Philosophy of Connectionism, Misc

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic audiovisual (...) media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Organizational learning can be described as a transfer of individuals’ cognitive mental models to shared mental models. Employees, seeking the same colleagues for advice, are structurally equivalent, and the aim of the paper is to study if the concept can act as a conduit for organizational learning. It is argued that the mimicking of colleagues’ advice seeking structures will induce structural equivalence and transfer the accuracy of individuals’ cognitive mental models to shared mental models. Taking a dyadic level of analysis (...) authors revisit a classical case and present novel data analyses.The empirical results indicate that the mimicking of advice seeking structures can alter cognitive accuracy. It is discussed the findings’ implications for organization learning theory and practice, addressed the study’s limitations, and suggested avenues for future research. (shrink)

A comprehensive introduction to the Language of Though Hypothesis (LOTH) accessible to general audiences. LOTH is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in (...) syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

In Book I, part iv, section 2 of the Treatise, "Of scepticism with regard to the senses," Hume presents two different answers to the question of how we come to believe in the continued existence of unperceived objects. He rejects his first answer shortly after its formulation, and the remainder of the section articulates an alternative account of the development of the belief. The account that Hume adopts, however, is susceptible to a number of insurmountable objections, which motivates a reassessment (...) of his original proposal. This paper defends a version of Hume's initial explanation of the belief in continued existence and examines some of its philosophical implications. (shrink)

Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels and the (...) status of levels which have no obvious relation to others. In speaking of levels, what is the connection, if there is one, between explanation and ontology? Which, if any, conccpt of reduction is applicable to connectionist systems? What kind of legitinrtcy can the constructs of common sense psychology, or of that vclsion ol intentional realism represented by classical symbol-systems n I, hirvc irr ir full-scale connectionist theory of mind? (shrink)

This paper has a two-fold aim. First, it reinforces a version of the "syntactic argument" given in Aizawa (1994). This argument shows that connectionist networks do not provide a means of implementing representations without rules. Horgan and Tlenson have responded to the syntactic argument in their book and in another paper (Horgan & Tlenson, 1993), but their responses do not meet the challenge posed by my formulation of the syntactic argument. My second aim is to describe a kind of cognitive (...) architecture. This architecture might be called a computational architecture, but it is not a rules and representations architecture nor the representations without rules architecture that Horgan and Tlenson wish to endorse. (shrink)