Core Viewpoint - The article discusses the paradox of AI in the medical field, emphasizing the importance of foundational skills and judgment over mere reliance on AI technology. It highlights that while AI can enhance efficiency, it may also lead to a devaluation of essential skills if individuals do not possess a deep understanding of their field [4][5][6]. Group 1: The Zhang Wenhong Paradox - Zhang Wenhong's refusal to integrate AI into hospital medical record systems stems from concerns that untrained reliance on AI could undermine the independent diagnostic abilities of young doctors [4][11]. - The core of the paradox is that if a young doctor relies on AI from the start, their clinical judgment may remain at zero, leading to a situation where AI's capabilities cannot compensate for a lack of foundational knowledge [10][12]. - The article posits that AI amplifies existing skills but does not create them; thus, individuals with no foundational understanding will not benefit from AI's capabilities [10][13]. Group 2: Skills and AI - The article identifies a growing anxiety among skilled professionals who initially believed AI would enhance their capabilities but now feel their value is diminished as AI can perform many tasks more efficiently [6][7]. - It argues that the true value in the AI era lies in the ability to think critically and validate AI outputs, rather than merely executing tasks [20][40]. - The shift in skills required in the AI era is from execution to oversight, where professionals must focus on strategic thinking and validation of AI-generated outputs [37][39]. Group 3: Understanding vs. Knowledge - The distinction between knowledge and understanding is crucial; knowledge is knowing what to do, while understanding is knowing why and when to do it [28][30]. - Professionals who rely solely on AI for information may lack the deeper understanding necessary to apply that knowledge effectively in unique situations [30][31]. - The article emphasizes that to outperform AI, individuals must develop their own cognitive frameworks through experience and critical thinking, rather than relying on AI-generated information [33][49]. Group 4: The Future of Work - The article draws parallels between the current AI revolution and past technological advancements, suggesting that while some jobs may be automated, the complexity and demand for skilled oversight will increase [36][38]. - As AI takes over routine tasks, the role of professionals will evolve from doing the work to managing and validating the work done by AI [37][40]. - The future skill set will require a combination of macro-level understanding and micro-level validation, creating a new definition of expertise in the AI era [40][41].