Filed under: Academia, Manifesto, Philosophy, Politics | Tags: empiricism, intellectuals, jacques ellul, judgement, over-simplification, propaganda, rationality, reason, reductionism
Intellectuals are more prone to propaganda than others.
That’s one of the claims of Jacques Ellul in his book Propaganda which got me quite excited about it. His explanation of this is that intellectuals want to have an opinion on every subject, they follow current events carefully, and because they’re intelligent they think they can understand what is going on. This leads to their being more prone to propaganda because there isn’t enough time to have an informed opinion on every subject, because following current events carefully means being led by the news agenda and investing energy in comprehending things from within that given framework, and because intelligence is not enough to understand complex events which require huge breadth of knowledge and experience.
I find this idea very interesting, but there’s another aspect that I want to focus on, which is that intellectuals want to try to understand the world by simplifying it. They want to reduce complex ideas to simple models of them, and to understand them by doing so. This ties in with Ellul’s claim because if you have a simple model of the world that you think explains everything, it’s very hard to give it up. You end up reinterpreting events and facts to fit the theory rather than the much more onerous and difficult prospect of giving up the theory, which would require you to rethink the whole way you look at the world. One of Ellul’s points is that one of the two main functions of propaganda – what he calls integration propaganda – is to intensify currently existing ways of looking at the world and to turn them into actions. Integration propaganda must work better on someone who has a strong personal incentive not to give up his already existing simplified model of the world.
What I would like to understand though, is why people who seem to be intelligent, caring, and even kind, can be capable of believing things that are quite mad, and have consequences which are morally horrific. The obvious example is Nazism, but there are many less dramatic examples. Some people are not upset, for example, by the sight of a homeless person freezing on the streets during the winter.
I can see two sorts of explanation for this, at the emotional level and the rational level. I’m going to come back to the emotional part in a future post, but roughly speaking it’s something like cognitive dissonance. It’s too hard to live in the world if you are to have an emotional reaction to everything that is horrible, and so we have a strong incentive to try to see the world in a way that makes unpleasant things inevitable or out of our control. The other type of explanation is that we want to try to understand things by simplifying them, but that the world is too messy and complicated for this to really work, so we end up making the facts fit the theory.
The neoconservative economist believes that free markets are always efficient, so he sees the creation of new markets as the solution to all the world’s problems. The Marxist sees everything in terms of a dialectical process and class conflict. Both see the pain and suffering that happen as a consequence of these theories as necessary, and so are not shocked by them. The theist believes absolutely in the teachings of their religion, and so cannot see the human suffering that those beliefs can entail. For example, the Catholic who opposes the use of condoms in Africa. On the other hand, the vehement atheist sees that belief in God is wrong and so blames religion for all the world’s problems, blinding himself to the political or economic cause of many of them. Consequently, they can end up supporting incredibly bloody war and torture on a scale that dwarfs the Crusades, as in the case of Christopher Hitchens and Sam Harris for example.
The intellectual is particularly prone to this sort of thinking, because reductionism is our intellectual cultural heritage, something they are totally immersed in. Reducing complex situations to simple models of them through mathematics, physics, etc. has enabled us to make enormous leaps forward in our understanding and control of the physical world. But there is no successful reductionist model of politics or of human problems. Attempting to find reductionist explanations of politics or human behaviour is a reasonable scientific endeavour, albeit so far an unsuccessful one. But believing that we are already in a position to understand people or politics so simplistically, and – worse – acting on those beliefs, is a gross intellectual error (even if it is understandable). Empiricism is incredibly hard, even trained scientists working in much more concrete fields than politics or human behaviour find it very difficult to separate a good scientific explanation of a phenomenon from a confusion.
We cannot wait for an empirical scientific understanding of politics. We have to try to understand the world now, and make decisions and actions based on that understanding. I think it is important that we recognise that we cannot be over-reliant on reductionist models to guide our thinking on these matters, but that leaves a huge open problem of what we can rely on. My feeling is we can use these models of the world, but we need to bear in mind that none of them have a very wide scope, and that all of them are likely to be wrong in fairly major ways. In the end, we need to rely on our essentially human judgement rather than our theories as the final arbiter of our political thinking. That doesn’t mean abandoning reason and logic, it means being committed to pragmatically training our judgement and trying to make decisions as best as possible within the limits of our ability to reason about the world. It means attempting to imperfectly understand complex situations as they are rather than perfectly understanding over-simplifications of them. It means attending to the details rather than trying to find a theory that enables us to ignore them.
This is of course, incredibly difficult. One strategy that may make it more tractable is the idea of having multiple, overlapping, and weakly held principles for understanding the world rather than a smaller number of strongly held principles which attempt to explain everything in one grand scheme. Combined with this is the strategy of having multiple views on a given situation with varying degrees of conviction, rather than having a single one. These views can even be, in fact probably must be, mutually contradictory. Again, this is not to abandon reason in favour of accepting contradiction, but to remember to bear in mind that there are alternative views on a given situation rather than to put the alternatives out of mind. This may of course not be the best strategy. It would have been a bad strategy in the long term for understanding physics, for example. The test for whether or not it is a good strategy, is whether it helps us to get a better understanding of things from an empirical and pragmatic point of view. The main point is not that this strategy is necessarily the best one, but that the reductionist strategy is consistently leading us into error.
I’ll end with an example of this method applied to a reasonably contemporary political problem, the US invasion of Iraq. Before the invasion happened, there was huge debate about whether or not it was a good thing, or could be a good thing. Perhaps, regardless of the US’ reasons for wanting the war, it could have been a good thing for the Iraqi people. Well absolutely. It could, despite the hundreds of thousands of casualties, still be a good thing in the long run, although that seems a very remote possibility now. The reason I opposed it was not because I could foresee these hundreds of thousands of deaths – in fact that vastly exceeded my worst imaginings of how bad it could be – but that everything about the proposed war was dubious. The US and the UK governments lied to us repeatedly and their motives were clearly not either disarmament or helping the Iraqi people. Mostly, I felt that whether or not the war had a positive outcome would depend on the way in which it was conducted, and given that the principal agent in that clearly didn’t have the interests of disarmament or the Iraqi people at heart, I couldn’t believe that they would conduct it well. My opposition to the war was not based on predictions about what would happen, it wasn’t based on the illegality of the war according to international law (which wouldn’t concern me greatly if the war had really been a huge success for the Iraqi people), it was made in ignorance of what the US’ real motives were in the war. And yet, I believe, despite all that uncertainty and ignorance on my part, my judgement was essentially correct, and that subsequent events have shown that to be the case. You can read what I wrote about it in February 2003 here.
p.s. I’m not sure that I would recommend Ellul’s book. I haven’t finished it yet, but it appears to be rather self-contradictory from chapter to chapter and even occasionally from paragraph to paragraph.
p.p.s. When you’re reading a book about propaganda on the train, it’s weird how suddenly when you look up from it you realise that everyone around you is reading propaganda: the Economist telling you how great capitalism is; the glossy magazine telling women they have to look like these incredibly thin models; everything stuffed full of adverts, advertorials and PR-driven stories.
Filed under: Academia, Anarchism, Internet, Manifesto | Tags: blogs, elitism, expertise, experts, knowledge, scholarpedia, wikipedia
Wikipedia has a very bad reputation for accuracy, and recently it’s been getting a bit of a trashing for its internal politics. Despite this, millions of people continue to use it, and I think it’s easy to see why.
Despite its problems, Wikipedia is a better resource for the public dissemination of knowledge than almost anything else out there. It can be misused by blindly relying on what is included there, but this isn’t a reason to attack Wikipedia. You just have to approach it with the right attitude: a Wikipedia article is a starting point for further research, not an end point. It’s a means for discovering new information as much as a repository of information. We shouldn’t underestimate the importance of this. Discovering that certain knowledge exists is itself a very difficult and important thing to do.
Wikipedia articles are like a quick and dirty map of a knowledge space. They give you a rough idea of what something is about, even if the details may be wrong, and they suggest where you could go to find out more. As a sample, I picked the Wikipedia entry on dynamical systems more or less at random. As well as a decent length article, it has a bibliography of 17 books, including 13 serious academic books at varying levels and 4 popular mathematics books, and 22 internet links, including complete books available online, tutorials and the web pages of relevant research groups.
The nature of knowledge is that it is constantly expanding, and at the moment it is doing so at an incredible rate. Traditional repositories of knowledge like textbooks and encyclopaedias find it difficult to keep up, and are often years if not decades out of date. Wikipedia may be less authoritative than these, but it is often only days after a new discovery is made that a detailed write up is available on wikipedia with links to the original research paper for those who need more accurate information. Textbooks and printed encyclopaedias cannot compete with this.
It is interesting that much of the criticism of Wikipedia comes from those with a vested interest in doing so. The Encyclopaedia Britannica has criticised Wikipedia, and it’s obvious enough why they would do so because they’re in direct competition. But Wikipedia also gets a very bad treatment from the press, by people who are not directly in competition with it. The coverage from The Register (article linked to above) is a case in point. Their stories about Wikipedia are hostile almost to the point of absurdity.
So why is this? My feeling is that it’s because the model of public knowledge espoused by Wikipedia is a direct challenge to the elitist model of knowledge of journalists, and the reason they attack it so strongly is the same as the reason they attack blogs so strongly. Their whole reason for existence is based on the idea that they are providing something through their expertise and knowledge that cannot be obtained elsewhere (for free). If people could just directly access knowledge without going through them, why would be bother doing so? They feel their existence is threatened.
And they are right to feel that way. Wikipedia articles on new scientific discoveries are often much better researched than the write ups in newspapers, and Wikipedia authors often seem to have a better understanding of the discovery in question than the science writers in the newspaper. This shouldn’t be surprising: a newspaper typically only has one or two science writers (and they’re often failed scientists or those with only an undergraduate degree in science), whereas a Wikipedia article could be directly written by someone in that field or even by the original authors themselves. A newspaper article will never cite it’s sources because there isn’t enough space, but most Wikipedia articles do so (and those that don’t are conspicuously flagged).
Similarly, blogs often provide a much broader and more interesting range of political analysis than you find in a newspaper. One of the criticisms that traditional media such as newspapers level at blogs is that they don’t do investigative journalism, but in fact the heavy competition and diminishing revenues of traditional media mean that they are doing less investigative journalism than ever. When the US invaded Iraq, the traditional media were telling us how great everything was because their information was all coming through the filter of the military forces. On the other hand, Iraqi blogs gave a much broader picture.
Getting back to Wikipedia, the journalists and others would be right to criticise Wikipedia if the point of it was to provide an authoritative reference point for factual information. But this really shouldn’t be the point, and the criticism is fundamentally based on an inaccurate picture of the nature of knowledge. Truly authoritative knowledge is very rare. Anyone relying on a single source, however authoritative that source is, is making a serious error. Wikipedia shouldn’t be relied on in this way, but neither should an Encyclopaedia Brittanica entry or even a scientific textbook (and certainly not a newspaper article!). The critics cannot understand this point, or cannot concede it, because their view of themselves is that they are this sort of authority, and so they cannot comprehend the suggestion that this sort of authority is not needed.
So in defending Wikipedia from its critics, I am not – as they might imagine – denying the need for expertise, but attacking the false and elitist nature of expertise that they represent, and defending a view of knowledge that is inherently diverse.
As a postscript, a very interesting project is Scholarpedia. It is inspired by Wikipedia, but has a different balance of openness and expertise by essentially restricting editing rights to academics, with the level of control increasing with scientific status. As the front page of Scholarpedia states, “The approach of Scholarpedia does not compete with, but rather complements that of Wikipedia” (my emphasis). Scholarpedia is a recognition that both expertise and the dynamic, open approach of Wikipedia are important. At the moment, Scholarpedia is restricted to articles about theoretical and computational neuroscience, some mathematical fields, and astrophysics, but it will grow.
Filed under: Academia, Neuroscience | Tags: neural network, Programming, python, simulation
I’m part of a small group working on a new scientific endeavour, and we need your help!
We’re writing a new piece of software to simulate the behaviour of networks of neurons (nerve cells in the brain). Well, we’ve solved the differential equations, worked out the technical problems, written the code, but now we’re stuck. We’ve hit a barrier, our own CDD (creativity deficit disorder).
We need a name.
And it needs to be so damned snappy that as soon as someone hears it they’ll want to download our software and stop using the competition (with names like Neuron, XPP and Nest).
So can you help? Your scientific community needs you!
Boring technical details follow for those who are interested (not necessary for thinking up a cool name): The software is going to be written in Python, with some bits possibly in C++, using SciPy and vectorised code for efficient computations. The emphasis is on the code being easy to use for people without much experience in programming, and easy to extend. Initially, the software will focus on networks of simple model neurons rather than detailed anatomical models (although we might get round to adding that later).