Infantilising education through risk-averse educational technologies of calculability: a critical essay

This paper describes a paradox in education where AI-driven technologies foster risk-averse learning while contributing to heightened global uncertainties. We highlight how the promises of AI promote risk-aversion at the individual level through personalised learning while inducing unpredictable ‘superrisks’ at the societal level, affecting areas like the labour market, environment, societal relations. This paradox exposes gaps in educational policies that focus on integrating AI, ultimately legitimating AI-defined risks and needs (e.g., data literacy, coding) over broader societal risks (e.g., gender inequality, climate). We contend that AI’s reductive nature infantilises learners by reducing them to objects within calculable frameworks, stripping away opportunities to engage with and learn to manage real-world complexities. We argue for policy and educational paradigm shift that aims to reconnect education with the world, where students learn to navigate and embrace real-world risks directly, aligning with Hannah Arendt’s vision of taking responsibility for the world we inhabit.