Mohamed Amine Chatti looks at the differences between network learning and Actor-Network Theory (ANT). "ANT is based upon the principle of generalized symmetry employing a single conceptual framework when interpreting actors, human and non-human," he writes. "Central to ANT is the concept of translation... it reduces all actors into black-boxes, and thus ignores internal actions which are crucial for the creation of PKNs, and hence learning, such as seeing patterns, reflecting, (self-)criticizing, and detecting/correcting errors." Also, "it does not distinguish between complex and complicated systems... and so turn a network from a heterogeneous set of bits and pieces each with its own inclinations, into something that passes as a punctualised actor." Good argument.
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