In my experience, most scientists don’t know or care much about the philosophy of science, but if they do know one thing, it’s Karl Popper’s idea that the hallmark of a scientific hypothesis is falsifiability. In general, scientists seem to have taken this idea to heart. For instance, when a scientist wants to explain why astrology, or Creationism, or any number of other things aren’t science, the accusation of unfalsifiability invariably comes up. Although I’ll admit to using this rhetorical trick myself from time to time, to me the idea of falsifiability fails in a big way to capture the scientific way of thinking. I hinted about this in an earlier post, but now I’d like to go into it in a bit more detail.
Let me begin with a confession: I have never read Popper. For all I know, the position I’m about to argue against is not what he really thought at all. It is of course a cardinal academic sin to argue against someone’s position without actually knowing what that person wrote. My excuse is that I’m going to argue against Popper as he is generally understood by scientists, which may be different from the real Popper. As a constant reminder that I may be arguing against a cartoon version of Popper, I’ll refer to cartoon-Popper as “Popper” from now on. (If that’s not showing up in a different font on your browser, you’ll just have to imagine it. Maybe you’re better off.)
I bet that the vast majority of scientists, like me, know only Popper‘s views, not Popper’s views, so I don’t feel too bad about addressing the former, not the latter.
Popper‘s main idea is that a scientific hypothesis must be falsifiable, meaning that it must be possible for some sort of experimental evidence to prove the hypothesis wrong. For instance, consider the “Matrix-like” hypothesis that you’re just a brain in a vat, with inputs artificially pumped in to make it seem like you’re sensing and experiencing all of the things you think you are. Every experiment you can imagine doing could be explained under this hypothesis, so it’s not falsifiable, and hence not scientific.
When Popper says that a scientific hypothesis must be falsifiable, it’s not clear whether this is supposed to be a descriptive statement (“this is how scientists actually think”) or a normative one (“this is how scientists should think”). Either way, though, I think it misses the boat, in two different but related ways.
1. Negativity. The most obvious thing about Popper‘s falsifiability criterion is that it privileges falsifying over verifying. When scientists talk about Popper, they often regard this as a feature, not a bug. They say that scientific theories can never be proved right, but they can be proved wrong.
At the level of individual hypotheses, this is self-evidently silly. Does anyone really believe that “there is life on other planets” is an unscientific hypothesis, but “there is no life on other planets” is scientific? When I write a grant proposal to NSF, should I carefully insert “not”s in appropriate places to make sure that the questions I’m proposing to address are phrased in a suitably falsifiable way? It’d be like submitting a proposal to Alex Trebek.
From what little I’ve read on the subject, I think that this objection is about Popper, not Popper, in at least one way. The real Popper apparently applied the falsifiability criterion to entire scientific theories, not to individual hypotheses. But it’s not obvious to me that that helps, and anyway Popper as understood by most scientists is definitely about falsifiability of individual hypotheses. For example, I was recently on a committee to establish learning outcomes for our general-education science courses as part of our accreditation process. One of the outcomes had to do with formulating scientific hypotheses, and we discussed whether to include Popperian falsifiability as a criterion for these hypotheses. (Fortunately, we decided not to.)
2. “All-or-nothing-ness.” The other thing I don’t like about Popperian falsifiability is the way it thinks of hypotheses as either definitely true or definitely false. (Once again, the real Popper’s view is apparently more sophisticated than Popper‘s on this point.) This problem is actually much more important to me than the first one. The way I reason as a scientist places much more emphasis on the uncertain, tentative nature of scientific knowledge: it’s crucial to remember that beliefs about scientific hypotheses are always probabilistic.
Bayesian inference provides a much better model for understanding both how scientists do think and how they should think. At any given time, you have a set of beliefs about the probabilities of various statements about the world being true. When you acquire some new information (say by doing an experiment), the additional information causes you to update those sets of probabilities. Over time, that accumulation of evidence drives some of those probabilities very close to one and others very close to zero. As I noted in my earlier post,Bayes’s theorem provides a precise description of this process.
(By the way, scientists sometimes divide themselves into “frequentist” and “Bayesian” camps, with different interpretations of what probabilities are all about. Some frequentists will reject what I’m saying here, but I claim that they’re just in denial: Bayesian inference still describes how they reason, even if they won’t admit it.)
For rhetorical purposes if nothing else, it’s nice to have a clean way of describing what makes a hypothesis scientific, so that we can state succinctly why, say, astrology doesn’t count. Popperian falsifiability nicely meets that need, which is probably part of the reason scientists like it. Since I’m asking you to reject it, I should offer up a replacement. The Bayesian way of looking at things does supply a natural replacement for falsifiability, although I don’t know of a catchy one-word name for it. To me, what makes a hypothesis scientific is that it is amenable to evidence. That just means that we can imagine experiments whose results would drive the probability of the hypothesis arbitrarily close to one, and (possibly different) experiments that would drive the probability arbitrarily close to zero.
If you write down Bayes’s theorem, you can convince yourself that this is equivalent to the following: a hypothesis H is amenable to evidence as long as there are some possible experimental results E with the property that P(E | H) is significantly different from P(E | not-H). That is, there have to be experimental outcomes that are much more (or less) likely if the hypothesis is true than if it’s not true.
Most examples of unscientific hypotheses (e.g., astrology) fail this test on the ground that they’re too vague to allow decent estimates of these probabilities.
The idea of evidence, and the amenability-to-evidence criterion, are pretty intuitive and not too hard to explain: “Evidence” for a hypothesis just means an observation that is more consistent with the hypothesis being true than with its being false. A hypothesis is scientific if you can imagine ways of gathering evidence. Isn’t that nicer than Popperian falsifiability?