Panel I.08 — Schools and universities facing open artificial intelligence: Perspectives, Opportunities, and Risks
Convenors Ciofalo Giovanni (Sapienza University of Rome, Italy); Pedroni Marco (University of Ferrara, Italy); Francesca Setiffi (University of Padova, Italy, Italy)
Keywords Artificial intelligence, school, university, skills, educational practices
Artificial intelligence (AI) culture pervades contemporary society and daily life practices and can have different consequences on the process of democratisation, the private and public spheres, organisations, social systems, and the global economy (Elliot 2019). Moreover, algorithms can be considered as interaction partners (Esposito 2022). Every field of education is shaped by technological and digital processes, from technological devices to digital practices involved in teacher-student activities. Digital devices, technology infrastructure, and educational/training practices can impact educational contexts in different ways and be sustained by the perspective of Society and Technology Studies and precisely how sociomaterial processes are (re)shaping education and how digitalization and platformization processes are reassembling educational policy and practice (Viteritti, Piromalli 2021). The proposed panel will investigate the opportunities and risks associated with the various uses and impacts of AI through different theoretical frameworks and empirical perspectives. AI can have an impact on the professional activities of teachers, academics, and the study practices of high schools and university students. We identified three main categories of analysis:
– micro level: the uses, educational practices, and imaginaries of AI within the educational/university context; the impact of the ‘creation’ of knowledge, the development of skills, the relationships between teachers and students, and controversial ethical issues related to the use of AI.
– meso level: real/potential impacts of AI on educational organizations, such as schools and universities (e.g., analysis of policies, guidelines, official statements).
– macro level: social representations of AI (e.g., stereotypes and prejudices) and the public reactions of public institutions thematising risks and opportunities.
Mascheroni and Siiback (2021) analyzed the impacts of a datafied world on children and how a child-centered approach can shed light on the relation with AI in different contexts (e.g., at home, at school, and during play). Given that AI can have different impacts in several educational contexts (primary/middle school, high school, and university), we invite authors to submit articles that tackle the micro, meso or macro levels of analysis (or multiple levels of analysis) and that examine how AI can affect educational contexts and skills as a ‘boundary object’. Using Giancola and Viteritti’s perspective (2019), we consider skills as symbolic artifacts that can create a field of meaning, in which dissonances and tensions can be relevant.