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The Metacognitive Demands and Opportunities of Generative AI

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arxiv 2312.10893 v3 pith:F7BEZHXI submitted 2023-12-18 cs.HC

classification cs.HC
keywords genaimetacognitivesystemschallengesdemandscontroldesigngenerative
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abstract

Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on outputs, and optimizing workflows. We argue that metacognition$\unicode{x2013}$the psychological ability to monitor and control one's thoughts and behavior$\unicode{x2013}$offers a valuable lens to understand and design for these usability challenges. Drawing on research in psychology and cognitive science, and recent GenAI user studies, we illustrate how GenAI systems impose metacognitive demands on users, requiring a high degree of metacognitive monitoring and control. We propose these demands could be addressed by integrating metacognitive support strategies into GenAI systems, and by designing GenAI systems to reduce their metacognitive demand by targeting explainability and customizability. Metacognition offers a coherent framework for understanding the usability challenges posed by GenAI, and provides novel research and design directions to advance human-AI interaction.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Exploring the Potential of Metacognitive Support Agents for Human-AI Co-Creation

    cs.HC 2025-06 conditional novelty 6.0 of 10

    Metacognitive support agents, simulated by human wizards, improved the feasibility of AI-generated mechanical designs in a 20-participant formative study.

  2. HARP: The Human--AI Research Platform

    cs.HC 2026-07 conditional novelty 5.0 of 10

    HARP is a proposed platform for controlled live-LLM experiments, combining configurable AI agents, in-context surveys, and fine-grained keystroke behavior logging.

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