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The Taibai Questions of Artificial Intelligence: Rethinking Silicon-Based and Carbon-Based Intelligence

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  • Corresponding author: Bin Chen, E-mail: chenbin06@uestc.edu.cn  
  • As Artificial Intelligence integrates into human society at an accelerating pace, deep reflection on Silicon-based Intelligence and Carbon-based Intelligence has become a focal point for scientists in the field of intelligent computing[1]. Drawing on years of Artificial Intelligence research experience, the researchers from the editorial committee conducted intense Santa Fe style discussions. The discussion begins with Li Bai(李白)'s poem Zhuang Zhou Dreams of a Butterfly(《古风·庄周梦胡蝶》) as a starting point: Zhuang Zhou dreams of being a butterfly, and the butterfly dreams of being Zhuang Zhou. One body transforms itself, and all things are leisurely (庄周梦蝴蝶, 蝴蝶为庄周. 一身自变化,万事良悠悠). The poem presents a thought experiment regarding intelligence, articulated in the language of the AI field: How does a system verify the authenticity of its own consciousness? If an Artificial Intelligence claims to possess consciousness, the scientific community must determine how to judge and evaluate this claim. Humans have pondered the relationship between consciousness and intelligence since ancient times. The editorial board focuses on the following three questions to explore the theoretical starting point for the co-evolution of Human and Machine Intelligence within the logic of intelligence generation, and these questions are named the Taibai Questions of Artificial Intelligence.
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    Bin Chen, Zhu Zhengqiu, Rongxiao Wang, Duo Xu, Xiaogang Qiu, Aiguo Chen, Jincai Huang. The Taibai Questions of Artificial Intelligence: Rethinking Silicon-Based and Carbon-Based Intelligence[J]. The Innovation Informatics. https://doi.org/10.59717/j.xinn-inform.2026.100067
    Bin Chen, Zhu Zhengqiu, Rongxiao Wang, Duo Xu, Xiaogang Qiu, Aiguo Chen, Jincai Huang. The Taibai Questions of Artificial Intelligence: Rethinking Silicon-Based and Carbon-Based Intelligence[J]. The Innovation Informatics. https://doi.org/10.59717/j.xinn-inform.2026.100067

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