The myth of the “data‐driven” society: Exploring the interactions of data interfaces, circulations, and abstractions

Abstract

The prominence of data and data technologies in society, such as algorithms, social media, mobile technology, and artificial intelligence, have heralded numerous claims of the revolutionary potential of these systems. From public policy, to business management, to scientific research, a “data‐driven” society is apparently imminent—or currently happening—where “objective” and asocial data systems are believed to be comprehensively improving human life. Through a review of existing sociological literature, in this article, we critically examine the relationship between data and society and propose a new model for understanding these dynamics. “Using the concept of the informatic,” we argue the relationship between data and society can be understood as representing the interaction of several different social trends around data; that of data interfaces (that connect individuals to digital contexts), data circulation (trends in the movement and storage of data), and data abstraction (data manipulation practices). Data and data technologies are founded to be entwined and embedded in numerous social relationships, and while not all are fair and equitable relationships, there is ample evidence of the deeply social nature of data across many streams of social life. Our three‐part informatic framework allows these complex relationships to be understood in the social dynamic through which they are witnessed and experienced.

Open Government Data as a Reform and Ecosystem : A conceptual framework for evolution and health

“…I understand that people, to a greater extent, are connected and share data. They or artifacts also move, store, manipulate, use, and act on data to a greater degree (Lee and Cook, 2020). Similar to an information society, a data society is not something new.…”

“…The data sector is in a state of being ancient and nascent. It can be understood as (1) data interfaces that help people to connect and share data, (2) data circulations where data are moved and stored, and (3) data processing where data are manipulated, used, and acted on (Lee and Cook, 2020). Data are also collected, acquired, gathered, or created (Checkland and Holwell, 1997).…”

“…The data sector is the area populated with actors that work with data, and I believe it to be the heart of an OGD ecosystem. It contains nodes and flows of providers and enrichers (based on Alter, 2003b;Crusoe, Zuiderwijk, and Melin, 2020;De Saulles, 2020;Lee and Cook, 2020). However, it is deep below the information surface and requires certain knowledge to navigate and know-how (Crusoe, 2021a).…”

Big Data and the Little Big Bang: An Epistemological (R)evolution

“…Last year's Cambridge Analytica scandal and the case of Russian trolls targeting teens with memes over Facebook prove the extension of such an issue and how artificially certain supposedly natural actors can behave. As photography might not be a truthful representation of reality, big data might not be utterly exhaustive nor accurate (Bollier, 2010 ; Arbesman, 2013 ; Brooks, 2013 ; Frické, 2014 ; Welles, 2014 ; Bail, 2015 ; Jones, 2019 ; Corple and Linabary, 2020 ; Lee and Cook, 2020 ). Everything is significant and outliers are difficult to identify; as such, artificial actors cannot always be distinguished from natural ones, online and offline behaviors can differ, there may be multiple users behind an account, etc.…”

The Legalhood of Artificial Intelligence: AI Applications as Energy Services

“…Nowadays, our society is rapidly changing into a raw data-based one [14] and the basic resources are no longer capital or natural resources, but data sets. With huge amounts of data being the core resource, the capability of effectively managing heterogeneous data is becoming a crucial factor which involves information technology, and especially Artificial Intelligence (AI).…”