人工智慧如何影響技能形成

摘要

人工智慧輔助在各專業領域均帶來顯著的生產力提升，尤其對初階工作者而言。然而這類輔助如何影響有效監管AI所需技能的培養，目前尚不明確。過度依賴AI完成陌生任務的初階工作者，可能在過程中削弱自身技能獲取。我們透過隨機對照實驗，研究開發者在有無AI輔助的情況下，掌握新型非同步程式庫的學習成效。結果發現使用AI會損害對程式庫的概念理解、程式碼閱讀與除錯能力，且平均未能帶來顯著效率提升。完全委託AI編碼的參與者雖展現部分生產力改善，卻以犧牲程式庫學習為代價。我們識別出六種AI互動模式，其中三種涉及認知投入的模式即便在獲得AI協助時仍能維持學習成效。研究結果表明，AI驅動的生產力提升並非通往專業能力的捷徑，應審慎將AI輔助整合至工作流程中以維護技能養成——尤其在安全關鍵領域更需如此。

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.

人工智慧如何影響技能形成

How AI Impacts Skill Formation

摘要

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