Aug 2026· AI, Brain and Child· Vol 2· 0 citations· 65 references
TL;DR
It is argued for a conceptual reorientation from pedagogical scaffolding toward learning-ecosystem architecture and proposed a pedagogy of friction that preserves the desirable difficulties through which authentic agency is nurtured.
Abstract
The integration of artificial intelligence (AI) into early childhood environments is most often judged through a binary lens of educational benefit versus technological harm. This framing overlooks a deeper question: how these systems reshape the ecological conditions on which child development depends. This exploratory, theory-generating conceptual inquiry examines how experts conceptualize the tension between the highly efficient illusion of agency presented by AI systems and the ecological conditions that support the development of authentic agency in young children. Using a qualitative expert-interview approach, we gathered the perspectives of six interdisciplinary scholars and analyzed them through a primarily deductive and partly inductive content analysis. Anchored in the multiple-realizability-of-agency thesis, actor-network theory, and complexity systems thinking, the analysis suggests that experts perceive AI’s simulation of interactivity, autonomy, and adaptability as potentially reducing the physical and social frictions that support developmental processes, redistributing decision-making within child–adult–AI networks, and limiting opportunities for the development of resilience. Drawing on these expert perspectives and the study’s theoretical framework, we argue for a conceptual reorientation from pedagogical scaffolding toward learning-ecosystem architecture and propose a pedagogy of friction that preserves the desirable difficulties through which authentic agency is nurtured.
The findings suggest that while GenAI may enhance learner agency through personalisation and support, it also risks exacerbating educational inequalities and diminishing learner autonomy in certain contexts.
Jasper Roe, Mike Perkins· Academia AI and Applications· 23 citations
Generative artificial intelligence (GenAI) has been primarily framed as an impartial educational tool. However, this framing overlooks an even larger shift: the reassignment of epistemological authority from teachers to students to machines. This paper presents a conceptual evaluation of the extent to which GenAI redistributes students'and teachers'ability to act in classrooms to produce knowledge, validate each other's claims, and create evidence of student learning while collaborating with and competing against humans. This evaluation draws on various theoretical paradigms, including Distributed Agency, Self-Determination Theory, Society 5.0, and Technology Integration Paradigms, including TPACK and SAMR. While all of the theoretical paradigms evaluated are relevant to the role of agency within education mediated by AI, none of them address the ongoing disparity regarding equitable distribution of power, ownership of the data used to mediate interaction, and accountability in relation to human-mediated interactions. As such, this paper introduces the Ecological Co-Agency Framework, which defines agency in terms of relational, regulatory, and pedagogical processes, conditioned by a defined commitment to human accountability for epistemological claims.
Artificial intelligence is being adopted in educational settings faster than its consequences are understood. We argue that the central risk is misalignment: AI that eliminates human effort erodes the very capacities education is meant to build. We organize this risk into an integrative framework of four interrelated dimensions -cognition, agency, emotional well-being, and ethics- linked by a self-reinforcing cycle where cognitive offloading reduces effort, weakens agency, and compounds emotional and ethical harm. We ground the framework in the perspective of a small cohort of students: an exploratory analysis of 49 International Baccalaureate argumentative essays about the impact of AI reveals that learners perceive these risks, with $80\%$ of essays reporting that AI reliance reduces thinking. At the same time, the essays articulate a consistent vision of the AI the students want: systems that support rather than replace learning by withholding immediate answers, prompting recall, and encouraging reflection through questions instead of solutions. These desiderata closely align with established principles from the learning sciences. Building on these insights, we propose a single design principle, scaffold, do not substitute. We argue that this principle extends beyond education. It represents a broader challenge for the AI ecosystem: any system that mediates human thinking can either weaken human capabilities through substitution or strengthen them through scaffolding. We conclude by outlining a research agenda for developing AI systems that foster enduring human capacity, an imperative not only for learners but, ultimately, for democratic societies.
Lucile Favero, J. A. Pérez-Ortiz, Tanja Käser et al.· 0 citations
The concept of “alienated intelligence” is introduced to critically examine contemporary cultural perceptions of artificial intelligence to argue that certain visions of AI function as cultural projections of human cognitive capacities that become externalized, idealized, and reified in technological systems.
This study examines the transformative impact of artificial intelligence (AI) on the future of work from a human-centered, interdisciplinary perspective, highlighting the necessity of interdisciplinary collaboration to ensure that AI not only enhances efficiency but also promotes justice, well-being, and sustainability.
Cumali Kılıç· Çukurova Üniversitesi Sosyal...· 0 citations
It is argued that anthropology requires a new conceptual framework for understanding the contemporary social life of artificial intelligence (AI), and "the magic of AI" is proposed as an analytical concept that shifts attention from AI's technical capacities to the beliefs, uncertainties, and sociotechnical imaginaries through which it acquires authority and efficacy.
M. Baas, Roanne van Voorst· Anthropological Theory· 2 citations
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