Abstract

Prior theory – that is theorising on the basis of thought and intuition , as opposed to attempting to explain observed data – inevitably distorts what comes after. It biases us in the selection of our data (the data model) and certainly biases any theorising that follows. It does this because we (as humans) can not help but see the world through our theorising – we are blind without the theoretical “spectacles” described by Kuhn (1962). If a theory has shown to be essentially correct in some domain (i.e. by thorough validation against the target problem or domain) using it as a framework can be helpful, however, if the theory is not mature or even speculative then it can effectively prevent progress . I argue that, although we can not ever completely avoid this sort of bias, we can minimise its effect. Two sources of prior theorising coming from opposite directions are sociology and formal systems – neither of these is inherently biased towards prior theorising, but just happens to be a source for such theorising at the present time. Computer scientists who project the results of interesting models onto society are also guilty of constructing first and fitting later.