The authors introduce Agentivism as a learning theory for human-AI interaction that explains how durable capability develops through selective delegation, epistemic monitoring, reconstructive internalization, and transfer under reduced support.
Build- ing Machines That Learn and Think with People
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
The paper claims that alignment requires treating AI as part of the self through cognitive co-regulation, identifying risks like deskilling and automation bias while drawing on System 0 cognition theory.
Explicit memory modeled on the hippocampus is the cornerstone needed to advance LLMs to AGI because their implicit statistical learning cannot produce higher cognitive functions.
citing papers explorer
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Agentivism: a learning theory for the age of artificial intelligence
The authors introduce Agentivism as a learning theory for human-AI interaction that explains how durable capability develops through selective delegation, epistemic monitoring, reconstructive internalization, and transfer under reduced support.
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Position: AI as Part of Self -- Extending the Mind Requires Cognitive Co-Regulation
The paper claims that alignment requires treating AI as part of the self through cognitive co-regulation, identifying risks like deskilling and automation bias while drawing on System 0 cognition theory.
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Position: Hippocampal Explicit Memory Is the Cornerstone for AGI
Explicit memory modeled on the hippocampus is the cornerstone needed to advance LLMs to AGI because their implicit statistical learning cannot produce higher cognitive functions.