The Society of Algorithms

Abstract

The pairing of massive data sets with processes—or algorithms—written in computer code to sort through, organize, extract, or mine them has made inroads in almost every major social institution. This article proposes a reading of the scholarly literature concerned with the social implications of this transformation. First, we discuss the rise of a new occupational class, which we call the coding elite. This group has consolidated power through their technical control over the digital means of production and by extracting labor from a newly marginalized or unpaid workforce, the cybertariat. Second, we show that the implementation of techniques of mathematical optimization across domains as varied as education, medicine, credit and finance, and criminal justice has intensified the dominance of actuarial logics of decision-making, potentially transforming pathways to social reproduction and mobility but also generating a pushback by those so governed. Third, we explore how the same pervasive algorithmic intermediation in digital communication is transforming the way people interact, associate, and think. We conclude by cautioning against the wildest promises of artificial intelligence but acknowledging the increasingly tight coupling between algorithmic processes, social structures, and subjectivities. Expected final online publication date for the Annual Review of Sociology, Volume 47 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Evolving Conceptions of Work-Family Boundaries: In Defense of The Family as Stakeholder

“…We do not consider that our scenarios exhaust interpretive possibilities. Other approaches such as differences between family and non-family businesses, dual and non-dual work couples, as well as differences between the knowledge work elite and the “cybertariat” (Burrell and Fourcade 2021 ) might have been chosen as a basis for analysis. We have chosen to consider the tensions between work and family domains of organization as our conceptual focus.…”

Artificial intelligence, algorithms, and social inequality: Sociological contributions to contemporary debates

“…Projecting from current trends, it is easy to imagine a future world where wealth and power are even more concentrated in the hands of the ‘coding elite’ (Burrell & Fourcade, 2021) than today – a scenario that one RAND‐affiliated author has called ‘Bezos World’ (Lempert, 2019). This sort of speculative dystopia has already generated social engineering proposals to redistribute wealth and inequality along both radical and conservative lines – from ‘luxury communism’ (Bastani, 2019), to new capital taxes that fund basic income for citizens (Clifford, 2021), or a ‘cyber republic’ in which new kinds of ownership and ‘data property rights’ are maintained through tokens and distributed ledgers (Zarkadakis, 2020).…”

“…Some sociologists have addressed AI in a general sense, either to argue that it is indeed transforming our everyday lives (Elliott, 2019), or to push back against grandiose claims of AI's capabilities (Collins, 2018). Burrell and Fourcade (2021) remind us that 'we can both reject magical thinking about machine intelligence and acknowledge the enormous economic, political, and cultural power of the tech industry to transform the world we live in' (p. 231). Questions of power (see Kalluri, 2020) should be a primary concern for us as sociologists, given what is at stake in this ongoing transformation and the inequalities that algorithmic systems can either shift or lock into place.…”

“…Over the past several years, the idea that society is being radically transformed through artificial intelligence (AI), machine learning, and automation has been widely discussed in popular venues. This transformation has been addressed through a growing body of sociological scholarship (see Joyce et al., 2021; also; Airoldi, 2022; Burrell & Fourcade, 2021; Davis et al., 2021; Elliott, 2022; Issar & Aneesh, 2022; Jaton, 2021), although some of the most prominent sociological analyses of these technologies have come from academics who are not (formally) sociologists (Crawford, 2021; Eubanks, 2017; Zuboff, 2018). Societal questions are now recognized as crucial ones for the developers of new algorithmic technologies, but ‘AI scientists continue to demonstrate a limited understanding of the social’ (Joyce et al., 2021, p. 5).…”

Because the Machine Can Discriminate: How Machine Learning Serves and Transforms Biological Explanations of Human Difference

“…To date, the literature on algorithms and society has largely organized into two positions. One strand theorizes how algorithms are used to consciously and fundamentally transform society (Burrell and Fourcade 2021;Cheney-Lippold 2017;Kiviat 2019). The other strand theorizes how algorithms tend to unreflexively reproduce longstanding social patterns (Benjamin 2019;Eubanks 2017;Noble 2018).…”