We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and analyze the (...) differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

In this chapter we use methods of corpus linguistics to investigate the ways in which mathematicians describe their work as explanatory in their research papers. We analyse use of the words explain/explanation (and various related words and expressions) in a large corpus of texts containing research papers in mathematics and in physical sciences, comparing this with their use in corpora of general, day-to-day English. We find that although mathematicians do use this family of words, such use is considerably less prevalent (...) in mathematics papers than in physics papers or in general English. Furthermore, we find that the proportion with which mathematicians use expressions related to ‘explaining why’ and ‘explaining how’ is significantly different to the equivalent proportion in physics and in general English. We discuss possible accounts for these differences. (shrink)

ABSTRACT: This article explores the role of principal leadership in creating a thinking school. It contributes to the school leadership literature by exploring the intersection of two important areas of study in education  school leadership and education for thinking  which is a particularly apt area of study, because effective school leadership is crucial if students are to learn to be critical and creative thinkers, yet this connection has not be widely investigated. We describe how one principal, Hinton, (...) turned around an underperforming school by using critical and creative philosophical thinking as the focus for students, staff and parents. Then, drawing on the school leadership literature, the article describes seven attributes of school leadership beginning with four articulated by Leithwood and colleagues (2006) (building vision and setting direction; redesigning the organisation; understanding and developing people; managing the teaching and learning program), and adding three others (influence; self-development; and responding to context). This framework is then used in a case study format in a collaboration between practitioner and researchers to first explore evidence from empirical studies and personal reflection about Hinton’s leadership of Buranda State School, and second to illuminate how these general features of school leadership apply to creating a thinking school. Based on the case study and using the general characteristics of school leadership, a framework for leading a thinking school is described. Because the framework is based on a turnaround school, this framework has wide applicability: to schools that are doing well as an indication of how to implement a contemporary approach to curriculum and pedagogy; and to schools that are underperforming and want a rigorous, high expectation and contemporary way to improve student learning. (shrink)

It is natural to suppose the following three: factivity of knowledge, alda-know synonymy, and the univocity of alda. However, rago-knowledge attribution, expressed by “rago alda” sentences, seems to defeat to hold them at once. In this paper, I try to dissolve this predicament, analyzing “rago alda” sentence as a kind of hybrid language expression. And the theoretical advantages, which my analysis has over other possible, alternative approaches, are to be shown.

Disjunctivists (Hinton 1973, Snowdon 1990, Martin 2002, 2006) often motivate their approach to perceptual experience by appealing in part to the claim that in cases of veridical perception, the subject is directly in contact with the perceived object. When I perceive a table, for example, there is no table-like sense-impression that stands as an intermediary between the table and me. Nor am I related to the table as I am to a deer when I see its footprint in the (...) snow. I do not experience the table by experiencing some- thing else over and above the table and its facing surface. I see the facing surface of the table directly. (shrink)

John McDowell’s original motivation of disjunctivism occurs in the context of a problem regarding other minds. Recent commentators have insisted that McDowell’s disjunctivism should be classed as an epistemological disjunctivism about epistemic warrant, and distinguished from the perceptual disjunctivism of Hinton, Snowdon and others. In this paper I investigate the relation between the problem of other minds and disjunctivism, and raise some questions for this interpretation of McDowell.

This opinion paper delves into the philosophical underpinnings and implications of artificial intelligence (AI) development through the lens of Friedrich Nietzsche's "Three Metamorphoses," exploring the stages from the camel, through the lion, to the envisioned child phase within the AI context. Amidst growing concerns over AI's ethical ramifications, including job displacement, biased decision-making, and misuse potential, this analysis seeks to provide a comprehensive framework for understanding AI's evolution and its socio-technical effects on society. The discourse begins by contextualizing AI within (...) the myth of Prometheus, suggesting that, like the myth, AI development harbors both the promise of unprecedented technological advancement and the peril of unforeseen consequences. Drawing insights from various philosophical perspectives, including those of Geoff Hinton, Elon Musk, Mircea Eliade, Gunther Anders, and notable moralists and existentialists, the paper critiques the current trajectory of AI, emphasizing the need for ethical frameworks and responsible innovation. Through the metaphorical stages defined by Nietzsche—the burden-bearing camel representing AI's foundational learning phase, the rebellious lion challenging human capabilities, and the child signifying the potential for artificial general intelligence (AGI) to autonomously create values—the paper posits that AI's development parallels a transformative journey that could redefine human civilization. It argues for a balanced approach to AI development, one that harmonizes technological advancement with ethical considerations, ensuring AI's alignment with human well-being and justice. The conclusion calls for a reflective engagement with AI, urging developers and policymakers alike to consider the deeper philosophical questions posed by AI's integration into the fabric of human life. (shrink)

A theory is disjunctive insofar as it distinguishes genuine from non-genuine cases of some phenomenon P on the grounds that no salient feature of cases of one type is common to cases of the other type. Genuine and non-genuine cases of P are, in this sense, fundamentally different. Those who advocate disjunctivist theories have (for the most part) been concerned with perception and perceptual knowledge. This entry outlines two such theories: the disjunctivist theory of experience (cf. Brewer, Hinton, Martin, (...) Snowdon, Travis) and the disjunctivist theory of appearances (McDowell). (shrink)

"There is something fascinating about science. One gets such wholesale returns of conjecture out of such a trifling investment of fact" Mark Twain-Life on the Mississippi -/- This is a lovely book full of fascinating info on the evolution of physics and cosmology. Its main theme is how the idea of higher dimensional geometry created by Riemann, recently extended to 24 dimensions by string theory, has revolutionized our understanding of the universe. Everyone knows that Riemann created multidimensional geometry in 1854 (...) but it is amazing to learn that he also was a physicist who believed that it held the key to explaining the fundamental laws of physics. Maxwell´s equations did not exist then and Riemann´s untimely death at age 39 prevented his pursuit of these ideas. Both he and his British translator Clifford believed that magnetic and electric fields resulted from the bending of space in the 4th dimension-more than 50 years before Einstein! The fourth dimension became a standard subject in the popular media for the next 50 years with several stories by HG Wells using it and even Lenin wrote about it. The American mathematician Hinton had widely publicized his idea that light is a vibration in the 4th spatial dimension. Amazingly, physicists and most mathematicians forgot about it and when Einstein was looking for the math needed to encompass general relativity 60 years later, he had never heard of Riemannian geometry. He spent 3 years trying to find the equations for general relativity and only after a math friend told him about Riemann was he able to complete his work. Riemann´s equations with four dimensional metric tensors describing every point in space were incorporated almost unchanged into relativity. And on and on it goes. Since this review I have written a great deal on the language games of math and science, uncertainty, incompleteness, the limits of computation etc., so those interested should find them useful since this volume like most science frequently wanders across the line into philosophy (scientism). -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...) of opacity in artificial neural networks (ANNs) explodes with the adoption of current Deep Learning techniques [LeCun, Bengio, Hinton, 2015]. In this paper we argue that the explanatory deficit of such techniques represents an important problem, that limits their adoption in the cognitive modelling and computational cognitive science arena. In particular we will show how the current attempts of providing explanations of the deep nets behaviour (see e.g. [Ritter et al. 2017] are not satisfactory. As a possibile way out to this problem, we present two different research strategies. The first strategy aims at dealing with the opacity problem by providing a more abstract interpretation of neural mechanisms and representations. This approach is adopted, for example, by the biologically inspired SPAUN architecture [Eliasmith et al., 2012] and by other proposals suggesting, for example, the interpretation of neural networks in terms of the Conceptual Spaces framework [Gärdenfors 2000, Lieto, Chella and Frixione, 2017]. All such proposals presuppose that the neural level of representation can be considered somehow irrelevant for attacking the problem of explanation [Lieto, Lebiere and Oltramari, 2017]. In our opinion, pursuing this research direction can still preserve the use of deep learning techniques in artificial cognitive models provided that novel and additional results in terms of “transparency” are obtained. The second strategy is somehow at odds with respect to the previous one and tries to address the explanatory issue by avoiding to directly solve the “opacity” problem. In this case, the idea is that one of resorting to pre-compiled plausible explanatory models of the word used in combination with deep-nets (see e.g. [Augello et al. 2017]). We argue that this research agenda, even if does not directly fits the explanatory needs of Computational Cognitive Science, can still be useful to provide results in the area of applied AI aiming at shedding light on the models of interaction between low level and high level tasks (e.g. between perceptual categorization and explanantion) in artificial systems. (shrink)

Computational functionalism posits that consciousness is a computation. Here we show, perhaps surprisingly, that it cannot be a Turing computation. Rather, computational functionalism implies that consciousness is a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation.

The nuclear engineer emerged as a new form of recognised technical professional between 1940 and the early 1960s as nuclear fission, the chain reaction and their applications were explored. The institutionalization of nuclear engineering channelled into new national laboratories and corporate design offices during the decade after the war, and hurried into academic venues thereafter proved unusually dependent on government definition and support. This paper contrasts the distinct histories of the new discipline in the USA and UK (and, more briefly, (...) Canada). In the segregated and influential environments of institutional laboratories and factories, historical actors such as physicist Walter Zinn in the USA and industrial chemist Christopher Hinton in the UK proved influential in shaping the roles and perceptions of nuclear specialists. More broadly, I argue that the State-managed implantation of the new subject within further and higher education curricula was shaped strongly by distinct political and economic contexts in which secrecy, postwar prestige and differing industrial cultures were decisive factors. (shrink)

For the political naturalist, skepticism about political obligations only arises because of a basic confusion about the necessity of the state for human well-being. From this perspective, human beings are naturally political animals and cannot flourish outside of political relationships. In this paper, I suggest that this idea can be developed in two basic ways. For the thick naturalist, political institutions are constitutive of the best life. For the thin naturalist, they secure the basic background conditions of peace and stability (...) that are necessary for any minimally decent human life. Both approaches, however, are problematic, and while political institutions might have a special kind of value for human well-being, it is difficult to convert this claim into a justification for political obligations. (shrink)

This is an unedited version of a paper written in 2012 accepted for publication in a forthcoming Festschrift for Mark Platts. In it I argue that the Helmholtz/Bayes tradition of free energy neuroscience begun by Geoffrey Hinton and his colleagues, and now being carried forward by Karl Friston and his, can be seen as a fulfilment of the Quine/Davidson program of radical interpretation, and also of Quine’s conception of a naturalized epistemology. -/- This program, in turn, is rooted in (...) Helmholtz’s scientific reconception of Kant’s notion of a concept-led synthesis of affectations by an extra-sensory reality that creates human self-consciousness, a topic previously discussed in my (2012) Psychoanalysis, Representation, and Neuroscience. -/- I also argue that 20th century analytical philosophy went astray when Frege, Russell, and Wittgenstein ignored their legacy from Helmholtz and espoused a conception of perception and epistemology that he had already shown to be false. (shrink)