Experimental versus historical science

Long time no blog; it seems to come to me in bursts.

Anyway, a colleague has drawn my attention to a paper that has recently appeared, From Correlation to Causation: What Do We Need in the Historical Sciences?, by Ebach and Michael. It argues that "the integrity of historical science is in peril due [to] the way speculative and often unexamined causal assumptions are being used", and further suggests six criteria to check these supposedly speculative assumptions against.

In effect, the issue appears to be the use of models in phylogenetics and, in particular, in biogeography, and here, in particular and unless my reading between the lines is mistaken, the acceptance of any process except vicariance.

Before even delving into any other parts of the argumentation, it would be interesting to consider one of the underlying premises, which is clear already from the title of the paper: the assumption that historical sciences are fundamentally different from experimental sciences. As the authors write, "any evidence we adduce for some historical event needs must be contemporary evidence from which we make inferences on the basis of auxiliary hypotheses". But is it really any different in experimental sciences like medicine or physics? Do they not also have auxiliary hypotheses and assumptions at every step? Perhaps it is a failing on my part, but I at least cannot clearly see a marked difference.

Yes, of course we have easier access to evidence about things that happen around us every day today, and it is much easier to gather more of it. But that is a question of quantity, not the question of a qualitative, let alone epistemological, difference. To illustrate the point, let us consider an extremely simple case, the textbook statistics example of die throws.

First assume that I give you a die and ask you if you think it is loaded. You will then perhaps roll it twelve times, and get the result 2, 6, 5, 6, 6, 6, 6, 6, 3, 6, 6, and 6. Instinctively you might now conclude that it is, indeed, loaded. If you want to be scientific about it you would do statistics to calculate what the likelihood is of rolling these results with a fair die. It is, after all, possible that a fair die produces nine sixes out of twelve rolls; in fact it could produce a hundred sixes out of a hundred rolls, the question is merely how unlikely that is.

You have the die in your hand and you just did an experiment. Experimental science, right? Okay, now assume that after the twelve rolls described above, I snatch the die away from you and drop it in the Mariana Trench. It could be argued that from that moment on the research question "is the die loaded?" has turned into historical science. The twelve rolls are all the data we will ever get. From there we can take the next step and consider a scenario where we read about the twelve rolls in a book that is hundreds of years old. Surely now the question is squarely in the realm of historical science.

But has anything changed? I don't see it. The exact same statistical approach that applied before still applies afterwards. There is no difference in how we address the problem in either case.

And of course this situation is what we always face in science, in a certain sense. We don't literally have a die snatched away, but we do have time, money and other resource constraints. At some point we stop collecting data for any given study and analyse them. Consequently I fail to see where the philosophical difference is between being limited by the data that are available due to an accident of history and being limited by the data that are available due to, for example, our luck with DNA sequencing success before the project budget ran out.

The flip side of being limited by the dataset we have in any given situation is whether we can get more data in the future. Again, with experimental science we can get additional data more easily than in, say, palaeontology. But in real life historical research we are usually not reliant on a single die that has been destroyed either, as the most interesting questions are broader than that. So even with historical data we can usually go back and try to acquire more fossils or archaeological artefacts.

What we have considered so far was inferring what process operated in the past (a fair or a loaded die?) from data we have available (the results of twelve rolls). Thinking of biogeography this would be comparable to inferring whether long distance dispersal of plants and animals happened in the past from contemporary patterns of distribution. We can also flip that around now and consider the inference of past one-off events from processes we can still observe today. In biogeography, we can today observe spores, seeds, insects, birds, and ballooning spiders being blown across vast distances and arriving on remote shores. Did Rhipsalis, the only cactus genus naturally occurring outside of the Americas, arrive in Africa through chance dispersal across the ocean or is its current distribution the result of a much older vicariance event?

Of course this was a one-off event, and yes, we will never know the answer for certain. But again I fail to see the difference in principle. I cannot possibly know for certain that the sun will rise again tomorrow morning, but I can have a great deal of confidence in my admittedly tentative conclusion. Going back to the die example, if I give you a die and then ask you, "I rolled it once yesterday evening - what do you think the result was?", you cannot know it for certain either unless I tell you. But you can observe the process - you can roll it a thousand times - and then infer a probability distribution. If you find that it is severely loaded and produces a six 81% of the time, you may be willing to go so far as to suggest that my roll was a six.

In summary, I personally do not at this moment see the big difference between experimental and historical science; at least not a difference that could be used to argue that the latter cannot employ, for example, models of the same complexity as the former. Admittedly I am not a philosopher of science though.