This paper argues that the existing frameworks for AI literacy are insufficient because they enforce a consumer-orientation toward AI rather than fostering genuine epistemic agency, and proposes a three-part framework of AI literacy based on the notions of contextual use, critical interrogation, and participatory governance.
Abstract
As generative artificial intelligence becomes one of the most significant systems of knowledge production in our society today, questions relating to who can access and shape that production grow increasingly important in our discourse. This paper argues that the existing frameworks for AI literacy, which are dominated by technical competency and responsible-use principles, are insufficient because they enforce a"consumer"orientation toward AI rather than fostering genuine epistemic agency. Based upon Foucault's concept of power-knowledge, Freire's pedagogy of critical consciousness, and scholarship of digital literacy, this paper proposes a reconceptualization of AI literacy as a critical practice that equips individuals not just to use AI systems, but to critically evaluate them, resist their structuring assumptions, and participate in their governance. The paper further argues that unequal access to AI tools in society recapitulates longstanding epistemic injustices, and that a literacy framework oriented toward empowerment must account for these structural inequities. A three-part framework of AI literacy based on the notions of contextual use, critical interrogation, and participatory governance frames this literacy as a cultivation of epistemic"agents"rather than the training of competent consumers of AI-generated information.
Generative artificial intelligence (GenAI) is rapidly reshaping engineering education, yet prevailing debates frame its impact narrowly as either pedagogical innovation or epistemic threat. In this article, we argue that such framings misdiagnose the problem by treating GenAI as a tool rather than as a sociotechnical reorganization of epistemic authority, agency, and professional formation. Drawing on sociological theory, philosophy of science, labor economics, and recent empirical studies, we show that GenAI lowers epistemic floors by expanding access to competent performance while leaving epistemic ceilings, those associated with judgment, authority, and problem framing, largely intact. This asymmetry produces new forms of stratification, redistributes responsibility without redistributing control, and stabilizes plausibility‐based forms of knowledge in place of warrant‐based engineering reasoning. We advance three central contributions. First, we conceptualize a shift from warrant to plausibility in engineering knowledge, in which fluent, algorithmically generated outputs increasingly circulate as legitimate despite bypassing core practices of verification, critique, and accountability. Second, we extend the concept of the AI wall beyond productivity to describe a ceiling of epistemic development, where further learning and judgment are not institutionally rewarded without deeper expertise, authority, or complementary organizational resources. Third, we theorize how engineering education participates in stabilizing these dynamics through what we term the social campus, the institutional space in which curricular norms, assessment regimes, professional signaling, and peer comparison converge to normalize AI‐mediated epistemic authority. Together, these dynamics position engineering education at a critical juncture. We argue for a reorientation toward epistemic stewardship, in which engineering programs deliberately cultivate the capacities needed to interrogate, govern, and responsibly deploy AI systems rather than merely operate within them. The question we want to highlight is not whether engineering education will adapt to AI, but whether it will do so as a steward of epistemic responsibility or as an accelerator of epistemic stratification.
Artificial intelligence (AI) is increasingly embedded in organizational information environments, reshaping how knowledge is created, interpreted, and applied. As AI systems become active participants in organizational information processes, employees are required not only to operate digital technologies but also to interpret algorithmic outputs and collaborate effectively with intelligent systems. While prior research has extensively examined digital literacy, human–AI collaboration, and AI literacy, these streams of literature remain largely fragmented, providing limited conceptual integration regarding the competencies required for knowledge work in AI-enabled organizations. This study develops a conceptual framework that positions AI literacy as an extension of digital literacy within contemporary knowledge work environments. Drawing on human capital theory and sociotechnical systems theory, the paper explains how digital literacy provides foundational capabilities for navigating digital infrastructures, while AI literacy enables employees to critically evaluate algorithmic outputs and collaborate effectively with AI systems. The framework further proposes that human–AI collaboration acts as a key mechanism through which digital and AI-related competencies enhance knowledge work outcomes. The study contributes to the literature in three ways. First, it integrates fragmented research on digital literacy, AI literacy, and knowledge work into a unified conceptual perspective. Second, it reconceptualizes AI literacy as an emerging capability that extends digital literacy in AI-mediated organizational environments. Third, it proposes a theoretical framework explaining how human capabilities interact with intelligent technologies to support knowledge creation, decision-making, and organizational learning. By highlighting AI literacy as a strategic organizational capability, this study provides implications for information professionals and managers seeking to develop human competencies required for effective human–AI collaboration. The framework also provides a foundation for future empirical research examining how AI-related competencies influence knowledge work performance in digitally transformed organizations.
Kha Huy Tran· Business Information Review· 0 citations
A research-based approach to make the abstract concrete, metaphorically speaking, by putting the concepts into a wheelbarrow so the authors can push them around more successfully in the context of the higher education institutional and classroom settings.
Janet L Hanson· International Journal of Lea...· 0 citations
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
This paper conceptualizes AI literacy as an extension rather than a replacement of information literacy and argues that academic libraries are uniquely positioned to mediate this transition due to their longstanding expertise in critical inquiry, ethical information use, and learner-centered pedagogy.
Vafa Mammadova· Proceedings of the Internati...· 0 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.
Biranchi Poudyal· 0 citations
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