Artificial intelligence and metaphor making: Some philosophic considerations

This article argues that the metaphors presently employed in describing artificial intelligence represent the use of personification and anthropomorphism. They attempt to develop an isomorphic relationship between the human mind and a computer’s logic. It is suggested that an analogic metaphor is more appropriate in describing this relationship and is more epistemologically correct. Reprinted from Knowledge and Policy: The International Journal of Knowledge Transfer and Utilization, Spring 1990, Vol. 3, No. 1, pp. 46–61. His current research interests include the behavioral and philosophic aspects of artificial intelligence and expert computer systems in work situations, and the behavioral perceptions of decision processes in the workplace.     

人工智能辅助下的心理健康新型测评

近年来,人工智能技术的飞速发展及应用催生了"智能化心理健康测评"这一领域。智能化心理健康测评能够弥补传统方法的不足,降低漏诊率并提高诊断效率,这对于心理健康问题的普查及预警具有重大意义。目前,智能化心理健康测评处于初步发展阶段,研究者基于在线行为数据、便携式设备数据等开展主要以数据驱动为导向的探索研究,旨在实现更高的预测准确率,但是测评结果的可解释性等指标尚不够理想。未来的智能化心理健康测评需要强调心理学领域知识和经验的深度介入,提高测评的针对性和精细化程度,加强信效度检验,这对于智能化心理健康测评工具的进一步发展和应用至关重要。     

Relationships of analytical,practical, and emotional intelligence with behavioral dimensions of performance of top managers

This study examined the relationships among analytical, practical, and emotional intelligence (EI) and five dimensions of managerial behavior. Two sets of hypotheses were tested: one set examined the relationship of each of the three types of intelligence with each of the behavioral dimensions; the second set examined the unique contribution of each type of intelligence to the prediction of each dimension. Twenty‐three one‐day assessment center sessions, including tests and simulation exercises, were administered to 163 top managers in Poland. The behavioral dimensions of leadership, initiative, goal orientation, change orientation, and employee development were related to analytical intelligence and practical intelligence, but not to EI. These findings make unique contributions to understanding the relationships of types of intelligence and managerial behavioral dimensions.     

Epistemology of AI Revisited in the Light of the Philosophy of Information

Artificial intelligence has often been seen as an attempt to reduce the natural mind to informational processes and, consequently, to naturalize philosophy. The many criticisms that were addressed to the so-called “old-fashioned AI” do not concern this attempt itself, but the methods it used, especially the reduction of the mind to a symbolic level of abstraction, which has often appeared to be inadequate to capture the richness of our mental activity. As a consequence, there were many efforts to evacuate the semantical models in favor of elementary physiological mechanisms simulated by information processes. However, these views, and the subsequent criticisms against artificial intelligence that they contain, miss the very nature of artificial intelligence, which is not reducible to a “science of the nature”, but which directly impacts our culture. More precisely, they lead to evacuate the role of the semantic information. In other words, they tend to throw the baby out with the bath-water. This paper tries to revisit the epistemology of artificial intelligence in the light of the opposition between the “sciences of nature” and the “sciences of culture”, which has been introduced by German neo-Kantian philosophers. It then shows how this epistemological view opens on the many contemporary applications of artificial intelligence that have already transformed—and will continue to transform—all our cultural activities and our world. Lastly, it places those perspectives in the context of the philosophy of information and more particularly it emphasizes the role played by the notions of context and level of abstraction in artificial intelligence.     

Impacts of artificial intelligence on organizational decision making

Of all of the new technologies emerging in the late 20th century, the production of artificial intelligence may provide the most profound impacts on organizational decision making. Because the development of artificial intelligence technologies and models has largely been based on psychological models of human cognition, the effects of their implementation in complex social settings have not been thoroughly examined. This paper is an attempt to generate research which will develop a comprehensive understanding of the impacts of artificial intelligence and its role in complex organizations. A set of 11 hypotheses has been developed which examine the relationships between artificial intelligence technologies and the dimensions of organizational decision making. It is argued here that the implementation of expert systems will lead to less complex and political decision processes, while the implementation of natural language systems will lead to more complex and political decision processes.     

Accurate intelligence assessments in social interactions: mediators and gender effects

Research indicates that people can assess a stranger's measured intelligence more accurately than expected by chance, based on minimal information involving appearance and behavior. The present research documents behavioral correlates of perceived and measured intelligence and identifies behaviors that mediate the relationship between perceived and measured intelligence. In particular, when judges rated targets with video and auditory stimuli available, responsiveness to conversation partner, eye-gaze, and looking at partner while speaking were each significant mediators in the accurate assessment of intelligence. Each of those behaviors, as well as the percentage of looking at partner while speaking as a function of the target's own speaking time, were significant mediators in the video silent condition. Additionally, judge and target gender contributed to accurate intelligence assessments.     

CONSCIOUSNESS AND THE MACHINE

Abstract. We consider only the relationship of consciousness to physical reality, whether physical reality is interpreted as the brain, artificial intelligence, or the universe as a whole. The difficulties with starting the analysis with physical reality on the one hand and with consciousness on the other are delineated. We consider how one may derive from the other. Concepts of universal or pure consciousness versus local or ego consciousness are explored with the possibility that consciousness may be physically creative. We examine whether artificial intelligence can possess consciousness as an extension of the interrelationship between consciousness and the brain or material reality.     

The dynamic lift of developmental process

What are the essential properties of human intelligence, currently unparalleled in its power relative to other biological forms and relative to artificial forms of intelligence? We suggest that answering this question depends critically on understanding developmental process. This paper considers three principles potentially essential to building human‐like intelligence: the heterogeneity of the component processes, the embedding of development in a social world, and developmental processes that change the cognitive system as a function of the history of soft‐assemblies of these heterogeneous processes in specific tasks. The paper uses examples from human development and from developmental robotics to show how these processes also may underlie biological intelligence and enable us to generate more advanced forms of artificial intelligence.     

The Relationship Between Creativity and Intelligence: A Combined Yogic-Scientific Approach

ABSTRACT

Three ancient yogic philosophies, describing the evolution of cognitive–affective phenomena toward the nondual state of yoga, or union, (e.g., dissolution of the subject–object dichotomy) couple with empirical studies to redefine, and expand, existing constructs for, and relationship between, creativity and intelligence. The Ocean Model addresses the integration of novelty, appropriateness, and authenticity in creative endeavor with intelligence: the intrinsic factors being recognition, informational limitation, choice, and selective adaptation to the environment. Creativity and intelligence are described in three increasingly subtle states, crystallized, fluid, and vacuous, which are influenced by the psychological interplay of dispassion (vairāgya) and discrimination (viveka) at variegated levels. It is argued that the key difference between intelligence and creativity lies in the nature of intention: whether limited or, transcendent. A 9-module matrix is developed to map variations in the expanded creativity–intelligence relationship. Suggestions for empirically testing the Ocean Model are further supported by studies of empathy and wisdom. A unique method to test dispassion, involving ambivalent character traits and their relationship to psychological integration, is presented.     

Psychometric intelligence dissociates implicit and explicit learning

The hypothesis that performance on implicit learning tasks is unrelated to psychometric intelligence was examined in a sample of 605 German pupils. Performance in artificial grammar learning, process control, and serial learning did not correlate with various measures of intelligence when participants were given standard implicit instructions. Under an explicit rule discovery instruction, however, a significant relationship between performance on the learning tasks and intelligence appeared. This finding provides support for Reber's hypothesis that implicit learning, in contrast to explicit learning, is independent of intelligence, and confirms thereby the distinction between the 2 modes of learning. However, because there were virtually no correlations among the 3 learning tasks, the assumption of a unitary ability of implicit learning was not supported.     

Pollock on token physicalism,agent materialism and strong artificial intelligence

An examination of John Pollock's theory of artificial intelligence and philosophy of mind raises difficulties for his mechanist concept of person. Token physicalism, agent materialism, and strong artificial intelligence are so related that if the first two propositions are not well‐established, then there is no justification for believing that an artificial consciousness can be designed and built. Pollock's arguments are shown to be inconclusive in upholding a functionalist theory of persons as supervenient but purely physical entities. In part this is the result of Pollock's thin definition of the concept of supervenience, according to which any complex supervenes on its proper parts. The limitations of this account are apparent when contrasted with richer conceptions of supervenience, such as Joseph Margolis’. But on Margolis’ theory, the mind and its expressions supervene on or rise above their material embodiments in the sense that they cannot be fully explained in physical terms, which contradicts Pollock's token physicalism and agent materialism. The consequence for Pollock's project to explain the mind as mechanical, and to manufacture artificial persons, is that these systems can at best aspire to impressive innovations in weak artificial intelligence, but realistically cannot aspire to strong or mentalistic artificial intelligence.     

A challenge to Watson

Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same challenge that humans face when they take an IQ test. The challenge has two levels. In the first, programmers could supply data and post hoc organizational algorithms to the computer. In the second, all algorithms would have to be provided before data are supplied and information would have to be self organizing as it is in humans.     

Subjective time perception and behavioral activation system strength predict delay of gratification ability

This study investigated the relationship between subjective time perception and behavioral impulsivity in a healthy, undergraduate population. Data were collected from 62 participants on internal clock speed (ICS, a measure of subjective time perception), behavioral impulsivity, intelligence, and Behavioral Inhibition and Activation Strengths (BIS and BAS). As expected, after controlling for other significant predictors, ICS accounted for a significant amount of variance in behavioral impulsivity. Surprisingly, participants who had slower ICSs were more behaviorally impulsive than participants who had faster ICSs. In addition, and as anticipated, participants who had less accurate ICSs were significantly more impulsive than participants who were more accurate. Last, higher BAS significantly predicted decreased behavioral impulsivity. Results are discussed in terms of current theory relating ICS to impulsivity, and a new theoretical framework is advanced.     

A computational analysis of general intelligence tests for evaluating cognitive development

The progression in several cognitive tests for the same subjects at different ages provides valuable information about their cognitive development. One question that has caught recent interest is whether the same approach can be used to assess the cognitive development of artificial systems. In particular, can we assess whether the ‘fluid’ or ‘crystallised’ intelligence of an artificial cognitive system is changing during its cognitive development as a result of acquiring more concepts? In this paper, we address several IQ tests problems (odd-one-out problems, Raven’s Progressive Matrices and Thurstone’s letter series) with a general learning system that is not particularly designed on purpose to solve intelligence tests. The goal is to better understand the role of the basic cognitive operational constructs (such as identity, difference, order, counting, logic, etc.) that are needed to solve these intelligence test problems and serve as a proof-of-concept for evaluation in other developmental problems. From here, we gain some insights into the characteristics and usefulness of these tests and how careful we need to be when applying human test problems to assess the abilities and cognitive development of robots and other artificial cognitive systems.     

Connectionist models of conditioning: A tutorial

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations.     

Cognitive reserve as a moderator of responsiveness to an online problem-solving intervention for adolescents with complicated mild-to-severe traumatic brain injury

Children and adolescents with traumatic brain injury (TBI) often experience behavior difficulties that may arise from problem-solving deficits and impaired self-regulation. However, little is known about the relationship of neurocognitive ability to post-TBI behavioral recovery. To address this question, we examined whether verbal intelligence, as estimated by Vocabulary scores from the Wechsler Abbreviated Scale of Intelligence, predicted improvements in behavior and executive functioning following a problem-solving intervention for adolescents with TBI. One hundred and thirty-two adolescents with complicated mild-to-severe TBI were randomly assigned to a six-month Web-based problem-solving intervention (CAPS; n = 65) or to an Internet resource comparison (IRC; n = 67) group. Vocabulary moderated the association between treatment group and improvements in metacognitive abilities. Examination of the mean estimates indicated that for those with lower Vocabulary scores, pre-intervention Metacognition Index scores from the Behavior Rating Inventory of Executive Function (BRIEF) did not differ between the groups, but post-intervention scores were significantly lower (more improved) for those in the CAPS group. These findings suggest that low verbal intelligence was associated with greater improvements in executive functioning following the CAPS intervention and that verbal intelligence may have an important role in response to intervention for TBI. Understanding predictors of responsiveness to interventions allows clinicians to tailor treatments to individuals, thus improving efficacy.     

Appearing smart: the impression management of intelligence, person perception accuracy, and behavior in social interaction

Intelligence is an important trait that affects everyday social interaction. The present research utilized the ecological perspective of social perception to investigate the impression management of intelligence and strangers' evaluations of targets' intelligence levels. The ability to effectively portray an impression of intelligence to outside judges as well as interaction partners was appraised and the effect of impression management on the accurate judgment of intelligence was assessed. In addition, targets' behavior was studied in relation to impression management, perceived intelligence, and actual measured intelligence. Impression-managing targets appeared more intelligent to video judges but not to their interaction partner as compared to controls. The intelligence quotient (IQ) of impression-managing targets was more accurately judged than controls' IQ. Impression-managing targets displayed distinct nonverbal behavioral patterns that differed from controls. Looking while speaking was a key behavior: It significantly correlated with IQ, was successfully manipulated by impression-managing targets, and contributed to higher perceived intelligence ratings.     

From teachers’ implicit theories of intelligence to job stress: The mediating role of teachers’ causal attribution of students’ academic achievement

To better understand the cognitive antecedents of teachers’ stress in the school setting, the effects of teachers’ beliefs regarding intelligence and their causal attributions of students’ academic performance on teachers’ job stress were examined in the current study. We recruited 271 teachers who voluntarily filled out an anonymous questionnaire. Findings demonstrated that teachers who endorsed the entity theory of intelligence tended to attribute students’ poor performance to students’ inability but not lack of effort. Results showed a positive relationship between teachers’ fixed view of intelligence and job stress, and this relationship was mediated by teachers’ attributing students’ poor performance to students’ lack of ability, even after controlling for teacher efficacy. We suggest to promote the psychological health of teachers by incorporating intelligence mindset and attribution training programs in preservice teacher education, professional development, and cognitive behavioral stress intervention for in-service teachers.     

Why More Intelligent Individuals Like Classical Music

The origin of values and preferences is an unresolved theoretical problem in social and behavioral sciences. The Savanna‐IQ Interaction Hypothesis, derived from the Savanna Principle and a theory of the evolution of general intelligence, suggests that more intelligent individuals are more likely to acquire and espouse evolutionarily novel values and preferences than less intelligent individuals but that general intelligence has no effect on the acquisition and espousal of evolutionarily familiar values and preferences. Recent work on the evolution of music suggests that music in its evolutionary origin was always vocal and that purely instrumental music is evolutionarily novel. The Savanna‐IQ Interaction Hypothesis would then imply that more intelligent individuals are more likely to prefer purely instrumental music than less intelligent individuals, but general intelligence has no effect on the preference for vocal music. The analyses of American (General Social Surveys) and British (British Cohort Study) data are consistent with this hypothesis. Additional analyses suggest that the effect of intelligence on musical preference is not a function of the cognitive complexity of music. Copyright © 2011 John Wiley & Sons, Ltd.