Hoy en día vivimos aún con el estereotipo de las dos culturas, con la idea de una cierta incomunicabilidad entre ciencias y humanidades, en términos más generales: entre la esfera de la ciencia y la de la cultura. Este artículo presenta una visión filosófica de la relación entre cultura y ciencia más allá de la tópica dicotomía, sosteniendo en cambio un enfoque en el que se concibe la ciencia como fenómeno cultural. Un recorrido histórico-sistemático por algunos hitos de la filosofía (...) de la cultura y la filosofía de la ciencia muestra cómo las dos se compenetran entre sí y se influyen mutuamente. Poner el foco en las convergencias entre ambas permite identificar una serie de preocupaciones y retos compartidos que conciernen al campo de la epistemología en su conjunto: afrontar la complejidad de la condición epistémica y la vulnerabilidad cognitiva del ser humano; hacer frente a las posiciones más extremas tanto del relativismo como del fundamentalismo; y desarrollar un concepto de responsabilidad epistémica en los distintos ámbitos de conocimiento para contrarrestar la cultura de desconfianza y la percepción de nuestra época como era de la posverdad. (shrink)

In componential analysis, word meanings are (partly) decomposed into other meanings, and semantic and syntactic markers. Although a theory of word meaning based on such semantic decompositions remains compatible with the linguistic labor division thesis, it is not compatible with Kripke/Putnam-style indexical externalism. Instead of abandoning indexical externalism, a Separation Thesis is defended according to which lexical meaning need not enter the truth-conditional content of an utterance. Lexical meaning reflects beliefs about word meaning shared in a speaker community, and these (...) may rest on possibly erroneous world-level theories. It is argued that this type of lexical meaning is indispensable for explaining word composition processes and the rationality of metalinguistic disputes. (shrink)

Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...) to higher-level cognitive representations of structures, systems of knowledge, and algorithmic processes. This theory implements a version of conceptual role semantics by positing an internal universal representation language in which learners may create mental models to capture dynamics they observe in the world. The theory formalizes one account of how truly novel conceptual content may arise, allowing us to explain how even elementary logical and computational operations may be learned from a more primitive basis. I provide an implementation that learns to represent a variety of structures, including logic, number, kinship trees, regular languages, context-free languages, domains of theories like magnetism, dominance hierarchies, list structures, quantification, and computational primitives like repetition, reversal, and recursion. This account is based on simple discrete dynamical processes that could be implemented in a variety of different physical or biological systems. In particular, I describe how the required dynamics can be directly implemented in a connectionist framework. The resulting theory provides an “assembly language” for cognition, where high-level theories of symbolic computation can be implemented in simple dynamics that themselves could be encoded in biologically plausible systems. (shrink)

Psychologism is defined as “the doctrine that the laws of mathematics and logic can be reduced to or depend on the laws governing thinking” (Moran & Cohen, 2012 266). And for Husserl, the laws of logic include the laws of meaning: “logic evidently is the science of meanings as such [Wissenschaft von Bedeutungen als solchen]” (Husserl ( 1975 ) 98/2001 225). I argue that, since it is sufficient for a theory to be psychologistic if the empiricistic theory of abstraction is (...) employed, it follows that neural networks are psychologistic insofar as they use this theory of abstraction, which I demonstrate is the case (Husserl ( 1975 ) 191/2001 120). It’s sufficient for psychologism because, according to Husserl, the theory in question reduces one’s phenomenological ability to intend types (or universals) to one’s past history of intending tokens (or particulars), usually amalgamated in some fashion (classically via associations; recently via autoencoders) (ibid; Kelleher, 2019 ). Similarly dynamical systems theory entails psychologism. For dynamical systems theory ties content to the temporal evolution of a system, which, according to Husserl, violates the fact that intentionality toward validities and objectivities does not pertain to "particular temporal experience[s]" (Husserl ( 1975 ) 194/2001 121). It follows that neither the species (neural networks), nor the genus (dynamical systems), can avoid psychologism and intend objects "in specie" (ibid). After critiquing these two approaches, I proceed to give an account based on the essentialist school of cognitive psychology of how we may intend objects "in specie" while avoiding the empiricistic theory of abstraction (Keil, 1989, Carey, 2009, Marcus & Davis, 2019 ). Such an account preserves the type-token distinction without psychologistic reduction to the temporal evolution of a dynamical system (Hinzen, 2006 ). This opens the way toward a truly unifying account of Husserlian phenomenology in league with cognitive science that avoids Yoshimi's ( 2016 ) and neurophenomenology's psychologistic foundation (herein demonstrated) and builds upon Sokolowski's ( 2003 ) syntactic account of Husserlian phenomenology. (shrink)