General Intelligence

The notion of intelligence is relevant to several fields of research, including cognitive and comparative psychology, neuroscience, artificial intelligence, and philosophy, among others. However, there is little agreement within and across these fields on how to characterise and explain intelligence. I put forward a behavioural, operational characterisation of intelligence that can play an integrative role in the sciences of intelligence, as well as preserve the distinctive explanatory value of the notion, setting it apart from the related concepts of cognition and (...) rationality. Finally, I examine a popular hypothesis about the underpinnings of intelligence: the capacity to manipulate internal representations of the environment. I argue that the hypothesis needs refinement, and that so refined, it applies only to some forms of intelligence. (shrink)

ENG: We all have our own ideas about what it is like to be intelligent. Indeed, even the experts disagree on this topic. This has generated diverse theories on the nature of intelligence and its genetic and environmental bases. Many scientific and philosophical questions thus remain unaddressed: is it possible to characterize intelligence in scientific terms? What do IQ tests measure? How is intelligence influenced by genetics, epigenetics, and the environment? What are the ethical and social implications of the research (...) on this topic? This book aims to provide the readers with the conceptual resources to critically analyze scientific findings and orientate themselves in this multi-faceted debate across biology, psychology, neuroscience, philosophy, and anthropology. -/- ITA: Ognuno di noi ha una propria idea di cosa significhi essere intelligenti, tanto che anche gli scienziati esperti in materia hanno opinioni differenti al riguardo. Ciò ha contribuito a generare teorie contrastanti sulla natura dell’intelligenza e su quali siano le sue basi genetiche e ambientali. Non è un caso, dunque, che diverse domande scientifiche e filosofiche restino ancora aperte: è possibile caratterizzare scientificamente l’intelligenza? Cosa misurano i test del QI? In che modo genetica, epigenetica e ambiente influenzano l’intelligenza? Quali sono le implicazioni etiche e sociali della ricerca sull’argomento? Oltre ad analizzare questi problemi, il testo intende fornire gli strumenti concettuali necessari per leggere criticamente i dati scientifici e orientarsi in uno sfaccettato e affascinante dibattito a cavallo tra biologia, psicologia, neuroscienze, filosofia e antropologia. (shrink)

ITA: In che modo il nostro cervello è in grado di produrre quel tipo di comportamento flessibile e volto a specifici scopi che chiamiamo intelligenza? Le differenze cognitive tra individui sono dovute a una varietà di abilità mentali o a una sola? Questo articolo discute gli elementi centrali della teoria dell’intelligenza generale proposta da John Duncan nel volume How intelligence happens, tradotto recentemente in italiano e corredato da un capitolo conclusivo inedito. Prendendo le mosse dalla ricerca di Charles Spearman sull’intelligenza (...) generale e sui test d’intelligenza, Duncan caratterizza l’intelligenza nei termini di integrazione e controllo cognitivo. I dati neuroscientifici raccolti da Duncan suggeriscono che questi aspetti chiave del comportamento intelligente siano realizzati da un circuito cerebrale, chiamato multiple-demand system, in grado di scomporre problemi complessi in sotto-problemi più semplici e integrare informazioni da varie aree del cervello. ENG: How does our brain generate that sort of flexible and goal-directed behaviour that we call intelligence? Are individual differences in intelligence due to a variety of cognitive abilities or do they depend on one single mental ability? In this commentary, I revise and critically assess the key elements of John Duncan’s theory of general intelligence presented in the popular-science book How intelligence happens, recently translated into Italian and edited by F. Pavani, with a new final chapter. Starting from Charles Spearman’s research on a general intelligence factor and psychometric tests, Duncan advances a theory that characterises intelligence in terms of integration and cognitive control. Neuropsychological and neuroimaging data suggest that such key aspects of intelligent behaviour are realised by a brain network called a multiple-demand system, which is capable of decomposing complex problems into simpler sub-problems and then integrating information from different brain areas. (shrink)

Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...) the relationship between its two targets and, thereby, helps demystify the relationship between folk and scientific psychology. (shrink)

In 1976, the Genetics Society of America published a document entitled “Resolution of Genetics, Race, and Intelligence.” This document laid out the Society’s position in the IQ controversy, particularly that on scientific and ethical questions involving the genetics of intellectual differences between human populations. Since the GSA was the largest scientific society of geneticists in the world, many expected the document to be of central importance in settling the controversy. Unfortunately, the Resolution had surprisingly little influence on the discussion. In (...) 1979, William Provine analyzed the possible factors that decreased the impact of the Resolution, among them scientists’ limited understanding of the relationship between science and ethics. Through the analysis of unpublished versions of the Resolution and exchanges between GSA members, I will suggest that the limited impact of the statement likely depended on a shift in the aims of the GSA due to the controversies that surrounded the preparation of the document. Indeed, the demands of the membership made it progressively more impartial in both scientific and political terms, decreasing its potential significance for a wider audience. Notably, the troubled history of the Resolution raises the question of what can make effective or ineffective the communication between scientists and the public—a question with resonance in past and present discussions on topics of social importance. (shrink)

The model of human intelligence that is most widely adopted derives from psychometrics and behavioral genetics. This standard approach conceives intelligence as a general cognitive ability that is genetically highly heritable and describable using quantitative traits analysis. The paper analyzes intelligence within the debate on natural kinds and contends that the general intelligence conceptualization does not carve psychological nature at its joints. Moreover, I argue that this model assumes an essentialist perspective. As an alternative, I consider an HPC theory of (...) intelligence and evaluate how it deals with essentialism and with intuitions coming from cognitive science. Finally, I highlight some concerns about the HPC model as well, and conclude by suggesting that it is unnecessary to treat intelligence as a kind in any sense. (shrink)

Although brain size and the concept of intelligence have been extensively used in comparative neuroscience to study cognition and its evolution, such coarse-grained traits may not be informative enough about important aspects of neurocognitive systems. By taking into account the different evolutionary trajectories and the selection pressures on neurophysiology across species, Logan and colleagues suggest that the cognitive abilities of an organism should be investigated by considering the fine-grained and species-specific phenotypic traits that characterize it. In such a way, we (...) would avoid adopting human-oriented, coarse-grained traits, typical of the standard approach in cognitive neuroscience. We argue that this standard approach can fail in some cases, but can, however, work in others, by discussing two major topics in contemporary neuroscience as examples: general intelligence and brain asymmetries. (shrink)

In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and b) what is the relationship, if (...) any, between the concept of general intelligence adopted by AGI and that adopted by psychometricians, i.e., the g factor? In this paper, we address these ques-tions and invite researchers in AI to open a dis-cussion on the theoretical conceptions and practi-cal purposes of the AGI approach. (shrink)

This chapter has two main goals: to update philosophers on the state of the art in the scientific psychology of intelligence, and to explain and evaluate challenges to the measurement invariance of intelligence tests. First, we provide a brief history of the scientific psychology of intelligence. Next, we discuss the metaphysics of intelligence in light of scientific studies in psychology and neuroimaging. Finally, we turn to recent skeptical developments related to measurement invariance. These have largely focused on attributability: Where do (...) the mechanisms and dispositions that explain people’s performance on tests of intelligence inhere – in the agent, in the local testing environment, in the culture, or in the interactions among these? After explaining what measurement invariance is in the context of intelligence testing, we explore the phenomenon of stereotype threat as a challenge to measurement invariance, as well as more recent work on overcoming or buffering against stereotype threat. (shrink)