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

Ned Block has recently adduced some new arguments to show that “psychologism is true and thus a natural behaviorist analysis of intelligence that is incompatible with psychologism is false”. He introduces a thought experiment in which a machine is programmed to exhibit intelligent-seeming behavior and appeals to our intuition that such a machine is nevertheless not really inteligent; he traces that intuition to the fact that the machine is being thought of as operating with internal processes that, first, (...) lack a certain internal structure with a certain kind of complexity and, second, are in a certain sense mechanical, reflecting only the programmer’s intelligence.I argue against Block both that the mistakes the source and nature of our intuition and that the conclusion he draws concerning psychologism does not follow. While the intuition he appeals to may show that behaviorism is false, that is not equivalent to showing that psychologism in the sense intended by Block is true.Em trabalhos recentes Ned Block fornece alguns argumentos novos para mostrar que “o psicologismo é verdadeiro e, portanto, uma análise behaviorista da inteligência que seja incompatível com este último tem de ser falsa”. Ele elabora um experimento mental no qual uma máquina é programada para exibir comportamento aparentemente inteligente e mostra em que sentido nossa intuição leva-nos a concluir que tal máquina não é realmente inteligente. Tal intuição origina-se no fato de que a máquina é concebida como operando com processos internos aos quais falta uma estrutura interior dotada de um certo tipo de complexidade e que tais processos internos são mecânicos, refletindo apenas a inteligência do programador.A argumentação contra Block é feita em duas direções: em primeiro lugar mostra-se que a origem e a natureza de nossa intuição é incorreta; em segundo que as conclusões que ele extrai a partir do psicologismo não procedem. Embora a intuição que Block invoca possa mostrar que o behaviorismo é falso, isso não equivale a provar que o psicologismo no sentido por ele pretendido seja verdadeiro. (shrink)

Biosemiotics deals with the processes of signs in all dimensions of nature. Semiosis is the primary form of intelligence. Intelligent behaviour becomes immediately understandable in this approach because semiosis combines causality with the triadic structure of the semiotic sign. Intelligence is a process created in a given context. In the course of evolution organisms have learned to create increasingly sophisticated internal representations of external state. Semiosis is the precursor of the emergence of a feature we consider intelligence. Biosemiotics also (...) draws attention to the distributed intelligence, which relies on external semiotic scaffoldings as much as on the subject’s abilities and knowledge. (shrink)

Emotional Intelligence (EI) has been conceptualized in the literature either as a dispositional tendency, in line with a personality trait (trait EI; Petrides and Furnham, 2001), or as an ability, moderately correlated with general intelligence (ability EI; Mayer and Salovey, 1997). Surprisingly, there have been few empirical attempts conceptualizing how the different EI approaches should be related to each other. However, understanding how the different approaches of EI may be interwoven and/or complementary is of primary importance for clarifying the conceptualization (...) of EI and organizing the literature around it. We introduce a theoretical framework explaining how trait EI, ability EI, and emotion information processing – a novel component related to EI recently introduced in the literature (e.g., Fiori and Vesely Maillefer, 2018) – may contribute to effective emotion-related performance and provide initial evidence supporting its usefulness in predicting EI-related outcomes. More specifically, we show that performance in a task in which participants had to infer the mental and emotional states of others, namely a Theory of Mind task, was predicted jointly (e.g., interaction effects) by trait EI, ability EI, and emotion information processing, after controlling for personality and IQ (N = 323). Our results argue for the importance of investigating the joint contribution of different aspects of EI in explaining variability in emotionally laden outcomes. (shrink)

This research investigates the efficacy of business ethics intervention, tests a theoretical model that the love of money is directly or indirectly related to propensity to engage in unethical behavior (PUB), and treats college major (business vs. psychology) and gender (male vs. female) as moderators in multi-group analyses. Results suggested that business students who received business ethics intervention significantly changed their conceptions of unethical behavior and reduced their propensity to engage in theft; while psychology students without intervention had (...) no such changes. Therefore, ethics training had some impacts on business students' learning and education (intelligence). For our theoretical model, results of the whole sample (N = 298) revealed that Machiavellianism (measured at Time 1) was a mediator of the relationship between the love of money (measured at Time 1) and unethical behavior (measured at Time 2) (the Love of Money → Machiavellianism → Unethical Behavior). Further, this mediating effect existed for business students (n = 198) but not for psychology students (n = 100), for male students (n = 165) but not for female students (n = 133), and for male business students (n = 128) but not for female business students (n = 70). Moreover, when examined alone, the direct effect (the Love of Money → Unethical Behavior) existed for business students but not for psychology students. We concluded that a short business ethics intervention may have no impact on the issue of virtue (wisdom). (shrink)

In a paper that recently appeared in this journal, we proposed a model that aims at providing a comprehensive account of our ability to intelligently use tools, bridging sensorimotor and reasoning-based explanations of this ability. Central to our model is the notion of generalized motor programs for tool use, which we defined as a synthesis between classic motor programs, as described in the scientific literature, and Peircean habits. In his commentary, Osiurak proposes a critique of the notion of generalized motor (...) program, and suggests that the limitations of our model can be solved by integrating it with the view that motor programs are generated by a previous mechanical reasoning, independent from sensorimotor knowledge. Here we reply that while on the one hand our reference to Peircean habits gets over the temptation to consider motor programs as fixed internal entities, it also rejects the view, endorsed by Osiurak, that intelligent practice is a mixture of antecedent abstract reasoning and subsequent motor execution. (shrink)

Collective intelligence in organizational teams has been predominantly understood and explained in terms of the quality of the outcomes that the team produces. This manuscript aims to extend the understanding of CI in teams, by disentangling the core of actual collective intelligent team behavior that unfolds over time during a collaboration period. We posit that outcomes do support the presence of CI, but that collective intelligence itself resides in the interaction processes within the team. Teams behave collectively (...) class='Hi'>intelligent when the collective behaviors during the collaboration period are in line with the requirements of the tasks the team is assigned to and the environment. This perspective results in a challenging, but promising research agenda armed with new research questions that call for unraveling longitudinal fine-grained interactional processes over time. We conclude with exploring methodological considerations that assist researchers to align concept and methodology. In sum, this manuscript proposes a more direct, thorough, and nuanced understanding of collective intelligence in teams, by disentangling micro-level team behaviors over the course of a collaboration period. With this in mind, the field of CI will get a more fine-grained understanding of what really happens at what point in time: when teams behave more or less intelligently. Additionally, when we understand collectively intelligent processes in teams, we can organize targeted interventions to improve or maintain collective intelligence in teams. (shrink)

Information is a peculiar quantity. Unlike matter and energy, which are conserved by the laws of physics, the aggregation of knowledge from many sources can in fact produce more information (synergy) or less (redundancy) than the sum of its parts. This feature can endow groups with problem‐solving strategies that are superior to those possible among noninteracting individuals and, in turn, may provide a selection drive toward collective cooperation and coordination. Here we explore the formal properties of information aggregation as a (...) general principle for explaining features of social organization. We quantify information in terms of the general formalism of information theory, which also prescribes the rules of how different pieces of evidence inform the solution of a given problem. We then show how several canonical examples of collective cognition and coordination can be understood through principles of minimization of uncertainty (maximization of predictability) under information pooling over many individuals. We discuss in some detail how collective coordination in swarms, markets, natural language processing, and collaborative filtering may be guided by the optimal aggregation of information in social collectives. We also identify circumstances when these processes fail, leading, for example, to inefficient markets. The contrast to approaches to understand coordination and collaboration via decision and game theory is also briefly discussed. (shrink)

Artificial intelligence receives attention in media as well as in academe and business. In media coverage and reporting, AI is predominantly described in contrasted terms, either as the ultimate solution to all human problems or the ultimate threat to all human existence. In academe, the focus of computer scientists is on developing systems that function, whereas philosophy scholars theorize about the implications of this functionality for human life. In the interface between technology and philosophy there is, however, one imperative aspect (...) of AI yet to be articulated: how do intelligent systems make inferences? We use the overarching concept “Artificial Intelligent Behaviour” which would include both cognition/processing and judgment/behaviour. We argue that due to the complexity and opacity of artificial inference, one needs to initiate systematic empirical studies of artificial intelligent behavior similar to what has previously been done to study human cognition, judgment and decision making. This will provide valid knowledge, outside of what current computer science methods can offer, about the judgments and decisions made by intelligent systems. Moreover, outside academe—in the public as well as the private sector—expertise in epistemology, critical thinking and reasoning are crucial to ensure human oversight of the artificial intelligent judgments and decisions that are made, because only competent human insight into AI-inference processes will ensure accountability. Such insights require systematic studies of AI-behaviour founded on the natural sciences and philosophy, as well as the employment of methodologies from the cognitive and behavioral sciences. (shrink)

This study investigates factors impacting perceptions of ethical conduct of peers of 293 students in four US universities. Self-reported ethical behavior and recognition of emotions in others (a dimension of emotional intelligence) impacted perception of ethical behavior of peers. None of the other dimensions of emotional intelligence were significant. Age, Race, Sex, GPA, or type of major (business versus nonbusiness) did not impact perception of ethical behavior of peers. Implications of the results of the study for business (...) schools and industry professionals are discussed. (shrink)

In this paper the authors argue that many of the ethical problems raised by Ambient Intelligence stems from presupposing a behaviourist conception of the relation between human desires and behaviour. Insofar as Ambient Intelligence systems take overt, natural behaviour as input, they are likely to suffer from many of the same problems that have fuelled the widespread criticism of behaviourist explanations of human behaviour. If these limitations of the technology are not sufficiently recognized, the technology is likely to be insufficiently (...) successful in supporting the needs and desires of human users. We will focus on four distinct challenges that result from this behaviourist presupposition, all of which ought to be taken into consideration at the design stage: reciprocal adaptation, bias towards isolated use, culture-specific behaviour, and inability to manually configure the system. By considering these issues, our purpose is to raise awareness of the ethical problems that can arise because of intelligent user interfaces that rely on natural, overt behaviour. (shrink)

This study examines factors impacting ethical behavior of 103 hospital nurses. The level of emotional intelligence and ethical behavior of peers had a significant impact on ethical behavior of nurses. Independence climate had a significant impact on ethical behavior of nurses. Other ethical climate types such as professional, caring, rules, instrumental, and efficiency did not impact ethical behavior of respondents. Implications of this study for researchers and practitioners are discussed.

Intelligent big data analysis is an evolving pattern in the age of big data science and artificial intelligence. Analysis of organized data has been very successful, but analyzing human behavior using social media data becomes challenging. The social media data comprises a vast and unstructured format of data sources that can include likes, comments, tweets, shares, and views. Data analytics of social media data became a challenging task for companies, such as Dailymotion, that have billions of daily users (...) and vast numbers of comments, likes, and views. Social media data is created in a significant amount and at a tremendous pace. There is a very high volume to store, sort, process, and carefully study the data for making possible decisions. This article proposes an architecture using a big data analytics mechanism to efficiently and logically process the huge social media datasets. The proposed architecture is composed of three layers. The main objective of the project is to demonstrate Apache Spark parallel processing and distributed framework technologies with other storage and processing mechanisms. The social media data generated from Dailymotion is used in this article to demonstrate the benefits of this architecture. The project utilized the application programming interface of Dailymotion, allowing it to incorporate functions suitable to fetch and view information. The API key is generated to fetch information of public channel data in the form of text files. Hive storage machinist is utilized with Apache Spark for efficient data processing. The effectiveness of the proposed architecture is also highlighted. (shrink)

The need for better incorporation of the construct emotional intelligence (EI) into counterproductive work behavior (CWB) research may be achieved via a unified conceptual framework. Accordingly, the purpose of this paper is to use the Profile Analysis via Multidimensional Scaling (PAMS) approach, a conceptual framework that unifies motivational process with antecedents and outcomes, to assess differences in EI concerning a variety of constructs: organizational justice, CWB, emotional exhaustion, job satisfaction, and intrinsic motivation. Employing established scales within a framework unifying (...) CWB, intrinsic motivation, EI, organizational justice, and outcome constructs, two EI-based profiles displayed associations with CWB based on responses from 3,293 employees. Both the first core profile, high overall justice and low emotional intelligence, and the second core profile, high emotional intelligence and low work motivation, displayed associations with interpersonal deviance and organizational deviance, as well as emotional exhaustion and job satisfaction. The results are discussed with respect to possible underlying theory and an overarching unified motivation framework that incorporates goal choice, intrinsic motivation, antecedents, and outcomes. We also provide directions for future research and implications for managers in the workplace based on heuristic conceptual frameworks that combine multiple motivational perspectives into a unified model. (shrink)

This empirical study explores the effect of cultural intelligence (CQ) on migrant workers’ innovative behavior, as well as the mediating role of knowledge sharing on the CQ-innovative behavior relationship. Besides, it also examines the extent to which the mediating process is moderated by climate for inclusion. Using survey data collected from Chinese migrant workers and their supervisors working in South Korea (n = 386), migrant workers’ CQ is found to positively impact their innovative behavior through enhanced knowledge (...) sharing. However, it is observed that this indirect relationship is significant, only for migrant workers in a strong climate for inclusion. Thus, these findings reveal the underlying mediation and moderation mechanism and consequently unveil the important role of migrant workers’ CQ in shaping their behavior. This study provides insightful and practical implications to a multicultural organization, where culturally diverse migrant workers work together. (shrink)

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes (...) to use artificial intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

This study examines the impact of various factors on ethical behavior of 507 employees working for three state-owned Chinese firms. Regulation of one’s emotions had a significant positive impact on ethical behavior of respondents. Organizational commitment also had a significant positive impact on ethical behavior of the respondents. Among various facets of job satisfaction, satisfaction with promotion, coworker, and supervision had a significant positive impact on ethical behavior of respondents. Among control variables, age of the employee (...) had a significant negative impact on ethical behavior, which indicated that the young employees showed a better ethical behavior than the old employees. (shrink)

From artistic performances in the visual arts and in music to motor control in gymnastics, from tool use to chess and language, humans excel in a variety of skills. On the plausible assumption that skillful behavior is a visible manifestation of intelligence, a theory of intelligence—whether human or not—should be informed by a theory of skills. More controversial is the question as to whether, in order to theorize about intelligence, we should study certain skills in particular. My target is (...) the view that only a particular class/kind of skill (i.e., ‘theoretical’, or ‘intellectual’ skills, versus ‘practical’, or ‘embodied’ skills) manifests intelligence, or especially does so. I call this view ‘Intelligence Elitism’. Intelligence Elitism is pervasive in popular culture, in academic culture, as well as in psychometrics. It has, arguably, a long pedigree in philosophy (though explicit arguments for it are rare). But it is a substantive view which, if false, can promote unfairness. In this article, I defend Intelligence Socialism—the claim that intelligent behavior is everywhere skillful behavior is. I go on to isolate the best case for the further Elitist claim that, even if all skillful behavior is intelligent in some modest sense of ‘intelligence’, there is a principled difference in intelligence between theoretical, or intellectual, skills, on one side, and practical, or embodied skills, on the other, and I show it wanting. (shrink)

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are stored, not as representations in (...) the mind, but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body's tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either.Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman's account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty's account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip. (shrink)

This paper presents the intelligent virtual animals that inhabit Omosa, a virtual learning environment to help secondary school students learn how to conduct scientific inquiry and gain concepts from biology. Omosa supports multiple agents, including animals, plants, and human hunters, which live in groups of varying sizes and in a predator-prey relationship with other agent types (species). In this paper we present our generic agent architecture and the algorithms that drive all animals. We concentrate on two of our animals (...) to present how different parameter values affect their movements and inter/intra-group interactions. Two evaluations studies are included: one to demonstrate the effect of different components of our architecture; another to provide domain expert validation of the animal behavior. (shrink)

Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM. 1 With this collection, I expect it to become equally well known to philosophers.

In late September 1838, Darwin read Malthus's Essay on Population, which left him with “a theory by which to work.”115 Yet he waited some twenty years to publish his discovery in the Origin of Species. Those interested in the fine grain of Darwin's development have been curious about this delay. One recent explanation has his hand stayed by fear of reaction to the materialist implications of linking man with animals. “Darwin sensed,” according to Howard Gruber, “that some would object to (...) seeing rudiments of human mentality in animals, while others would recoil at the idea of remnants of animality in man.”116 With this link closed, Darwin hung the materialist chain around his own neck, where it rested most uncomfortably. Stephen Gould, supporting Gruber's argument, finds evidence for this reconstruction in Darwin's M and N notebooks, whichinclude many statements showing that he espoused but feared to expose something he perceived as far more heretical than evolution itself: philosophical materialism-the postulate that matter is the stuff of all existence and that all mental and spiritual phenomena are its by-products. No notion could be more upsetting to the deepest traditions of Western thought than the statement that mind-however complex and powerful-is simply a product of brain.117The proferred hypothesis suggests, then, that Darwin was acutely sensible of the social consequences of equating men with animals and therefore mind with brian, and that he thus shied from publically revealing his views until the intellectual climate became more tolerant.The history I have examined makes this hypothesis implausible. Even if Darwin warily explored the implications of his emerging theory in his notebooks, his subsequent study of Fleming, Wells, Brougham, and Kirby should have quieted any trepidation. If these natural theologians did not flinch at seeing human reason prefigured in the mind of a worm, should Darwin have? Moreover, he recognized in his M notebook that the thesis of evolutionary continuity between men and animals did not require an explicit avowal of his conviction that brain was the agent of thought.118 And in any case, his materialism was of a rather benign sort; at least he so expressed it in an annotation in Abercrombie's Inquiries concerning the Intellectual Powers (1838): “By materialism I mean, merely the intimate connection of thought with form of brain — like kind of attraction with nature of element.”119 This belief would have held little terror for British intellectuals, who were quite familiar — some even comfortable-with Locke's anti-Cartesian argument that there was nothing contradictory in supposing God could make matter to think.120 Finally, even if the intellectual atmosphere of early nineteenth-century Britain were inhospitable to Darwin's brand of materialism, there is little reason to believe he breathed a different air at mid-century while preparing his manuscript.That Darwin should not have feared suspicions of materialism, of course, does not mean that he did not. But I think there were other, more persistent sources of anxiety that kept him from rushing to publish: namely, the several conceptual obstacles he had to overcome if his theory of evolution by natural selection were to be made scientifically acceptable. Prominent among these were the problems surrounding his changing notions of instinct.The inertia of his older ideas about instinct at first made it hard for Darwin to gauge how far the theory of natural selection might be applied to behavior. By the early 1840s he finally felt ready to meet the challenge of the natural theologians by providing a naturalistic explanation for the wonderful instincts of animals. In his “Essays” of 1842 and 1844 one sort of instinct is, however, not considered-that of neuter insects. Yet Darwin seems to have appreciated the difficulties such instincts entailed at least by 1843, when he read Kirby and Spence. He simply required time to work out a solution to a problem he initially perceived as “fatal to my whole theory.” Even while writing the “Species Book” in the summer of 1857, he was still juggling several possible solutions compatible with natural selection. It was only a short time before he actually turned to work on the Origin of Species that he appears to have settled on a single explanation for the difficulties posed by the instincts of worker bees and ants. The force of his theory of community selection snapped the last critical support of the creationist hypothesis and, conveniently enough, also fractured the generalized Lamarckian account of the evolution of behavior. These results were worth waiting for. (shrink)

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in (...) the mind, but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body's tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either.Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman's account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty's account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip. (shrink)

Acute stress has been linked with prosocial behavior, yet it is entirely unexplored how different types of stressors may affect individuals’ willingness to help: This is particularly relevant while people is experiencing multiple sources of stress due to the COVID-19 pandemic. Here we explore whether different types of stress influence peoples’ giving behavior and the moderating role of emotional intelligence. Undergraduate students were exposed to experimentally induced social, cognitive, or emotional stress and were asked to self-report on their (...) willingness to help and donate to a charity raising funds for COVID-19 and flu patients. Results showed that when compared to a control condition, after being exposed to a social stress, participants were more willing to help a person in need. Our results also provide evidence that, after experiencing a social stress, participants with high trait EI were more willing to help, and, as a result, donated more. Findings indicate that moderate levels of distress are associated with increased donations. Interestingly, when stress is not too threatening, high EI can regulate it and promote prosocial behaviors. (shrink)

In trying to make sense out of our behavior, we reach a point at which we stop talking about what we did and start talking about what we wish we had done, about what we mean to do next. But we think we are still talking about our motives and intentions in what we did. How do we know when we cross the line between finding out what actually happened and ascribing to a situation what we think ought to (...) have happened?This is a serious question, precisely because we usually do not know the difference between what we do and what we imagine that we do. For since all action is governed by our conception of “how we would have it” and “what we would bring about,” we can always honestly claim to have meant what we did for the best. We frequently find ourselves in the situation in which we don't know why we did what we did, but by casting about, we can always turn up a purpose for which our action must have been meant - a purpose which we now perceive.The reasons we ascribe to our actions, like our excuses, are governed by the demands made on us now, rather than by the factual content of what we did. Thus the behavior of reason-giving or excusing is meant to satisfy the social situation in which we presently find ourselves: the demand for explanation, the need to be “in the right,” the need to reinforce our convictions. The verbal account of what we did is thus literally about (as representing and serving) where we are now rather than what we did then.Our verbal account is about the context of social obligation in which we have to explain ourselves, not about the behavior we claim to interpret. This is why, proverbially, we will give any excuse which will satisfy the accuser and why “understanding” i.e. inventing reasons for our conduct, is no corrective. The addict, alcoholic, neurotic and criminal recidivist are frequently rational and even persuasive in giving reasons for what they do. And we wonder why if they understand their problems so well they can't do something about them. The problem is that the habitué doesn't understand his behavior at all. He is simply trained to give a certain after the fact explanation as a conditioned response to his habitual behavior. What he “understands” is not what makes him go back to the pill, the bottle or to crime, but what to tell people each time after he does. Naturally, when the habit-triggering occasion arises, it is never that reason - the stated one - which leads to repetition, but some new, special crisis, difficulty or impulse.Bluntly stated, our reasons and justifications have little or nothing to do with our actual behavior. We continue to suppose that we intend to do this or that immediately before we do it. But insofar as this intention is expressed it is a separate verbal act having its own conditions and consequences; insofar as it is unexpressed (and in general) intention is disclosed only through conduct. It is only the powerful social convention of justification that supports the illusion that verbal expressions are causal antecedents of acts.Two conclusions follow. First, the “sense” of our activity is either evident in the activity or else it is nonexistent, since not yet discovered meaning is meaning not yet achieved. Second, our verbal justifications are acts having a peculiar sense of their own. They express the relation of our convictions and objectives to the convictions and objectives of those to whom our explanations are addressed. Here is where, in the process of making sense of our activity, the crossover from discovery to invention occurs. This is why we may never discover the extent to which our justifications are inventions superimposed on the conduct they are supposed to represent. Insofar as our justification satisfies those to whom it is addressed, (including ourselves) it is right. But we take this rightness, which is actually the the compatibility of our values and objectives, to be the rightness of the act in question. The reasons we give for our actions make great sense, but despite our invincible “rightness” our actions, taken in themselves, make no more sense.What are our options? They are either to put ourselves in the power of those to whom we explain ourselves, or to take responsibility for our own nonsense. Take our conduct out of the medium of talk - of habitual justification - in which it is suspended and sustained, and what is it? Whatever has become of the “importance” of our appointments, our meetings, our appearances, our obligations, our consistency? Experience, not persuasion and reasoning, is the corrective. Only the direct experience of futility is powerful enough to break our addiction to justification. (shrink)

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in (...) the mind, but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body's tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either.Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman's account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty's account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip. (shrink)

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)

According to Bickerton, the behavioral sciences have failed to give an adequate account of human nature at least partly because of the conjunction and mutual reinforcement of two widespread beliefs: that language is simply a means of communication and that human intelligence is the result of the rapid growth and unusual size of human brains. Bickerton argues that each of the properties distinguishing human intelligence and consciousness from that of other animals can be shown to derive straightforwardly from properties of (...) language. In essence, language arose as a representational system, not a means of communication or a skill, and not a product of culture but an evolutionary adaptation. The author stresses the necessity of viewing intelligence in evolutionary terms, seeing it not as problem solving but as a way of maintaining homeostasis - the preservation of those conditions most favorable to an organism, the optimal achievable conditions for survival and well-being. The term protolanguage is used to describe the stringing together of symbols that prehuman hominids employed. "It did not allow them to turn today's imagination into tomorrow's fact. But it is just this power to transform imagination into fact that distinguishes human behavior from that of our ancestral species, and indeed from that of all other species. It is exactly what enables us to change our behavior, or invent vast ranges of new behavior, practically overnight, with no concomitant genetic changes." Language and Human Behavior should be of interest to anyone in the behavioral and evolutionary sciences and to all those concerned with the role of language in human behavior. (shrink)

Insofar as artificial intelligence is to be used to guide automated systems in their interactions with humans, the dominant view is probably that it would be appropriate to programme them to maximize (expected) utility. According to utilitarianism, which is a characteristically western conception of moral reason, machines should be programmed to do whatever they could in a given circumstance to produce in the long run the highest net balance of what is good for human beings minus what is bad for (...) them. In this essay, I appeal to values that are characteristically African––but that will resonate with those from a variety of moral-philosophical traditions, particularly in the Global South––to cast doubt on a utilitarian approach. Drawing on norms salient in sub-Saharan ethics, I provide four reasons for thinking it would be immoral for automated systems governed by artificial intelligence to maximize utility. In catchphrases, I argue that utilitarianism cannot make adequate sense of the ways that human dignity, group rights, family first, and (surprisingly) self-sacrifice should determine the behaviour of smart machines. (shrink)

: Artificial intelligences and robots increasingly mimic human mental powers and intelligent behaviour. However, many authors claim that ascribing human mental powers to them is both conceptually mistaken and morally dangerous. This article defends the view that artificial intelligences can have human-like mental powers, by claiming that both human and artificial minds can be seen as extended minds – along the lines of Chalmers and Clark’s view of mind and cognition. The main idea of this article is that the (...) Extended Mind Model is independently plausible and can easily be extended to artificial intelligences, providing a solid base for concluding that artificial intelligences possess minds. This may warrant viewing them as morally responsible agents. Keywords: Artificial Intelligence; Mind; Moral Responsibility; Extended Cognition Intelligenze artificiali come menti estese. Perché no? Riassunto: Intelligenze artificiali e robot simulano in misura sempre crescente le capacità mentali e i comportamenti intelligenti umani. Molti autori, tuttavia, sostengono che attribuire loro capacità mentali umane sia concettualmente errato e moralmente pericoloso. In questo lavoro si difende l’idea per cui le intelligenze artificiali possano avere capacità mentali simili a quelle umane, sostenendo che menti umane e artificiali possano essere considerate come menti estese – sulla scorta della prospettiva di Chalmers e Clark circa la mente e la cognizione. L’idea principale alla base di questo lavoro è che il Modello della Mente Estesa abbia plausibilità a prescindere e che possa essere facilmente esteso alle intelligenze artificiali, fornendo una base solida per concludere che le intelligenze artificiali possiedano delle menti e si possano considerare come agenti moralmente responsabili. Parole chiave: Intelligenza artificiale; Mente; Responsabilità morale; Conoscenza estesa. (shrink)