The research group “Quantification and Social Regulation” investigates how regulation changes when it makes use of contemporary automated information and decision-making systems. Ubiquitous computing, big data and artificial intelligence (AI) entail new practices of quantification and valuation whose role for regulation and for democracy require further examination. The research group undertakes this endeavor by combining perspectives from social science and computer science.
Regulation can be understood as the intentional steering of individual and corporative actors’ behavior by state and non-state organizations in order to attain a pre-specified goal (Black) and is a key component of modern social life. Societies can thus be characterized with respect to the specific tools of regulation that they use.
In the last decades, scholars have drawn attention to the historical ties between, on the one hand, modern statehood and modern capitalism and, on the other hand, practices of quantification: processes such as the development of statistics as a tool of statecraft (Hacking) or the role of accounting in modern governance (Miller) have been well documented by social scientific research.
Yet in the face of profound technological developments in the last ten to twenty years we have to ask whether what we know about quantification and regulation still holds true or whether new technologies have changed the rules of the game. Is “governing by Big Data” different from “governing by numbers”? As of today digital technologies pervade modern societies at all levels: while the individual lifestyle and life decisions are increasingly guided by online environments and digital devices, organizations adopt algorithmic procedures and Artificial Intelligence to optimize their workflows.
This holds true for both companies and state actors, including political parties, public administration and courts. Modern computer technologies seem to render regulation more encompassing, tailored and effective – simply more powerful.
Yet such assumptions need to be validated against empirical analysis. Technological change is no force of nature; it is shaped by the very social contexts that it tries to order. Only empirical studies can reveal how automated information and decision-making systems work in a specific institutional context; how they are affected by organizational structures, power relations as well as professional norms and identities, all the while having an impact on these factors.
A detailed project description can be found here.
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