Pragmatic Realism and Scientific Prediction: The Role of Complexity

Abstract

According to the general emphasis of pragmatic realism in science as human activity and the role of objectivity, prediction in the social sciences, like economics, and in the sciences of the artificial, like the sciences of the Internet, cannot be seen as if it were a mere intellectual exercise of knowledge, but rather it should be oriented towards relevant issues. These could be regarding a) the validity of the theories available (which is very important in the case of economics), b) the reliability of the practical solutions to specific problems, or c) the large amount of variability in the application of the tested scientific solutions. Within this context of pragmatic realism, the evaluation of the axis of the proposal - scientific realism around activity and objectivity - comes from how scientific prediction deals with complexity, both structural and dynamic. This is crucial in the case of prediction of the social sciences, where complexity is in the social world (particularly, in economics) at different levels (micro, meso, and macro: individuals and groups, organizations and markets, governments and international institutions). In addition, it is decisive for the sciences of the artificial, which enlarge human possibilities based on predictions of the viability of the aims of the designs, as can be seen in the sciences of the Internet. The test of the dealings of prediction in these sciences with complexity should reinforce the need for objectivity while developing the scientific activity in the three spheres indicated: basic science, applied science, and application of science.

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