Ateneo - UPO

Digital sociology is a mode of investigating, analyzing, and understanding the impact, development, and use of technologies and their integration into social worlds, social institutions, daily life, and relationships between people and groups. Simultaneously, on a more individual level, there is a true "embodiment" of technologies in the imagination, mind, symbolic sphere, cognition, and the very body of individuals. By introducing the various social, cultural, and political dimensions of the digital society, the course aims to provide a set of theoretical, methodological, and operational tools with the intention of enabling students to navigate the various themes and issues related to this field of research. These include, for example, the role of users in innovation processes, the issue of behavioral data and its use in the context of "surveillance capitalism," the problem of ownership and common goods in the platform economy, issues related to science, knowledge, and information and their reconceptualization in the digital risk society, the contribution of digital devices to the incorporation and perception of the self, digital politics, and the evolution of forms and tools of democratic participation.

None. The teacher will provide handouts and materials through the DIR - Didattica In Rete platform.

Knowledge and Understanding. The course aims to present and discuss with students the main issues related to the digitalisation of society and which have been studied by sociology. These themes concern the characteristics and controversies of the digital society, understanding the social and technological processes of digital spaces, and empirical research in digital platforms. The course therefore offers the theoretical and methodological tools necessary for the analysis of forms of sociality, social change, processes of public opinion, and economic and social inequalities that characterise the present in the context of daily digital interaction. Ability to apply knowledge and understanding. Students will acquire: 1) the ability to understand the social change associated with the development of artificial intelligence; 2) the ability to reflect critically on the processes generating decision-making models by means of algorithms and their possible social consequences; 3) the ability to orient themselves in the debate on the social impact of digitalisation and the mechanisms of social interaction underlying its development; 4) the ability to orient oneself on the main empirical tools of social research in digital contexts. Autonomy of judgement. The course aims to promote a strong autonomy of judgement in recognising, analysing and communicating possible criticalities related to social processes within the socio-digital space, analysing the consequences at micro and macro social level also with the use of specific empirical research strategies. Communication skills. Ability to present one's skills and knowledge in a clear and articulate manner at public, academic and dissemination, events on digital society issues and to interact with scholars from other disciplines dealing with artificial intelligence. Learning skills. Students will acquire the theoretical and methodological tools to address and participate in the contemporary debate on the social impact of artificial intelligence as well as the analytical tools for its analysis.

No prerequisites required.

Lectures, seminar-style sessions, and practical exercises.

Students with disabilities, Specific Learning Disorders (SLD), or Special Educational Needs (SEN) may request dedicated services and support tools by contacting the Career Development and Student Services Coordination Staff and consulting the dedicated page on the University website: https://uniupo.it/it/servizi/servizi-studenti-disabili-e-dsa Additionally, students with disabilities, SLD, or SEN are encouraged to contact the course teacher to clarify or define the specific exam arrangements.

Final oral exam. The discussion will start from the project that students will work on during the course. During the discussion, students will be required to demonstrate their knowledge on theories and tools learned throughout the course. Additionally, they should show proficiency in the methodological and technical skills relevant to applied social research in the field of digital innovation.They have applied these knowledge already mentioned to develop their project.

The first part (20 hours) will introduce general theories and issues specific to sociological disciplines, with brief hints. It will also cover some historical background elements related to digital innovation and artificial intelligence. The second part (10 hours) will explore areas of interest in digital sociology and the sociology of innovation. The third part (20 hours) will focus on issues of innovation and the digital society, including seminars on types and narratives of innovation, common goods, and collective dynamics of innovation. The fourth part (20 hours) will address issues related to the social dimension of innovation, as well as the identification, formulation, and discussion of project proposals.

Knowledge - By the end of the course, students should have acquired the following knowledge: to be able to problematise the relationship between digital technologies and society; to be able to critically interpret the phenomena that characterise the digital society, with particular attention to the forms of sociality and social inequalities that distinguish it; to be able to evaluate the role of technology in a given social context. Competences and skills Competences - Ability to analyse phenomena and social contexts by setting them in the context of the historical, socio-economic, cultural and political transformations of the digital society and to understand and analyse the digital transformation of knowledge production processes in different fields (welfare, work, education, environment, territory, urban life, etc.) Skills - Ability to constantly follow the scientific debate on the central topics of the course. Ability to collect and critically manage digital data and to collaborate in the definition of research and policy strategies based on digital data, also in integration with other scientific disciplines.