Societal Algorithmification and its Computational Measurement

Abstract

The digitalization and algorithmification of individual behavior and social conduct have become the dominant socio-technological paradigm of our times. Its all-pervasive applicability modernizes all facets of human life. Computational social science methods have shown to be useful in studying the resulting dynamics by making effective use of the very same computational technologies that constitute the digital paradigm. The proposal of this line of research is to go one step further and not only take advantage of the tools, but also of the theoretical framework of the digital age. Information theory and theoretical computer science gave rise to the digital paradigm and, at the same time, turn out to be useful in its conceptualization and quantification. Variables like 'information', 'predictability', and 'knowledge' become measurable constructs in their own right. This Chapter reviews the underlying theoretical justifications and presents an overview of empirical applications, which include studies of recommender systems, collective dynamics on Wikipedia and the stock market, and the evolution of economic growth.

Keywords: information theory, algorithms, complexity, digitalization, artificial intelligence, complexity.