This, we argue, avoids committing “naturalistic fallacy,” which is an. We propose that designers of VA systems incorporate ethics by utilizing a hybrid approach in which both ethical reasoning and empirical observation play a role. We survey a number of the standard arguments that have been offered in favor of Connectionism, and conclude that they are coherent only on this interpretation.Īn important step in the development of value alignment (VA) systems in artificial intelligence (AI) is understanding how VA can reflect valid ethical principles. We then consider the possibility that Connectionism may provide an account of the neural (or 'abstract neurological') structures in which Classical cognitive architecture is implemented. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. These include arguments based on the 'systematicity' of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. Several arguments for combinatorial structure in mental representations are then reviewed.

We claim that the major distinction is that, while both Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a 'language of thought': i.e., to representational states that have combinatorial syntactic and semantic structure.

This paper explores differences between Connectionist proposals for cognitive architecture and the sorts of models that have traditionally been assumed in cognitive science.

Ian mcewan ai