人工智能心理学：神经网络认知分析的认识论标志
Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networks
AI总结：
本研究围绕人工智能的认知本质与知识存在形式问题，提出需以神经元层面的认知粒度开展人工智能心理学研究，并明确相关认识论里程碑是探究合成神经认知的前提。
摘要：
人工神经网络的认知过程与认知内容的“本质”是什么？换言之，人工智能从根本上如何“思考”，其知识又以何种形式存在？正如阿西莫夫（1950）所预言的，人工智能心理学旨在研究这一与AI探测及可解释性密切相关的议题。该研究需要神经元层面的认知粒度，以免仅局限于合成神经认知的次级宏观认知结果（例如认知偏差与文化偏差）。探究后者的前提是厘清一些认识论里程碑，它们关乎我们可赋予其现象学的认知地位。
英文摘要：
What is the "nature" of the cognitive processes and contents of an artificial neural network? In other words, how does an artificial intelligence fundamentally "think," and in what form does its knowledge reside? The psychology of artificial intelligence, as predicted by Asimov (1950), aims to study this AI probing and explainability-sensitive matter. This study requires a neuronal level of cognitive granularity, so as not to be limited solely to the secondary macro-cognitive results (such as cognitive and cultural biases) of synthetic neural cognition. A prerequisite for examining the latter is to clarify some epistemological milestones regarding the cognitive status we can attribute to its phenomenology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
