'Without symbolism the life of man would be like that of the prisoners in the cave of Plato's simile…confined within the limits of his biological needs and practical interests; it could find no access to the "ideal world" which is opened to him from different sides by religion, art, philosophy, science.' Ernst Cassirer 1 ABSTRACT I begin by outlining some of the positions that have been taken by those who have reflected upon the nature of language. In his early work Wittgenstein asserts that language becomes meaningful when we tacitly adhere to the rules of logic. In his later work he claims that lan- guages become meaningful when they are situated within forms of life. Polanyi describes language as a toolbox for deploying our tacit awareness. A meaning is generated when a point of view attends from a subsidiary to a focal awareness. Languages re-present these meanings. Although all languages rely upon rules, what it is to be a meaning is not reduc- ible to rules. Nor is there a universal grammar. Because it renders abstract reflection possi- ble, language renders minds possible. A mind is not the product of an innate language of thought; it is a consequence of indwelling within a natural language. Indwelling within languages enables us to access new realities. Languages however do not supply us with the boundaries of the world. Not only do we know more than we can say, we can also say more than we know. The ultimate context of our linguistic meanings is not our social practices; it is our embodied awareness of the world. A representationalist account is in accordance with the view that minds are Turing machines. But the symbols processed by a Turing ma- chine derive their meaning from the agents that use them to achieve their purposes. Only if the processing of symbolic representations is related to the tacit context within which they become meaningful, does a semantic engine becomes possible.

The Tacit Dimension

A computer program capable of acting intelligently in the world must have a general representation of the world in terms of which its inputs are interpreted. Designing such a program requires commitments about what knowledge is and how it is obtained. Thus, some of the major traditional problems of philosophy arise in artificial intelligence. More specifically, we want a computer program that decides what to do by inferring in a formal language that a certain strategy will achieve its assigned goal. This requires formalizing concepts of causality, ability, and knowledge. Such formalisms are also considered in philosophical logic. The first part of the paper begins with a philosophical point of view that seems to arise naturally once we take seriously the idea of actually making an intelligent machine. We go on to the notions of metaphysically and epistemo-logically adequate representations of the world and then to an explanation of can, causes, and knows in terms of a representation of the world by a system of interacting automata. A proposed resolution of the problem of freewill in a deterministic universe and of counterfactual conditional sentences is presented. The second part is mainly concerned with formalisms within which it can be proved that a strategy will achieve a goal. Concepts of situation, fluent, future operator, action, strategy, result of a strategy and knowledge are formalized. A method is given of constructing a sentence of first-order logic which will be true in all models of certain axioms if and only if a certain strategy will achieve a certain goal. The formalism of this paper represents an advance over McCarthy (1963) and Green (1969) in that it permits proof of the correctness of strategies that contain loops and strategies that involve the acquisition of knowledge; and it is also somewhat more concise. The third part discusses open problems in extending the formalism of part 2. The fourth part is a review of work in philosophical logic in relation to problems of artificial intelligence and a discussion of previous efforts to program ‘general intelligence’ from the point of view of this paper.

/pdf/some-philosophical-problems-from-the-standpoint-of-6oprg9bbyt.pdf

Some philosophical problems from the standpoint of artificial intelligence

A number of emerging technologies including virtual reality, simulation rides, video conferencing, home theater, and high definition television are designed to provide media users with an illusion that a mediated experience is not mediated, a perception defined here as presence. Traditional media such as the telephone, radio, television, film, and many others offer a lesser degree of presence as well. This article examines the key concept of presence. It begins by noting practical and theoretical reasons for studying this concept. Six conceptualizations of presence found in a diverse set of literatures are identified and a detailed explication of the concept that incorporates these conceptualizations is presented. Existing research and speculation about the factors that encourage or discourage a sense of presence in media users as well as the physiological and psychological effects of presence are then outlined. Finally, suggestions concerning future systematic research about presence are presented.

At the Heart of It All: The Concept of Presence

The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient-doctor relationship or facilitate its erosion remains to be seen.

High-performance medicine: the convergence of human and artificial intelligence

Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.

/pdf/word-sense-disambiguation-a-survey-20csyn4stq.pdf

Alan M. Turing

Papers

I.—computing machinery and intelligence