Intellectual Stewardship: Re-adapting Human Minds for Creative Knowledge Work in the Age of AI
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Abstract (arXiv)
Background: Amid the opportunities and risks introduced by generative AI, learning research needs to envision how human minds and responsibilities should re-adapt as AI augments or automates various tasks and enters daily learning, knowledge work, and social life. Approach: Drawing on theories of learning, intelligence, and knowledge creation, this conceptual paper proposes intellectual stewardship as a human-centered, conceptually grounded framework for advancing creative learning practices with AI. Key points: Students and teachers work as responsible governors of intellectual processes distributed across human and artificial systems, guided by five core principles. Being knowledge-wise involves understanding the evolving state of knowledge and taking purposeful actions to advance it. Being intelligence-wise emphasizes making informed choices about how to orchestrate distributed cognitive processes and resources. Being context-wise requires sensitivity to recognize opportunities and risks. Being ethics-wise foregrounds ethical judgment, responsibility, and care in the use of knowledge and intellectual power. Finally, self- and community-growing defines the overarching purpose, aligning intellectual work with personal development and the advancement of collective well-being. Contribution: The principles provide a lens for viewing the adaptation of human minds in AI-infused learning environments, calling for the development of meta-level dispositions and capabilities that characterize wisdom-oriented, socially responsible knowledge builders in the AI age.
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References · 5
- 2024Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning Motivation, Processes, and Performancecited by 58
- 2026How AI Impacts Skill Formationcited by 20
- 2023An Ontology of Co-Creative AI Systemscited by 7
- 2025Beyond Tools: Generative AI as Epistemic Infrastructure in Educationcited by 4
- 2025Learning Context: A Unified Framework and Roadmap for Context-Aware AI in Educationcited by 1
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