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Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networks
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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.
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Cited by 2 Pith papers
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The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition
Words that strongly activate both a lower-layer neuron and its strongly connected upper-layer neuron in GPT-2XL form more semantically similar clusters, which the paper interprets as a clipping process.
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How Do Artificial Intelligences Think? The Three Mathematico-Cognitive Factors of Categorical Segmentation Operated by Synthetic Neurons
The paper names three components of a neuron's aggregation function as cognitive factors and reports near-unity correlations in GPT-2XL, but the effects are largely true by construction.
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