Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should (...) be interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

Recent times have seen increasing interest in conversational assistants (e.g., Amazon Alexa) designed to help users in their daily tasks. In military settings, it is critical to design assistants that are, simultaneously, helpful and able to minimize the user’s cognitive load. Here we show that embodiment plays a key role in achieving that goal. We present an experiment where participants engaged in the desert survival task in augmented reality. Participants were paired with a voice assistant, an embodied assistant, or (...) no assistant. The assistants made suggestions verbally throughout the task, whereas the embodied assistant further used gestures and emotion to communicate with the user. Our results indicate that both assistant conditions led to higher performance over the no assistant condition, but the embodied assistant achieved this with less cognitive burden on the decision maker than the non-embodied assistant. We discuss implications for the design of intelligent collaborative systems for the warfighter. (shrink)

The use of forward models is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model account, forward models lie at the heart of all forms of perception and action. We compare (...) these neighbouring but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches. (shrink)

Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of (...) avoiding unwanted behaviors of intelligent agents, and at the same time specifying what we want such systems to do. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop our moral preferences simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic cognitive approach proposed by Dreyfus, whose phenomenological philosophy defends that the human experience of being-in-the-world cannot be represented by the symbolic or connectionist cognitive methods. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI. (shrink)

Although Darwin insisted that human intelligence could be fully explained by the theory of evolution, the codiscoverer of natural selection, Alfred Russel Wallace, claimed that abstract intelligence was of no use to ancestral humans and could only be explained by intelligent design. Wallace’s apparent paradox can be dissolved with two hypotheses about human cognition. One is that intelligence is an adaptation to a knowledge-using, socially interdependent lifestyle, the “cognitive niche.” This embraces the ability to overcome the (...) evolutionary fixed defenses of plants and animals by applications of reasoning, including weapons, traps, coordinated driving of game, and detoxification of plants. Such reasoning exploits intuitive theories about different aspects of the world, such as objects, forces, paths, places, states, substances, and other people’s beliefs and desires. The theory explains many zoologically unusual traits in Homo sapiens, including our complex toolkit, wide range of habitats and diets, extended childhoods and long lives, hypersociality, complex mating, division into cultures, and language (which multiplies the benefit of knowledge because know-how is useful not only for its practical benefits but as a trade good with others, enhancing the evolution.. (shrink)

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition (...) in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition. (shrink)

As artificial intelligence (AI) thrives and propagates through modern life, a key question to ask is how to include humans in future AI? Despite human involvement at every stage of the production process from conception and design through to implementation, modern AI is still often criticized for its “black box” characteristics. Sometimes, we do not know what really goes on inside or how and why certain conclusions are met. Future AI will face many dilemmas and ethical issues unforeseen by (...) their creators beyond those commonly discussed (e.g., trolley problems and variants of it) and to which solutions cannot be hard-coded and are often still up for debate. Given the sensitivity of such social and ethical dilemmas and the implications of these for human society at large, when and if our AI make the “wrong” choice we need to understand how they got there in order to make corrections and prevent recurrences. This is particularly true in situations where human livelihoods are at stake (e.g., health, well-being, finance, law) or when major individual or household decisions are taken. Doing so requires opening up the “black box” of AI; especially as they act, interact, and adapt in a human world and how they interact with other AI in this world. In this article, we argue for the application of cognitive architectures for ethical AI. In particular, for their potential contributions to AI transparency, explainability, and accountability. We need to understand how our AI get to the solutions they do, and we should seek to do this on a deeper level in terms of the machine-equivalents of motivations, attitudes, values, and so on. The path to future AI is long and winding but it could arrive faster than we think. In order to harness the positive potential outcomes of AI for humans and society (and avoid the negatives), we need to understand AI more fully in the first place and we expect this will simultaneously contribute towards greater understanding of their human counterparts also. (shrink)

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human–machine interaction, group behavior, and community organization, the individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping (...) society tackle major real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other. (shrink)

The general idea that we have of artificial intelligence (AI) consists of the belief that machines will be able to develop conscious thoughts such as those possessed by human beings, and, as computing advances, such thinking will also advance until intelligence to surpass the human being, with which the advancement of AI represents ethical risks in the future. In reality, such a belief hides a cognitive assumption, which assumes that computational engineering explains human intelligence through the (...) mind-computer metaphor. According to this assumption, technology explains cognition, and philosophy, through ethics, reflects on the impact of said technology. However, in this article, I contradict such an assumption and defend that the philosophy in AI is not reduced to the ethics that is present after the use and impact of AI in the world. I intend to expose that a good ethics of AI is the one that reflects on the appropriate risks facing AI, and for this, philosophy, beforehand, must make a cognitive analysis about the possibilities that computing has to create intelligent machines, namely, whether or not the mindcomputer metaphor makes sense. My thesis consists in defending that the philosophical analysis about AI must be carried out both on a cognitive level and on an ethical level, but that the philosophical priority in the cognitive analysis over the ethical priority, since the ethical risks of AI depend of the possibilities of technology, and only the cognitive approach can account for this. (shrink)

The scientific field of Artificial Intelligence (AI) began in the 1950s but the concept of artificial intelligence, the idea of something with mind-like attributes, predates it by centuries. This historically rich concept has served as a blueprint for the research into intelligent machines. But it also has staggering implications for our notions of who we are: our psychology, biology, philosophy, technology and society. This reference work provides scholars in both the humanities and the sciences with the material essential (...) for charting the development of this concept. The set brings together; * primary texts from antiquity to the present, including the crucial foundational texts which defined the field of AI * historical accounts, including both comprehensive overviews and detailed snapshots of key periods * secondary material discussing the intellectual issues and implications which place the concept in a wider context. (shrink)

Neuroscientists have formulated the model of emotional intelligence based on brain imaging findings of individual differences in EI. The main objective of our study was to operationalize the advantage of high EI individuals in emotional information processing and regulation both at behavioral and neural levels of investigation. We used a self-report measure and a cognitive reappraisal task to demonstrate the role of EI in emotional perception and regulation. Participants saw pictures with negative or neutral captions and shifted from (...) negative context to neutral while we registered brain activation. Behavioral results showed that higher EI participants reported more unpleasant emotions. The Utilization of emotions scores negatively correlated with the valence ratings and the subjective difficulty of reappraisal. In the negative condition, we found activation in hippocampus, parahippocampal gyrus, cingulate cortex, insula and superior temporal lobe. In the neutral context, we found elevated activation in vision-related areas and HC. During reappraisal condition, we found activation in the medial frontal gyrus, temporal areas, vision-related regions and in cingulate gyrus. We conclude that higher EI is associated with intensive affective experiences even if emotions are unpleasant. Strong skills in utilizing emotions enable one not to repress negative feelings but to use them as source of information. High EI individuals use effective cognitive processes such as directing attention to relevant details; have advantages in allocation of cognitive resources, in conceptualization of emotional scenes and in building emotional memories; they use visual cues, imagination and executive functions to regulate negative emotions effectively. (shrink)

Wagman examines the emulation of human cognition by artificial intelligence systems. The book provides detailed examples of artificial intelligence programs (such as the FERMI System and KEKADA program) accomplishing highly intellectual tasks.

For all of recorded history prior to the second half of the twentieth century, there has been but one realm in which the cognitive processes of reasoning and problem solving, learning and discovery, language and mathematics took place. The realm of human intellect no longer has an exclusive claim on these cognitive processes--artificial intelligence represents a parallel claim. Wagman compares the two realms, focusing on each of the major components of cognition: logic, reasoning, problem-solving, language, memory, learning, (...) and discovery. He identifies consonant and disparate modes of cognition, and develops a general theory of human and artificial intelligence. (shrink)

The World Wide Web (Web) provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the advent of the Social Web has transformed our understanding of the Web. In addition to viewing the Web as a form of information repository, we are now able to view the Web (...) in more social terms. In particular, it has become possible to see the Web as providing access to the human social environment. This is important, because issues of social embedding and social interaction have been seen to contribute to the emergence of human cognitive capabilities. The ability of the Web to provide access to the human social environment thus raises an important question: Can humanity play a productive role in the emergence of advanced forms of machine intelligence by virtue of their interactions and engagements with the online realm? The present paper attempts to show why this question is worth asking. It also attempts to highlight some of the ways in which Web-based forms of contact with the human social environment may be relevant to research into machine intelligence. (shrink)

The paper argues in favour of a direct realist reading of Aquinas’s theory of intelligible species, in opposition to the recent representationalist challenges. In order to secure the direct realist reading, the paper follows three steps: a short description of Aquinas’s process of cognition, a survey of the direct realist arguments and the analysis of the representationalist interpretation. The final step consists of investigating the representationalist reading as it is suggested by two scholars, Claude Panaccio in Aquinas on Intellectual Representation (...) and Robert Pasnau in Theories of Cognition in the Latter Middle Ages. Thus, the paper can be construed as a reply to these two authors, due to the thorough attention paid to their argumentative trails. With regard to Panaccio’s reading the paper focuses on the identity between the intelligible species and the essence of the extra-mental object and argues that Panaccio understands identity in a very narrow sense. Concerning Pasnau’s line of reasoning the focus is on the primum cognitum status of the intelligible species, and the main argument is that intelligible species is understood by Aquinas as the quo and not the quod of cognition. As the paper shows, neither one, nor the other interpretation poses a threat to the direct realist reading of Aquinas’s intelligible species. (shrink)

Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication to computer-mediated communication online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is (...) added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed—digital—organizations should align the individual’s cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers. (shrink)

Some have claimed that since machines lack emotional “qualia”, or conscious experiences of emotion, machine intelligence will fall short of human intelligence. I examine this objection, ultimately finding it unpersuasive. I first discuss recent work on emotion that suggests that emotion plays various roles in cognition. I then raise the following question: are phenomenal experiences of emotion an essential or necessary component of the performance of these cognitive abilities? I then sharpen the question by distinguishing between four (...) possible positions one might take. I reject one of these four positions largely on empirical grounds. But the remaining three positions all suggest that even if emotional qualia play an important role in human cognition, emotional qualia are not essential to the performance of these cognitive abilities in principle, so, e.g., a machine that lacks emotional qualia might still be able to perform them. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense categorization (...) and knowledge invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

First published in 1998. Routledge is an imprint of Taylor & Francis, an informa company.

Imagine you are the CEO of a hospital [. . .]. Decisions are constantly being made in your organization about how to spend the organization's money. The amount of money available to spend is never adequate to pay for everything you wish you could spend it on, therefore you must set spending priorities. There are two questions you need to be able to answer . . . How should we set priorities in this organization? How do we know when we (...) are doing it well? When people seek to achieve good public policy, the result will tend to be good public policy. In a collective choice process, public‐spirited individual participants produce good public policy by deliberating—talking with each other, listening to each other's arguments, and being willing to learn and change their minds based on such dialogue. –Steven Kelman (1992: 181) Public policy scholars agree that those persons (or agencies) vested with the authority to establish health care priorities should elicit public input before making rationing decisions. The two most common approaches are (i) consultation and (ii) deliberation. Though deliberation has obvious advantages over consultation, it falters in the face of the objection that ordinary citizens lack the cognitive resources for the extended, rigorous inquiry required of them in undertaking the priority‐setting task. To overcome this objection, I propose that deliberative forums for health care rationing should be designed so that they imitate the natural pattern of human experience. The experience of deliberation should encompass both prolonged periods of less‐demanding cognitive activity, in which citizens passively receive information, and briefer periods of more‐demanding cognitive activity, in which they engage in active problem‐solving. In arguing for this thesis, I rely on two theoretical sources and one practical case study, in the following order: (i) John Dewey's metaphysics of experience, (ii) cognitive science research on schemas and frames, and (iii) the Health Care Council in São Paulo, Brazil. (shrink)

Proceedings of the Workshop on AI and Cognition.

A scholarly examination of the centrality of the mind-body problem within and across the science of cognition--from philosophy to psychology to artificial intelligence to neural science. Conceptions of the mind-body problem range from the heritage of Cartesianism to the identification of the circumscribed brain structures responsible for domain specific cognitive mechanisms. Neither narrowly technical nor philosophically vague, this is a structured and detailed account of advancing intellectual developments in theory, research, and knowledge illumined by the conceptual vicissitudes of (...) the mind-body problem. This unique treatment will be of special interest to creative scholars in the disciplines of he sciences of cognition. (shrink)

This target article considers the relation of fluid cognitive functioning to general intelligence. A neurobiological model differentiating working memory/executive function cognitive processes of the prefrontal cortex from aspects of psychometrically defined general intelligence is presented. Work examining the rise in mean intelligence-test performance between normative cohorts, the neuropsychology and neuroscience of cognitive function in typically and atypically developing human populations, and stress, brain development, and corticolimbic connectivity in human and nonhuman animal models is reviewed (...) and found to provide evidence of mechanisms through which early experience affects the development of an aspect of cognition closely related to, but distinct from, general intelligence. Particular emphasis is placed on the role of emotion in fluid cognition and on research indicating fluid cognitive deficits associated with early hippocampal pathology and with dysregulation of the hypothalamic-pituitary-adrenal axis stress-response system. Findings are seen to be consistent with the idea of an independent fluid cognitive construct and to assist with the interpretation of findings from the study of early compensatory education for children facing psychosocial adversity and from behavior genetic research on intelligence. It is concluded that ongoing development of neurobiologically grounded measures of fluid cognitive skills appropriate for young children will play a key role in understanding early mental development and the adaptive success to which it is related, particularly for young children facing social and economic disadvantage. Specifically, in the evaluation of the efficacy of compensatory education efforts such as Head Start and the readiness for school of children from diverse backgrounds, it is important to distinguish fluid cognition from psychometrically defined general intelligence. (Published Online April 5 2006) Key Words: cognition; cognition-emotion reciprocity; developmental disorders; emotion; fluid cognition; Flynn effect; general intelligence; limbic system; neuroscience; phenylketonuria; prefrontal cortex; psychometrics; schizophrenia. (shrink)

A new theory of time; Events and observability; Multimedial units and language: verbal and nonverbal communication; Judgment formation and problems of description; Memory and perception: some new models; Stochastic models of expertise formation, opinion change, and learning.

Resumen: El presente trabajo analiza si los Sistemas de apoyo a la decisión (DSSs) y otros asistentes para su uso, como las Reflection machines o los Personal Assistants that Learn (PAL), contribuyen de hecho a una mejora cognitiva, como habitualmente se tiende a asumir. Es decir, se examina si su potencial para expandir e impulsar la acción de las facultades cognoscitivas se ve efectivamente actualizado y, en consecuencia, si sirven para reafirmar el sentido capacitante de la IA y la extensión (...) de la agencia del sujeto a través de ella. Para ello, se pone de manifiesto que el diseño y aplicación de estos sistemas están mediados por una comprensión del conocimiento que actúa a modo de marco que limita sus posibilidades de mejorar las capacidades cognoscitivas humanas. Se analizan las condiciones en que la mejora cognitiva es posible a través del uso de estos sistemas, que remiten a una aproximación integradora que no tiene en cuenta solo el factor tecnológico, sino que repara en cómo, en su uso, intervienen factores gnoseológicos, así como psicológicos y sociológicos, que median en la capacidad efectiva de estos sistemas de ampliar las facultades de conocimiento, y de los que las tecnologías se sirven para ejercer su influencia. Abstract: The present article questions whether Decision Support Systems (DSSs) and other assistants for their use, such as Reflection machines or Personal Assistants that Learn (PAL), do in fact contribute to cognitive enhancement, as it is usually taken for granted. In other words, it is analysed whether their potential to effectively expand or augment cognitive capacities is actualised and, therefore, if the capabilities and the agency of the person appear in fact extended through artificial intelligence. For that purpose, it is highlighted that the design and implementation of AI systems are dependent on a certain understanding of human knowledge that acts as a framework that limits their actual capacity to enhance the cognitive faculties of the mind. The conditions under which this cognitive enhancement is possible through these systems are analysed and require an integrative approach that not only takes technology into account but realises that, in its use, gnoseological, as well as psychological and sociological factors are involved and mediate in the actual capacity of these systems to extend cognitive functions. These factors are also crucial for these technologies to exert their influence. (shrink)

Much of our everyday, embodied action comes in the form of smooth coping. Smooth coping is skillful action that has become habituated and ingrained, generally placing less stress on cognitive load than considered and deliberative thought and action. When performed with skill and expertise, walking, driving, skiing, musical performances, and short-order cooking are all examples of the phenomenon. Smooth coping is characterized by its rapidity and relative lack of reflection, both being hallmarks of automatization. Deliberative and reflective actions provide (...) the contrast case. In Dreyfus’ classic view, smooth coping is “mindless” absorption into action, being in the flow, and any reflective thought will only interrupt this flow. Building on the pragmatist account of Dewey, others, such as Sutton, Montero, and Gallagher, insist on the intelligent flexibility built into smooth coping, suggesting that it is not equivalent to automatization. We seek to answer two complementary challenges in this article. First, how might we model smooth coping in autonomous agents at fine granularity? Second, we use this model of smooth coping to show how we might implement smooth coping in artificial intelligent agents. We develop a conceptual model of smooth coping in LIDA. LIDA is an embodied cognitive architecture implementing the global workspace theory of consciousness, among other psychological theories. LIDA’s implementation of consciousness enables us to account for the phenomenology of smooth coping, something that few cognitive architectures would be able to do. Through the fine granular analysis of LIDA, we argue that smooth coping is a sequence of automatized actions intermittently interspersed with consciously mediated action selection, supplemented by dorsal stream processes. In other words, non-conscious, automatized actions often require occasional bursts of conscious cognition to achieve the skillful and flexible adjustments of smooth coping. In addition, never-conscious dorsal stream information and associated sensorimotor processes provide further online adjustments during smooth coping. To achieve smooth coping in LIDA we introduce a new module to the LIDA cognitive architecture the Automatized Action Selection sub-module. Our complex model of smooth coping borrows notions of “embodied intelligence” from enactivism and augments these by allowing representations and more detailed mechanisms of conscious control. We explore several extended examples of smooth coping, starting from basic activities like walking and scaling up to more complex tasks like driving and short-order cooking. (shrink)

The Internet is an important focus of attention for the philosophy of mind and cognitive science communities. This is partly because the Internet serves as an important part of the material environment in which a broad array of human cognitive and epistemic activities are situated. The Internet can thus be seen as an important part of the ‘cognitive ecology’ that helps to shape, support and realize aspects of human cognizing. Much of the previous philosophical work in this (...) area has sought to analyze the cognitive significance of the Internet from the perspective of human cognition. There has, as such, been little effort to assess the cognitive significance of the Internet from the perspective of ‘machine cognition’. This is unfortunate, because the Internet is likely to exert a significant influence on the shape of machine intelligence. The present paper attempts to evaluate the extent to which the Internet serves as a form of cognitive ecology for synthetic forms of intelligence. In particular, the phenomenon of Internet-situated machine intelligence is analyzed from the perspective of a number of approaches that are typically subsumed under the heading of situated cognition. These include extended, embedded, scaffolded and embodied approaches to cognition. For each of these approaches, the Internet is shown to be of potential relevance to the development and operation of machine-based cognitive capabilities. Such insights help us to appreciate the role of the Internet in advancing the current state-of-the-art in machine intelligence. (shrink)

One of the greatest dramatists of all time, Shakespeare, recognized that dramatic action was not limited to the stage. Now, in Drama and Intelligence, a work firmly rooted in developmental drama, Richard Courtney is the first to examine dramatic action as an intellectual and cognitive activity. Courtney explores the nature of those experiences we live "through" and which involve us in what is termed "as if" thinking and action.

There exists a significant disparity within society between individuals in terms of intelligence. While intelligence varies naturally throughout society, the extent to which this impacts on the life opportunities it affords to each individual is greatly undervalued. Intelligence appears to have a prominent effect over a broad range of social and economic life outcomes. Many key determinants of well-being correlate highly with the results of IQ tests, and other measures of intelligence, and an IQ of 75 (...) is generally accepted as the most important threshold in modern life. The ability to enhance our cognitive capacities offers an exciting opportunity to correct disabling natural variation and inequality in intelligence. Pharmaceutical cognitive enhancers, such as modafinil and methylphenidate, have been shown to have the capacity to enhance cognition in normal, healthy individuals. Perhaps of most relevance is the presence of an ‘inverted U effect’ for most pharmaceutical cognitive enhancers, whereby the degree of enhancement increases as intelligence levels deviate further below the mean. Although enhancement, including cognitive enhancement, has been much debated recently, we argue that there are egalitarian reasons to enhance individuals with low but normal intelligence. Under egalitarianism, cognitive enhancement has the potential to reduce opportunity inequality and contribute to relative income and welfare equality in the lower, normal intelligence subgroup. Cognitive enhancement use is justifiable under prioritarianism through various means of distribution; selective access to the lower, normal intelligence subgroup, universal access, or paradoxically through access primarily to the average and above average intelligence subgroups. Similarly, an aggregate increase in social well-being is achieved through similar means of distribution under utilitarianism. In addition, the use of cognitive enhancement within the lower, normal intelligence subgroup negates, or at the very least minimises, several common objections to cognitive enhancement. Subsequently, this paper demonstrates that there is a compelling case for cognitive enhancement use in individuals with lower, normal intelligence. (shrink)

This paper presents work in progress on artificial intelligence in medicine (AIM) within the larger context of cognitive science. It introduces and develops the notion ofemergence both as an inevitable evolution of artificial intelligence towards machine learning programs and as the result of a synergistic co-operation between the physician and the computer. From this perspective, the emergence of knowledge takes placein fine in the expert's mind and is enhanced both by computerised strategies of induction and deduction, and (...) by software abilities to dialogue, co-operate and function as a cognitive extension of the physician's intellectual capabilities. The proposed methodology gives the expert a prominent role which consists, first, of faithfully enunciating the descriptive features of his medical knowledge, thus giving the computer a precise description of his own perception of basic medicine, and secondly, of painstakingly gathering patients into computerised case bases which simulate exhaustive long-term memory. The AI capacities for knowledge elaboration are then triggered, giving rise to mathematically optimal diagnoses, prognoses, or treatment protocols which the physician may then evaluate, accept, reject, or adapt at his convenience, and finally append to a knowledge base. The idea of emergence embraces many issues concerning the purpose and intent of artificial intelligence in medical practice. Particularly, we address the representation problem as it is raised by classical decisional knowledge-based systems, and develop the notions of classifiers and hybrid systems as possible answers to this problem. Finally, since the whole methodology touches the problem of technological investment in health care, now inherent in modern medical practice, some ethical considerations accompany the exposé. (shrink)

Visual inspections have been typically used in condition assessment of infrastructure. However, they are based on human judgment and their interpretation of data can differ from acquired results. In psychology, this difference is called cognitive bias which directly affects Structural Health Monitoring -based decision making. Besides, the confusion between condition state and safety of a bridge is another example of cognitive bias in bridge monitoring. Therefore, integrated computer-based approaches as powerful tools can be significantly applied in SHM systems. (...) This paper explores the relationship between the use of advanced computational intelligence and the development of SHM solutions through conducting an infrastructure monitoring methodology. Artificial Intelligence -based algorithms, i.e., Artificial Neural Network, hybrid ANN-based Imperial Competitive Algorithm, and hybrid ANN-based Genetic Algorithm, are developed for damage assessment using a lab-scale composite bridge deck structure. Based on the comparison of the results, the employed evolutionary algorithms could improve the prediction error of the pre-developed network by enhancing the learning procedure of the ANN. (shrink)

The computational hypothesis was formulated with due concern for limits and is consistent with imposed intelligibility doctrines. Theories are products of scientific work that impose human classifications and formalisms on nature. The claim that “cognitive agents are dynamical systems” is untenable. Dynamical formalisms imposed on a natural system, given an approximate fit, serve as an explanatory framework and render a represented system predictable and intelligible.

The paper explores integrating AI into scholarly communication for enhanced human cognitive abilities. The conception of human-machine communication (HMC) approach that regards AI-based technologies not as interactive objects, but communicative subjects, throws issues that are more philosophical in scholarly communication. It is a known fact that, there is increased interaction between humans and machines especially consolidated by COVID-19 pandemic, which heightened the development of Individual Adaptive Learning System thereby necessarily requiring inputs from NI to strengthen AI. This positioned university (...) at the juxtaposition for ensuring the production of highly talented individuals who can continue to think beyond the thinkable intelligently and enabling AI experts to carry on building algorithms that can further the development of technology to the next level. To perform such a task, research output is paramount in connecting university and publishing industry. The paper critically examines important components and tries to do justice for emanating of critical questions from researchers (NI) thus feeding the development of technology (AI). (shrink)

Science as a social institution today is experiencing a phase of profound transformation. Objects, methods, research technological tools, methods of institutional communication and mechanisms for commercializing new knowledge are changing. The creation of new interdisciplinary communication platforms is more relevant today than ever before. This review pro[1]vides key information about the First Conference «Mind, Body, Intelligence, Language in the Age of Cognitive Technologies». The organizers created an event that brought together IT developers, academic researchers, and business representatives.

Some philosophers have argued that relativism is not defensible because the doctrine itself is not intelligible. In a recent book and two papers Hilary Putnam has repeatedly denied the intelligibility of relativism. He has offered a range of arguments, or hints of arguments, which will be answered, one by one, in this paper. Putnam has been particularly opposed to the relativist’s “criterial” or culture-relative conception of rationality, proposing a “non-criterial conception” instead; but his own formulation of the non-criterial conception and (...) his arguments in its defence will be seen to be inadequate. (shrink)

L'auteur distingue, dans les.travaux sur l'intelligence artifi- cielle, deux approches : l'approche technologique et l'approche cognitiviste. Il montre que les rapprochements faits, dans l'approche cognitiviste, entre l'intelligence humaine et l'intelligence artificielle, ne vont pas de soi, et que les thèses sur l'intelligence artificielle sont largement tributaires de certaines spéculations rationalistes et empi- ristes de la philosophie classique. Il expose la principale difficulté que rencontre alors une compréhension de l'intelligence humaine à partir de l'approche cognitiviste, à (...) savoir la nécessité d'oblitérer la dimension sémantique et de professer un solipsisme radical, et il plaide en faveur d'une compréhension de l'intelligence humaine selon ce qu'elle est dans la culture plutôt que dans les machines.In the literature on artificial intelligence, the author distinguishes two approaches : the technological approach and the cognitivist approach. He shows that the parallels made between human intelligence and artificial intelligence within the cognitivist approach do not go without saying, and that the theses on artificial intelligence are largely dependent upon certain rationalist and empiricist speculations of classical philosophy. He exposes the principal problem that then encounters an understanding of human intelligence in the light of the cognitivist approach, namely the necessity to obliterate the semantic dimension and to profess a radical solipsism, and he pleads for an understanding of human intelligence commensurable with what it is in culture rather than in machines. (shrink)

Thelen et al.'s account of cognition as the dynamic interaction of processes of perceiving, reaching, and remembering within a movement planning field is a useful articulation of the Piagetian concept of sensorimotor cognition. The claim that the same kind of analysis applies to all kinds of cognition at all ages, however, is questioned in light of the distinction between sensorimotor and symbolic cognition.