Philosophy of Computational Social Science

Abstract

Computational social science is an emerging field at the intersection of statistics, computer science, and the social sciences. This paper addresses the philosophical foundations of this new field. Kant and Peirce provide an understanding of scientific objectivity as intersubjective validity. Modern mathematics, and especially the mathematics of algorithms and statistics, get their objectivity from the intersubjective validity of formal proof. Algorithms implementing statistical inference, or scientific algorithms, are what distinguish computational social science epistemically from other social sciences. This gives computational social science an objective validity that other social sciences do not have. Objections to the scientific realism of this philosophy from the positions of anti-instrumentalism, postmodern interpretivism, and situated epistemology are considered and either incorporated into this philosophy of computational social science or refuted. Speculative predictions for the field of computational social science are offered in conclusion: computational social science will bring about an end of narrative in the social sciences, contract the field of social scientific knowledge into a narrower, more hierarchical field of expertise, and create a democratic crisis that will only be resolved through universal education in computational statistics.