Conference Program

AI systems, as well as tools with increasingly widespread access, are a pervasive symbol of technological power. Between the object and the figuration, the algorithmic machines contribute to develop a multidimension fracture (epistemic, cultural, technical) in doctoral education (Lund & Wang, 2023). The doctoral subject is inserted inside the network of different possibilities between access to tools, skills and heterogeneous and subjective perceptions inside a network in which AI is a co-agent in the development of knowledge (Floridi, 2025).

Referring to epistemic cultures (Knorr Cetina, 1999) and of actantiality, the latter in line with the Actor-Network Theory (Latour, 2005), the contribution aims to reflect on how to intervene educationally in the relationship between AI, symbol and divide from a perspective of equity in the context of university education. The study is based on contents taken from semi-structured interviews conducted with professors of Science Education in Italy.

Beyond a technocratic vision, the reflection aims to investigate the factors of inequality in the knowledge production (planning, reviewing, source gathering, synthesis), focusing on cultural constructs, interacting within a heterogeneous network, characterized by human individualities and collectivities (doctoral subjects, supervisors, doctoral communities), and technological tools (algorithmic models, writing assistants platforms, edtech resources). In particular, within this system, the contribution explores the question of the image of technological singularity, a radical discourse on AI’s potentiality and role (Eden et. al., 2012), when combined with the principle of efficient performance (Dardot & Laval, 2019). The reflection underlines how the combination of the two elements contributes to internalizing and naturalizing the human-AI relationship in the production of university knowledge production in competitive- individualistical terms rather than one of openness to comparison and dialogue.

Finally the alliance between the technological singularity and the performance pushes towards the necessity of measurability and the importance of operability and commercial attractiveness; these qualities, in great tension with the principle of research autonomy, will be examined with the aim of valorizing metacognitive principles in the doctoral context from the perspective of critical, intellectual and democratic exploration (Fenwick & Edwards, 2018; Reid, 2025).