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This study reveals a critical trade-off in AI adoption: while on-demand assistance boosts immediate task performance, it can erode long-term skill acquisition by substituting independent reasoning. The findings suggest that lower-cost AI access leads to overreliance, resulting in diminished latent ability once the tool is removed and inflated self-assessments of competence. For the AI community, this highlights the need for designing systems or policies that encourage active problem-solving rather than passive consumption of generated solutions.
Surse care acoperăarXiv, AI Alignment Forum, Quantum Computing Report, LessWrong
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How AI Assistance Affects Human Skill Development: A Study of Learning with Logic Puzzles

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.23543v1 Announce Type: new Abstract: While AI assistance can improve human task performance in the short term, it may also undermine the development of skills in the longer term. We examine this tension in a controlled logic-puzzle experiment involving on-demand AI assistance, where participants complete tasks before, during, and after AI is available. By experimentally varying AI request costs, we find that lower-cost assistance induces more frequent AI use. We also find that participants who request AI assistance during the AI-access phase perform worse at the task after assistance is removed, and their subsequent unassisted performance is overestimated when predicted from earlier AI-assisted performance. We use a Bayesian latent ability model to separate initial ability, post-AI ability, and participant-specific skill change, while estimating how independent reasoning during the AI-access phase relates to skill development. The results show that greater independent problem-solving effort is associated with larger gains in latent ability, consistent with the interpretation that skill development is weaker when AI assistance substitutes for independent reasoning.

Abstract:While AI assistance can improve human task performance in the short term, it may also undermine the development of skills in the longer term. We examine this tension in a controlled logic-puzzle experiment involving on-demand AI assistance, where participants complete tasks before, during, and after AI is available. By experimentally varying AI request costs, we find that lower-cost assistance induces more frequent AI use. We also find that participants who request AI assistance during the AI-access phase perform worse at the task after assistance is removed, and their subsequent unassisted performance is overestimated when predicted from earlier AI-assisted performance. We use a Bayesian latent ability model to separate initial ability, post-AI ability, and participant-specific skill change, while estimating how independent reasoning during the AI-access phase relates to skill development. The results show that greater independent problem-solving effort is associated with larger gains in latent ability, consistent with the interpretation that skill development is weaker when AI assistance substitutes for independent reasoning.

Artificial Intelligence (cs.AI)

arXiv:2608.23543 [cs.AI]

(or arXiv:2608.23543v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.23543 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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