理解与理论:人工智能基础问题的悲观与乐观  

Understanding and Theory: The Optimistic Attitude and Pessimistic Attitude in the Discussion of Artificial Intelligence

作　　者：梅剑华[1] MEI Jianhua(Department of Philosophy, Capital Normal University, Beijing, 10008)

机构地区：[1]首都师范大学哲学系,北京100089

出　　处：《自然辩证法通讯》2018年第4期1-8,共8页Journal of Dialectics of Nature

摘　　要：人工智能的基础问题遇到两种类型的问题,第一种类型的问题是理解上的:计算机能否思考?强人工智能是否实现?奇点能否来临?这些取决于我们对相关问题、论证及其概念的反思;第二种类型的问题是理论上的:人工智能需要相关性的推理模型还是因果性的推理模型?人工智能可否建立一种反映真实世界的四维符号系统?这取决于科学家的理论工作。在理解问题上,一旦澄清相关的概念和论证,会消除对人工智能的悲观。在理论问题上,一旦深入理解了相关数学的、技术的难题,会消除对人工智能的乐观心态。There are two problems concerning the foundation of AI： The first is about how to understand the AI, Can computer thinking？ Are strong AI possible？ Is their a singularity AI suppress human？ This kind of question can be clarified and solved by conceptual refection, while the second is about how to overcome the obstacle of AI, such as how to implanted program with causal model, can scientist found a four dimensional symbol system for AI. This kind of question can be rejected or solved by scientists. Regards understanding problem, we will never be pessimistic if we clarify related concepts and arguments. Regards theory problem, we will never be optimistic if we know the related formalized and technique trouble.

关 键 词：强/弱人工智能 通用人工智能 实验哲学 因果推理 奇点 

分 类 号：N0[自然科学总论—科学技术哲学]