Toward a Sociology of Artificial Intelligence: A Call for Research on Inequalities and Structural Change

Abstract

This article outlines a research agenda for a sociology of artificial intelligence (AI). The authors review two areas in which sociological theories and methods have made significant contributions to the study of inequalities and AI: (1) the politics of algorithms, data, and code and (2) the social shaping of AI in practice. The authors contrast sociological approaches that emphasize intersectional inequalities and social structure with other disciplines’ approaches to the social dimensions of AI, which often have a thin understanding of the social and emphasize individual-level interventions. This scoping article invites sociologists to use the discipline’s theoretical and methodological tools to analyze when and how inequalities are made more durable by AI systems. Sociologists have an ability to identify how inequalities are embedded in all aspects of society and to point toward avenues for structural social change. Therefore, sociologists should play a leading role in the imagining and shaping of AI futures.

Digital Society and Digital Sociology: One Thing Leads to the Other

“…Digital sociology is an opportunity for sociological analysis given that the artifacts, practices and representations shaped by the digital have a socially and culturally constructed component (2), which enables sociology to study it, contributing to explaining this social by the social (35). Sociology can contribute to a sociologically informed society, in which sociological scientific knowledge, although this is not its main goal (31,32), can also be applied to foster a more integrated, inclusive and sustainable development (9,11,19,20).…”

“…However, digital technologies are not neutral and can work either through access or practice as a reinforcement of existing social inequalities or as a generator of new inequalities in a digital divide scenario (1-3, 14, 19). This emerges as a crucial new area of study for sociology and can even revitalize sociological science (2,7,19…”

AI Ethics Principles in Practice: Perspectives of Designers and Developers

“…In response to this principle, some participants raised concerns about data analyses and recommendations that may have uneven benefits and reinforce disadvantage in society. This reinforces the need for diverse perspectives and collaborative teams in the design, development and use of AI technologies [42]. Participants were also concerned about applications of AI systems that they regarded as having contested impacts on human and social wellbeing, such as facial recognition, dual-use applications, and non-civilian applications.…”

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

“…None of this has been surprising to scholars in fields such as science and technology studies (STS), critical data studies, or critical algorithm studies, who have long examined the relationships between technology and social structures (Felt et al., 2017; Gillespie & Seaver, 2016; Iliadis & Russo, 2016). Sociologists in general have been less engaged in these issues thus far, which is unfortunate given that social theory can fill the conceptual chasm currently identified as ‘bias’ in data science (Joyce et al., 2021; Zajko, 2021).…”

“…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).…”