The Impact of Alan Turing: Formal Methods and Beyond

© 2019, Springer Nature Switzerland AG. In this paper, we discuss the influence and reputation of Alan Turing since his death in 1954, specifically in the field of formal methods, especially for program proving, but also in a much wider context. Although he received some recognition during his lifetime, this image was tarnished by the controversy at the time of his death. While he was known and appreciated in scientific circles, he did not enter the public’s consciousness for several decades. A turning point was the definitive biography produced by Andrew Hodges in 1983 but, even then, the tide did not turn very rapidly. More recent events, such as the celebrations of his birth centenary in 2012 and the official British royal pardon in 2013, have raised Turing’s fame and popularity among the informed general public in the United Kingdom and elsewhere. Cultural works in the arts featuring Turing have enhanced his profile still further. Thus, the paper discusses not only Turing’s scientific impact, especially for formal methods, but in addition his historical, cultural, and even political significance. Turing’s academic ‘family tree’ in terms of heritage and legacy is also covered

The Machine as Data: A Computational View of Emergence and Definability

Turing’s (Proceedings of the London Mathematical Society 42:230–265, 1936) paper on computable numbers has played its role in underpinning different perspectives on the world of information. On the one hand, it encourages a digital ontology, with a perceived flatness of computational structure comprehensively hosting causality at the physical level and beyond. On the other (the main point of Turing’s paper), it can give an insight into the way in which higher order information arises and leads to loss of computational control—while demonstrating how the control can be re-established, in special circumstances, via suitable type reductions. We examine the classical computational framework more closely than is usual, drawing out lessons for the wider application of information–theoretical approaches to characterizing the real world. The problem which arises across a range of contexts is the characterizing of the balance of power between the complexity of informational structure (with emergence, chaos, randomness and ‘big data’ prominently on the scene) and the means available (simulation, codes, statistical sampling, human intuition, semantic constructs) to bring this information back into the computational fold. We proceed via appropriate mathematical modelling to a more coherent view of the computational structure of information, relevant to a wide spectrum of areas of investigation

Quantum collapse as undecidable proposition in an Everettian multiverse

Our representation of the Universe is built with sequences of symbols, numbers, operators, rules and undecidable propositions defining our mathematical truths, represented either by classical, quantum and probabilistic Turing Machines containing intrinsic randomness. Each representation is at all effects a physical subset of the Universe, a metastructure of events in space and time, which actively participate to the evolution of the Universe as we are internal observers. The evolution is a deterministic sequence of local events, quantum measurements, originated from the local wavefunction collapse of the complementary set of the observers that generate the local events in the Universe. With these assumptions, the Universe and its evolution are described in terms of a semantically closed structure without a global object-environment loss of decoherence as a von Neumann's universal constructor with a semantical abstract whose structure cannot be decided deterministically a-priori from an internal observer. In a semantically closed structure the realization of a specific event writing the semantical abstract of the constructor is a problem that finds a "which way" for the evolution of the Universe in terms of a choice of the constructor's state in a metastructure, the many-world Everett scenario from the specific result of a quantum measurement, a classical G\"odel undecidable proposition for an internal observer, exposing the limits of our description and possible simulation of the Universe.Comment: 27 page

Perspective Chapter: Reflections on the Future of Higher Education in the United Kingdom

The problems being faced in the UK university sector are considered, how these problems have arisen, what needs to be done about them, and, how the future of the UK’s knowledge economy will be influenced by the strategies currently being implemented by the UK government. This is done by revisiting some examples of problems from the past, and how they were solved. This is undertaken using a framework that is characterised by the following fundamental issues: (i) educational philosophies; (ii) ethics in educational provision; (iii) knowledge economies, and; (iv) the goals of education. In this context, the chapter discusses the evolving, and necessary connectivity, between government, education and industry - the so-called ‘Triple Helix Concept’. This is coupled with a discussion on the future of Higher Education in terms of the underlying strategy of the UK government, which reflects the new age of the ‘Technological College’ that the UK is now entering

All the King’s Men: British Codebreaking Operations: 1938-43

The Enigma code was one of the most dangerous and effective weapons the Germans wielded at the outbreak of the Second World War. The Enigma machine was capable of encrypting radio messages that seemed virtually unbreakable. In fact, there were 158,900, 000,000,000 possible combinations in any given message transmitted. On the eve of the war’s outbreak, the British had recently learned that the Poles had made significant progress against this intimidating cipher in the early 1930s. Incensed and with little help, the British Government Code & Cipher School began the war searching for a solution. Drawing from their experiences from the First World War, and under the visionary guidance of Alan Turing, Gordon Welchman, and countless others, the British created a new, mechanical approach to breaking the seemingly impossible German code. By breaking the code, they could very well save Britain

Language Processing and the Artificial Mind: Teaching Code Literacy in the Humanities

Humanities majors often find themselves in jobs where they either manage programmers or work with them in close collaboration. These interactions often pose difficulties because specialists in literature, history, philosophy, and so on are not usually code literate. They do not understand what tasks computers are best suited to, or how programmers solve problems. Learning code literacy would be a great benefit to humanities majors, but the traditional computer science curriculum is heavily math oriented, and students outside of science and technology majors are often math averse. Yet they are often interested in language, linguistics, and science fiction. This thesis is a case study to explore whether computational linguistics and artificial intelligence provide a suitable setting for teaching basic code literacy. I researched, designed, and taught a course called “Language Processing and the Artificial Mind.” Instead of math, it focuses on language processing, artificial intelligence, and the formidable challenges that programmers face when trying to create machines that understand natural language. This thesis is a detailed description of the material, how the material was chosen, and the outcome for student learning. Student performance on exams indicates that students learned code literacy basics and important linguistics issues in natural language processing. An exit survey indicates that students found the course to be valuable, though a minority reacted negatively to the material on programming. Future studies should explore teaching code literacy with less programming and new ways to make coding more interesting to the target audience