Current sociology doesn’t have a settled view on what to do with a phenomenon that in the literature has been titled as “artificial intelligence” (AI). Sociological textbooks, handbooks, encyclopedias, and sociology classes’ syllabi typically either don’t have entries about AI at all or talk about it haphazardly with a stress on AI’s social effects and without discerning the underlying logic that moves the prodigy on. This paper is an invitation to a professional conversation about what and how social sciences can/should study “artificial intelligence”. It is based on a discussion of the preliminary results of an on-going three-year research project that has been launched at the ISA Congress in Toronto. The paper examines AI in relation with ‘artificial sociality’. It argues that research on AI-based technologies is flourishing mainly outside established disciplinary boundaries. Thus, social sciences have to look for new theoretical and methodological frameworks to approach AI and ‘artificial sociality’.

What can variously be understood as “comparative sociology” take different contours and raise further issues and questions in different sociological traditions which in turn are shaped by different theoretical paradigms. The paper outlines conceptual and theoretical framework for a discussion about the current status of comparative sociology. Comparative sociology is perceived as an organization of research through constant comparisons at the different levels and stages of research. The paper presents outcomes of the field research that is developed on the basis of distinction between two modalities of comparative sociology: comparative sociology as an inquiry and comparative sociology as a teaching discipline. One basic and two subordinate alternative hypotheses are tested in the course of comparative analysis of the seven cases. Discussion of these cases results in formulation of specific questions for further research.

The objective of this paper is to outline and compare frameworks for studying post-Soviet transformations developed by social scientists from various disciplines in Belarus, Russia and Ukraine. The objective is realized by means of quantitative content analysis of scholarly articles’ abstracts in ninety-four journals in eight (inter)disciplinary fields that covers the period of 2001-2015. This paper seeks to answer the question whether differences in the studies of the post-Soviet transformations are defined by country discourse or by the field of study. The research results suggest that there is a two-level mechanism, by which the societal context affects academia, in this case, social sciences and humanities. While general directions of scholarly attention are determined by societal differences, representations of post-Soviet transformations are framed through specific disciplinary lenses that combine both international and post-Soviet features.

This article examines how transnational labor migrants to Russia from the five former Soviet Union countries – Azerbaijan, Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan – identify themselves in social media. The authors combine Rogers Brubaker's theory of identifications with Randall Collins' interaction ritual theory to study migrants' online interactions in the largest Russian social media (VK.com). They observed online interactions in 23 groups. The article illuminates how normative and policy contexts affect the Russian Federation's migration processes through a detailed discussion of migrants' everyday online interactions. Results reveal common and country-specific identifications of migrants in their online interactions. Migrants from Kazakhstan and Azerbaijan employ identifications connected to diasporic connections. Migrants from Kyrgyzstan, Uzbekistan, and Tajikistan in their identifications refer to low-skilled labor migration to Russia as a fact, a subject for assessment, and as a unifying category. For these countries, the present and the future of the nation is discussed in the framework of evaluation of mass immigration to Russia.

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