Aug 2026· Journal of Applied Learning and Teaching· 0 citations
TL;DR
It is argued that this understanding of human-GAI engagement, as explained through epistemological beliefs, lays the foundation for alternative approaches to teaching and assessment, student interactions, professional development, and AI governance and policy, while noting that the framework remains an exploratory heuristic requiring empirical validation.
Abstract
In this paper, I introduce the theorising of seven human-generative artificial intelligence (GAI) paradigms, grounded in personal epistemological beliefs. Following a conceptual, theory-building approach, I begin by outlining the construct of personal epistemological beliefs, differentiating among the source of knowledge, certainty of knowledge, organisation of knowledge, control of knowledge acquisition and speed of knowledge acquisition by drawing on Schommer (1994) and Schommer-Aikins and Easter (2008)’s multidimensional model. I contend that these epistemological dimensions offer an understanding of human-GAI engagement. I proceed by introducing the dynamic human-GAI paradigms (guarded, possibility-focused, augmented, pioneering, symbiotic, values-based and equity), outlining each and examining them against the five epistemological dimensions. Rather than fixed traits held by individuals, the paradigms are conceptualised as enacted patterns of engagement that emerge across different disciplinary, socio-technical and institutional contexts. I conclude by arguing that this understanding of human-GAI engagement, as explained through epistemological beliefs, lays the foundation for alternative approaches to teaching and assessment, student interactions, professional development, and AI governance and policy, while noting that the framework remains an exploratory heuristic requiring empirical validation.
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
It is argued that intelligence should be assessed not by output quality or efficiency alone, but by its impact on intellectual character, arguing that intelligence should be assessed not by output quality or efficiency alone, but by its impact on intellectual character.
This article develops a sociology of generative knowledge for the age of AI. It treats contemporary systems as hybrid actors within sociotechnical networks and reframes classical anchors – Mannheim’s situatedness, Merton’s norms, and Latour’s distributed agency – for model-mediated inquiry. Generative knowledge is defined as knowledge organized to produce further knowledge through iterative, tool-mediated, and socially embedded processes. On this basis, the paper advances epistemic stewardship as a practical orientation that sustains human agency while harnessing computational acceleration. Stewardship is operationalized through transparency-by-design, provenance and traceability, calibrated trust, independent verification and red teaming, structured challenge routines, inclusivity in data and participation, and proportional delegation to machines. The account clarifies gains in discovery and education alongside risks from opacity, automation bias, feedback loops, and cognitive drift, and it specifies institutional reforms: standardized disclosure artifacts, replication triggers for AI-assisted claims, revised authorship taxonomies, and equitable access to compute, benchmarks, and community-governed datasets. A research agenda follows, calling for comparative evaluations of stewardship designs, longitudinal studies of hybrid practice, and field-specific protocols that link evaluation to adoption thresholds. The result is a framework that integrates social theory with design and governance guidance, aiming to convert acceleration into certified advance while keeping responsibility legible and contestable.
Paolo Granata· Journal of Emerging Perspect...· 0 citations
The article demonstrates how attempts to decentre the human often reconstitute new forms of authority in attempts to decentre the human and examines the possibility of surpassing standard anthropocentric approaches in AI while maintaining a critical philosophical engagement with the structurally necessary yet precarious character of organizing principles.
The findings reveal that coaches report using GenAI extensively for structured, information-intensive tasks while maintaining control over relational and interpretative work, which can be understood as boundary work preserving human authority over domains of tacit expertise.
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.