Disrupting Cognitive Passivity: Rethinking AI-Assisted Data Literacy through Cognitive Alignment
AI chatbots are increasingly stepping into roles as collaborators or teachers in analyzing, visualizing, and reasoning through data and domain problem. Yet, AI's default assistant mode with its comprehensive and one-off responses may undermine opportunities for practitioners to develop literacy through their own thinking, inducing cognitive passivity. Drawing on evidence from empirical studies and theories, we argue that disrupting cognitive passivity necessitates a nuanced approach: rather than
Record details
Published: 3 April 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Cognitive Comparability and the Limits of Governance: Evaluating Authority Under Radical Capability Asymmetry
arXiv · 3 April 2026
DocShield: Towards AI Document Safety via Evidence-Grounded Agentic Reasoning
arXiv · 3 April 2026
Generalization Limits of Reinforcement Learning Alignment
arXiv · 3 April 2026
Do Audio-Visual Large Language Models Really See and Hear?
arXiv · 3 April 2026
Understanding the Effects of Safety Unalignment on Large Language Models
arXiv · 2 April 2026
Disentangled Dual-Branch Graph Learning for Conversational Emotion Recognition
arXiv · 3 April 2026
How to cite this record
ethics.ai (3 April 2026), “Disrupting Cognitive Passivity: Rethinking AI-Assisted Data Literacy through Cognitive Alignment,” evidence record 6407, https://ethics.ai/record/6407 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.