It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both the behaviour of the (...) network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)

The emperor's new mind (hereafter Emperor) is an attempt to put forward a scientific alternative to the viewpoint of according to which mental activity is merely the acting out of some algorithmic procedure. John Searle and other thinkers have likewise argued that mere calculation does not, of itself, evoke conscious mental attributes, such as understanding or intentionality, but they are still prepared to accept the action the brain, like that of any other physical object, could in principle be simulated by (...) a computer. In Emperor I go further than this and suggest that the outward manifestations ofconscious mental activity cannot even be properly simulated by calculation. To support this view, I use various arguments to show that the results of mathematical insight, in particular, do not seem to be obtained algorithmically. The main thrust ofthis work, however, is to present an overview ofthe present state of physical understanding and to show that an important gap exists at the point where, quantum and classical physics meet, as well as to speculate on how the conscious brain might be taking advantage ofwhatever new physics is needed to fill this gap to achieve its nonalgorithmic effects. (shrink)

Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...) human society held a prejudiced attitude toward machinery—seeing machines a priori as mindless objects—machines could not be said to be intelligent, by definition. He also realized, though, that if humans’ a priori, chauvinistic attitude toward machinery changed, the existence of intelligent machines would become logically possible. Turing thought that such a change would eventually occur: He believed that when scientists overcome the technological challenge of constructing sophisticated machines that could imitate human verbal behavior—i.e., do well in the imitation game—humans’ prejudiced attitude toward machinery will have altered in such a way that machines could be said to be intelligent. The imitation game, for Turing, was not an intelligence test, but a technological aspiration whose realization would likely involve a change in society’s attitude toward machines. (shrink)

This essay accounts for the notion of _Lebensform_ by assigning it a _logical _role in Wittgenstein’s later philosophy. Wittgenstein’s additions of the notion to his manuscripts of the _PI_ occurred during the initial drafting of the book 1936-7, after he abandoned his effort to revise _The Brown Book_. It is argued that this constituted a substantive step forward in his attitude toward the notion of simplicity as it figures within the notion of logical analysis. Next, a reconstruction of his later (...) remarks on _Lebensformen_ is offered which factors in his reading of Alan Turing’s “On computable numbers, with an application to the _Entscheidungsproblem_“, as well as his discussions with Turing 1937-1939. An interpretation of the five occurrences of _Lebensform_ in the PI is then given in terms of a logical “regression” to _Lebensform_ as a fundamental notion. This regression characterizes Wittgenstein’s mature answer to the question, “What is the nature of the logical?”. (shrink)

In the centenary year of Turing’s birth, a lot of good things are sure to be written about him. But it is hard to find something new to write about Turing. This is the biggest merit of this article: it shows how von Neumann’s architecture of the modern computer is a serendipitous consequence of the universal Turing machine, built to solve a logical problem.

This paper elaborates on the Golem metaphor as a way of understanding uncertainty in science. Its implications for the ethics of communicating science are explored.

The aim of this paper is an attempt to give an answer to the question what does it mean that a computational system is intelligent. We base on some theses that though debatable are commonly accepted. Intelligence is conceived as the ability of tractable solving of some problems that in general are not solvable by deterministic Turing Machine.

Este artículo esboza una respuesta a la pregunta sobre cómo explicar los efectos de las tecnologías en la sociedad. Su propósito es mostrar una alternativa a los tradicionales discursos deterministas, los cuales suponen que las tecnologías impactan las formas de organización social. A partir de una crítica a las explicaciones deterministas que predominan actualmente, se presenta una primera conclusión: no hay una relación clara entre los cambios sociales y las características técnicas de las tecnologías. Así, se argu¬menta que las tecnologías (...) no causan impactos, sino que los cambios sociales son productos de procesos de interpretación, negociación y materialización de los intereses de los actores involucrados. De esta forma, los artefactos tecnológicos se asumen como agentes del cambio, pero no por una esencia técnica, sino por el papel que desempeñan, el cual resulta definido en el proceso de significación del artefacto a medida que es vinculado a la red, es decir, en la construcción del cambio. (shrink)

‘Interactional expertise’ is developed through linguistic interaction without full scale practical immersion in a culture. Interactional expertise is the medium of communication in peer review in science, in review committees, and in interdisciplinary projects. It is also the medium of specialist journalists and of interpretative methods in the social sciences. We describe imitation game experiments designed to make concrete the idea of interactional expertise. The experiments show that the linguistic performance of those well socialized in the language of a specialist (...) group is indistinguishable from those with full blown practical socialization but distinguishable from those who are not well socialized. The imitation game can also be used to indicate whether an individual can enter an esoteric domain and master the interactional expertise, a skill required by interpretative sociologists of science, anthropologists, ethnographers, and the like.Keywords: Expertise; Interactional expertise; Imitation game; Turing test; Colour blindness; Interpretative methods. (shrink)

Advances in neuroscience might make it possible to develop techniques for directly altering offenders’ brains, in order to make offenders more responsible and law-abiding. The idea of using such techniques within the criminal justice system can seem intuitively troubling, even if they were more effective in preventing crime than traditional methods of rehabilitation. One standard argument against this use of brain interventions is that it would undermine the individual’s free will. This paper maintains that ‘free will’ (at least, as that (...) notion is understood by those who adopt the influential compatibilist approach) is an inadequate basis for explaining what is problematic about some direct brain interventions. This paper then defends an alternative way of objecting to certain kinds of direct brain interventions, focusing on the relationship between the offender and the state rather than the notion of free will. It opposes the use of interventions which aim to enhance ‘virtue responsibility’ (by instilling particular values about what is right and wrong), arguing that this would objectify offenders. In contrast, it argues that it may be acceptable to use direct brain interventions to enhance ‘capacity responsibility’ (i.e. to strengthen the abilities necessary for the exercise of responsible agency, such as self-control). Finally it considers how to distinguish these different kinds of responsibility enhancement. (shrink)

Cognitive science is held, not only by its practitioners, to offer something distinctively new in the philosophy of mind. This novelty is seen as the product of two factors. First, philosophy of mind takes itself to have well and truly jettisoned the ‘old paradigm’, the theory of the mind as embodied soul, easily and completely known through introspection but not amenable to scientific inquiry. This is replaced by the ‘new paradigm’, the theory of mind as neurally-instantiated computational mechanism, relatively opaque (...) to introspection and the proper subject of detailed empirical investigation. Second, in the constitutive disciplines of cognitive science we have for the first time the theoretical, experimental and technological resources to begin this investigation. My concern here is to show that, despite its scientific and philosophical sophistication, the new paradigm is in certain striking ways very similar to the old paradigm and that Wittgenstein's criticisms of the former apply to much of the latter. (shrink)

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and (...) sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems. (shrink)

Turing was an exceptional mathematician with a peculiar and fascinating personality and yet he remains largely unknown. In fact, he might be considered the father of the von Neumann architecture computer and the pioneer of Artificial Intelligence. And all thanks to his machines; both those that Church called “Turing machines” and the a-, c-, o-, unorganized- and p-machines, which gave rise to evolutionary computations and genetic programming as well as connectionism and learning. This paper looks at all of these and (...) at why he is such an often overlooked and misunderstood figure. (shrink)

The foundations of AI design discourse are worth analyzing. Here, attention is paid to the nature of theory languages used in designing new AI technologies because the limits of these languages can clarify some fundamental questions in the development of AI. We discuss three types of theory language used in designing AI products: formal, computational, and natural. Formal languages, such as mathematics, logic, and programming languages, have fixed meanings and no actual-world semantics. They are context- and practically content-free. Computational languages (...) use terms referring to the actual world, i.e., to entities, events, and thoughts. Thus, computational languages have actual-world references and semantics. They are thus no longer context- or content-free. However, computational languages always have fixed meanings and, for this reason, limited domains of reference. Finally, unlike formal and computational languages, natural languages are creative, dynamic, and productive. Consequently, they can refer to an unlimited number of objects and their attributes in an unlimited number of domains. The differences between the three theory languages enable us to reflect on the traditional problems of strong and weak AI. (shrink)

Ioannidis [Why most published research findings are false. PLoS Med 2: e124 ] identifies six factors that contribute to explaining why most of the current published research findings are more likely to be false than true, and argues that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this article, we argue that three “hot” areas in current biological research, viz., agent-based modeling, evolutionary developmental biology, and systems biology, are especially (...) prone to the flaws. (shrink)