AI助编程虽提效，却损害新手技能成长。
How AI Impacts Skill Formation
- 通过随机实验对比有无AI辅助学习异步编程库。
- 使用AI者概念理解与调试能力下降，平均效率未显著提升。
- 仅三类互动模式能保学习效果，适合安全关键领域。
AI辅助在专业领域带来显著生产力提升，尤其对新手工作者。然而，这种辅助如何影响有效监管AI所需技能的形成尚不明确。过度依赖AI完成陌生任务的新手，可能在过程中损害自身技能习得。我们开展随机实验，研究开发者在有无AI辅助下掌握新型异步编程库的过程。结果发现，使用AI会削弱概念理解、代码阅读和调试能力，且平均效率未显著提高。完全委托编码任务的参与者虽有部分生产力提升，但牺牲了对库的学习。我们识别出六种不同的AI交互模式，其中三种涉及认知参与，即使获得AI辅助也能保持学习成果。研究提示，AI增强的生产力并非胜任力的捷径，应审慎将AI辅助融入工作流程以保障技能发展，尤其在安全关键领域。
原文摘要 · Abstract (English)
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.
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