A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.

A critical survey of some attempts to define ‘computer’, beginning with some informal ones, then critically evaluating those of three philosophers, and concluding with an examination of whether the brain and the universe are computers.

Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.

A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.

This paper seeks to understand machine cognition. The nature of machine cognition has been shrouded in incomprehensibility. We have often encountered familiar arguments in cognitive science that human cognition is still faintly understood. This paper will argue that machine cognition is far less understood than even human cognition despite the fact that a lot about computer architecture and computational operations is known. Even if there have been putative claims about the transparency of the notion of machine computations, these claims do (...) not hold out in unraveling machine cognition, let alone machine consciousness (if there is any such thing). The nature and form of machine cognition remains further confused also because of attempts to explain human cognition in terms of computation and to model/simulate (aspects of) human cognitive processing in machines. Given that these problems in characterizing machine cognition persist, a view of machine cognition that aims to avoid these problems is outlined. The argument that is advanced is that something becomes a computation in machines only when a human interprets it, which is a kind of semiotic causation. From this it follows that a computing machine is not engaged in a computation unless a human interprets what it is doing; instead, it is engaged in machine cognition, which is defined as a member or subset of the set of all possible mappings of inputs to outputs. The human interpretation, which is a semiotic process, gives meaning to what a machine does, and then what it does becomes a computation. (shrink)

The algorithm, a building block of computer science, is defined from an intuitive and pragmatic point of view, through a methodological lens of philosophy rather than that of formal computation. The treatment extracts properties of abstraction, control, structure, finiteness, effective mechanism, and imperativity, and intentional aspects of goal and preconditions. The focus on the algorithm as a robust conceptual object obviates issues of correctness and minimality. Neither the articulation of an algorithm nor the dynamic process constitute the algorithm itself. Analysis (...) for implications in computer science and philosophy reveals unexpected results, new questions, and new perspectives on current questions, including the relationship between our informally construed algorithms and Turing machines. Exploration in terms of current computational and philosophical thinking invites further developments. (shrink)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting (...) the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness. (shrink)

This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.

In this paper, I review the objections against the claim that brains are computers, or, to be precise, information-processing mechanisms. By showing that practically all the popular objections are either based on uncharitable interpretation of the claim, or simply wrong, I argue that the claim is likely to be true, relevant to contemporary cognitive (neuro)science, and non-trivial.

There are two main ways to teach a course online: synchronously or asynchronously. In an asynchronous course, students can log on at their convenience and do the course work. In a synchronous course, there is a requirement that all students be online at specific times, to allow for a shared course environment. In this article, the author discusses the strengths and weaknesses of synchronous online learning for the teaching of undergraduate philosophy courses. The author discusses specific strategies and technologies he (...) uses in the teaching of online philosophy courses. In particular, the author discusses how he uses videoconferencing to create a classroom-like environment in an online class. (shrink)