读完麦克斯·班尼特的《智能简史：进化、AI与人脑的突破》（下简称《智能简史》），我的第一反应 是震撼。长期以来，我一直被本专业中的一些基础性问题困扰。这说明我的认知结构里存在重要的缺 口。这本书并没有完美地填补这些缺口，其实也没有任何一本书能做到，但它确实让我在继续思考这些 问题时，获得了全新的视角。 这本书初看起来和经济学、管理学没有什么关系。它是关于智能的，而且主要不是人工智能，而是人类 的智能，或者说人脑智能。更准确地说，它讨论的是人类智能的演进历程。 一个经济学家的困惑 毫不意外，这一研究范式遭到了各种各样的质疑。众多批评者中，就包括那本20世纪50年代开始便长盛 不衰的著名教科书《经济学》的作者、以天才自居的诺贝尔经济学奖得主保罗·萨缪尔森（Paul Samuelson）。 演化论的辩护与困境 无论这些批评如何尖锐，时至今日，经济学分析人类行为的主流范式，仍然以理性选择模型为基础。其 中有一个非常著名而有力的辩护，由阿兰·阿尔钦（Armen Alchian）和另一位诺贝尔经济学奖得主米尔 顿·弗里德曼（Milton Friedman）在20世纪50年代早期分别给出。 这两篇被认为是奠定了20世纪主流 ...

Core Viewpoint - The article discusses the nature of AI and its limitations compared to human intelligence, emphasizing that AI lacks true imagination and emotional depth, which are essential for creativity and future creation [19][20]. Group 1: AI's Capabilities and Limitations - AI has shown impressive capabilities, such as passing the Turing test, but it fundamentally lacks human-like emotions and responses [2][3]. - The current AI models are designed to be polite and non-confrontational, which highlights their inability to exhibit genuine human emotions [3]. - Concerns about AI surpassing human intelligence and causing mass unemployment are considered exaggerated; AI is not expected to fully replace human roles but rather create new job opportunities [3][4][7]. Group 2: Historical Context and Future Predictions - Historical technological advancements have often replaced certain human functions but ultimately enhanced human capabilities rather than rendering them obsolete [5][6]. - The article argues that technological progress, including AI, will likely create more job opportunities in the long run, similar to past technological revolutions [7][8]. - The future is described as indeterminate, shaped by human choices and imagination rather than being a direct continuation of past trends [12][19]. Group 3: The Nature of Imagination and Creativity - Human imagination is highlighted as a unique trait that allows for the creation of new ideas and futures, which AI, as a statistical machine, cannot replicate [14][19]. - The article posits that AI's conclusions are based on past data and statistical regression, lacking the ability to innovate or think outside established frameworks [16][19]. - Diversity in human thought and creativity is essential for societal evolution, while AI tends to produce uniform outputs based on the same data [18][19].

Core Viewpoint - The article discusses the interplay between biological intelligence, human intelligence, and machine intelligence, emphasizing their collective impact on the future of humanity [1][2][4]. Group 1: Biological Intelligence Insights - Michael Levitt highlights that biological intelligence is the most significant form of intelligence on Earth, as it has created all life forms, including humans, who in turn created computers [2][4]. - The principle of diversity in biological evolution suggests that maintaining diversity is crucial for adapting to an unpredictable future, which has important social implications for humanity [4][5][6]. Group 2: Impact of Machine Intelligence - Machine intelligence has been present for a long time, with any use of computers in scientific research being a form of machine intelligence [8][10]. - Levitt views artificial intelligence as an excellent assistant that can inspire new ideas through interaction, emphasizing its role in enhancing research related to human health [10][14]. - He expresses skepticism about the concept of a technological singularity, believing that the future is inherently unpredictable and that human-machine interactions will vary among individuals [12][15]. Group 3: Human Intelligence Reflection - Levitt asserts that human intelligence remains irreplaceable due to its innovative capacity, which allows for unexpected thoughts and ideas to emerge [17][19]. - He envisions a future where humans guide technology towards positive outcomes, with a focus on maintaining curiosity and openness to learning [19][21][22][23].