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.     

Examining differential item functioning due to item difficulty and alternative attractiveness

A method for analyzing test item responses is proposed to examine differential item functioning (DIF) in multiple-choice items through a combination of the usual notion of DIF, for correct/incorrect responses and information about DIF contained in each of the alternatives. The proposed method uses incomplete latent class models to examine whether DIF is caused by the attractiveness of the alternatives, difficulty of the item, or both. DIF with respect to either known or unknown subgroups can be tested by a likelihood ratio test that is asymptotically distributed as a chi-square random variable.     

Subjects' inferential performance and the interaction of data and hypotheses in probabilistic inference tasks

In a recent paper, Knez (1991) showed an interaction of data and hypotheses in probabilistic inference tasks. The results illustrated two, earlier not obtained, significant main effects on subjects' hypothesis sampling , viz. the effect of different forms of data presentation and subjects' execution of cognitive control over their hypothesis pool throughout the series of trials. The present paper followed up these results in that the subjects' hypothesis testing , in Knez (1991) was subjected to an analysis. Hence, to see if the effects mentioned above significantly influenced the subjects' hypothesis testing, as they did for subjects' hypothesis sampling. The results showed a consistency with Knez (1991), i.e. the results emphasize the interaction of data and hypothesis in probabilistic inference tasks, as well as the subjects' execution of cognitive control over their hypothesis pool concerning both the subjects' hypothesis sampling and testing.     

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.     

Statistical consistency and hypothesis testing for nonmetric multidimensional scaling

The properties of nonmetric multidimensional scaling (NMDS) are explored by specifying statistical models, proving statistical consistency, and developing hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. For these models, statistical consistency often depends crucially upon how error enters the model and how data are collected and summarized (e.g., by means, medians, or rank statistics). A maximum likelihood estimator for NMDS is developed, and its relationship to the standard Shepard-Kruskal estimation method is described. This maximum likelihood framework is used to develop a method for testing the overall fit of the model.     

Millon Clinical Multiaxial Inventory (MCMI) computer-generated diagnoses: How do they compare to clinician judgment?

During the past several decades, computers have achieved increasing prominence in psychological assessment procedures. This is particularly true for computer-based test interpretation and diagnosis. This study reports on a study designed to compare the accuracy of computer-based diagnoses with clinician-generated diagnoses. The Millon Clinical Multiaxial Inventory (MCMI) was administered to 151 consecutively admitted inpatients at a large private psychiatric hospital. The computer-generated diagnoses were compared with those generated by admitting psychiatrists. The results indicated that the MCMI diagnostic impressions underestimated the severity of depressive disorders when compared with clinician diagnoses on Axis I. Specifically, clinicians diagnosed major depression much more frequently than did the MCMI. In addition, clinicians diagnosed anxiety disorders much less frequently than did the MCMI.     

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.