the scientists are busy taking Model X^100 to X^101, and then someone says, “Hey guys, it’s actually Y.”

    In regard to your claim that “Kuhn was wrong matters because… because if he were right then you could turn around science funding and simply identify the “revolutionary science” and support that instead of wasting time with “normal science”. But, of course, if there was some way to tell apart “normal science” from “revolutionary science”, we would know.”

    The problem is that when things from outside the prevailing paradigm often sound crazy. Crazy things often don’t get funded.

    1. So saying that electrons are real is pretty close to saying that Zeus created the moon.

      We have “electron guns” (X-rays) that are difficult to comprehend if we do not have the concept of an electron. Meanwhile, Zeus does nothing to explain the Moon.

      Let me ask you this: How many scientists will get funded who propose research outside of our current model of the physical world?

      In Canada, the humanities are about as well funded as science. There is little difference in how humanity professors secure funding versus physics professors. And, of course, the humanities have little to do with science.

      How science gets funding in the present system (which was created in the 1970s) tells us little about the nature of science, especially when this same system is applied to fund the arts, for example.

      “Revolutionary Science” happens when someone is pushing our model of the physical world closer to “reality” by creating a model that is fundamentally different than the one it is trying to replace.

      Sociology is not a science. Let us substitute “sociology” for “science”:

      “Revolutionary Sociology” happens when someone is pushing our model of reality closer to “reality” by creating a model that is fundamentally different than the one it is trying to replace.

      Sounds good?

      There is nothing particularly insightful to the term “revolutionary science”, at least nothing that informs us about the nature of science. You can talk about revolutions in finance, engineering, politics, business… and, yes, in science too. Revolutions are not a fundamental characteristic of science anymore than it is a fundamental characteristic of any other human field.

    1. Reproducibility pre-dates science. If I have a recipe to create a given sword, and I want to outsource the production to you, then I need to make it reproducible… I have to make sure you can generate the same result. That, by itself, does not buy us science. In fact, lots of stagnant pre-scientific civilizations had excellent skills at reproducibility.

      It is uncommon to attempt to reproduce results in science. I invite you to open any science journal and look for the phrase “we reproduced results from Y showing X”. You will find that, overwhelmingly, authors present “novel” work, with experiments “never done before”.

      It is actually not necessary to have good reproducibility in science. The important characteristic is falsifiability.

  2. Many scientists do not have a clear idea what “science” means, because the concept does not exist in their native languages. For example, the closest Finnish equivalent is “tiede”, which is more closely related to the German concept “Wissenschaft”. It encompasses all fields of research that could exist in a reputable university.

    I have a general idea which fields are usually considered science, but I am not aware of any features that can reliably differentiate them from other fields of research. Natural sciences are definitely science. Parts of many social sciences are often considered science, as they use similar methods to many natural sciences. On the other hand, some natural sciences such as astronomy do not use such “scientific” methods that much. Mathematics and statistics are probably not science, while aesthetics and theology are definitely not science. Even computer scientists cannot agree what computer science is.

  3. 1) String theory/M-theory is, as I dimly understand the situation, not falsifiable. Therefore, it is not science. Or?

    2) Given any mathematical statement I can come up with a set of axioms within which it can be proven true, a set of axioms within which it can be proven false, and a third set within which the statement is undecidable. Is mathematics a science? (Actually I don’t think mathematics is a science any more than French is a science. Mathematics is a language and I don’t know what falsifying a language would mean.)

  4. Is it fair to say that you’re arguing that most science is iterative, small steps, by everyone? That what seems revolutionary is more a lot of drudgery, the pile of knowledge accumulating, until one of the many standing on that growing pile has the right timing and inclination to take a leap?

    I don’t quite see the point you made about “a clearly stated hypothesis is often the end result, not the starting point”, but I think what you’re saying is that iteration on many speculative hypotheses eventually leads to a much more clever, clearly stated, and valuable hypothesis? In the absence of information, we can’t have a scientific breakthrough, so it’s very much a process of the accumulation of knowledge to get to the point where we understand enough to have that breakthrough?

    1. Is it fair to say that you’re arguing that most science is iterative, small steps, by everyone? That what seems revolutionary is more a lot of drudgery, the pile of knowledge accumulating, until one of the many standing on that growing pile has the right timing and inclination to take a leap?

      That’s well stated but I’d go even further. It is only in retrospect that we can tell this story… that we can pinpoint the “leaps”. These leaps are not objectively identifiable as they happen, and this makes the whole narrative suspect.

      We have to be careful because human beings are great at making up stories about what happened.

      I don’t quite see the point you made about “a clearly stated hypothesis is often the end result, not the starting point”, but I think what you’re saying is that iteration on many speculative hypotheses eventually leads to a much more clever, clearly stated, and valuable hypothesis? In the absence of information, we can’t have a scientific breakthrough, so it’s very much a process of the accumulation of knowledge to get to the point where we understand enough to have that breakthrough?

      Let us take anything we do not understand. Let us take the accelerated aging of astronauts, including low-orbit astronauts. We can quibble about whether it is “aging” but for my purpose it will do to call it aging. So what causes it? It seems that people first thought it was radiation, but then if you do the math, many airline pilots are exposed to just as much if not more radiations. And we now work a lot harder to protect astronauts from radiations. Microgravity seems to be a possible culprit. But how would you go from microgravity to early cataracts and diabetes? What is going on there? Let us try to get our astronauts to do a lot of intensive workouts, maybe it will help. Ah. No, it does not seem to stop the accelerated aging. This is a subproblem of a large problem: aging. Your body ages. Ok. So how does this cell at the end of your finger knows how old it is? Logically, there must be a clock, but what is it? If you workout a lot, will it slow or accelerate this clock? Do all human beings have the same clock? And it is not just human beings. Many plants die on schedule, though you can often perenialize them. If there is a schedule, there must be a clock… where is the clock? Is it the same clock as human beings? Or are they many different clocks. There are vaguely stated theories… but nothing clear-cut that you can test.

      What is consciousness? Is it a thing or an illusion?

      Let us take deep learning… the latest craze. Even the very best experts will tell you that they are surprised by how well it can work in some instances. They have vague theories as to why it happens… but we are still lacking the precise theorems… and they may never come.

      Let us take another one. We know without a doubt that cigarettes cause cancer. Fine. Why? There are vaguely stated theories, but it is unclear.

      So maybe you are interested in astronaut aging. Maybe you want to go to Mars one day, so you care about that. You don’t want to launch with the body of a 35-year-old and get there with the body of a 65-year-old. What are you going to do? You may start by taking small mammals in near space and measure all sorts of things… then you may try again, this time changing a few parameters… and so forth. Each time you hope to learn something. Knowledge piles up. In time you will build up a nice hypothesis that people can check easily enough because it is concrete and testable… but you usually do not start there.

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