A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...) We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines. (shrink)

This paper argues in favor of the epistemic properties of inclusiveness in the context of democratic deliberative assemblies and derives the implications of this argument in terms of the epistemically superior mode of selection of representatives. The paper makes the general case that, all other things being equal and under some reasonable assumptions, more is smarter. When applied to deliberative assemblies of representatives, where there is an upper limit to the number of people that can be included in the group, (...) the argument translates into a defense of a specific selection mode of participants: random selection. (shrink)

This article is a synopsis of a triarchic theory of human intelligence. The theory comprises three subtheories: a contextual subtheory, which relates intelligence to the external world of the individual; a componential subtheory, which relates intelligence to the individual's internal world; and a two-facet subtheory, which relates intelligence to both the external and internal worlds. The contextual subtheory defines intelligent behavior in terms of purposive adaptation to, shaping of, and selection of real-world environments relevant to one's life. The normal course (...) of intelligent functioning in the everyday world entails adaptation to the environment; when the environment does not fit one's values, aptitudes, or interests, one may attempt to shape the environment so as to achieve a better person-environment fit; when shaping fails, an attempt may be made to select a new environment that provides a better fit. The two-facet subtheory further constrains this definition by regarding as most relevant to the demonstration of intelligence contextually intelligent behavior that involves either adaptation to novelty, automatization of information processing, or both. Efficacious automatization of processing allows allocation of additional resources to the processing of novelty in the environment; conversely, efficacious adaptation to novelty allows automatization to occur earlier in one's experience with new tasks and situations. The componential subtheory specifies the mental mechanisms responsible for the learning, planning, execution, and evaluation of intelligent behavior. Metacomponents of intelligence control one's information processing and enable one to monitor and later evaluate it; performance components execute the plans constructed by the metacomponents; knowledge-acquisition components selectively encode and combine new information and selectively compare new information to old so as to allow new information to be learned. (shrink)

Edmund Husserl, the founder of phenomenological philosophy, developed the concept of the so-called pure transcendental consciousness. The author of the article asks whether the concept of consciousness understood this way can constitute a model for AI consciousness. It should be remembered that transcendental consciousness is the result of the use of the phenomenological method, the essence of which is referring to experience (“back to things themselves”). Therefore, one can legitimately ask whether the consciousness that AI can achieve can possess the (...) characteristics attributed by Husserl to pure transcendental consciousness. The answer to such questions seems to be negative because AI, as created by humans, can only operate in the field of phenomena. Human intelligence, however, is capable of operating at the ontological level. In the face of difficulties in understanding the phenomenon of consciousness on a scientific basis, the question arises about the possibility of using the phenomenological concept of consciousness developed by Husserl as a starting point in analyzes aimed at answering the question about AI consciousness (The aim of the article is not to discuss in detail the contemporary state of research on consciousness. Therefore, many results currently achieved mainly in the field of neuroscience are omitted. It is just about indicating the possible application of Husserl’s transcendental concept of consciousness in research on AI consciousness). (shrink)

Individual differences in performance on a variety of selection tasks were examined in three studies employing over 800 participants. Nondeontic tasks were solved disproportionately by individuals of higher cognitive ability. In contrast, responses on two deontic tasks that have shown robust performance facilitationthe Drinking-age Problem and the Sears Problem-were unrelated to cognitive ability. Performance on deontic and nondeontic tasks was consistently associated. Individuals in the correct/correct cell of the bivariate performance matrix were over-represented. That is, individuals giving the modal response (...) on a nondeontic task (P and Q) were significantly less likely to give the modal response on a deontic task (P and not-Q) than were individuals who made the non-modal P and not-Q selection on nondeontic problems. The implications of the results are discussed within the heuristic-analytic framework of Evans (1996; Evans & Over, 1996) and the optimal data selection model of Oaksford and Chater (1994). (shrink)

Artificial intelligence algorithms, fueled by continuous technological development and increased computing power, have proven effective across a variety of tasks. Concurrently, quantum computers have shown promise in solving problems beyond the reach of classical computers. These advancements have contributed to a misconception that quantum computers enable hypercomputation, sparking speculation about quantum supremacy leading to an intelligence explosion and the creation of superintelligent agents. We challenge this notion, arguing that current evidence does not support the idea that quantum technologies enable hypercomputation. (...) Fundamental limitations on information storage within finite spaces and the accessibility of information from quantum states constrain quantum computers from surpassing the Turing computing barrier. While quantum technologies may offer exponential speed-ups in specific computing cases, there is insufficient evidence to suggest that focusing solely on quantum-related problems will lead to technological singularity and the emergence of superintelligence. Subsequently, there is no premise suggesting that general intelligence depends on quantum effects or that accelerating existing algorithms through quantum means will replicate true intelligence. We propose that if superintelligence is to be achieved, it will not be solely through quantum technologies. Instead, the attainment of superintelligence remains a conceptual challenge that humanity has yet to overcome, with quantum technologies showing no clear path toward its resolution. (shrink)

Theories of different and independent types of intelligence constitute a Lakatosian research program, as they all claim that human intelligence has a multidimensional structure, consisting of independent cognitive abilities, and that human intelligence is not characterized by any general ability that is of greater practical importance, or that has greater predictive validity, than other, more specialized cognitive abilities. This paper argues that the independent intelligences research program is degenerating, since it has not led to novel, empirically corroborated predictions. However, despite (...) its flaws, the program provides an illustrative example of some of the philosophical problems that inhere in Lakatos’s so-called “methodology”. Indeed, Lakatos’s conceptions of the negative heuristic, the positive heuristic, and the relationship between scientific appraisal and advice are all vulnerable to objections. The upshot is that theories of independent intelligences indeed teach us more about philosophy of science than about the nature of human intelligence. (shrink)

This essay reflects upon certain aspects of Wittgenstein's own practices as a teacher. Doing philosophy always took priority for Wittgenstein, whether this was in oral or written form: it was important to show the deep puzzles in our language (and our culture and thinking) as a step toward dissolving them. In this respect, one can teach only as a guide; it is a matter of showing more than saying. Wittgenstein's approach suggests a model that I will call tacit teaching. Tacit (...) teaching refers to the many forms of informal instruction—some intentional, some unintentional, and some difficult to categorize simply as one or the other—by which skills, capacities, and dispositions are passed along within a domain of practice. Wittgenstein repeatedly uses the language of signposts, of wandering through a city, of being lost and finding one's way, of needing a guide, of learning how to go on by one's self, to refer to the complex web of knowledge and understanding that allows successful autonomous practice in some discipline: most pertinently, in the context of Wittgenstein's own teaching and writing, the discipline of doing philosophy, but with clear reference to teaching and learning in other complex and ill-structured domains as well. (shrink)

The recent proliferation of AI scandals led private and public organisations to implement new ethics guidelines, introduce AI ethics boards, and list ethical principles. Nevertheless, some of these efforts remained a façade not backed by any substantive action. Such behaviour made the public question the legitimacy of the AI industry and prompted scholars to accuse the sector of ethicswashing, machinewashing, and ethics trivialisation—criticisms that spilt over to institutional AI ethics boards. To counter this widespread issue, contributions in the literature have (...) proposed fixes that do not consider its systemic character and are based on a top-down, expert-centric governance. To fill this gap, we propose to make use of qualified informed lotteries: a two-step model that transposes the documented benefits of the ancient practice of sortition into the selection of AI ethics boards’ members and combines them with the advantages of a stakeholder-driven, participative, and deliberative bottom-up process typical of Citizens’ Assemblies. The model permits increasing the public’s legitimacy and participation in the decision-making process and its deliverables, curbing the industry’s over-influence and lobbying, and diminishing the instrumentalisation of ethics boards. We suggest that this sortition-based approach may provide a sound base for both public and private organisations in smart societies for constructing a decentralised, bottom-up, participative digital democracy. (shrink)

One of the most debated questions in psychology and cognitive science is the nature and the functioning of the mental processes involved in deductive reasoning. However, all existing theories refer to a specific deductive domain, like syllogistic, propositional or relational reasoning.Our goal is to unify the main types of deductive reasoning into a single set of basic procedures. In particular, we bring together the microtheories developed from a mental models perspective in a single theory, for which we provide a formal (...) foundation. We validate the theory through a computational model (UNICORE) which allows fine‐grained predictions of subjects' performance in different reasoning domains.The performance of the model is tested against the performance of experimental subjects—as reported in the relevant literature—in the three areas of syllogistic, relational and propositional reasoning. The computational model proves to be a satisfactory artificial subject, reproducing both correct and erroneous performance of the human subjects. Moreover, we introduce a developmental trend in the program, in order to simulate the performance of subjects of different ages, ranging from children (3–6) to adolescents (8–12) to adults (>21). The simulation model performs similarly to the subjects of different ages.Our conclusion is that the validity of the mental model approach is confirmed for the deductive reasoning domain, and that it is possible to devise a unique mechanism able to deal with the specific subareas. The proposed computational model (UNICORE) represents such a unifying structure. (shrink)

This paper uses Pierre Bourdieu’s field theory to develop tools for analyzing interdisciplinary scientific fields. Interdisciplinary fields are scientific spaces where no single form of scientific capital has a monopoly and therefore multiple forms of scientific capital constitute the structures and stakes of scientific competition. Scientists compete to accumulate and define forms of scientific capital and also to set the rates of exchange between them. The paper illustrates this framework by applying it to the interdisciplinary field of behavior genetics. Most (...) behavior geneticists envision their participation in the field as a means to compete for scientific capital in other fields. However, the scientific capital of behavior genetics has different values for scientists attempting to deploy it in different neighboring fields. These values depend on situations in each field and the ways behavior genetics mediates relationships among them. The pattern of relationships of exchange helps explain the social hierarchy and several features of knowledge production within behavior genetics. (shrink)

Social robots are designed to perform intelligent, emotional, and autonomous behavior in order to establish intimate relationships with humans, for instance, in the context of elderly care. However, the imitation of qualities usually assumed to be necessary for human reciprocal interaction may impact our understanding of social interaction. Against this background, we compare the technical operations based on which social robots imitate human-like behavior with the concepts of emotionality, intelligence, and autonomy as usually attached to humans. In doing so, we (...) aim at making a conceptual contribution to the intuition that the technical imitation of emotional, intelligent, and autonomous behavior differs qualitatively from human forms of emotionality, intelligence, and autonomy. We conclude that the increasing tendency of social robots to imitate human characteristics and the thus increased human tendency of anthropomorphizing technical systems put forth new forms of human–machine interactions (HMI) that call for a critical examination. Thus, the emerging forms of interaction may lead, for instance, to false, reinforced, and perplexing assumptions regarding reciprocity. Therefore, studies are needed that critically examine the potential consequences and psychological effects that may be associated with the use of social robots, especially with regard to vulnerable groups such as children or the elderly. (shrink)

This paper is in two parts. Part I outlines three traditional approaches to the teaching of critical thinking: the normative, cognitive psychology, and educational approaches. Each of these approaches is discussed in relation to the influences of various methods of critical thinking instruction. The paper contrasts these approaches with what I call the “visualisation” approach. This approach is explained with reference to computer-aided argument mapping (CAAM) which uses dedicated computer software to represent inferences between premise and conclusions. The paper presents (...) a detailed account of the CAAM methodology, and theoretical justification for its use, illustrating this with the argument mapping software Rationale™. A number of Rationale™ design conventions and logical principles are outlined including the principle of abstraction, the MECE principle, and the “Holding Hands” and “Rabbit Rule” heuristics. Part II of this paper outlines the growing empirical evidence for the effectiveness of CAAM as a method of teaching critical thinking. (shrink)

This paper investigates the multidimensional phenomenon of wisdom in organizations and management as an integral and relational process. In particular, the paper will show how phenomenology can help to render an extended understanding of the "incorporated" dimensions of wisdom situated in organizations and managerial life-world practises. Based on this, an integral (and holonic) pheno-practice of wisdom in organisations will be proposed. Accordingly the interior and exterior dimensions as well as individual and collective spheres of wisdom are assessed together. Furthermore, the (...) interconnected processes of intentional, behavioural, cultural and systemic domains of wisdom can be integrated. Following a processual turn, a dynamic and decentred perspective on wisdom will be developed by which it is interpreted as an emerging and inter-relational event. Finally, theoretical and practical implications and further research on a more integrated understanding of wisdom are discussed. (shrink)

In domains with multiple competing goals, people face a basic challenge: How to make their strategy use flexible enough to deal with shifting circumstances without losing track of their overall objectives. This article examines how young children meet this challenge in one such domain, tic‐tac‐toe. Experiment 1 provides an overviews of development in the area; it indicates that children's tic‐tac‐toe strategies are rule based and that new rules are added one at a time. Experiment 2 demonstrates that even young children (...) flexibly tailor their strategy use to meet shifting circumstances. Experiment 3 indicates that these adaptations are accomplished through a process of goal‐based resource allocation, whereby children focus their cognitive resources on applying rules most consistent with their current primary goal. A computer simulation specifies how this process works and demonstrates its sufficiency for producing behavior much like that of the children. The findings are discussed as part of a broader framework of mechanisms for generating problem‐solving approaches. (shrink)

A close scrutiny of the psychological literature reveals that many psychologists favor a 'segregative' approach to theory development. One theory is pitted against another, and the one that accounts for the data most successfully is deemed the theory of choice. However, an examination of the theoretical debates in which the segregative approach has been pursued reveals a variety of weaknesses to the approach, namely, masking an underlying theoretical indistinguishability of theoretical predictions, causing psychologists to focus unknowingly on different aspects of (...) the same phenomemon, and locking the theorist into a particular way of looking at a phenomemon. Although recent work in the philosophy of science has sought to develop a more satisfactory approach to theory development, this work also suffers from a variety of shortcomings. Work on intentionality and constructionism by philosophers of mind suggests an alternative to the segregative approach to theory development. We call this alternative the 'integrative' approach. In this approach one integrates the best aspects of a set of given theories with one's own ideas regarding the domain under investigation. Instead of emphasising those features that discriminate among theories, this approach seeks to identify those facets of competing theories that can provide a unified explanation of a given problem area. (shrink)

Sources of difficulty in insight problem-solving have been identified, but current theories are less successful at explaining discovery of solution ideas. Here, we explore the role of expertise in promoting insight. In Experiment 1, experienced designers and financiers solved visual and verbal problems. Expertise did not influence solution rates for verbal problems, but designers solved more visual problems than financiers, despite similar incorrect initial attempts. In Experiment 2, experienced and novice designers attempted problems either unconstrained, prevented from drawing, or sitting (...) on their hands to prevent drawing and gesture. Hand and drawing constraints removed the positive benefits of expertise. Experienced designers appear to solve visual problems by using strategies to explore the visuo-spatial environment in search of new representations. The results indicate that expert strategic knowledge can be a source of insight. They also show that strategic transfer of expertise to far domains can be achieved. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 451-466, July 2022.

La creatividad, un constructo que se ha planteado desde distintas perspectivas a lo largo de la historia y son distintos autores los que la definen, la miden y la interpretan. Este artículo quiere estudiar cómo funciona la creatividad en alumnos con altas capacidades. Para ello se aplican dos instrumentos, dos pruebas, que están contrastados, para analizar las dimensiones de la creatividad a una muestra de alumnos de secundaria. Los resultados arrogan diferencias a favor de alumnos con alta capacidad. Las conclusiones (...) son que permite establecer una relación significativa entre la creatividad y los alumnos con alta capacidad. (shrink)

The purpose of this study was to examine the relationship between metacognition as measured in real-life situations and IQ scores as reflected by performance on the Raven Standard Progressive Matrices Scale. It is also intended in this study to report on whether or not there were significant differences in performance on the metacognitive instrument among participants with typical development, deaf and hard-of-hearing, and low-achieving individuals with and without the influence of IQ. Analysis showed significant correlations between IQ, metacognitive test, and (...) metacognitive test scores divided by mean reaction time but not with reaction time itself. Results revealed the influence of IQ on metacognition being greater than the influence of metacognition on IQ. Results showed when controlling for the effect of IQ, differences among the three groups of participants on the metacognitive instrument become non-significant. Implications and suggestions are presented. (shrink)