The Dark Side of the Force: When computer simulations lead us astray and "model think" narrows our imagination
|Table of Contents|
|2 Different aims of computer simulations in science|
|3 Criteria for “explanatory” simulations|
|4 Simulations that fail to explain|
Quite a few lessons that can be learned from the previous examples of failures of computer models. Some of them are truisms, but as they are often neglected they are important nonetheless.
First of all, if our models are to be explanatory then the establishment of a close fit between model and reality is at least as important as the construction of the model itself. The biological examples such as Milinski's and Parker's studies on predator inspection suggest that establishing this fit may even be much harder and more time consuming than constructing the model itself.
Secondly, when there is no close fit between model and reality, then the model has approximately the epistemological status of a metaphor. The results of such non explanatory simulations are hardly more than computer generated metaphors. Therefore, one must be very careful when drawing conclusions from them. At best one can regard these conclusions as mere hypotheses that still require an independent empirical confirmation. It should be clear that explanations based on non explanatory computer simulations amount to nothing more than model based story telling. I am introducing these terms, because I believe that we need some negative catch phrases to characterize the misuses of formal models and, specifically, computer simulations.
Finally, we should be aware of the fact that although the ease and power of formal modelling has been greatly increased with the advent of the computer, there still remain scientific areas where the advantages of formal modelling are doubtful or where it is not possible at all. Computer simulations are just one scientific tool among others. It is helpful in some situations but useless in others. In my opinion the employment of the tool of computer simulations should be seen as something that requires justification. Apart from the aim to prove logical possibilities or to produce predictions it can be justified when there exists a close fit to the sort of empirical situation the simulation models or there is at least a realistic prospect of developing the simulation further so that a close fit can be established. Where computer simulations cannot not go beyond a merely metaphorical resemblance of empirical reality they are probably not worthwhile.