A guideline for understanding and measuring algorithmic governance in everyday life

Abstract

Algorithmic governance affects individuals’ reality construction and consequently social order in societies. Vague concepts of algorithmic governance and the lack of comprehensive empirical insights into this kind of institutional steering by software from a user perspective may, however, lead to unrealistic risk assessments and premature policy conclusions. Therefore, this paper offers a theoretical model to measure the significance of algorithmic governance and an empirical mixed-methods approach to test it in different life domains. Applying this guideline should lead to a more nuanced understanding of the actual significance of algorithmic governance, thus contributing to an empirically better-informed risk assessment and governance of algorithms.