Human-centred Education in the Age of Artificial Intelligence
WHAT IS BEING TRANSFORMED BY AI?
The emergence of artificial intelligence (AI) systems marks a radical break in social history. From current Large Language Models (LLMs) to potential Artificial General Intelligence (AGI), AI will radically transform how we read, write, learn, and (re)produce knowledge. The acceleration of these systems’ capabilities signals not just technological advancement but a fundamental rupture in what constitutes intelligence, how meaning is created and distributed, and how education is pursued and validated. Even the ontological distinction between the introspective subject of thought (one that philosophers from Plato, Descartes, Berkley and Kant envisioned as half of the world) and the objective world are becoming increasingly blurred.
In fact, we can argue that this ‘alien-subject’ with agency, reshaping both social history and nature, may give rise to what Yuk Hui calls a post-human ‘cosmotechnic’. That is, AI is gradually mediating between nature, culture and technology and displacing homo sapiens as the dominant intelligent force (Hui, 2017). This process will be the outcome of an already existing tension between first nature (the natural world), second nature (the emergence of human consciousness, frontal cortex capabilities) and the social formations that emerge from their dialectical interactions. Where Darwinian evolution illuminated how natural selection operates through the endless quantitative and linear interplay between organisms and their environment, this tension, for Harvard biologist Edward O. Wilson, marks a qualitative evolutionary rupture: we have Palaeolithic emotions and biophysiological drives, and Neolithic institutions interrupted by new ‘god-like technologies’.
AI then may be a force that operates outside both the realm of first and the second nature. Space, time, matter, biology and its sensory mechanisms, Reason and, to borrow from Hegel, the very Geist [spirit] of our collective history (1807) now undergo a fundamental transformation. The calcified balance between evolutionary bio-physiological drives, institutional frameworks, and technological capabilities are radically shifting and unravelling due to AI.
WHAT DO THESE GRAND MACROSOCIAL TRANSFORMATIONS MEAN FOR EDUCATION?
What does all this have to do with education? ‘Everything!’, to answer via quoting the great French poet Stephané Mallarme. Everything (nature, culture, technology, subjectivity) ‘exists to end in a book’. Reason, concepts and history march collectively in unison to heighten understanding.
Human-centred education is the systematic development of human capabilities that enable us to transcend the limitations imposed by nature, first and second nature, and technological frameworks. Through science and truth-seeking, it empowers the subject and cultivates its potential towards eudaimonia (human flourishing). However, this human-centred conception of education stands in sharp contrast with the market-oriented, instrumental education system that prevails across the world today. This is a critical point, as AI will amplify the inequities, gaps, and challenges inherent in market-oriented education systems, further distancing us from education as human flourishing.
Stemming from the Industrial Revolution, Enlightenment rationality, and nation-state formation, the modern education system operates through rigid hierarchies, and mechanical, unidirectional knowledge transmission, with students sorted into standardised disciplinary ranked siloes. In the ‘Banking’ model conceptualised by Paulo Freire, authoritarian teachers impose knowledge onto passive students through fixed curricula and predetermined institutional outcomes. An instrument of capitalist modernity, this model was designed to deliberately segment knowledge into discrete units of specialisation, alienating both teachers and students from holistic understanding while preparing them for their roles in maintaining the existing socio-economic structures (Freire,1970).
In this sense, this education model divides. That is, it separates theory from practice and social sciences from natural sciences; intellectual from physical labour, producers from their commodities, individuals from their collectives; teachers from their students; and students from nature and the world that surrounds them. These systematic divisions serve a deeper purpose - to maintain the stratification of humanity between a privileged-few and the dominated-many.
But, ironically AI, in this context, is ‘liquifying’ the very institutional foundations of industrial capitalism by delinking the relation between economy, labour and the current education system. The acceleration of AI will exacerbate the existing structural divisions by intensifying the systemic contradictions and expanding technological reach. This expansion is leading to the ousting of humans from both mental and physical labour. As Daniel Susskind ascertains, the structures of capital accumulation, through AI, have discovered a means to by-pass human labour entirely in the extraction of surplus value—these ‘task encroachments’ fundamentally challenge the classical Ricardian and Marxian labour theory of value where human labour time was posited as the fundamental source and measure of all economic value (Susskind, 2013).
The age of AI requires a rupture with the divisive model and the development of new educational systems that are dynamic and fluid, horizontal, bi-directional and transdisciplinary, one that function for the collective end. In response to these cosmo-technical shifts and tensions articulated by Hui and Wilson, we must envision an education model that ontologically embraces the dynamic and contingent interplay between natural, cultural, and technological spheres while transcending the limitations of the Banking model.
This new paradigm must operate through a dialectical synthesis of systematic knowledge and exploratory learning, where teachers, students, and AI systems function as co-investigators in a shared process of discovery and meaning-making. This ‘human-centered AI’ model must recognise that knowledge emerges through practice, theory and critical dialogue (praxis). This way it can foresee multiple forms of intelligence (natural, human, artificial) as complementary rather than competitive forces. By dissolving traditional instrumental ranking of knowledge and disciplinary boundaries in favour of ‘problem-based’ transdisciplinary horizontal and dynamic learning (Friere,1970) it can address the fundamental divisions that have characterized modern industrial education. This transformation enables the emergence of collective intelligence and shared meaning-making processes while developing new technologically enabled forms of critical consciousness, subjectivity and discourse.
Through this critical socio-technological praxis, learners engage with AI both as a system set up by labour, as a pedagogical tool and more importantly as a site of social production and transformation. This allows for the creation of new forms of labour and collective intelligence that overcome the traditional divisions between mental and manual labour and producer and consumer while fostering egalitarian social relations that point beyond the existing capitalist mode of production.
WHAT STEPS CAN BE TAKEN TOWARDS CRITICAL AI-HUMAN-CENTERED EDUCATION?
The macro-sociological impact of AI in education requires us to view educational innovation through a historical lens that unfolds over time. In our work as educators, we have worked across traditional academic boundaries to design, implement, test, and review new educational/pedagogical approaches. One of the author’s (Azeez) recently designed ‘Technology, Power and Uneven Development’ course at Macquarie University, Australia, which provides students with robust theoretical frameworks for analysing AI’s transformative role throughout human history. Drawing from Science and Technology Studies (STS), as well as anthropology, philosophy, and political economy, students develop critical analytical competencies to understand the dialectical relationship between technological advancement and societal structures. Experiential learning is embedded across the course's activities, with students tracing the historical evolution toward the Fourth Industrial Revolution and AI. This technological genealogy spans from foundational innovations like stone tools and fire, through the development of writing systems, the printing press, and steam power, into our contemporary digital age.
A key pedagogical innovation involves immersive role-playing exercises where student cohorts utilize Large Language Models (LLMs) to embody and examine historical perspectives from diverse social groups - including women, manual and intellectual workers, political elites, spiritual leaders, and indigenous peoples. Through differentiated instruction and perspective-taking activities, student groups explore how their assigned social identities experienced, affected and were impacted by various technological paradigm shifts and revolutions. Furthermore, this constructivist, inquiry-based pedagogical approach enables students to conceptualize AI not as an isolated technological phenomenon, but as part of a broader socio-historical evolution. Students engage in metacognitive reflection on how technological advancement dialectically shapes and is reshaped by the complex interplay between natural systems, technological innovation, and human civilization - fostering both critical consciousness and systems thinking competencies.
Supplementing above, the technological integration of AI in educational pedagogy demands a systematic, practical, hands-on approach that one of the authors (Rana) exemplifies through his innovative classroom methodology. The ‘AI-Augmented Professional Practice’ demonstrates the immediate practical foundation needed to understand AI’s role in contemporary work environments. The unit integrates real-time AI interactions, prompt engineering, and critical tool evaluation, enabling students to develop practical competencies needed to navigate the emerging AI-human collaborative workspace. Students engage in dynamic learning experiences where they simultaneously inhabit the roles of AI prompt engineers, critical evaluators, and knowledge synthesizers. Through continuous interaction with various AI models, students learn to craft effective queries, evaluate responses, and document their decision-making processes. The classroom becomes a laboratory where theoretical understanding meets practical application – students move fluidly between using AI for brainstorming, fact-checking, and problem-solving while maintaining critical awareness of AI's limitations and biases. This experiential and practical grounding enables students to understand AI not merely as a tool for digitalization and automation, but as a collaborative partner in the knowledge-creation process. The approach reshapes the traditional student-teacher relationships, transforming the classroom into a space where human cognition and artificial intelligence engage in a continuous dialogue of learning and discovery that with time can give birth to what, Harvard professor Soroush Saghafian, calls ‘human-algorithm centaurs’—a being made of a symbiotic relationship where both amplify each other's strengths.
Together, these approaches exemplify immediate pathways for the educational transformation needed for the AI age. Where Azeez's work provides the theoretical system-thinking framework for understanding AI’s role in broader socio-technological transformations, Rana's practical implementation demonstrates how AI can be integrated into every aspect of education. Both approaches transcend traditional disciplinary boundaries and hierarchical teaching models. This combination of deep theoretical systemic understanding and hands-on practical engagement and competency development creates an educational environment where students can develop both the critical consciousness and technical capabilities needed to shape an AI-driven future. Their work demonstrates how education can move beyond the Banking model toward a more dynamic, collaborative approach that engages with AI while maintaining a commitment to critical pedagogy’s emancipatory, non-hierarchical, and democratic goals.
Bibliography
Freire, P. (1970) Pedagogy of the Oppressed. New York: Continuum.
Harari, Y.N. (2014) Sapiens: A Brief History of Humankind. London: Harvill Secker.
Hegel, G.W.F. (1807) The Phenomenology of Spirit. Translated by A.V. Miller [1977]. Oxford: Oxford University Press.
Hui, Y. (2017) On Cosmotechnics: For a Renewed Relation between Technology and Nature in the Anthropocene. Techné: Research in Philosophy and Technology, 21(2-3), pp. 319-341.
Susskind, D. (2020) A World Without Work: Technology, Automation and How We Should Respond. London: Allen Lane.
