The Turing Test as Interactive Proof

In 1950, Alan Turing proposed his eponymous test based on indistinguishability of verbal behavior as a replacement for the question “Can machines think?” Since then, two mutually contradictory but well‐founded attitudes towards the Turing Test have arisen in the philosophical literature. On the one hand is the attitude that has become philosophical conventional wisdom, viz., that the Turing Test is hopelessly flawed as a sufficient condition for intelligence, while on the other hand is the overwhelming sense that were a machine to pass a real live full‐fledged Turing Test, it would be a sign of nothing but our orneriness to deny it the attribution of intelligence. The arguments against the sufficiency of the Turing Test for determining intelligence rely on showing that some extra conditions are logically necessary for intelligence beyond the behavioral properties exhibited by an agent under a Turing Test. Therefore, it cannot follow logically from passing a Turing Test that the agent is intelligent. I argue that these extra conditions can be revealed by the Turing Test, so long as we allow a very slight weakening of the criterion from one of logical proof to one of statistical proof under weak realizability assumptions. The argument depends on the notion of interactive proof developed in theoretical computer science, along with some simple physical facts that constrain the information capacity of agents. Crucially, the weakening is so slight as to make no conceivable difference from a practical standpoint. Thus, the Gordian knot between the two opposing views of the sufficiency of the Turing Test can be cut.     

Spirituality’ as reconceptualisation of the self: Alan Turing and his pioneering ideas on artificial intelligence

This article investigates the underlying agenda of the philosophy of artificial intelligence (AI) – a discipline of computer science – and proposes a threefold model of ‘spirituality’ as reconceptualisation of the self, composed of one’s search, adaptation and transformation of self-knowledge, specifically concerning the rational humanity. By using the life and ideas of the father of AI and computer science, Alan Turing (1912–1954) as a case study, I will carefully examine his three stages of self-reconceptualisation and highlight the relevance of seeing spirituality as self-reconceptualisation for the current digital age.     

Meaning Relations,Syntax, and Understanding

Axiomathes - This paper revisits the conception of intelligence and understanding as embodied in the Turing Test. It argues that a simple system of meaning relations drawn from words/lexical items...     

ARTIFICIAL INTELLIGENCE AND DE LAS CASAS: A 1492 RESONANCE

Abstract. A comparison is made between two unlikely debates over intelligence. One debate took place in 1550 at Valladolid, Spain, between Bartolomé de las Casas and Juan Gines de Sepúlveda over the intelligence of the Amerindian. The other debate is contemporary, between John Searle and various representatives of the "strong" artificial intelligence (AI) community over the adequacy of the Turing test for intelligence. Although the contemporary debate has yet to die down, the Valladolid debate has been over for four hundred years. The question asked here is whether the contemporary debate can profit from the previous one. The common bond providing the basis for contrast is the issue of the "other" which is present in both debates. From this contrast, the observation is made that the question of meaning is intimately tied to the question of intelligence.     

Is the human mind a Turing machine?

In this paper I discuss the topics of mechanism and algorithmicity. I emphasise that a characterisation of algorithmicity such as the Turing machine is iterative; and I argue that if the human mind can solve problems that no Turing machine can, the mind must depend on some non-iterative principle — in fact, Cantor's second principle of generation, a principle of the actual infinite rather than the potential infinite of Turing machines. But as there has been theorisation that all physical systems can be represented by Turing machines, I investigate claims that seem to contradict this: specifically, claims that there are noncomputable phenomena. One conclusion I reach is that if it is believed that the human mind is more than a Turing machine, a belief in a kind of Cartesian dualist gulf between the mental and the physical is concomitant.     

Simulating Turing machines on Maurer machines

In a previous paper, we used Maurer machines to model and analyse micro-architectures. In the current paper, we investigate the connections between Turing machines and Maurer machines with the purpose to gain an insight into computability issues relating to Maurer machines. We introduce ways to simulate Turing machines on a Maurer machine which, dissenting from the classical theory of computability, take into account that in reality computations always take place on finite machines. In one of those ways, multi-threads and thread forking have an interesting theoretical application.     

简评认知神经科学取向的智力观

随着认知神经科学与生物技术的发展,现当代智力理论的构建明显地受到其影响。这些智力理论被称之为认知神经科学取向的智力观,如Garlick的神经可塑性模型;Das等人根据Luria的神经模型提出的智力PASS模型;Kaufman提出的儿童评估成套测验（K-ABC）;Ceci的生物-生态学智力模型及Perkins的真智力理论等。这些智力观都直接将认知神经过程或神经生物学的某些研究成果融合于其理论模型之中。认知神经科学取向的智力观为智力研究提供了新的研究视角和思考维度,但同时也可能面临某种发展困境。第二代认知科学的具身认知思想可能是解决传统身-心争论的有效途径。     

The future of IQ testing in education

Will IQ tests as we currently know them be used in schools in the year 2000? Will they be used as they are now or will they serve different functions? What new kinds of tests of aptitude and intelligence are likely to be developed in the next twenty years? In this article, the author attempts to answer the first two questions by considering the functions that IQ and aptitude tests now serve in schools and the trends that may modify the present pattern of test use. To answer the third question, she examines current research on intelligence and aptitude and discusses the kind of intelligence tests that might prove more useful in instructional planning.     

Representationalism and the Metonymic Fallacy

Representationalism in cognitive science holds that semantic meaning should be explained by representations in the mind or brain. In this paper it is argued that semantic meaning should instead be explained by an abstract theory of semantic machines -- machines with predicative capability. The concept of a semantic machine (like that of a Turing machine or of Dennett's intentional systems) is not a physical concept -- although it has physical implementations. The predicative competence of semantic machines is defined in terms of independent agreement alone (cf. independent, and yet synchronised, clocks). Abstract theories are analysed as systems of quasi-apriori rules for abstract predicates. A relatively limited number of such theories and a few fundamental dimensions (space, time, mass, etc.) are today assumed to exhaust physical reality. However, that assumption need not be in conflict with predicates that cannot be defined in physical terms – for instance the functional and intentional terms that are crucial for cognitive science.     

Computation,hypercomputation, and physical science

Copeland and others have argued that the Church–Turing thesis (CTT) has been widely misunderstood by philosophers and cognitive scientists. In particular, they have claimed that CTT is in principle compatible with the existence of machines that compute functions above the “Turing limit,” and that empirical investigation is needed to determine the “exact membership” of the set of functions that are physically computable. I argue for the following points: (a) It is highly doubtful that philosophers and cognitive scientists have widely misunderstood CTT as alleged.¹ In fact, by and large, computability theorists and mathematical logicians understand CTT in the exact same way. (b) That understanding most likely coincides with what Turing and Church had in mind. Even if it does not, an accurate exegesis of Turing and Church need not dictate how today's working scientists understand the thesis. (c) Even if we grant Copeland's reading of CTT, an orthodox stronger version of it which he rejects (Gandy's thesis) follows readily if we only accept a highly plausible necessary condition for what constitutes a deterministic digital computer. Finally, (d) regardless of whether we accept this condition, the prospects for a scientific theory of hypercomputation are exceedingly poor because physical science does not have the wherewithal to investigate computability or to discover its ultimate “limit.”     

团体儿童智力测验的编制：目的、准则及其衡鉴

论文阐述了选择编制与世界著名的个别施测的韦克斯勒儿童智力测验相似的但团体施行的儿童智力测验的理由;论述了指导新编测验的五条准则以及选题过程;还报告了对新编测验试用稿的几次相继的因素分析及其它的信度、效度检验结果。     

Review for Cognitive Systems Research of the book The Brain and AI,by authors Karl Schlagenhauf and Fanji Gu

The human brain is often considered the most complex system known. It has a fantastic capacity to learn and remember, to recognize patterns in space and time, solve problems of all kinds, innovate tools and machines, create beautiful art and science. Is it reasonable to believe that we, in a foreseeable future, will be able to understand all the wonders of our own brain, enough to be able to mimic it and build artificial brains and minds that correspond to or even surpass the capacity of the human origin? Can we seriously believe that we (soon, or ever) will be able to build robots that know of and can reflect upon their own existence?This review of the book, The Brain and AI, deals with such issues, but in a very special way. It is written as a fascinating dialogue between the two authors, Chinese scientist Fanji Gu and German engineer Karl Schlagenhauf, where they discuss the development of neuroscience and artificial intelligence (AI) with a critical examination of given “truths” in these fields. The Brain and AI is indeed worth reading for many reasons, regardless if you are a student or researcher in any of the many fields of science discussed here (e.g. physics, computer science, neuroscience, cognitive science psychology, social science), or if you are just interested in the current and future development of brain research and artificial intelligence. The book is both educating and entertaining and can be strongly recommended.     

Safety Engineering for Artificial General Intelligence

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we challenge the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement.     

Measurement of ability emotional intelligence: Results for two new tests

Emotional intelligence (EI) has attracted considerable interest amongst both individual differences researchers and those in other areas of psychology who are interested in how EI relates to criteria such as well‐being and career success. Both trait (self‐report) and ability EI measures have been developed; the focus of this paper is on ability EI. The associations of two new ability EI tests with psychometric intelligence, emotion perception, and the Mayer–Salovey–Caruso EI test (MSCEIT) were examined. The new EI tests were the Situational Test of Emotion Management (STEM) and the Situational Test of Emotional Understanding (STEU). Only the STEU and the MSCEIT Understanding Emotions branch were significantly correlated with psychometric intelligence, suggesting that only understanding emotions can be regarded as a candidate new intelligence component. These understanding emotions tests were also positively correlated with emotion perception tests, and STEM and STEU scores were positively correlated with MSCEIT total score and most branch scores. Neither the STEM nor the STEU were significantly correlated with trait EI tests, confirming the distinctness of trait and ability EI. Taking the present results as a starting‐point, approaches to the development of new ability EI tests and models of EI are suggested.     

THE POPULAR APPEAL OF APOCALYPTIC AI

The belief that computers will soon become transcendently intelligent and that human beings will “upload” their minds into machines has become ubiquitous in public discussions of robotics and artificial intelligence in Western cultures. Such beliefs are the result of pervasive Judaeo‐Christian apocalyptic beliefs, and they have rapidly spread through modern pop and technological culture, including such varied and influential sources as Rolling Stone, the IEEE Spectrum, and official United States government reports. They have gained sufficient credibility to enable the construction of Singularity University in California. While different approaches are possible (and, indeed, are common in Japan and possibly elsewhere), this particular vision of artificial intelligence and robotics has gained ground in the West through the influence of figures such as Hans Moravec and Ray Kurzweil. Because pop‐science books help frame public discussion of new sciences and technologies for individuals, corporations, and governments alike, the integration of religious and technoscientific claims made by their authors should be clear and open for public and scientific debate. As we move forward into an increasingly robotic future, we should do so aware of the ways in which a group's religious environment can help set the tone for public acceptance and use of robotic technologies.     

The WISC-III: A reality check

Although the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) is arguably the best instrument currently available for assessing students' intelligence, its use will present practitioners, especially school psychologists, with some unique challenges. Recent research suggests that significant reductions in special education students' WISC-III Verbal, Performance, and Full Scale IQ scores will be found, compared with their previous WISC-R results. This finding will have a profound impact on special education placement decisions. Specifically, students who were previously found eligible for learning disability programs may now no longer evidence the significant discrepancies necessary in order to receive continued services. Conversely, students earlier identified as “slow learners” may now be eligible to receive services for those classified under the category of educably mentally handicapped. In addition, the notion that the WISC-III may underestimate the ability of certain populations of students requires further exploration. This article will address these issues as well as implications for practitioners presently administering the WISC-III.     

Olympia and Other O-Machines

Against Maudlin, I argue that machines which merely reproduce a pre-programmed series of changes ought to be classed with Turing’s O-Machines even if they would counterfactually show Turing Machine-like activity. This can be seen on an interventionist picture of computational architectures, on which basic operations are the primitive loci for interventions. While constructions like Maudlin’s Olympia still compute, then, claims about them do not threaten philosophical arguments that depend on Turing Machine architectures and their computational equivalents.     

Uncritical inference making and intellectual functioning

The relationship between uncritical inference making and intelligence has been uncertain. In the present study a group of 30 advanced undergraduate students were administered the Uncritical Inference Test and the Otis-Lennon Test of Mental Ability. A significant Pearson correlation of .52 indicates that this measure of intellectual functioning is associated with uncritical inference making. Further research needs to be conducted using standard intelligence measures of specific kinds of intellectual processes.     

Establishing consciousness in non-communicative patients: a modern-day version of the Turing test

In a recent study of a patient in a persistent vegetative state, [Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. (2006). Detecting awareness in the vegetative state. Science, 313, 1402] claimed that they had demonstrated the presence of consciousness in this patient. This bold conclusion was based on the isomorphy between brain activity in this patient and a set of conscious control subjects, obtained in various imagery tasks. However, establishing consciousness in unresponsive patients is fraught with methodological and conceptual difficulties. The aim of this paper is to demonstrate that the current debate surrounding consciousness in VS patients has parallels in the artificial intelligence (AI) debate as to whether machines can think. Basically, (Owen et al., 2006) used a method analogous to the Turing test to reveal the presence of consciousness, whereas their adversaries adopted a line of reasoning akin to Searle's Chinese room argument. Highlighting the correspondence between these two debates can help to clarify the issues surrounding consciousness in non-communicative agents.     

Many Concepts and Two Logics of Algorithmic Reduction

Within the program of finding axiomatizations for various parts of computability logic, it was proven earlier that the logic of interactive Turing reduction is exactly the implicative fragment of Heyting’s intuitionistic calculus. That sort of reduction permits unlimited reusage of the computational resource represented by the antecedent. An at least equally basic and natural sort of algorithmic reduction, however, is the one that does not allow such reusage. The present article shows that turning the logic of the first sort of reduction into the logic of the second sort of reduction takes nothing more than just deleting the contraction rule from its Gentzen-style axiomatization. The first (Turing) sort of interactive reduction is also shown to come in three natural versions. While those three versions are very different from each other, their logical behaviors (in isolation) turn out to be indistinguishable, with that common behavior being precisely captured by implicative intuitionistic logic. Among the other contributions of the present article is an informal introduction of a series of new — finite and bounded — versions of recurrence operations and the associated reduction operations. Presented by Robert Goldblatt