What is an hypertextual author

The creators of digital works will need to be a new kind of artist , or team, with a distinct mix of expertise in at least three areas – the specific subject matter and associated critical and analytical techniques, technical computing processes, and principles of content selection and organization...

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Paradox lust

Heidegger's notion of enframing is seminal to the understanding of how hypertext can be thought as operating across the assumed boundaries of the semantic field, as well as all other fields of signifying convention.

Among the issues that arise here is how the solicitation of hypertext would mark, as Samuel Weber puts it, a way "in which the 'technics' of Heidegger's quest(ion) entails the destabilisation of such fields," and how this solicitation as a general bringing-forth might be regarded simultaneously as a function of poiesis and of technics, both "originary" and mechanical production, reproduction or repetition.In other words, how this solicitation would describe what Joyce terms a "paradox lust," operating somewhere between the concepts of techne and logos.

Similarly, in light of the various recent developments in the application of computing science within the field of Joycean scholarship, the question arises as to what it might imply if we were to approach hypertext as a particular technology, as technological - what the word "technology" might signify in the context of Joyce's writing practice-keeping in mind Heidegger's assertion that "techne belongs to bringing-forth, to poiesis; it is something poetic."

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Halting problem

In computability theory the halting problem is a decision problem which can be informally stated as follows:
Given a description of a program and a finite input, decide whether the program finishes running or will run forever, given that input.
Alan Turing proved in 1936 that a general algorithm to solve the halting problem for all possible program-input pairs cannot exist. We say that the halting problem is undecidable over Turing machines.

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Human computer interaction

Human–computer interaction (HCI), alternatively man–machine interaction (MMI) or computer–human interaction (CHI), is the study of interaction between people (users) and computers.

It is an interdisciplinary subject, relating computer science with many other fields of study and research. Interaction between users and computers occurs at the user interface (or simply interface), which includes both software and hardware, for example, general purpose computer peripherals and large-scale mechanical systems such as aircraft and power plants.

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Computational semiotics

Computational semiotics is an interdisciplinary field that applies, conducts, and draws on research in logic, mathematics, the theory and practice of computation, formal and natural language studies, the cognitive sciences generally, and semiotics proper.

A common theme of this work is the adoption of a sign-theoretic perspective on issues of artificial intelligence and knowledge representation. Many of its applications lie in the field of computer-human interaction (CHI) and the fundamental devices of recognition (work at IASE in California).

One part of this field, known as algebraic semiotics, combines aspects of algebraic specification and social semiotics, and has been applied to user interface design and to the representation of mathematical proofs.

Computational methods

According to L. Floridi, one can think of three main ways for applying computational methods towards philosophical matters:

Conceptual experiments in silico: As an innovative extension of an ancient tradition of thought experiment, a trend has begun in philosophy to apply computational modeling schemes to questions in logic, epistemology, philosophy of science, philosophy of biology, philosophy of mind, and so on.

Pancomputationalism (or the fallacy of a powerful metaphor): By this view, computational and informational concepts are considered to be so powerful that given the right Level of abstraction, anything in the world could be modeled and represented as a computational system, and any process could be simulated computationally. Then, however, pancomputationalists have the hard task of providing credible answers to the following two questions:

how can one avoid blurring all differences among systems, thus transforming pancomputationalism into a night in which all cows are black, to paraphrase Hegel?
what would it mean for the system under investigation not to be an informational system (or a computational system, if computation = information processing)?

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Computer science

Computer science concerns itself with the automatic processing of information (or at least with physical systems of symbols to which information is assigned) by means of such things as computers.

From the beginning, computer programmers have been able to develop programs which permit computers to carry out tasks for which organic beings need a mind. A simple example is multiplication. But it is clear that computers do not use a mind to multiply. Could they, someday, come to have what we call a mind? This question has been propelled into the forefront of much philosophical debate because of investigations in the field of artificial intelligence.

Within AI, it is common to distinguish between a modest research program and a more ambitious one: this distinction was coined by John Searle in terms of a weak AI and a strong AI. The exclusive objective of "weak AI", according to Searle, is the successful simulation of mental states, with no attempt to make computers become conscious or aware, etc. The objective of strong AI, on the contrary, is a computer with consciousness similar to that of human beingsThe program of strong AI goes back to one of the pioneers of computation Alan Turing. As an answer to the question "Can computers think?", he formulated the famous Turing test. Turing believed that a computer could be said to "think" when, if placed in a room by itself next to another room which contained a human being and with the same questions being asked of both the computer and the human being by a third party human being, the computer's responses turned out to be indistinguishable from those of the human. Essentially, Turing's view of machine intelligence followed the behaviourist model of the mind - intelligence is as intelligence does. The Turing test has received many criticisms, among which the most famous is probably the Chinese room thought experiment formulated by Searle.

The question about the possible sensitivity (qualia) of computers or robots still remains open. Some computer scientists believe that the specialty of AI can still make new contributions to the resolution of the "mind body problem". They suggest that based on the reciprocal influences between software and hardware that takes place in all computers, it is possible that someday theories can be discovered that help us to understand the reciprocal influences between the human mind and the brain (wetware).

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