Science Friction

[posted by Gavin Robinson, 10:38 am, 8 June 2007]

Rachel at A Historian’s Craft and Kevin at Civil War Memory have both been thinking about how much historians should think about philosophy. Although they take different positions on the issue, they both approach it in a refreshingly un-polemical fashion (contrast with the “that’s you that is” pettiness of this embarrassing exchange between Alun Munslow and Arthur Marwick). It’s almost inevitable that the p-word comes up, but it’s interesting that the word “postmodernism” seems to be used more often by people who are against it than people who are for it, whatever it is. Too often it seems to be a label attached to a conflation of lots of different (and not always compatible) theories, but let’s stick with the stereotypical view of postmodernism for now. Here are two recognisable stereotypes:

The traditional empiricist, who believes that what historians do is to scientifically examine archival evidence to find out what really happened in the past, something which is achievable if you eliminate bias.

The postmodernist who believes that everything is culturally constructed, that an objective scientific study of the past is impossible, and that even science itself is an ideologically suspect paradigm.

Whether these stereotypes are true or not (and you should always be suspicious of stereotyping – isn’t it funny how stereotypes are always someone else?) they crudely illustrate what I’m trying to get at in this post: that both extremes in the postmodernism wars seem to have a stereotypical and inaccurate view of science.


First of all I have to say that most scientists would laugh at the idea that history can be scientific, but that seems so obvious that it’s hardly worth discussing. The more interesting point is that science undermines some of the assumptions of traditional empirical history and supports some points of view which might be characterised as “postmodern”.

Chris at Mixing Memory says: “Spend a little time in a cognitive science lab, and you will quickly be disabused of any inclinations towards naive realism.” Spend some time reading Mixing Memory and you’ll find plenty of empirical scientific evidence that human perceptions can be very unreliable (even before conscious bias has any chance to act on them) and that language can influence perception. In this post Chris discusses linguistic relativity and looks at an experiment which appears to show that the colour terms in a language influence how people perceive colour. He points out that colour perception is one of the hardest areas in which to prove linguistic influence, but that the influence of language on concepts such as gender is much less controversial.

Language isn’t just problematic because of its insidious influence on perception and conceptualisation. The biggest problem is meaning. Post-structuralist theory (often conflated with postmodernism but not quite the same thing) suggests that meaning does not reside in text and cannot be fixed. This is a controversial idea to some people, but I don’t see many convincing arguments against it. So far science has been unable to even define what meaning is, let alone where it comes from. Edmund Blair Bolles grapples with the problem at Babel’s Dawn (here and here), a blog devoted to investigating the evolutionary origins of human speech. His mention of Searle’s “Chinese room” is particularly interesting here. Searle has been criticised for failing to define “understanding” but I don’t blame him for that because nobody really knows. Whatever it is, his thought experiment convincingly demonstrates that computers do not understand anything in the way that humans do. All the work that has gone into Artificial Intelligence has failed to come up with a machine which can understand the meaning of human language. Even passing the Turing test (which only requires creating the illusion of talking to a real person, not actual understanding) is surprisingly difficult. If language is as straightforward as the opponents of post-structuralism believe, then shouldn’t it be easy for machines to understand?

Nothing actually is what it’s called. Science can give us some incidental illustrations of this principle at work. Not too long ago, astronomers decided to change their definition of “planet” so that it no longer included Pluto. These astronomers clearly recognised that they are not just neutrally discovering what’s out there. Instead they are classifying things according to an arbitrary taxonomy which they have constructed themselves. If that taxonomy turns out not to be very useful for its intended purpose then it can be changed. But we all know that that’s not how the move was interpreted outside astronomy. Some people got quite emotional about it – Pluto is a planet because everyone knows it is!

When he laid the foundations of information theory, Claude Shannon was careful to separate information from meaning. A mathematician and engineer writing equations about the transmission of signals might be a prime suspect for being a realist/reductionist/whatever, but thanks to the separation of meaning from information Shannon’s theory is compatible with structuralism and post-structuralism.

But the real point I want to make about information theory is the way it undermines reconstruction of the past. (A lot of what I know about this come from Andrew Hickey, who explains it here) Complete information allows you to reconstruct the original message exactly as it was. In Shannon’s calculations the message was either a series of characters drawn from a finite set, or a continuous signal, such as a sound wave. If the message we want to reconstruct is the reality of the past then we clearly don’t have enough information to reconstruct anything. At best, historical sources (whether they’re documents, photographs, films, sound recordings) only capture some aspects of reality (and remember that reality is usually filtered through people’s perception and cognition, with all the problems that cognitive science has identified).

Another thing I learned from Andrew Hickey is Ashby’s first law of cybernetics, which he sums up as: in order to be in control of something, you need more available options than possible outcomes. This has major implications for historical causation. Think of how many possible outcomes there are when ruling a country or commanding an army. Can we really talk about anyone in history being in control of anything? This is one of the reasons why I’m dissatisfied with the explanations offered by most historians. Should we be talking about “influence” rather than “command” or “control”?

Chaos theory makes things even more difficult. In a chaotic system, small changes in the initial conditions can produce disproportionately large difference in the outcome. These systems can be difficult to model accurately because of their complexity, which is a major problem for counter-factual thinking. The consequences of something in history happening slightly differently might be wildly unpredictable.

This post is a fairly superficial introduction to things I don’t really understand very well (and I haven’t even gone into quantum theory, where things get really crazy) but if I’m even half right you’d have to ask why an extreme empiricist would cling to science and an extreme postmodernist would reject science. Maybe they don’t. After all, I did start with some unrealistic stereotypes. Nevertheless, it should now be clear that we do have some big problems here. Can we just ignore them and get on with doing history? If not, how much time should we spend thinking about them? I’ll be thinking about that in the next post.

  1. C E Shannon, ‘A mathematical theory of communication’, Bell System Technical Journal, 27 (1948), pp. 379-423, 623-656.

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