Those who have been following my blogs, may have noticed that I develop certain patterns, which I then use to 'think through' certain issues or habits in science, or other intellectual endeavours. This blending between science and philosophy has mainly been done to test the self-referentiality of PAC.

Methodological Stuff:
  1. Introduction
  2. Patterns
  3. Patterns, Objectivity and Truth
  4. Patterns and Processes
  5. Complexity and Randomness
  6. Complexity and Postmodernism
  7. Complexity and Rationality
  8. Complexity and Professionalism

The Pattern Library:

  1. A Pattern of Difference
  2. A Pattern of Feedback
  3. The Hourglass Pattern
  4. The Pattern of Contextual Diminution

Practical PAC:

  1. Performing Research on Complex Themes
  2. So What’s The Deal With The Singularity Again?
If I take up a more or less philosophical role, I still often find myself wondering if I am just a scientist who is too lazy to put his ideas to the test, but then, what can you do...

Self-referentiality allows -at least for those who take a liking in this sort of stuff-all kinds of interesting epistemological games, and the more creative minds can learn to see our life-world in entirely different ways (I do not claim to be one of these creative minds, by the way).
For example, one of the classical ideas of science and philosophy involved a 'universal observer' who had a reflexive attitude and therefore was able to see things that others missed (the eyes were the most superior of senses). When looking at all kinds of things that happen in the academic world, we then need to find this 'external' position, which I then take up from craftsmanship. Immediately I run into the problem that the crafts are very close their subject, use all their senses and take up a lot of different positions and perspectives, using different tools. So I get trapped in a self-referential, and ambiguous system, which tells me that, in order to understand this, I need complexity-informed perspectives. And these perspectives usually boil down to a realisation that, as the running thread throughout the posts have been, everything we do comes with limitations, and that most of the models we make, tend to be somewhat skewed.

One of the concepts that I think most clearly demonstrates this, is the way 'competition' is often used in science. This concept has become tremendously important in many scientific disciplines, such as economy, biology and game theory, and it sometimes seems to blend with the self-image and self-justification of academic enterprises itself. Competition, so the story goes, is the driving force of academic excellence, because it drives a rigorous testing/selection of ideas so that 'the best' remain. These ideas are usually associated with certain persons, so this competitive force -which in some countries are more fiercely defended than others- is also at work to select 'top-talent'. Academia thus is a raging battle-field where the best men (yes, surprisingly, still very often men...hmmm...) win.

From the vantage point of the external observer who is looking at these academic claims in a somewhat detached fashion -the crafts (and the corresponding complexity-informed perspective on competition), I can see two problems with the way competition is used. The first is that it seems to get stretched in the course of time to fit an ever-increasing set of phenomena, with a risk of it becoming a hollow term. One good day, we may read an equivalent of “Two foxes are fighting over a rabbit... because they are in competition over scarce resources”. This sounds reasonable enough. The next day we may read “The fox and the rabbit are fighting...because they are in competition over scarce resources”. Well, you can't quite put the finger on it..., but it seems to stretch the meaning of the word a bit. The fox eats, needs the rabbit, so the dynamics between fox and rabbit are definitely different that those between two foxes fighting over a rabbit. The third day, things get even more messy, when mutualism is explained in what has now become a hollow container concept: “The clownfish and the anenome live together... because they are in competition over scarce resources”


Luckily objective science tells us that we can make a list of different types of interaction, in order to prevent such terminological stretching. This allows us to put competition 'in perspective' with others, like the following actor-co-actor interaction patterns.


We know, of course, that these lists are little more than a means to organise our observations, but it does helps to neutralise our biases. This immediately resolves my second objection to the way competition is used, for now it can be cross-referenced with other interaction patterns, and does not stand solitary on its lonely pedestal. Especially us males may have certain associations with competition, such as being brave warriors fighting evil and that sort of stuff, and this may get in the way of our objectivity. Jared Diamond has already shown that men are (probably genetically) programmed to start bluffing on issues concerning hunting and war (and politics).

I saw a documentary once, where some hunters were off to (illegaly) shoot American eagles, using high-tech rifles with laser-guided telescopes, a helicopter, and all kinds of equipment to monitor the area around them for wild-life. What was especially endearing, was their belief that the hunt was a means to 'get back to nature', and that it was 'an even fight' between them and a 'magnificent contender'.

Diamond, who has done research in tribes in new-Guinea, tended to notice a mismatch in the stories the men told about their hunting experiences (big and fierce animals) and what they actually brought home (the new-Guinea equivalents of birds and rabbits).

None of that for us objective scientists! We defy our natural predispotions to serve objectivity, and lists such as actor-co-actor can assist us in this. Now we may bicker over the choices of this list, but at least we see that competition is only one of a number of interactions. This is totally conform complexity thinking ( there is never a concept that can explain everything) and evolution is not (necessarily) about competition, rather it is about the emergence of forms that have some benefit in a certain environment.

Why do I bring this up? Well, any crafstman knows that, like all other things, competition only works well in certain circumstances. If we have a number (n) of runners, skaters, mountain bikers, or whatever, and we want to see which one is the best, then competition works perfectly. We have scarcety, because there is only one spot that designates 'the best', and we have more than one competitors. Even a 'softer' approach may work where k<n, k being a certain number of 'best' positions.

Suppose now that I am an electrotechnical engineer, and I am working on a machine with mechanical engineers, software engineers, operators, hydraulic engineers, sales people, etc, then the notion of 'competition' between these team members becomes problematic. I cannot say 'objectively' that I am 'better' than my colleagues, because we are all working on different things. We do have these discussions, of course, and depending on the atmosphere, these discussions can be good-natured or dead-serious, but they are never objective. In the end we are usually cooperating, and not competing. Or, put more precisely, it is the cooperative effort that defines the success of the machine and not the competition (although sometimes a bit of competition may speed up things, or improve the quality of the products that are made).

The point is, that according to the pattern of difference, 'competition' only works well if there is a common frame reference that allows a form of ranking between (scarce) alternatives. If there is no common frame of reference, then you usually get confusion.

In previous posts, I have made some minor statements about my objections of method-bashing, the science wars, and so on. PAC tries to be an integrative method, but not a friendly (or naive) one; we do not want a tasteless euro-pudding where anything is possible, and everyone can happily do his or her own thing. This would result in a meaningless (relativistic) state of science which I call 'theory gas', and is based on Weinberg's graph. It is the epistemological equivalent of unorganised complexity.

Competition between various scientific dialects (and we can empirically observe that there is no such thing as THE science, but there are a lot of different forms) usually is based on confusion. We all usually have naive conceptions about the work of others (which are normative, not objective), and this means that our opinions tend to overestimate our own preferred epistemologies (see pattern of contextual diminution) and underestimate those of others (sometimes it is the other way round, by the way...just to make things more complex). It is one of the reasons why I do not have a high regard for criticism -scientific or otherwise- on others without any thought for alternatives for that what is criticised , criticism that does not demonstrate that the preferred epistemology is actually able to address the kinds of issues the others are wrestling with, or criticism that does not follow its own consequences through far enough.

As an example, there have been a few discussions about the differences between science and philosophy here at science 2.0. Now take the issue of 'sustainability'. I like this particular issue, because it brings two extremes together. One one side it deals with scarcety, which we can pursue with hard math and other scientific means. On the other side it involves issues of justice, ethics and morality. Because of the specialisations in science and philosophy, this topic thus either tends to fall apart in solid analyses on the condition of our world, with naive conceptions on justice, or deep philosophical thoughts with little thought for, say, the fact the world has welcomed two billion people or so more in the last half of a century, and all the practical issues that are related to this. It is going to be challenge to reconcile these two, and it is evident that there are no clear answers, or solid one-line wisdoms that can conclusively settle these matters. For this we need a normative science, that is able to explore and develop -given certain ideas on how we ought to treat the world- scenarios and strategies to make these ideas work. I can only see how collaborative efforts between science and philosophy (and practices) can address these themes, at least if one respects the complexity of these issues.

Sadly, we live in times where theory gas abounds, and everyone is quick to express an opinion without much thought. So you get these beautiful discussions on fora on the Internet and elsewhere of the type “well..that's your opinion...”, and “I am entitled to my opinion”, with all the supportive gestures and facial expressions, that suggest that these truisms conclusively settle the debates. The champions of this form of relativism however forget the ultimate consequence of their stances, and that is that their audience diminishes to one person as well, namely themselves. Or, if you're lucky, only convince those who already share your opinions.

Cross-scientific research -and my previous posts basically suggests that this is inevitable for complex themes- implies entering the confusion, and trying to sufficiently understand what is happening in other scientific domains to create supportive bridges between them (cross-referencing). This means that we allow our specialisations to become semi-open epistemological systems. The benefit is a possibility of creating robust models, but at the price of allowing, to sonme extent, that uncertainty and ambiguity mingles with the internal coherence of specialised areas. Hard work! Only in certain circumstances will the confusion and ambiguity be sufficienty contained to make fairly overseeable crossings, as for instance is currently done in bio-informatics. The common frame of reference is quite large between biology and informatics. Effective interfaces between epistemological systems allow these systems to counter the skewing of the models with respect to their targets. And I don't think that this means that one has to be an expert in those other areas. Often it is sufficient to know enough to make a balanced judgement on that what other domains have to offer.

This also means that cooperation is going to be of more importance than competition. Competition in its extreme form is wasteful for people's talents. You may get a ranking from the 'best' to the 'worst', but this doesn't mean that the 'losers' have nothing to offer or to contribute. With complex themes, like large-scale engineering projects, competition makes way for a cooperative effort of continuous improvement.

...that's usually the pattern with these mushy 'soft' thingies...they're so tremendously persistent!