Morphing Intelligence: From IQ Measurement to Artificial Brains

The current edifice of our world is built-on the dual doctrine of determinism and the doctrine of change. The paper argues that the foundations of either doctrine are indeed very fragile, nurtured on the facile assumption that 'free-will' and 'self/auto-sustainability' have no bearing on anthropocentric processes, structures and experience. Is mediation of our worldly experience through the tools of determinism, holding captive the free will 'within', an outdated shibboleth? Save but intelligence, free will has few encumbrances in the process of its invocation (and revocation of causality). We will be far removed from this solemn invocation as long as we continue to treat intelligence just as a product of our conscious intellect (including conditioned manifestations of learning) and not as a general phenomenon. The phenomenon of intelligence is stretched over very long periods of time involving systems and environs whose boundaries go beyond the current metaphors of psychology or the deterministic worldview manifest in such clichés as development and change. There is no 'quantum effect' embodying this phenomenon, springing up in the last 5000 years of our so-called present civilization. It is in tandem and conterminous with evolution. For, if it were not, the million-year moving average of average IQ of our species would have still remained well nigh below unity! When Noam Chomsky theorized that the human capacity for learning language as a product of evolution by pointing to the primary importance of biological dispositions; it was a significant blow to the behaviourists that all human behaviours are

Intelligence, 2013

This paper examines the first moments of the emergence of “psychometrics” as a discipline, using a history of the Binet-Simon test (precursor to the Stanford-Binet) to engage the question of how intelligence became a “psychological object.” To begin to answer this, we used a previously-unexamined set of French texts to highlight the negotiations and collaborations that led Alfred Binet (1857-1911) to identify “mental testing” as a research area worth pursuing. This included a long-standing rivalry with Désiré-Magloire Bourneville (1840-1909), who argued for decades that psychiatrists ought to be the professional arbiters of which children would be removed from the standard curriculum and referred to special education classes in asylums. In contrast, Binet sought to keep children in schools and conceived of a way for psychologists to do this. Supported by the Société libre de l’étude psychologique de l’enfant [Free society for the psychological study of the child], and by a number of collaborators and friends, he thus undertook to create a “metric” scale of intelligence—and the associated testing apparatus—to legitimize the role of psychologists in a to-that-point psychiatric domain: identifying and treating “the abnormal.” The result was a change in the earlier law requiring all healthy French children to attend school, between the ages of 6 and 13, to recognize instead that otherwise normal children sometimes need special help: they are “slow” (arriéré), but not “sick.” This conceptualization of intelligence was then carried forward, through the test’s influence on Lewis Terman (1877-1956) and Lightner Witmer (1867-1956), to shape virtually all subsequent thinking about intelligence testing and its role in society. [Open access; feel free to share widely.]

Psychology in Spain, 2000

The book starts with some background on why previous attempts at understanding intelligence and building intelligent machines have failed. Then the core idea of the theory (the memory-prediction framework) is developed. There is an extensive discussion of how the highest level in the brain (the cortex) works; this is the heart of the book since our cortex is the primary region of human intelligence. There is a provocative section on the social and other implications of the theory. The book ends with a discussion of intelligent machineshow we can build them and what the future will be like. Hawkins' basic idea is that the brain is a mechanism to predict the future, specifically, hierarchical regions of the brain predict their near future input sequences. As such, the brain is a feed-forward hierarchical state machine, with features enabling it to learn. The state machine actually controls the behavior of the organism. The machine responds to future events predicted from past data. Neurologically, the focus is on the cortical column. Hawkins places particular emphasis on the role of the interconnections from peer columns, and the activation of columns as a whole. He strongly implies that a column is the cortex's physical representation of a state in a state machine.

Artificial Intelligence: Critical Concepts, 2000

Introduction to Section 1 of Volume 3 of the four-volume reference work, Artificial Intelligence: Critical Concepts. The most recent challenge to symbolic artificial intelligence is from a loose coalition of positions that has much in common with the field of artificial life. Although much of their critiques can be understood without adopting a biological perspective, the inteUectuaJ trend which these independent movements constitute is best grasped when acknowledging a common emphasis on studying the intelligence of living systems. This goes beyond the subsymbolism of neural networks to address the ecological. temporal and phylogenetic aspects of cognition.

Intelligence, 2001

Intelligence, 1979

The issue discussed in this paper is the loss of meaning for the expressionintelligence'. The term taken from everyday language has been applied to various psychological definitions, theories or psychometric tests across a period of time which has contributed to the corrosion in meaning of the original term. Attempts by science to isolate and identify the qualities or attrib- utes of intelligence have altered if not entirely destroyed the meaning of the expression. A brief review of the history of the modern investigation into intelligence is thereby presented.

Instructional Science, 1979

An organismic process-structural approach to the classic and modern issues of intelligence and experience is outlined. A Theory of Constructive Operators (TCO) originally designed to explicate Piaget's metatheoretical notions of stages and of equilibration is presented. The theory describes a psychological organism which is a very active semantic-pragmatic system geared to assimilatory praxis. Its organization is bilevel: a situation-bound level of subjective operators (schemes) and a situation-free level constituted either by silent operators (mental effort, learning operators, field factors, affective factors, etc.) or by basic principles which describe the dynamic articulation of subjective and silent operators (the central articulation is a principle of schematic overdetermination of performance). The presentation emphasizes the TCO's epistemological foundations and Piagetian roots. The rules governing its main constructs are given. The presentation is therefore detailed enough to make possible the theory's use and its evaluation. Some of the theory's constructs as well as the illustration of mathematical models derivable from the theory in order to make quantitative predictions in many different types of tasks are however omitted. Experimental-developmental work supporting the TCO is not presented but reference to relevant papers and unpublished dissertations is provided. Relations of the TCO to some recent information-processing models of artificial intelligence and to task analysis are explained. Five basic aspects or conceptions of intelligence are recognized: genotypic (Hebb's intelligence A), phenotypic (Hebb's intelligence B), psychometric (Veruon's intelligence C), developmental (intelligence D) and computer-simulation (i.e., CS) intelligence. All five are briefly discussed and their relations with the TCO's explication of intelligence are briefly mentioned. In this manner we tacitly suggest how the understanding of these various aspects of the complex notion of intelligence can be advanced by means of the TCO. Detailed discussion of this last issue is however beyond the scope of the paper.

Journal of Intelligence Studies in Business

This paper is a call for a new research agenda for the topic of intelligence studiesas a scientific discipline counterbalancing the present domination of research in the art ofintelligence or intelligence as a practice. I argue that there is a need to move away from a narrowperspective on practice to pursue a broader understanding of intelligence as an organizationaldiscipline with all of its complexities where the subject is seen as more critical and is allowed toreflect on itself as a topic. This path will help intelligence academics connect to theoreticaldevelopments gained elsewhere and move forward, towards establishing more of an intelligencescience. The article is critical of what the author sees as a constructionist line of thinking.Instead the author presents a theory of intelligence as learning how to “muddle through”influenced more by organizational theory. The author also argues for an independent scientificjournal in Intelligence.