The ingenuity of common workmen: and the invention of the computer

Since World War II, state support for scientific research has been assumed crucial to technological and economic progress. Governments accordingly spent tremendous sums to that end. Nothing epitomizes the alleged fruits of that involvement better than the electronic digital computer. The first such computer has been widely reputed to be the ENIAC, financed by the U.S. Army for the war but finished afterwards. Vastly improved computers followed, initially paid for in good share by the Federal Government of the United States, but with the private sector then dominating, both in development and use, and computers are of major significance.;Despite the supposed success of public-supported science, evidence is that computers would have evolved much the same without it but at less expense. Indeed, the foundations of modern computer theory and technology were articulated before World War II, both as a tool of applied mathematics and for information processing, and the computer was itself on the cusp of reality. Contrary to popular understanding, the ENIAC actually represented a movement backwards and a dead end.;Rather, modern computation derived more directly, for example, from the prewar work of John Vincent Atanasoff and Clifford Berry, a physics professor and graduate student, respectively, at Iowa State College (now University) in Ames, Iowa. They built the Atanasoff Berry Computer (ABC), which, although special purpose and inexpensive, heralded the efficient and elegant design of modern computers. Moreover, while no one foresaw commercialization of computers based on the ungainly and costly ENIAC, the commercial possibilities of the ABC were immediately evident, although unrealized due to war. Evidence indicates, furthermore, that the private sector was willing and able to develop computers beyond the ABC and could have done so more effectively than government, to the most sophisticated machines.;A full and inclusive history of computers suggests that Adam Smith, the eighteenth century Scottish philosopher, had it right. He believed that minimal and aloof government best served society, and that the inherent genius of citizens was itself enough to ensure the general prosperity

Computations and Computers in the Sciences of Mind and Brain

Computationalism says that brains are computing mechanisms, that is, mechanisms that perform computations. At present, there is no consensus on how to formulate computationalism precisely or adjudicate the dispute between computationalism and its foes, or between different versions of computationalism. An important reason for the current impasse is the lack of a satisfactory philosophical account of computing mechanisms. The main goal of this dissertation is to offer such an account. I also believe that the history of computationalism sheds light on the current debate. By tracing different versions of computationalism to their common historical origin, we can see how the current divisions originated and understand their motivation. Reconstructing debates over computationalism in the context of their own intellectual history can contribute to philosophical progress on the relation between brains and computing mechanisms and help determine how brains and computing mechanisms are alike, and how they differ. Accordingly, my dissertation is divided into a historical part, which traces the early history of computationalism up to 1946, and a philosophical part, which offers an account of computing mechanisms. The two main ideas developed in this dissertation are that (1) computational states are to be identified functionally not semantically, and (2) computing mechanisms are to be studied by functional analysis. The resulting account of computing mechanism, which I call the functional account of computing mechanisms, can be used to identify computing mechanisms and the functions they compute. I use the functional account of computing mechanisms to taxonomize computing mechanisms based on their different computing power, and I use this taxonomy of computing mechanisms to taxonomize different versions of computationalism based on the functional properties that they ascribe to brains. By doing so, I begin to tease out empirically testable statements about the functional organization of the brain that different versions of computationalism are committed to. I submit that when computationalism is reformulated in the more explicit and precise way I propose, the disputes about computationalism can be adjudicated on the grounds of empirical evidence from neuroscience

From analogy-making to modelling : the history of analog computing as a modelling technology

Today, modern computers are based on digital technology. However, during the decades after 1940, digital computers were complemented by the separate technology of analog computing. But what was analog computing, what were its merits, and who were its users? This thesis investigates the conceptual and technological history of analog computing. As a concept, analog computing represents the entwinement of a complex pre-history of meanings, including calculation, modelling, continuity and analogy. These themes are not only landmarks of analog's etymology, but also represent the blend of practices, ways of thinking, and social ties that together comprise an 'analog culture'. The first half of this thesis identifies how the history of this technology can be understood in terms of the two parallel themes of calculation and modelling. Structuring the history around these themes demonstrates that technologies associated with modelling have less representation in the historiography. Basing the investigation around modelling applications, the thesis investigates the formation of analog culture. The second half of this thesis applies the themes of modelling and information generation to understand analog use in context. Through looking at examples of analog use in academic research, oil reservoir modelling, aeronautical design, and meteorology, the thesis explores why certain communities used analog and considers the relationship between analog and digital in these contexts. This study demonstrates that analog modelling is an example of information generation rather than information processing. Rather than focusing on the categories of analog and digital, it is argued that future historical scholarship in this field should give greater prominence to the more general theme of modelling

From analogy-making to modelling : the history of analog computing as a modelling technology

Today, modern computers are based on digital technology. However, during the decades after 1940, digital computers were complemented by the separate technology of analog computing. But what was analog computing, what were its merits, and who were its users? This thesis investigates the conceptual and technological history of analog computing. As a concept, analog computing represents the entwinement of a complex pre-history of meanings, including calculation, modelling, continuity and analogy. These themes are not only landmarks of analog's etymology, but also represent the blend of practices, ways of thinking, and social ties that together comprise an `analog culture'. The first half of this thesis identifies how the history of this technology can be understood in terms of the two parallel themes of calculation and modelling. Structuring the history around these themes demonstrates that technologies associated with modelling have less representation in the historiography. Basing the investigation around modelling applications, the thesis investigates the formation of analog culture. The second half of this thesis applies the themes of modelling and information generation to understand analog use in context. Through looking at examples of analog use in academic research, oil reservoir modelling, aeronautical design, and meteorology, the thesis explores why certain communities used analog and considers the relationship between analog and digital in these contexts. This study demonstrates that analog modelling is an example of information generation rather than information processing. Rather than focusing on the categories of analog and digital, it is argued that future historical scholarship in this field should give greater prominence to the more general theme of modelling.EThOS - Electronic Theses Online ServiceUniversity of Warwick. Dept. of Computer Science (DCS)GBUnited Kingdo

Merging the Natural with the Artificial: The Nature of a Machine and the Collapse of Cybernetics

This thesis is concerned with the rise and fall of cybernetics, understood as an inquiry regarding the nature of a machine. The collapse of this scientific movement, usually explained by external factors such as lack of funding, will be addressed from a philosophical standpoint. Delving deeper into the theoretical core of cybernetics, one could find that the contributions of William Ross Ashby and John von Neumann shed light onto the particular ways in which cybernetics understood the nature and behavior of a machine. Ross Ashby offered an account of the nature of a machine and then extended the scope of “the mechanical”. This extension would encompass areas that will later be shown to be problematic for mechanization, such as learning and adaptation. The way in which a machine-ontology was applied would trigger effects seemingly contrary to cybernetics’ own distinctive features. Von Neumann, on the other hand, tinkered with a mechanical model of the brain, realizing grave limitations that prompted him to look for an alternative for cybernetics to work on. The proposal that came out of this resulted in a serious blow against the theoretical core of cybernetics. Why did cybernetics collapse? The contributions coming from both thinkers, in their own ways, spelled out the main tenets of the cybernetic proposal. But these very contributions led to cybernetics’ own demise. The whole story can be framed under the rubric of a serious inquiry into the metaphysical underpinnings of a machine. The rise and fall of cybernetics could thus help us better understand what a machine is from a philosophical standpoint. Although a historical component is present, my emphasis relies on a philosophical consideration of the cybernetic phenomenon. This metaphysical dissection will attempt to clarify how a machine-based ontology remained at the core of cybernetics. An emerging link will hopefully lead towards establishing a tri-partite correlation between cybernetics’ own evolution, its theoretical core, and its collapse. It will hopefully show how cybernetic inquiries into the nature of a machine might have proved fatal to the very enterprise at large, due to unsolvable theoretical tensions

Glossarium BITri 2016 : Interdisciplinary Elucidation of Concepts, Metaphors, Theories and Problems Concerning Information

222 p.Terms included in this glossary recap some of the main concepts, theories, problems and metaphors concerning INFORMATION in all spheres of knowledge. This is the first edition of an ambitious enterprise covering at its completion all relevant notions relating to INFORMATION in any scientific context. As such, this glossariumBITri is part of the broader project BITrum, which is committed to the mutual understanding of all disciplines devoted to information across fields of knowledge and practic

Machines will think: structure and interpretation of Alan Turing’s imitation game

Can machines think? I present a study of Alan Turing’s iconic imitation game or test and its central question. Seventy years of commentary has been produced about Turing’s 1950 proposal. The now legendary “Turing test” has grown a life of its own in the tradition of analytic philosophy with at best loose ties to the historical imitation tests (1948-1952) posed by Turing. I shall examine the historical and epistemological roots of Turing’s various versions of imitation game or test and make the case that they came out from within a dialogue, in fact a scientific controversy, most notably with physicist and computer pioneer Douglas Hartree, chemist and philosopher Michael Polanyi, and neurosurgeon Geoffrey Jefferson. Placing Turing’s views in their historical, social and cultural context, I shall reclaim their scientific and philosophical value for the sake of the discussion in the years to come. My study is organized according to three main philosophical problems whose analyses are backed by a subsidiary chronology of the concept of machine intelligence in Turing’s thought (1936-1952). The first problem I will address is the identification of Turing’s specific ambition which led him to announce that machines will think. War hero and brilliant mathematician, he challenged the conventional wisdom of what machines really were or could be and prophesized a future pervaded by intelligent machines which may be seen as a dystopia just as much as a utopia. I shall examine Turing’s profile and take special interest in the way he was seen by his contenders. In the second problem, over and above the mere proposal of a test for machine intelligence, I will study Turing’s proposition “machines can think” and its implied existential hypothesis — “there exists (will exist) a thinking machine” — from a point of view of the history of the philosophy of science. Unlike traditional readings of Turing, I found that Turing held a non-obvious realist attitude towards the existence of a mechanical mindbrain which he conjectured to frame the human and whose digital replica he intended to build in the machine. Turing’s 1950 paper has been acknowledged as a complex and multi-layered text. Opposing views can be identified in the literature relative to the question on whether or not Turing proposed his imitation test as an experiment to decide for machine intelligence. I shall call this the Turing test dilemma and address it as my third and main problem. My findings suggest that Turing cannot have proposed his imitation game as something other than a thought experiment. And yet its critical and heuristic functions within the mind-machine controversy are striking