人工智能思维的意义诠释及实现的可能路径

Interpretation of Bedeutung of Artificial Intelligence Thinking and Possible Path of Realization

图灵计算主义、塞尔早期意向性理论和哈纳德符号主义均对机器智能能否产生与人脑生物智能类似的意义思考展开讨论,人工智能技术的出现进一步推动机器思维的意义指向性研究,意义从本质上能还原为一种派生的意向性,关于意义的问题同样也是意向性问题,而意向性问题能够从因果性、信息语义学和目的论三者中获得自然化解释,在此基础上尝试通过符号转化、信息语义识别和生物进化三条路径寻求人工智能思维产生意向性的可能解,从而进一步探讨人工智能算法中的句法和符号能否产生意义和人工智能在未来发展中能否拥有类生物的语义思维能力。

Turing computationalism, Searle’s early theory of intentionality and Harnad symbolism all discuss whether machine intelligence can produce meaningful thinking similar to the biological intelligence of the human brain, and the emergence of artificial intelligence technology further promotes the study of the bedeutung of machine thinking. Bedeutung can be reduced to a derived intentionality by nature, and the question about bedeutung is also a question of intentionality. The question of intentionality can be naturalized from causality, information semantics and teleology. On the basis of this, we try to seek possible solutions for AI thinking to generate intentionality through three paths: symbolic transformation, information semantic recognition and biological evolution, so as to further explore whether syntax and symbols in AI algorithms can generate bedeutung and whether AI can have biology-like semantic thinking ability in future development.