100 years ago, the editors of the Journal of Educational Psychology conducted one of the most famous studies of experts' conceptions of human intelligence. Reason enough to prompt the question where we stand today with conceptualizing 'intelligence'. In this paper, I provide a synopsis of the latest research on human intelligence(s). I embrace the notion of intelligence as a non-unitary faculty with pluralistic forms. Even though I do not provide a definition of 'intelligence' (...) of my own, I provide good reasons for this reluctance. Nonetheless, I specify the term as complex, gradual, embedded, multidirectional, and dynamic. Furthermore, I argue for the special status of musical, not linguistic, intelligence. (shrink)

The question 'What is intelligence?' may seem simple to answer, but the study and measurement of human intelligence is one of the most controversial subjects in psychology. For much of its history, the focus has been on differences between people, on what it means for one person to be more intelligent than another, and how such differences might have arisen, obscuring efforts to understand the general nature of intelligence. These are obviously fundamental questions, still widely debated (...) and misunderstood. New definitions of intelligence and new factors affecting intelligence are frequently being described, while psychometric testing is applied in most large industries.IQ and Human Intelligence provides a clear, authoritative overview of the main issues surrounding this fascinating area, including the development of IQ tests, the heritability of intelligence, theories of intelligence, environmental effects on IQ, factor analysis, relationship of cognitive psychology to measuring IQ, and intelligence in the social context. The clear, accessible style and numerous explanatory boxes make this the ideal text for advanced undergraduate and graduate students in psychology. Online Resource CentreThe Online Resource Centre to accompany IQ and Human Intelligence features the following resources:For registered adopters of the text:- Figures from the book, available to downloadFor students:- Hyperlinks to primary literature articles cited in the and 'Further Reading' sections of the book. (shrink)

When it comes to the question of what kind of moral claim an intelligent or autonomous machine might have, one way to answer this is by way of comparison with humans: Is there a fundamental difference between humans and other entities? If so, on what basis, and what are the implications for science and ethics? This question is inherently imprecise, however, because it presupposes that we can readily determine what it means for two types of entities to be sufficiently different—what (...) I will refer to as being “discontinuous”. In this paper, I will sketch a formal characterization of what it means for types of entities to be unique with regard to each other. This expands upon Bruce Mazlish’s initial formulation of what he terms a continuity between humans and machines, Alan Turing’s epistemological approach to the question of machine intelligence, and Sigmund Freud’s notion of scientific revolutions dealing blows to the self-esteem of mankind. I will discuss on what basis we should regard entities as (dis-)continuous, the corresponding moral and scientific implications, as well as an important difference between what I term downgrading and upgrading continuities—a dramatic difference in how two previously discontinuous types of entities might become continuous. All of this will be phrased in terms of which scientific levels of explanation we need to presuppose, in principle or in practice, when we seek to explain a given type of entity. The ultimate purpose is to provide a framework that defines which questions we need to ask if we argue that two types of entities ought (not) to be explained (hence treated) in the same manner, as well as what it takes to reconsider scientific and ethical hierarchies imposed on the natural and artificial world. (shrink)

This article seeks to explain the correspondence between human intelligibility and that of the physical world by synthesizing the contributions of Jean Ladrière. Ladrière shows that the objectification function of formal symbolism in mathematics as an artificial language has operative power acquired through algorithm to represent physical reality. In physical theories, mathematics relates to observations through theoretic and empirical languages mutually interacting in a methodological circle, and nonmathematical anticipatory intention guides mathematical algorithmic exploration. Ladrière reasons that mathematics can make (...) the physical world comprehensible because of the presence of a rational principle in both kinds of intelligibility. (shrink)

As we move towards a world that is using machine learning and nascent artificial intelligence to analyse and, in many ways, guide most aspects of our lives, new forms of heterogeneous collaborative teams that include human/intelligent machine agents will become not just possible, but an inevitable part of our shared world. The conscious participation of the arts in the conversation about, and development and implementation of, these new collaborative possibilities is crucial, as the arts serve as our best (...) lens through which we can explore the full spectrum of potential possibilities and futures. Through the complex relationships formed through heterogeneous human/intelligent agent collaboration, we are given the opportunity to re-examine some of our assumptions and suppositions of teamwork and forms of relating and thinking within a group environment. (shrink)

There are two opposing equally well-argued views on the emergence and development of all things: either the evolution of the world that led to the emergence of life and intelligence is something natural, or everything happened quite by accident and could have been different. It determines the aim and the tasks which are the emergence of intelligence can be considered as a certain stage of such a naturally unfolding evolutionary process, or it is the result of a coincidence. (...) Research methods are complex and is based on philosophicalanthropological and philosophical-cultural analysis of the problems of global evolutionism and the development of human intelligence in their dialectical unity.The principles of systematicity, objectivity, ascent from the abstract to the concrete, etc. are also used to solve specific research tasks. Research results: Analysis of the process of universal evolutionism shows that the general direction of the development of existence is the movement from the appearance of simple objects to the formation of the highest of the material structures known today, which are the bearer of intelligence in its biological forms. The author argues the position that further evolution, with a high probability, will occur as a transition from intelligence on organic carriers - the human mind - to artificial intelligence based on inorganics. Together or separately from the human mind, artificial intelligence has the ability to give a new impetus to the development of earthly civilization, penetration into deep space and the development of its limitless possibilities.Discussion. Opponents of the concept of global evolutionism were limited to the planetary scale and for the most part considered the universe as a whole infinite and stationary, and therefore devoid of history. However, it is more attractive to think that the development of the biosphere embodies a number of trends that affected long before the formation of the Earth and the solar system, and this direction is focused on creating an integrated theory of the past from the Big Bang to the present. Conclusion. The global evolution of all things moves in the direction from inorganics to organics - in the form of life and mind, and then - again to inorganics - in the form of artificial intelligence. There is a kind of denial of denial, the further steps of which, and even more so, the end result, can only be guessed. (shrink)

Given the technical feasibility, not only scientists but also moral philosophers approve of an intervention in the genetic basis of our intellectual dispositions. Among the features not related to illnesses, intelligence seems to be an especially promising candidate for genetic enhancement, for intelligence is valued in every culture. The paper presents some of the arguments for and against genetic enhancement of intelligence. The author analyses what kind of good increased intelligence is: an instrumental good for the (...) wellbeing of mankind, a positional good for a given society or an individual, or something that is appreciated by the individual subject because of the positive experience the subject has by making use of it. Since such experiences are not bad in themselves the means of genetic enhancement have to be assessed and compared with accepted practices like education. The author comes to the conclusion that there are morally significant differences between genetic enhancement and accepted practices to enhance intelligence. (shrink)

In this series of lectures, a distinguished group of international contributors from a variety of disciplines debate the current position of the recent achievements in engineering and computer science. (Technology & Industrial).

A look at the relationship between the cosmos and human beings explores the complexity of the human brain and what constitutes real intelligence and the nature of consciousness.

The study of human intelligence features many points of consensus, but there are also many different perspectives. In this unique book Robert J. Sternberg invites the nineteen most highly cited psychological scientists in the leading textbooks on human intelligence to share their research programs and findings. Each chapter answers a standardized set of questions on the measurement, investigation, and development of intelligence - and the outcome represents a wide range of substantive and methodological emphases including (...) psychometric, cognitive, expertise-based, developmental, neuropsychological, genetic, cultural, systems, and group-difference approaches. This is an exciting and valuable course book for upper-level students to learn from the originators of the key contemporary ideas in intelligence research about how they think about their work and about the field. (shrink)

This article focuses on the interaction between man and machine, AI specifically, to analyse how these systems are slowly taking over roles that hitherto were thought ‘only’ for humans. More recent, as AI has stepped up in ability to learn without supervision, to recognize patterns, and to solve problems, it adopted characteristics like creativity, novelty, intentionality. These events take one to the heart of what it is to be human, and the emerging definitions of self that are increasingly central (...) to post humanist discourses. The discussion in these two threads is in philosophy of AI and is concerned with issues of consciousness, intentionality and creativity. Al as a result of causing a shift in the current anthropocentric perceptions resulted in portrayal of humans as special beings. Secondly, this exploration responds to important questions related to AI application, such as ethical, social, and existential ones. The article emphasizes a necessity to define the role of the advent of AI and its influence on the interaction between people and technology as well as the role of the social individuality in the wake of intelligent machines that mimic thinking and creativity. It seeks to prompt more specific analysis of how or why AI reduces the differences between artificial and human intelligence or increases the prospects for options expanding the notion of consciousness beyond the human-centric one. (shrink)

Why are some people more mentally able than others? In an authoritative, critical and intergrated series of review essays Professor Ian Deary inquires after the cognitive and biological foundations of human mental ability differences. Many accounts of intelligence have examined the structure and number of human mental ability differences and whether they can predict sucess in education,work and social life. Few books have taken psychometric intelligence differences as a starting point and brought together the reductionistic attempts (...) to explain them.New to the highly acclaimed Oxford Psychology Series, Looking Down on Human Intelligence appraises the search for the origins of psychometric intelligence differences in terms of brain function parameters. The book provides an original and thought provoking guide to ancient and modern research on one of the most compelling questions in human psychology. (shrink)

A large number of experimental results clearly indicate that sleep has an important role for human intelligence. Sleep-wake stages and their specific patterns of brain activation and neuromodulation subserve human memory, states of consciousness, and modes of information processing that strongly relate to intelligence. Therefore, human intelligence should be explained in a broader framework than is implicated by neuroimaging data alone.

This paper briefly surveys several prominent modeling approaches to knowledge-based intelligent systems design and, especially, expert systems and the breakthroughs that have most broadened and improved their applications. We argue that the implementation of technology that aims to emulate rudimentary aspects of human intelligence has enhanced KBIS design, but that weaknesses remain that could be addressed with existing research in cognitive science. For example, we propose that systems based on representational plasticity, functional dynamism, domain specificity, creativity, and concept (...) learning, with their theoretical and experimental rigor, can best characterize the problem-solving capabilities of humans and can best overcome five key limitations currently exhibited by knowledge-based intelligent systems. We begin with a brief survey of the relevant work related to KBIS design and then discuss these five shortcomings with new suggestions for how to integrate results from cognitive science to resolve each of them. Our ultimate goal is to increase awareness and direct attention to areas of theoretical and experimental cognitive research that are fundamentally relevant to the goals underlying KBISes. (shrink)

Ethical analyses of biomedical human enhancement often consider the issue of authenticity — to what degree can the accomplishments of those utilizing biomedical enhancements be considered authentic or worthy of praise? As research into Brain-Computer Interface technology progresses, it may soon be feasible to create a BCI device that enhances or augments natural human intelligence through some invasive or noninvasive biomedical means. In this article we will review currently existing BCI technologies and to what extent these can (...) be said to enhance or augment the capabilities of the respective users, describe one hypothetical type of BCI device that could augment or enhance a specific aspect of human knowledge — namely, mathematical ability, and relate these concepts to the active externalism view of the extended mind as espoused by Clark and Chalmers in order to argue that knowledge of mathematics derived from the usage of a BCI and the application thereof constitutes authentic knowledge and achievement. (shrink)

Intelligence is not a property unique to the human brain; rather it represents a spectrum of phenomena. An understanding of the evolution of intelligence makes it clear that the evolution of machine intelligence has no theoretical limits — unlike the evolution of the human brain. Machine intelligence will outpace human intelligence and very likely will do so during the lifetime of our children. The mix of advanced machine intelligence with human (...) individual and communal intelligence will create an evolutionary discontinuity as profound as the origin of life. It will presage the end of the human species as we know it. The question, in the author's view, is not whether this will happen, but when, and what should be our response. (shrink)

A parieto-frontal integration theory (P-FIT) model of human intelligence has been proposed based on a review of neuroimaging literature and lesion studies. The P-FIT model provides an important basis for future research. Future studies involving connectivity analyses and an integrative approach of imaging modalities using the P-FIT model should provide vastly increased understanding of the biological bases of intelligence.

There is little consensus on what artificial intelligence (AI) systems may or may not embrace. Although this may point to multiplicity of interpretations and backgrounds, a lack of conceptual clarity could thwart the development of common ground around the concept among researchers, practitioners and users of AI and pave the way for misinterpretation and abuse of the concept. This article argues that one of the effective ways to delineate the concept of AI is to compare and contrast it with (...) human intelligence. In doing so, the article broaches the unique capabilities of humans and AI in relation to one another (human and machine tacit knowledge), as well as two types of AI systems: one that goes beyond human intelligence and one that is necessarily and inherently tied to it. It finally highlights how humans and AI can augment their capabilities and intelligence through synergistic human–AI interactions (i.e., human-augmented AI and augmented human intelligence), resulting in hybrid intelligence, and concludes with a future-looking research agenda. (shrink)

The evolution of humans required performing increasingly hierarchically complex tasks within multiple domains. Hierarchical complexity increases task by task. Tasks occur within, and differ by, determinable domains, their stages of performance measurable using the Model of Hierarchical Complexity. How well one performs within single and multiple domains is considered to indicate intelligence. Original task-initiation is more difficult than imitational learning and can create new domains. Levels of support reduce task difficulty, increasing performance. Task-performance may be generalized to other domains. (...) Stages of developing tools and empathy are presented to demonstrate domains' roles in the evolution of human intelligence. (shrink)

While new generations of implantable brain computer interface devices are being developed, evidence in the literature about their impact on the patient experience is lagging. In this article, we address this knowledge gap by analysing data from the first-in-human clinical trial to study patients with implanted BCI advisory devices. We explored perceptions of self-change across six patients who volunteered to be implanted with artificially intelligent BCI devices. We used qualitative methodological tools grounded in phenomenology to conduct in-depth, semi-structured interviews. (...) Results show that, on the one hand, BCIs can positively increase a sense of the self and control; on the other hand, they can induce radical distress, feelings of loss of control, and a rupture of patient identity. We conclude by offering suggestions for the proactive creation of preparedness protocols specific to intelligent—predictive and advisory—BCI technologies essential to prevent potential iatrogenic harms. (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)

In Natural-Born Cyborgs, Clark argues that what makes humans so different from other species is our capacity to fully incorporate tools and supporting cultural ...

In the past, work on racial and ethnic variation in brain and behavior was marginalized within genetics. Against the backdrop of genetics’ eugenic legacy, wide consensus held such research to be both ethically problematic and methodologically controversial. But today it is finding new opportunistic venues in a global, transdisciplinary, data‐rich postgenomic research environment in which such a consensus is increasingly strained. The postgenomic sciences display worrisome deficits in their ability to govern and negotiate standards for making postgenomic claims in the (...) transdisciplinary space between human population variation research, studies of intelligence, neuroscience, and evolutionary biology.Today some researchers are pursuing the genomics of intelligence on a newly grand scale. They are sequencing large numbers of whole genomes of people considered highly intelligent (by varying empirical and social measures) in the hope of finding gene variants predictive of intelligence. Troubling and at times outlandish futurist claims accompany this research. Scientists involved in this research have openly discussed the possibility of marketing prenatal tests for intelligence, of genetic engineering or selective embryo implantation to increase the likelihood of a high‐IQ child, and of genotyping children to guide their education. In this permissive and contested environment, what would trustworthy research on the genomics of high intelligence look like? (shrink)

Tejera, strongly influenced by Dewey, operates on the working hypothesis that art is both a kind of experience and a kind of making, and addresses himself to the "inextricably related" problems of the ends and the creation of art. Creativity becomes the key; man is viewed as "the creative animal," and artistic creation is seen as a sort of natural human activity, to be understood in relation to all other human activities. Most traditional problems of aesthetics are taken (...) up at some point, but it is not quite clear how all the parts fit together. The book contains forty-five prints and, considered in terms of its physical format, is something of a work of art in its own right.—A. E. J. (shrink)

Here, I discuss how natural biological evolution might have selected human origin and the psychology of the better mind-brain. However, all humans are closely related; why do we make crimes, war, hate, and jealousy their primary reasons and overcoming methodologies? How can they gain their best happiness? What kind of philosophy apply to annalize this big question and convince humankind to evolve their mind? How we could achieve our optimum potential happiness by developing hidden intelligence to make the (...) world a happier place to live in. (shrink)

The target article by Locke & Bogin (L&B) focuses on the evolution of language as a communicative tool. They neglect, however, that from infancy onwards humans have the ability to go beyond successful behaviour and to reflect upon language (and other domains of knowledge) as a problem space in its own right. This ability is not found in other species and may well be what makes humans unique.

A fundamental task for any prospective cognitive architecture is information control: routing information to the relevant mechanisms to support a variety of tasks. Jerry Fodor has argued that the Massive Modularity Hypothesis cannot account for flexible information control due to its architectural commitments and its reliance on heuristic information processing. I argue instead that the real trouble lies in its commitment to nativism—recent massive modularity models, despite incorporating mechanisms for learning and self-organization, still cannot learn to control information flexibly enough. (...) After defending this position, I close the paper by discussing wider implications for control and cognitive architecture. (shrink)

For a long time, researchers in the fields of psychology and neuroscience have been interested in discovering ways to boost productivity in traditionally "healthy," "clinical," and "military" populations. However, one of the biggest challenges in reaching this objective is developing personalised performance phenotypes that can be used to build interventions that are specifically catered to each individual's needs. Impact: Thanks to AI's recent advancements, we can now create individualised training, preparation, and recovery plans that are tailored to each person's unique (...) cognitive and biological profile. Concurrent AI advancements, especially in the psychological and neurological sciences, have demonstrated the importance of incorporating domain expertise and stakeholder inputs into the development of trustworthy AI. Value: This Patterns themed issue seeks original empirical work, literature reviews, and methodological papers that establish and validate precision artificial intelligence methods for human performance optimization, with a focus on modelling individual differences via state-of-the-art computational methods. (shrink)