A Completenesss Theorem for a 3-Valued Semantics for a First-order Language

This document presents a Gentzen-style deductive calculus and proves that it is complete with respect to a 3-valued semantics for a language with quantifiers. The semantics resembles the strong Kleene semantics with respect to conjunction, disjunction and negation. The completeness proof for the sentential fragment fills in the details of a proof sketched in Arnon Avron (2003). The extension to quantifiers is original but uses standard techniques

On the Evidence for Prelinguistic Concepts

ABSTRACT: Language acquisition is often said to be a process of mapping words into pre-existing concepts. If that is right, then we ought to be able to obtain experimental evidence for the existence of concepts in prelinguistic children. One line of research that attempts to provide such evidence is the work of Paul Quinn, who claims that looking-time results show that four-month old infants form "category representations". This paper argues that Quinn's results have an alternative explanation. A distinction is drawn between conceptual thought and the perception of comparative similarity relations, and it is argued that Quinn's results can be explained in terms of the latter rather than the former

Language as an instrument of thought

I show that there are good arguments and evidence to boot that support the language as an instrument of thought hypothesis. The underlying mechanisms of language, comprising of expressions structured hierarchically and recursively, provide a perspective (in the form of a conceptual structure) on the world, for it is only via language that certain perspectives are avail- able to us and to our thought processes. These mechanisms provide us with a uniquely human way of thinking and talking about the world that is different to the sort of thinking we share with other animals. If the primary function of language were communication then one would expect that the underlying mechanisms of language will be structured in a way that favours successful communication. I show that not only is this not the case, but that the underlying mechanisms of language are in fact structured in a way to maximise computational efficiency, even if it means causing communicative problems. Moreover, I discuss evidence from comparative, neuropatho- logical, developmental, and neuroscientific evidence that supports the claim that language is an instrument of thought

A critique of Bernstein’s beyond objectivism and relativism: science, hermeneutics, and praxis

This analysis comments on Bernstein’s lack of clear understanding of subjectivity, based on his book, Beyond Objectivism and Relativism: Science, Hermeneutics, and Praxis. Bernstein limits his interpretation of subjectivity to thinkers such as Gadamer and Habermas. The authors analyze the ideas of classic scholars such as Edmund Husserl and Friedrich Nietzsche. Husserl put forward his notion of transcendental subjectivity and phenomenological ramifications of the relationship between subjectivity and objectivity. Nietzsche referred to subjectivity as “perspectivism,” the inescapable fact that any and all consciousnesses exist in space and time. Consciousness is fundamentally constituted of cultural, linguistic, and historical dimensions

Deep Learning: A Philosophical Introduction

Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been largely silent on this technology so far. This is remarkable, given that deep learning neural networks have blown past predicted upper limits on artificial intelligence performance—recognizing complex objects in natural photographs, and defeating world champions in strategy games as complex as Go and chess—yet there remains no universally-accepted explanation as to why they work so well. This article provides an introduction to these networks, as well as an opinionated guidebook on the philosophical significance of their structure and achievements. It argues that deep learning neural networks differ importantly in their structure and mathematical properties from the shallower neural networks that were the subject of so much philosophical reflection in the 1980s and 1990s. The article then explores several different explanations for their success, and ends by proposing ten areas of research that would benefit from future engagement by philosophers of mind, epistemology, science, perception, law, and ethics

What is Said?

It is sometimes argued that certain sentences of natural language fail to express truth conditional contents. Standard examples include e.g. Tipper is ready and Steel is strong enough. In this paper, we provide a novel analysis of truth conditional meaning using the notion of a question under discussion. This account explains why these types of sentences are not, in fact, semantically underdetermined, provides a principled analysis of the process by which natural language sentences can come to have enriched meanings in context, and shows why various alternative views, e.g. so-called Radical Contextualism, Moderate Contextualism, and Semantic Minimalism, are partially right in their respective analyses of the problem, but also all ultimately wrong. Our analysis achieves this result using a standard truth conditional and compositional semantics and without making any assumptions about enriched logical forms, i.e. logical forms containing phonologically null expression