It is widely known that when Turing first introduced his “imitation‐game” test for ascertaining whether a computing machine can think, he considered, and found wanting, a series…
Abstract
Purpose
It is widely known that when Turing first introduced his “imitation‐game” test for ascertaining whether a computing machine can think, he considered, and found wanting, a series of objections to his position. It seems safe to say that one of these objections, the “theological objection” (TO), is regarded by Turing to be positively anemic, and that ever since he delivered his rapid (purported!) refutation over half a century ago, the received view has been that, indeed, this objection is as weak as can be. The purpose of this paper is to show that TO is not the pushover Turing, and others since, take it to be.
Design/methodology/approach
The paper is devoted to the TO within the Turing test (TT) and to Turing's reply to this objection.
Findings
The paper reaches the conclusion that Turing's response to TO fails.
Originality/value
This paper is a defense of the TO to the TT.
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Considers whether Gödel’s results preclude the possibility or the impossibility of the artificial intelligence (AI) thesis; and also what the (possible) applications or…
Abstract
Considers whether Gödel’s results preclude the possibility or the impossibility of the artificial intelligence (AI) thesis; and also what the (possible) applications or consequences of them are for AI research. Shows that while the limitative Gödel’s results are shown to preclude neither the possibility nor the impossibility of the AI thesis, they have and will continue to shed significant light on the development of the AI field.
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The purpose of this paper is to review machine consciousness (MC) and machine modelling of consciousness (MMC) with acknowledgement that their study may contribute to…
Abstract
Purpose
The purpose of this paper is to review machine consciousness (MC) and machine modelling of consciousness (MMC) with acknowledgement that their study may contribute to understanding of biological consciousness. The death of Peter Fellgett, the first Professor of Cybernetics in the UK, is noted, with a brief reference to his work on infra‐red spectroscopy and slightly more on his work on ambisonics, or surround‐sound audio reproduction. The work of his collaborator in this, Michael Gerzon, is shown to be well represented on the internet.
Design/methodology/approach
The aim is to review developments on the internet, especially those of general cybernetic interest.
Findings
It is suggested that the evolutionary advantages of consciousness do not get the attention they should and also that reconciliation is needed with the “Cambrian Intelligence” viewpoint of Brooks. Only two fields of activity of Peter Fellgett are mentioned, particularly since his achievements will certainly be featured in a later issue of Kybernetes.
Practical implications
Speculation about MC may well contribute to understanding of the biological variety as well as to robotics techniques as such. Fellgett's contributions to spectroscopy are immensely valuable in astronomy and elsewhere and his work with Gerzon on audio reproduction is a classic study, even if commercially unsuccessful.
Originality/value
It is hoped this is a valuable periodic review.
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Sang Wu Kim and S.M. Kim
Establishes the claims that Gödel’s Incompleteness Theorems cannot prove the existence or the non‐existence of a machine proving all mathematical truths; there exists a machine…
Abstract
Establishes the claims that Gödel’s Incompleteness Theorems cannot prove the existence or the non‐existence of a machine proving all mathematical truths; there exists a machine proving all mathematical truths and the AI thesis is correct.
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Chui Ling Yeung, Chi Fai Cheung, Wai Ming Wang, Eric Tsui and Wing Bun Lee
Narratives are useful to educate novices to learn from the past in a safe environment. For some high-risk industries, narratives for lessons learnt are costly and limited, as they…
Abstract
Purpose
Narratives are useful to educate novices to learn from the past in a safe environment. For some high-risk industries, narratives for lessons learnt are costly and limited, as they are constructed from the occurrence of accidents. This paper aims to propose a new approach to facilitate narrative generation from existing narrative sources to support training and learning.
Design/methodology/approach
A computational narrative semi-fiction generation (CNSG) approach is proposed, and a case study was conducted in a statutory body in the construction industry in Hong Kong. Apart from measuring the learning outcomes gained by participants through the new narratives, domain experts were invited to evaluate the performance of the CNSG approach.
Findings
The performance of the CNSG approach is found to be effective in facilitating new narrative generation from existing narrative sources and to generate synthetic semi-fiction narratives to support and educate individuals to learn from past lessons. The new narratives generated by the CNSG approach help students learn and remember important things and learning points from the narratives. Domain experts agree that the validated narratives are useful for training and learning purposes.
Originality/value
This study presents a new narrative generation process for a high-risk industry, e.g. the construction industry. The CNSG approach incorporates the technologies of natural language processing and artificial intelligence to computationally identify narrative gaps in existing narrative sources and proposes narrative fragments to generate new semi-fiction narratives. Encouraging results were gained through the case study.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.