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Artificial intelligence (AI) technologies pervade myriad decision systems, mobilising data at a scale, speed, and scope that far exceed human capacities. Although it may be tempting to displace humans with these automated decision systems, doing so in high-stakes settings would be a mistake. Anchored by the example of states' resort to force, I argue that human expertise should be elevated—not relegated—within high-stakes decision contexts that incorporate AI tools. This argument builds from an empirical reality in which defence institutions increasingly rely on and invest in AI capabilities, an active debate about how (and if) humans should figure into automated decision loops, and a socio-technical landscape marked by both promise and peril. The argument proceeds through a primary claim about the amplified relevance of expert humans in light of AI, underpinned by the assumed risks of omitting human experts, together motivating a tripartite call to action. The position presented herein speaks directly to the military domain, but also generalises to a broader worldbuilding project that preserves humanism amidst suffusive AI. [ABSTRACT FROM AUTHOR]

The current period of disruptive social change is inextricably bound up with new means and modes of communication, information, and media streams. The Communication, Information Technologies & Media Sociology section of the American Sociological Association (CITAMS) locates these factors at the center of our collective interests, investigating them through a plethora of methods, theories, and empirical cases. Each year, CITAMS runs a special issue in ICS showcasing select works presented at the previous year's American Sociological Association conference and the affiliated Media Sociology preconference. Papers in the 2022 CITAMS Special Issue reflect a social context defined by a prolonged global pandemic and wrought by democratic uncertainty. Across these social circumstances, technology and media loom large. Simultaneously, everyday life continues and classic CITAMS scholarship sustains relevance for the ways people interact, construct identity, consume, and mobilize. All of this and more are contained in the pages of this year's Special Issue, from which readers can get a sense of what CITAMS has to offer and consider how their own work may fit within the broad CITAMS umbrella. [ABSTRACT FROM AUTHOR]

Each year the Communication, Information Technologies, and Media Sociology section of the American Sociological Association curates a special issue highlighting sociological contributions to technology and media studies. That tradition continued in 2020, even as everything else changed. The articles included in this year's special issue were mostly written pre-Pandemic, yet their implications seem amplified by the current historical moment. With a globe gone remote, mediated communication rose from a specialist academic subject to an acute social consideration, intersecting with and illuminating basic sociological concerns about inequality, the nature of work, family life, and the compounding effects of race, class, gender, and sexuality as they interplay with social and material conditions. These topics are all reflected in the articles from this year's issue, now inflected with a post-Pandemic reality that shows insights from CITAMS are needed now, more than ever. [ABSTRACT FROM AUTHOR]

Rating features on social media platforms affect visibility algorithms and act as symbolic markers of evaluation. This paper addresses the social effects of content ratings through a case study of Reddit. Reddit is a social news site on which users in topic-based communities (subreddits) create posts upon which others upvote, downvote, and comment. Vote scores indicate convergence with, and divergence from, community norms. Analysing data from the platform's three most popular subreddits, we ask: How do rating features afford emotional expression and content engagement? Findings from a Variable-Lag Granger Causality model show that for a portion of Reddit users (14.5%), vote scores predict subsequent emotional expression, with upvotes preceding positive sentiments and downvotes preceding negative sentiments. This is the first systematic test of how ratings influence emotional expression on a social media platform. Findings also show that downvoted content receives higher levels of engagement than upvoted content. Together, these findings suggest a paradox in which divergence from community norms, as indicated by vote score patterns, have emotional consequences and attention rewards. [ABSTRACT FROM AUTHOR]

Systems based on Artificial Intelligence (AI) are increasingly normalized as part of work, leisure, and governance in contemporary societies. Although ethics in AI has received significant attention, it remains unclear where the burden of responsibility lies. Through twenty-one interviews with AI practitioners in Australia, this research seeks to understand how ethical attributions figure into the professional imagination. As institutionally embedded technical experts, AI practitioners act as a connective tissue linking the range of actors that come in contact with, and have effects upon, AI products and services. Findings highlight that practitioners distribute ethical responsibility across a range of actors and factors, reserving a portion of responsibility for themselves, albeit constrained. Characterized by imbalances of decision-making power and technical expertise, practitioners position themselves as mediators between powerful bodies that set parameters for production; users who engage with products once they leave the proverbial workbench; and AI systems that evolve and develop beyond practitioner control. Distributing responsibility throughout complex sociotechnical networks, practitioners preclude simple attributions of accountability for the social effects of AI. This indicates that AI ethics are not the purview of any singular player but instead, derive from collectivities that require critical guidance and oversight at all stages of conception, production, distribution, and use. [ABSTRACT FROM AUTHOR]

Researchers increasingly draw on social media data to answer big questions about social patterns and dynamics. However, as with any data source, social media data present both opportunities and significant challenges. One major critique of social media data is that the data are not generalizable outside of the platforms from which the data originate. Problems of generalizability stem from non-universal participation rates on various platforms, demographically biased samples, as well as limited access to data based on infrastructural constraints and/or user privacy practices. We suggest that instead of empirical generalizability, social media data are theoretically generalizable in the formal theory tradition. Through a case example in which we use YouTube comments to test and extend a key tenet of identity theory, we show how social media data can instantiate theoretical variables and thus generalize to theoretical propositions. Mediated through formal theory, social media data maintain the capacity to address broad social questions while upholding methodological integrity. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including information technology; Media Sociology; and journalism.

Curation is a key mechanism of sociality in a digital era.With an abundance of information, sifting, sorting, selecting, hiding, and standing out become laborious tasks. While researchers have diligently documented people’s curatorial strategies, digital curation remains undertheorized in its own right. I therefore theorize digital curation by disentanglingproductive curationfromconsumptive curation, addressing how people curate content that they share, and that which they consume. I embed these agentic curatorial practices within structural bounds, both social and technological. In doing so, I offer a basic theoretical model that captures a dynamic relationship between individual curators, their social networks, and technological design. [ABSTRACT FROM PUBLISHER]

The collapsing of social contexts together has emerged as an important topic with the rise of social media that so often blurs the public and private, professional and personal, and the many different selves and situations in which individuals find themselves. Academic literature is starting to address how the meshing of social contexts online has many potentially beneficial as well as problematic consequences. In an effort to further theorize context collapse, we draw on this literature to consider the conditions under which context collapse occurs, offering key conceptual tools with which to address these conditions. Specifically, we distinguish two different types of context collapse, splitting collapse intocontext collusionsandcontext collisions. The former is an intentional collapsing of contexts, while the latter is unintentional. We further examine the ways in which both technological architectures and agentic user practices combine to facilitate and mitigate the various effects of collapsing contexts. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including formal theory for generalizability, attributions in artificial intelligence (AI)-human and symbolic interactionism in digitally mediated interaction structures.