中泰资管天团 | 李玉刚：挑战共识、提出有价值假说的能力，很难被AI替代

Core Viewpoint - The article emphasizes the distinction between AI's capabilities and human cognitive strengths, highlighting that while AI excels in processing known data and optimizing efficiency, human beings possess the unique ability to question consensus and generate valuable hypotheses [2][9]. Group 1: AI Capabilities - AI, particularly large language models (LLMs), demonstrates superior performance in structured tasks, achieving scores higher than 88% of human test-takers in various standardized exams [2]. - LLMs operate as statistical systems driven by data and computation, focusing on historical frequencies and correlations rather than genuine cognitive understanding [5][7]. - The learning process of LLMs involves discovering relationships between words and predicting the next word based on vast training data, which allows them to generate coherent and fluent text [5][6]. Group 2: Limitations of AI - Evidence suggests that LLMs do not engage in real-time reasoning but merely reproduce language patterns found in their training data, lacking true understanding or reasoning capabilities [6][10]. - The knowledge boundaries of LLMs are strictly limited to the historical distribution of their training data, which can lead to performance degradation when iteratively trained on their own outputs [10]. - Anomalous or extreme data points are often minimized in data-driven models, which can obscure opportunities for generating new hypotheses and theories [10]. Group 3: Human Cognitive Advantages - Humans can challenge existing consensus and construct theories based on causal understanding, allowing for the generation of new knowledge beyond historical data [9][12]. - The ability to remain sensitive to unexpected phenomena is crucial for scientific inquiry, as illustrated by historical examples where questioning prevailing theories led to significant discoveries [11]. - Knowledge discovery is characterized by a systematic exploration of the unknown, driven by curiosity and the formulation of valuable hypotheses, contrasting with AI's problem-solving capabilities [12][13].