The agent/consumer distinction is not primarily technical sophistication but capacity to interrogate the assumptions of AI outputs¶
Claim · All claims
Evidence · 1 study · theoreticalr2·q1
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
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q1 i? A technically sophisticated user operating within AI-as-productivity-tool logic remains a consumer, while a user with modest technical skills who can interrogate AI outputs' assumptions exercises epistemic agency the competency model does not capture. → Brady D. Lund and Zoë Abbie Teel 2026
Evidence¶
Brady D. Lund and Zoë Abbie Teel 2026¶
Brady D. Lund and Zoë Abbie Teel. (2026). AI Literacy: An Exercise in Power-Knowledge. University of North Texas. https://arxiv.org/abs/2607.27547 doi:10.48550/arxiv.2607.27547
q1 · i? · theoretical · r2
Conceptual argument drawing the paper's firm distinction between consumers, who receive and evaluate outputs within an unshaped frame, and agents, who understand the frame itself, interrogate its assumptions, and participate in governance. The distinction has direct implications for how AI literacy should be taught and assessed.
"A highly technically sophisticated user who uses their skills entirely within the logic of AI as a productivity tool is, in the relevant sense, still a consumer."
Discussion¶
Related Claims¶
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- The competency model of AI literacy functions as a Freirean banking model, training users to adapt rather than transform — a broader claim this one bears on
- Agentic AI invalidates the three assumptions (evaluation, reversibility, control) on which existing AI literacy frameworks rest — related
- The debt is incurred by deploying organizations but paid by users, patients, and citizens, making it an AI ethics problem — related
- Existing institutional AI literacy frameworks converge on a consumer model with no substantive treatment of training data politics or governance participation — related
- Existing philosophical accounts of AI in education share a Western architecture presupposing subject-object dualism, individualist epistemic agency, and representational knowledge — related
- LEARN reconceptualises scaffolding for GAI contexts as interactive, dialogic, and epistemically regulated interrogation of AI outputs — a broader claim this one bears on
- Most ITS applications augment existing mathematics teaching practices rather than transform instruction, indicating technological sophistication does not independently determine pedagogical value — related
- AI's role in shaping interaction, epistemic agency, and shared regulation in collaborative learning remains under-theorized — a broader claim this one bears on
- Existing AI literacy frameworks treat teacher agency narrowly as tool adoption, leaving human–AI co-agency undertheorized — related
- AI systems are non-neutral socio-technical artifacts embedding cultural assumptions and power relations — related
- One focal student exhibited a critical-pragmatic humanistic AI literacy, conceptualizing AI as a manipulable tool and evaluating it by rhetorical efficiency — related
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- All AI-generated outputs in the project underwent mandatory human-in-the-loop review, positioning AI as augmentative rather than substitutive — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
agent-consumer-distinction-epistemic-agency |
title |
The agent/consumer distinction is not primarily technical sophistication but capacity to interrogate the assumptions of AI outputs |
description |
The agent/consumer distinction is not primarily technical sophistication but capacity to interrogate the assumptions of AI outputs |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — brady-d-lund-and-zoë-abbie-teel-2026 |
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