ISLAMIC PHILOSOPHY AND ARTIFICIAL INTELLIGENCE: EPISTEMOLOGICAL ARGUMENTS

This essay presents an analysis of different processes of machine learning: supervised, unsupervised, and semisupervised, through the prism of the epistemologies of several prominent Islamic philosophical schools. I discuss the way each school conceptualizes the ontological absolute (immortality, death, afterlife) and the way this shapes their respective epistemologies. I present an analysis of the different machine learning processes through the prism of the epistemological constructs of each of these philosophic traditions. I conclude with the argument that more scholars from the Islamic philosophical tradition should engage in the debates about the development of artificial intelligence and its implications, given that many Muslim countries are among the leaders in this development and its application in everyday life.     

An automated test development of parallel tests from a seed test

Binary programming models are presented to generate parallel tests from an itembank. The parallel tests are created to match item for item an existing seed test and match user supplied taxonomic specifications. The taxonomic specifications may be either obtained from the seed test or from some other user requirement. An algorithm is presented along with computational results to indicate the overall efficiency of the process. Empirical findings based on an itembank for the Arithmetic Reasoning section of the Armed Services Vocational Aptitude Battery are given.The Office of Naval Research, Program in Cognitive Science, N00014-87-C-0696 partially supported the work of Douglas H. Jones. The Rutgers Research Resource Committee of the Graduate School of Management partially supported the work of Douglas H. Jones and Ing-Long Wu. A Thomas and Betts research fellowship partially supported the work of Ing-Long Wu. The Human Resources Laboratory, United States Air Force, partially supported the work of Ronald Armstrong. The authors benefited from conversations with Dr. Wayne Shore, Operational Technologies, San Antonio, Texas. The order of authors' names is alphabetical and denotes equal authorship.     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

A nonparametric approach for assessing latent trait unidimensionality

Assuming a nonparametric family of item response theory models, a theory-based procedure for testing the hypothesis of unidimensionality of the latent space is proposed. The asymptotic distribution of the test statistic is derived assuming unidimensionality, thereby establishing an asymptotically valid statistical test of the unidimensionality of the latent trait. Based upon a new notion of dimensionality, the test is shown to have asymptotic power 1. A 6300 trial Monte Carlo study using published item parameter estimates of widely used standardized tests indicates conservative adherence to the nominal level of significance and statistical power averaging 81 out of 100 rejections for examinee sample sizes and psychological test lengths often incurred in practice.The referees' comments were remarkably detailed and greatly enhanced the writeup and sensitized the author to certain pertinent issues. Discussions with Fritz Drasgow, Lloyd Humphreys, Dennis Jennings, Brian Junker, Robert Linn, Ratna Nandakumar, and Robin Shealy were also very useful.This research was supported by the Office of Naval Research under grant N00014-84-K-0186; NR 150-533, and by the National Science Foundation under grant DMS 85-03321.     

A taxonomy of item response models

A number of models for categorical item response data have been proposed in recent years. The models appear to be quite different. However, they may usefully be organized as members of only three distinct classes, within which the models are distinguished only by assumptions and constraints on their parameters. “Difference models” are appropriate for ordered responses, “divide-by-total” models may be used for either ordered or nominal responses, and “left-side added” models are used for multiple-choice responses with guessing. The details of the taxonomy and the models are described in this paper. The present study was supported in part by two postdoctoral fellowships awarded to Lynne Steinberg: an Educational Testing Service Postdoctoral Fellowship at ETS, Princeton, NJ and an NIMH Individual National Research Service Award at Stanford University, Stanford, CA. Helpful comments by the editor and three anonymous reviewers are gratefully acknowledged.     

Les théories implicites de l’intelligence : une question de perspectives ?

IntroductionImplicit theories of intelligence are beliefs that people form regarding the malleability of intelligence. The so-called “growth” and “fixed” mindsets respectively view intelligence as a characteristic that can or cannot be changed. Psychology, as a science, also offers diverging responses. The developmental and differential traditions in the study of intelligence merely provide different answers because they do not focus on the same sources of variability nor on the same dimensions of intelligence.ObjectivesThe research question that guided the present studies was: Are people's naïve theories influenced by the same factors that drive developmental and differential psychologists to different conclusions?MethodIn Study 1, we first assessed participants’ (n = 509) reference norm orientation (i.e. whether they tend to focus on individual or social comparison), using a task in which they had to predict the school results of an hypothetical child. Then we administered a French version of Dweck's (2007) mindset scale. In study 2, we first asked participants (n = 530) to choose between two definitions of intelligence focusing either on its fluid or crystalized dimensions. Then we administered the French Mindset Scale and asked participants to justify their conclusion.ResultsBoth variables of interest (reference norm orientation and preferred definition of intelligence) had a significant effect on the participant's incremental beliefs.ConclusionThe results of the two studies as well as the qualitative analysis of participants’ arguments suggest that mindsets, like scientific theories, partly stem from the fact that the same question regarding intelligence malleability can be approached with two different perspectives.     

When faces and voices come together: Face width-to-height ratio and voice pitch contribute independently to social perception

Prior research has shown that the face's width-to-height ratio (fWHR) and the voice's pitch influence social perception. Yet, the relative contribution of either cue has been largely unexplored. We examined the simultaneous effects of fWHR and pitch on social evaluations. Experiment 1 (N = 102) tested how such cues shaped global impressions. Experiment 2 (N = 121) tested fWHR and pitch's effect on behavioural affiliative intentions, framing social interaction as a physical or an intellectual competition. Experiment 3 (N = 57) assessed whether variations in fWHR and pitch could influence trait attribution (i.e., physical formidability and intelligence). Individuals with large faces or low-pitched voices elicited negative impressions, positive behavioural intentions in a physical competition, and the attribution of stronger formidability but lower intelligence. Across the studies, cues exerted independent effects. The implications of these findings for research on cross-modal social perception are discussed.     

SPIRITUAL INTELLIGENCE: PROCESSING DIFFERENT INFORMATION OR PROCESSING INFORMATION DIFFERENTLY?

This article introduces the concept of spiritual intelligence in terms of a natural human ability to take a different perspective on reality rather than an extraordinary ability to engage with a different/supernatural reality. From a cognitive perspective, spiritual intelligence entails a re-balancing of the two main modes of human cognition, with a prioritization of the holistic-intuitive mind over the conceptual one. From the psychological and phenomenological perspectives, it involves a different kind of engagement with information: slower, more participatory, less objectifying, and not focused entirely on problem solving. The article ends with a reflection on the theological implications of the proposed model and how such an account of spiritual intelligence as knowing differently might relate to theological anthropology and the theology of the spirit and the spiritual.