Historical and current machine intelligence

In this article, we provide an initial insight into the study of MI and what it means for a machine to be intelligent. We discuss how MI has progressed to date and consider future scenarios in a realistic and logical way as much as possible. To do this, we unravel one of the major stumbling blocks to the study of MI, which is the field that has become widely known as "artificial intelligence"

Authors' response to letter to the editor

Letter to the editor relates to article Warwick, K. and Nasuto, S.J (2006). 'Historical and Current Machine Intelligence.' IEEE Instrumentation and Measurement Magazine 9 (6):20-26.

On linking human and machine brains

A look is taken here at how the use of implant technology is rapidly diminishing the effects of certain neural illnesses and distinctly increasing the range of abilities of those affected. An indication is given of a number of problem areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. In order to assess the possible opportunities, both human and animal studies are reported on. The main thrust of the paper is, however, a discussion of neural implant experimentation linking the human nervous system bi-directionally with the internet. With this in place, neural signals were transmitted to various technological devices to directly control them, in some cases via the internet, and feedback to the brain was obtained from, for example, the fingertips of a robot hand, and ultrasonic (extra) sensory input and neural signals directly from another human's nervous system. Consideration is given to the prospects for neural implant technology in the future, both in the short term as a therapeutic device and in the long term as a form of enhancement, including the realistic potential for thought communication-potentially opening up commercial opportunities. Clearly though, an individual whose brain is part human-part machine can have abilities that far surpass those with a human brain alone. Will such an individual exhibit different moral and ethical values from those of a human? If so, what effects might this have on society? (C) 2008 Elsevier B.V. All rights reserved.

Issues impairing the success of neural implant technology

By monitoring signals from the central nervous system, humans can be provided with a novel extra channel of communication that can, for example, be used for the voluntary control of peripheral devices. Meanwhile, stimulation of neural tissue can bring about sensation such as touch, can facilitate feedback from external, potentially remote devices and even opens up the possibility of new sensory input for the individual to experience. The concept of successfully harnessing and stimulating nervous system activity is though something that can only be achieved through an appropriate interface. However, interfacing the nervous system by means of implant technology carries with it many problems and dangers. Further, results achieved may not be as expected or as they at first appear. This paper describes a comparative study investigating different implant types and procedures. It is aimed at highlighting potential problem areas and is intended to provide a useful reference explaining important tolerances and limits.

NOx and O3 above a tropical rainforest: an analysis with a global and box model

A cross-platform field campaign, OP3, was conducted in the state of Sabah in Malaysian Borneo between April and July of 2008. Among the suite of observations recorded, the campaign included measurements of NOx and O3 – crucial outputs of any model chemistry mechanism. We describe the measurements of these species made from both the ground site and aircraft. We then use the output from two resolutions of the chemistry transport model p-TOMCAT to illustrate the ability of a global model chemical mechanism to capture the chemistry at the rainforest site. The basic model performance is good for NOx and poor for ozone. A box model containing the same chemical mechanism is used to explore the results of the global model in more depth and make comparisons between the two. Without some parameterization of the nighttime boundary layer – free troposphere mixing (i.e. the use of a dilution parameter), the box model does not reproduce the observations, pointing to the importance of adequately representing physical processes for comparisons with surface measurements. We conclude with a discussion of box model budget calculations of chemical reaction fluxes, deposition and mixing, and compare these results to output from p-TOMCAT. These show the same chemical mechanism behaves similarly in both models, but that emissions and advection play particularly strong roles in influencing the comparison to surface measurements.

Single tap identification for fast BCI control

One of the major aims of BCI research is devoted to achieving faster and more efficient control of external devices. The identification of individual tap events in a motor imagery BCI is therefore a desirable goal. EEG is recorded from subjects performing and imagining finger taps with their left and right hands. A Differential Evolution based feature selection wrapper is used in order to identify optimal features in the spatial and frequency domains for tap identification. Channel-frequency band combinations are found which allow differentiation of tap vs. no-tap control conditions for executed and imagined taps. Left vs. right hand taps may also be differentiated with features found in this manner. A sliding time window is then used to accurately identify individual taps in the executed tap and imagined tap conditions. Highly statistically significant classification accuracies are achieved with time windows of 0.5 s and more allowing taps to be identified on a single trial basis.

Prediction of Parkinson’s disease tremor onset using radial basis function neural networks

The possibility of using a radial basis function neural network (RBFNN) to accurately recognise and predict the onset of Parkinson’s disease tremors in human subjects is discussed in this paper. The data for training the RBFNN are obtained by means of deep brain electrodes implanted in a Parkinson disease patient’s brain. The effectiveness of a RBFNN is initially demonstrated by a real case study.

Engaging robots: innovative outreach for attracting cybernetics students

Cybernetics is a broad subject, encompassing many aspects of electrical, electronic, and computer engineering, which suffers from a lack of understanding on the part of potential applicants and teachers when recruiting students. However, once the engineering values, fascinating science, and pathways to rewarding, diverse careers are communicated, appropriate students can be very interested in enrolling. At the University of Reading, Reading, U.K., a key route for outreach to prospective students has been achieved through the use of robots in interactive talks at schools, competitions (often funded by Public Understanding of Science projects), a collectable fortnightly magazine, exhibitions in museums, open days at the University, and appearances in the media. This paper identifies the interactive engagement, anthropomorphic acceptability, and inspirational nature of robots as being key to their successful use in outreach activities. The statistical results presented show that the continued popularity of degrees at Reading in cybernetics, electronic engineering, and robotics over the last 20 years is in part due to the outreach activities to schools and the general public.

Hidden interlocutor misidentification in practical Turing Tests

Based on insufficient evidence, and inadequate research, Floridi and his students report inaccuracies and draw false conclusions in their Minds and Machines evaluation, which this paper aims to clarify. Acting as invited judges, Floridi et al. participated in nine, of the ninety-six, Turing tests staged in the finals of the 18th Loebner Prize for Artificial Intelligence in October 2008. From the transcripts it appears that they used power over solidarity as an interrogation technique. As a result, they were fooled on several occasions into believing that a machine was a human and that a human was a machine. Worse still, they did not realise their mistake. This resulted in a combined correct identification rate of less than 56%. In their paper they assumed that they had made correct identifications when they in fact had been incorrect.

Testing Turing's five minutes, parallel-paired imitation game

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.

From the buzzing in Turing’s head to machine intelligence contests

This paper presents an analysis of three major contests for machine intelligence. We conclude that a new era for Turing’s test requires a fillip in the guise of a committed sponsor, not unlike DARPA, funders of the successful 2007 Urban Challenge.