[论文] How AI Assistance Affects Human Skill Development: A Study of Learning...

论文概要

研究领域: ML
作者: Shang Wu, Catarina G Belem, Shuyuan Fu
发布时间: 2025-08-26
arXiv: 2508.17621

中文摘要

虽然AI辅助可以在短期内提升人类任务表现，但长期来看可能削弱技能发展。本文在一项受控的逻辑谜题实验中考察了这一张力，参与者可以在AI可用前、期间和之后完成任务。通过实验性地改变AI请求成本，我们发现较低成本的辅助诱导了更频繁的AI使用。同时，在AI可访问阶段请求AI辅助的参与者在辅助移除后任务表现更差，且其后续无辅助表现从早期AI辅助表现预测时会被高估。我们使用贝叶斯潜在能力模型分离初始能力、AI后能力和参与者特定的技能变化，同时估计AI可访问阶段的独立推理与技能发展的关系。结果表明，更大的独立问题解决努力与更大的潜在能力增益相关，与"AI辅助替代独立推理时技能发展较弱"的解释一致。

原文摘要

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 chan...

自动采集于 2026-08-26

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