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This paper aims to present a methodology for defining and modeling context-awareness and describing efficiently the interactions between systems, applications and their context. Also, the relation of modern context-aware systems with distributed computation is investigated.

On this purpose, definitions of context and context-awareness are developed based on the theory of computation and especially on a computational model for interactive computation which extends the classical Turing Machine model. The computational model proposed here encloses interaction and networking capabilities for computational machines.

The definition of context presented here develops a mathematical framework for working with context. Also, the modeling approach of distributed computing enables us to build robust, scalable and detailed models for systems and application with context-aware capabilities. Also, it enables us to map the procedures that support context-aware operations providing detailed descriptions about the interactions of applications with their context and other external sources.

A case study of a cloud-based context-aware application is examined using the modeling methodology described in the paper so as to demonstrate the practical usage of the theoretical framework that is presented.

The originality on the framework presented here relies on the connection of context-awareness with the theory of computation and distributed computing.

The purpose of this paper is to consider Alan Turing's philosophical paper on “Computing machinery and intelligence”, in which he defined the “imitation game”, now usually known as the Turing test.

The paper shows that Turing's paper contained more than the test; it contained a wide survey of what a computer could do and its relation to human thought.

This paper discusses how Turing's paper represented the outcome of many years in which Turing has both developed the concept and the design of the digital computer, and considered how its action could be related to human thought.

Analysis of Turing's paper provides an understanding and appreciation of Turing's contributions and the significance of the Turing test.

The purpose of this paper is to consider Turing's two tests for machine intelligence: the parallel‐paired, three‐participants game presented in his 1950 paper, and the “jury‐service” one‐to‐one measure described two years later in a radio broadcast. Both versions were instantiated in practical Turing tests during the 18th Loebner Prize for artificial intelligence hosted at the University of Reading, UK, in October 2008. This involved jury‐service tests in the preliminary phase and parallel‐paired in the final phase.

Almost 100 test results from the final have been evaluated and this paper reports some intriguing nuances which arose as a result of the unique contest.

In the 2008 competition, Turing's 30 per cent pass rate is not achieved by any machine in the parallel‐paired tests but Turing's modified prediction: “at least in a hundred years time” is remembered.

The paper presents actual responses from “modern Elizas” to human interrogators during contest dialogues that show considerable improvement in artificial conversational entities (ACE). Unlike their ancestor – Weizenbaum's natural language understanding system – ACE are now able to recall, share information and disclose personal interests.

At the doorsteps of the fourth wave of the industrial revolution, it is compulsory to develop a new understanding regarding the future of human labor based on “Industry 4.0” for German manufacturers, and two American concepts: “The Industrial Internet” and “The Internet of Things.” How will the nature of human work be in the digital economy of the forthcoming future? The problem of unemployment and the composition of the labor market, in terms of professional skills, are yet to be waiting for answers. Scientific management is also transforming to answer the emerging requirements of this new era, as “Digital Taylorism” to re-organize work in a techno-centric manner. Accordingly, the aim of this chapter is to examine the nature and the possible opportunities and threats of the digital age and try to develop a digital Taylorism understanding to minimize the negative impacts of digitalism on both individual workers and society in a way that all parts including the manufacturers can fully take the benefit of potential advantages of this new era.

Speculations on the possibility of computers displaying intelligence are usually traced to Turing's 1950 paper, ‘Computing machinery and intelligence’. Claims for the literal intelligence of an appropriately programmed computer were publicly refuted by Searle in 1980. Optimism about the adequate simulation of intelligence is now further diminished. Analogies between the computer and the brain or mind have persisted. A contrasting perspective which links computers with documents through writing and through the faculty for constructing socially shared systems of signs has also been developed. From this perspective it can be shown that (i) claims for the literal intelligence of a computer rest on a similar basis to claims for the intelligence of a document, the production of depersonalised linguistic output, and (ii) that such claims are subject to an identical objection, that linguistic output is made available without a prior act of comprehension by the artefact. This paper places the Turing test in its intellectual and historical context. A claim that written words can give the appearance of intelligence, without the human capacity for dialectic response, is found in Plato's Phaedrus. This, too, must be placed in its historical context of a transition from predominantly oral to oral and written communication. Demonstrating that there are extensive similarities between the claims of computers and documents to literal intelligence is part of a progressive demystification of the computer.

Rice’s Theorem is a notorious stumbling block in Computer Science. We review some previous work of us that shows that we can extend Rice’s result to large segments of everyday mathematics, so that similar stumbling blocks appear in many areas of mathematics, as well as applied areas such as mathematical economics; one of its applications (Koppl’s conjecture) is discussed in some detail. Note: this paper has been written in an informal style.