The September 2015 photograph of Alan Kurdi, a 3-year-old Syrian boy, lying facedown and dead on a Turkish beach, quickly became an iconic representation of Europe's "refugee crisis." Even though images of distant suffering of refugees have become ubiquitous, only a few become iconic. It is this cultural process of iconization that often bedevils sociologists interested in visuality. How does an image gain the necessary currency to sway public opinion or even policy making? Why do some photographs elicit profound compassion that transcends the borders of its particular context?In this review, we explore how various authors have addressed these questions, focusing on the iconic images of Alan Kurdi. The "iconic turn" in cultural sociology and in the social sciences more broadly speaking offers theoretical and methodological insights for the analysis of images such as those depicting refugees and asylum seekers. For this reason, we situate the current work in the field of refugee photography within the framework of cultural sociology, even if many of the scholars discussed are from other disciplines.
As a social phenomenon, artificial intelligence (AI) is not just technically but also culturally constructed. This article investigates the meaning-making of AI in the case of AlphaGo by employing and refining cultural sociological narrative analysis. Building on Smith’s structural model of genre, whose horizontal axis reflects varying degrees of (dis-)enchantment, I propose an extended model of narrative genre, adding a vertical axis on the theoretical basis of Durkheim’s distinction between pure and impure sacred, to account for the empirical bifurcation between utopian and dystopian AI narratives. While critical approaches to AI, prevalent in sociology, tend to offer disenchanted narratives, my cultural sociological approach allows for the construction of a meta-narrative, which is able to capture not only enchantment as well as disenchantment but also purification and impurification as empirical processes that accompany the emergence and consolidation of new technologies. This approach is exemplified by a case study of AlphaGo, a Go-playing program utilizing machine learning and neural networks, which gained global prominence and cultural significance after beating a human grandmaster in 2016. Drawing on publicly available online data, this article investigates the discourses surrounding AlphaGo, focusing on its cultural construction through storytelling and genre. I not only show how characters and events were emplotted in different stories, which were in turn embedded in broader narratives about technological progress and AI, but also explain how the development of the main storyline was driven by in-game performances, audience expectations and collective representations. The article demonstrates the feasibility of a cultural sociology of AI and the usefulness of my extended model of narrative genre, which is not only applicable to AI discourses but other domains as well.
The concept of social performance is a major theoretical innovation of the strong program in cultural sociology, championed by Jeffrey C. Alexander. This article offers a critical assessment of Alexander’s last four monographs on political performances with the explicit aim of contributing to the future development of the performance approach. After an outline of Alexander’s theory of performance, I continue to discuss his book-length empirical contributions, highlighting the innovations introduced by each study. Confronting Alexander’s research strategies with his theoretical framework, I propose a recalibration of his ‘liberal’ sociology of performance, bringing ‘conservative’ aspects of political culture back in, first of all particularity and historicity. This entails a rethinking of performance effects in terms of ‘resonances’ attuned to particular audiences and a deeper hermeneutic engagement with specific historical backgrounds of collective representations in order to overcome the one-sidedness of Alexander’s constructivist approach.
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