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

Can an agent's intelligence level be negative? We extend the Legg-Hutter agent-environment framework to include punishments and argue for an affirmative answer to that question. We show that if the background encodings and Universal Turing Machine (UTM) admit certain Kolmogorov complexity symmetries, then the resulting Legg-Hutter intelligence measure is symmetric about the origin. In particular, this implies reward-ignoring agents have Legg-Hutter intelligence 0 according to such UTMs.

In their thought-provoking paper, Legg and Hutter consider a certain abstrac- tion of an intelligent agent, and define a universal intelligence measure, which assigns every such agent a numerical intelligence rating. We will briefly summarize Legg and Hutter’s paper, and then give a tongue-in-cheek argument that if one’s goal is to become more intelligent by cultivating music appreciation, then it is bet- ter to use classical music (such as Bach, Mozart, and Beethoven) than to use more recent (...) pop music. The same argument could be adapted to other media: books beat films, card games beat first-person shooters, parables beat dissertations, etc. We leave it to the reader to decide whether this argument tells us something about classical music, something about Legg-Hutter intelligence, or something about both. (shrink)

Sequential decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability distribution is known. Solomonoff's theory of universal induction formally solves the problem of sequence prediction for unknown prior distribution. We combine both ideas and get a parameter-free theory of universal Artificial Intelligence. We give strong arguments that the resulting AIXI model is the most intelligent unbiased agent possible. We outline how the AIXI model can formally solve a number (...) of problem classes, including sequence prediction, strategic games, function minimization, reinforcement and supervised learning. The major drawback of the AIXI model is that it is uncomputable. To overcome this problem, we construct a modified algorithm AIXItl that is still effectively more intelligent than any other time t and length l bounded agent. The computation time of AIXItl is of the order t x 2^l. The discussion includes formal definitions of intelligence order relations, the horizon problem and relations of the AIXI theory to other AI approaches. (shrink)

There has been considerable debate around the ethical issues raised by data-driven technologies such as artificial intelligence. Ethical principles for the field have focused on the need to ensure...

The primary aim of this study was to determine the role of psychometric intelligence, emotional intelligence, and emo-sensory intelligence in university students’ academic achievement. To this end, 212 university students at different academic levels, composed of 154 females and 58 males, were asked to complete the Raven’s Progressive Matrices, the Bar-On Emotional Quotient Inventory, and the Emo-Sensory Intelligence Scale. Data were then matched with students’ Grade Point Averages as a measure of their academic achievement. The results (...) revealed that students’ level of IQ and EQ could positively predict their academic achievement. In the case of their ESQ level, its auditory sub-component was found to be a positive predictor of academic success. Results were discussed, and possible implications and applications for increasing students’ chances for success were presented. (shrink)

The field of value alignment, or more broadly machine ethics, is becoming increasingly important as artificial intelligence developments accelerate. By ‘alignment’ we mean giving a generally intelligent software system the capability to act in ways that are beneficial, or at least minimally harmful, to humans. There are a large number of techniques that are being experimented with, but this work often fails to specify what values exactly we should be aligning. When making a decision, an agent is supposed to (...) maximize the expected utility of its value function. Classically, this has been referred to as happiness, but this is just one of many things that people value. -/- In order to resolve this issue, we need to determine a set of human values that represent humanity's interests. Although this problem might seem intractable, research shows that people of various cultures and religions actually share more in common than they realize. In this book we review world religions, moral philosophy and evolutionary psychology to elucidate a common set of shared values. We then show how these values can be used to address the alignment problem and conclude with problems and goals for future research. -/- The key audience for this book will be researchers in the field of ethics and artificial intelligence who are interested in, or working on this problem. These people will come from various professions and include philosophers, computer programmers and psychologists, as the problem itself is multi-disciplinary. (shrink)

To reach the conclusion that the universe is infinite, physicists (a) make some observations; (b) fit those observations to some mathematical model; (c) find that the neatest model that accommodates the data extrapolates to an infinite universe; (d) conclude that the universe is infinite. In my presentation I will examine the logic by which physicists reach this conclusion. Specifically, I will show that there is no way to empirically justify the move from (b) to (c). An infinite universe should therefore (...) properly be viewed as a metaphysical hypothesis consistent with certain physical theories but hardly mandated by them. By contrast, I will argue that the hypothesis of intelligent design—that a designing intelligence has left clear marks of intelligence in the biophysical universe—is not a metaphysical hypothesis at all but a fully scientific one. In particular, I will argue that whereas an infinite universe does not (and indeed cannot) admit empirical evidence, intelligent design can. Finally, I will indicate why an infinite universe, though sometimes introduced to get around the problem of design, in fact cannot get around it. (shrink)

This article centers on Hume’s position on the intelligibility of natural philosophy. To that end, the controversy surrounding universal gravitation shall be scrutinized. It is very well-known that Hume sides with the Newtonian experimentalist approach rather than with the Leibnizian demand for intelligibility. However, what is not clear is Hume’s overall position on the intelligibility of natural philosophy. It shall be argued that Hume declines Leibniz’s principle of intelligibility. However, Hume does not eschew intelligibility altogether; his concept of causation (...) itself stipulates mechanical intelligibility. (shrink)

Artificial Intelligence Applications in Higher Education offers direct examples of how artificial intelligence systems can be applied in today's higher education contexts. As use of AI rapidly advances within colleges and universities worldwide, there is a pressing need to showcase the challenges, opportunities, and ethical considerations inherent in deploying these advanced computational tools. This book highlights the multifaceted roles of AI across teaching and learning, institutional administration, student data management, and beyond. Its collected case studies furnish actionable insights (...) into enhancing academic institutions and addressing diverse learning priorities such as motivation, engagement, feedback, and achievement goals. This valuable reference for researchers, designers, administrators, teaching faculty, and graduate students across various university programs offers fresh perspectives on generative AI, adaptive learning, intelligent tutoring systems, chatbots, predictive technologies, remote learning, and more. (shrink)

Examines the origins of life on earth, analyzes the Darwinian theory of evolution, and argues that life is the result of a deliberate plan.

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, I (...) first contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

Due to the COVID-19 pandemic, educational centers and universities in Venezuela have closed their physical plants and are migrating to emergency remote education to continue with academic programs. This empirical study aimed to analyze the predictive capacity of academic self-efficacy and emotional intelligence skills on each of the dimensions of psychological well-being. We employed a cross-sectional predictive design. The sample comprised 277 university students, of which 252 were female. Their ages ranged from 18 to 45 years, with a mean (...) of 20.35. Non-probabilistic chance sampling was used. For data collection, we used an anonymous online form, contacted students by mail, and invited them to participate in the study. Questionnaires were available between 217 and 227 days of decreed quarantine in Venezuela. The results indicated average levels of academic self-efficacy, emotional intelligence: clarity, attention y repair, and psychological well-being. We found differences according to sex and age, specifically in emotional regulation and in bonds of psychological well-being favoring men, respectively. Regarding age, statistically significant differences were found in the group of students older than 21 years with higher perception of psychological well-being and in each of its dimensions. Emotional intelligence and academic self-efficacy were found to be significant predictors of psychological well-being and its dimensions, specifically on control, links, projects, acceptance, and total well-being. It was concluded that emotional intelligence and academic self-efficacy are protective psychological resources of psychological well-being that should be promoted at university to mitigate the negative effects of the pandemic on the mental health of young people. (shrink)

This study was conducted with the aim of developing the academic work in the Palestinian universities. No one can deny the technological stage that we are witnessing in the present era. Our mission is to use this development to develop the educational process. The Artificial Intelligence of the most important branches of computer science, which is interested in the development of computer software in order to make them simulate intelligent human, recently it emerged promised based on artificial intelligence (...) applications are intelligent tutoring system one of the most prominent of these applications is the most useful in the field of education. Intelligent tutoring system are programs that are helping the student and the teacher in the educational process, so that the student exploits these systems to increase his education and the acquisition of scientific skills, and we are not exaggerating if we say that the future of the development of the educational process is through the development of intelligent private teaching systems because it adapts to me intellectual level of the student as well as easy to use and available 24 hours every day. In this study, a smart tutor was designed using the ITSB tool developed by Prof. Sami Abu Nasser to develop the process of teaching the computer skills course. This course is a university course that teaches students of Israa University on different samples of students. After completion of the course, and evaluate the special lecturers who studied the course and used the system in the process of teaching and arrived at a set of conclusions and recommendations make sure that the use of the tutor Smart smartphone is important in the development of laboratory teaching has positive results in improving the level of scientific student . (shrink)

Complexity and life as we know it depend crucially on the laws and constants of nature as well as the boundary conditions, which seem at least partly “fine-tuned.” That deserves an explanation: Why are they the way they are? This essay discusses and systematizes the main options for answering these foundational questions. Fine-tuning might just be an illusion, or a result of irreducible chance, or nonexistent because nature could not have been otherwise (which might be shown within a fundamental theory (...) if some constants or laws could be reduced to boundary conditions or boundary conditions to laws), or it might be a product of selection: either observational selection (weak anthropic principle) within a vast multiverse of many different realizations of physical parameters, or a kind of cosmological natural selection making the measured parameter values quite likely within a multiverse of many different values, or even a teleological or intentional selection or a coevolutionary development, depending on a more or less goal-directed participatory contribution of life and intelligence. In contrast to observational selection, which is not predictive, an observer-independent selection mechanism must generate unequal reproduction rates of universes, a peaked probability distribution, or another kind of differential frequency, resulting in a stronger explanatory power. The hypothesis of Cosmological Artificial Selection (CAS) even suggests that our universe may be a vast computer simulation or could have been created and transcended by one. If so, this would be a far-reaching answer – within a naturalistic framework! – of fundamental questions such as: Why did the big bang and fine-tunings occur, what is the role of intelligence in the universe, and how can it escape cosmic doomsday? This essay critically discusses some of the premises and implications of CAS and related problems, both with the proposal itself and its possible physical realization: Does CAS deserve to be considered as a convincing explanation of cosmic fine-tuning? Is life incidental, or does CAS revalue it? And are life and intelligence ultimately doomed, or might CAS rescue them? (shrink)

This paper reviews two main historical approaches to creativity: the Romanticist approach, based on the culture of the irrational, and the Enlightenment approach, based on the culture of the objective. It defends a paradigm of creativity as a sum of rich semiotic systems that form the basis of distributed knowledge and learning, reviews historical ideas of the university, and identifies two conflicting mainstream models in regards to understanding of the university as a public good: the ‘Public’ University circa 1960–1980, and (...) the ‘post-historical’ university. Based on practical experiences, and on previous works by Peters and Jandrić, it develops the new model of ‘the creative university as digital public university’, and argues that it provides a useful philosophical goal for directing present and future practices of the contemporary university. (shrink)

Originally published in 1940, this book by famous Plotinus scholar Arthur Hilary Armstrong assesses how the philosopher's hierarchy of reality fits into the wider universal order, and how the historical and philosophical tradition gave rise to Plotinus' own philosophies. Armstrong also supplies a bibliography broken down by topic for those who wish to pursue any aspect of the text in greater depth. This book will be of value to anyone with an interest in Plotinus, Neoplatonism and in the pagan (...) roots of Christian philosophy. (shrink)

While practical efforts in the field of artificial intelligence grow exponentially, the truly scientific and mathematically exact understanding of the underlying phenomena of intelligence and consciousness is still missing in the conventional science framework. The inevitably dominating empirical, trial-and-error approach has vanishing efficiency for those extremely complicated phenomena, ending up in fundamentally limited imitations of intelligent behaviour. We provide the first-principle analysis of unreduced many-body interaction process in the brain revealing its qualitatively new features, which give rise to (...) rigorously defined chaotic, noncomputable, intelligent and conscious behaviour. Based on the obtained universal concepts of unreduced dynamic complexity, intelligence and consciousness, we derive the universal laws of intelligence applicable to any kind of intelligent system interacting with the environment. We finally show why and how these fundamentally substantiated and therefore practically efficient laws of intelligent system dynamics are indispensable for correct AI design and training, which is urgently needed in this time of critical global change towards the truly sustainable development. (shrink)

The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning (...) PhD thesis (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, without providing any domain knowledge, the same agent is able to self-adapt to a diverse range of interactive environments. For instance, AIXI is able to learn from scratch to play TicTacToe, Pacman, Kuhn Poker, and other games by trial and error, without even providing the rules of the games. These achievements give new hope that the grand goal of Artificial General Intelligence is not elusive. This article provides an informal overview of UAI in context. It attempts to gently introduce a very theoretical, formal, and mathematical subject, and discusses philosophical and technical ingredients, traits of intelligence, some social questions, and the past and future of UAI. (shrink)

In this study, we develop a theoretical model of monetary intelligence (MI), explore the extent to which individuals’ meaning of money is related to the pursuit of materialistic purposes, and test our model using the whole sample and across college major and gender. We select the 15-item love of money (LOM) construct—Factors Good, Evil (Affective), Budget (Behavioral), Achievement, and Power (Cognitive)—from the Money Ethic Scale and Factors Success and Centrality and two indicators—from the Materialism Scale. Based on our data (...) collected from 330 university students in Czech Republic, we provide the following findings. First, our formative models are superior to our reflective models. Second, for the reflective model, money represents Power, Good, Achievement, and not Evil, in the context of materialism. Our formative model suggests that those who pursuit materialism cherish Achievement (vanity) but Budget their money poorly. Third, multi-group analyses illustrate that humanities students (62.4 % female) consider money as Evil and Budget their money poorly, while those in natural sciences (37.6 % female) do not. Further, men are obsessed with Achievement, whereas women do not Budget their money properly, suggesting reflective temptation for males and impulsive temptation for females. Our novel discoveries shed new lights on the relationships between LOM and materialism and offer practical implications to the field of consumer behavior and business ethics. (shrink)

The COVID-19 pandemic has had a significant impact on education worldwide. The disease first hit China and numerous Chinese cities then started to conduct online courses. Therefore, this study aims to explore the effect of the Shanghai students’ emotional intelligence, learning motivation, and self-efficacy on their academic achievement when they participated in online English classes during the latter phase of the pandemic in China. Furthermore, the research also examines whether the students’ emotional intelligence can influence their academic achievement (...) through the mediation effect of their learning motivation and self-efficacy. Social Cognitive Theory and the social cognitive Expectancy-Value Model were employed to build the research framework, and the method of structural equation modeling was utilized to conduct the model verification. Ten universities in Shanghai, China were selected for sampling. In total, 450 students were surveyed of which 404 questionnaires were valid. The results show that the students’ emotional intelligence did not directly affect their academic achievement. Nevertheless, the students’ emotional intelligence had a positive effect on their learning motivation and self-efficacy. In addition, mediation analysis showed that the relation between emotional intelligence and academic achievement was sequentially mediated by learning motivation and self-efficacy. (shrink)

Recent findings about the capabilities of smart animals such as corvids or octopi and novel types of artificial intelligence, from social robots to cognitive assistants, are provoking the demand for new answers for meaningful comparison with other kinds of intelligence. This book fills this need by proposing a universal theory of intelligence which is based on causal learning as the central theme of intelligence. The goal is not just to describe, but mainly to explain queries (...) like why one kind of intelligence is more intelligent than another, whatsoever the intelligence. Shiny terms like "strong AI," "superintelligence," "singularity" or "artificial general intelligence" that have been coined by a Babylonian confusion of tongues are clarified on the way. (shrink)

The coronavirus/COVID-19 pandemic has brought about significant changes in the lifestyle of students. However, despite an extensive study of students’ life stress using a non-comprehensive scale and variable-centered approach, it has been little studied with a comprehensive scale and person-centered approach. Using the Student-Life Stress Inventory-revised (SSI-R), we analyzed students’ latent stress profiles and examined differences in psychological resilience and emotional intelligence by comparing stress profiles from a sample of 418 undergraduate and graduate students (aged 18–36) in various departments (...) of eight universities in Turkey. We identified five distinct stress profiles, defined as an extremely low stress group (ELSG), a low stress group (LSG), a medium stress group (MSG), a high stress group (HSG), and an extremely high stress group (EHSG). We found that (1) MSG and HSG were similar in terms of emotional intelligence, resilience, and possession of high standards, and they reported higher levels of physiological, emotional, and behavioral reactions than ELSG and LSG; (2) MSG felt more pressure than HSG; (3) ELSG reported higher levels of emotional intelligence (wellbeing, self-control, and emotionality) than others. Also, EHSG reported lower levels of emotional intelligence (specifically self-control) than others; (4) whereas resilience was highly positively correlated to wellbeing, resilience and wellbeing were moderately negatively correlated to stress. Extremely low stress group and LSG reported higher levels of resilience than others. Medium stress group, HSG, and EHSG did not differ with regard to resilience and wellbeing. Our results suggest that, university students are able to maintain their functionality by coping up with stress in some ways, no matter how stressful they are. These findings are discussed in relation to the relevant literature. (shrink)

Inspired by recent progress in multi-agent Reinforcement Learning (RL), in this work we examine the collective intelligent behaviour of theoretical universal agents by introducing a weighted mixture operation. Given a weighted set of agents, their weighted mixture is a new agent whose expected total reward in any environment is the corresponding weighted average of the original agents' expected total rewards in that environment. Thus, if RL agent intelligence is quantified in terms of performance across environments, the weighted mixture's (...) intelligence is the weighted average of the original agents' intelligences. This operation enables various interesting new theorems that shed light on the geometry of RL agent intelligence, namely: results about symmetries, convex agent-sets, and local extrema. We also show that any RL agent intelligence measure based on average performance across environments, subject to certain weak technical conditions, is identical (up to a constant factor) to performance within a single environment dependent on said intelligence measure. (shrink)

This study aimed to explore the mediating role of emotional regulation strategies in the relationship between emotional intelligence and subjective well-being among Chinese university teachers, and evaluate whether effort-reward imbalance moderated the mediating effect of emotional regulation strategies. A total of 308 Chinese university teachers were recruited for this study. The results showed that emotional regulation strategies played a partial mediating role in the relationship between EI and SWB. Moreover, an effort-reward imbalance moderated the relationship between emotional regulation strategies (...) and SWB. For individuals with more balanced perceptions, EI had a significant effect on SWB via cognitive reappraisal, while for individuals with more imbalanced perceptions, EI did not have a significant effect on SWB via cognitive reappraisal. These findings provide a better understanding of the effects of EI and emotional regulation strategies on SWB, which could provide interventions for promoting SWB among teachers. (shrink)

Hume famously warned us that the ‘[The] ultimate springs and principles are totally shut up from human curiosity and enquiry’. Or, again, Newton: ‘Hitherto I have not been able to discover the cause of these properties of gravity … and I frame no hypotheses.’ Aristotelian science was concerned with just such questions, the specification of occult qualities, the real essences that answer the question What is matter, etc?, the preoccupation with circular definitions such as dormative virtues, and so on. The (...) rise of modern science is usually seen as a break with the sterility of Aristotelianism, so what exactly is it that modern science does discover, if it is not the essential nature of matter, of force, of energy, of space and time? A famous answer was provided by Poincaré: ‘The true relations between these real objects are the only reality we can attain.’ This is often regarded as the manifesto of so-called structural realism, as espoused in recent years by John Worrall, for example ). In response to the arguments of Larry Laudan against convergent realism, Worrall points to the continuity in the formal relations between elements of reality expressed by mathematical equations, while the intrinsic nature of these elements of reality gets constantly revised. (shrink)

This study was conducted with the aim of developing the academic work in the Palestinian universities. No one can deny the technological stage that we are witnessing in the present era. Our mission is to use this development to develop the educational process. The Artificial Intelligence of the most important branches of computer science, which is interested in the development of computer software in order to make them simulate intelligent human, recently it emerged promised based on artificial intelligence (...) applications are intelligent tutoring system one of the most prominent of these applications is the most useful in the field of education. Intelligent tutoring system are programs that are helping the student and the teacher in the educational process, so that the student exploits these systems to increase his education and the acquisition of scientific skills, and we are not exaggerating if we say that the future of the development of the educational process is through the development of intelligent private teaching systems because it adapts to me intellectual level of the student as well as easy to use and available 24 hours every day. In this study, a smart tutor was designed using the ITSB tool developed by Prof. Sami Abu Nasser to develop the process of teaching the computer skills course. This course is a university course that teaches students of Israa University on different samples of students. After completion of the course, and evaluate the special lecturers who studied the course and used the system in the process of teaching and arrived at a set of conclusions and recommendations make sure that the use of the tutor Smart smartphone is important in the development of laboratory teaching has positive results in improving the level of scientific student . (shrink)

The COVID-19 global health emergency has greatly impacted the educational field. Faced with unprecedented stress situations, professors, students, and families have employed various coping and resilience strategies throughout the confinement period. High and persistent stress levels are associated with other pathologies; hence, their detection and prevention are needed. Consequently, this study aimed to design a predictive model of stress in the educational field based on artificial intelligence that included certain sociodemographic variables, coping strategies, and resilience capacity, and to study (...) the relationship between them. The non-probabilistic snowball sampling method was used, involving 337 people from the university education community in south-eastern Spain. The Perceived Stress Scale, Stress Management Questionnaire, and Brief Resilience Scale were administered. The Statistical Package for the Social Sciences was used to design the architecture of artificial neural networks. The results found that stress levels could be predicted by the synaptic weights of coping strategies and timing of the epidemic, with a predictive capacity of over 80% found in the neural network model. Additionally, direct and significant associations were identified between the use of certain coping strategies, stress levels, and resilience. The conclusions of this research are essential for effective stress detection, and therefore, early intervention in the field of educational psychology, by discussing the influence of resilience or lack thereof on the prediction of stress levels. Identifying the variables that maintain a greater predictive power in stress levels is an effective strategy to design more adjusted prevention programs and to anticipate the needs of the community. (shrink)

The current study analyzed how trait emotional intelligence (trait EI) mediates the relationship between self-esteem and state anxiety (STAI-S) and trait anxiety (STAI-T). The sample was composed of 153 undergraduate students from the University of Cádiz, Spain (71.9% women and 28.1% men). Students completed measures of self-esteem, STAI-S, STAI-T, and trait EI. Mediation analyses were completed with three trait EI dimensions (emotional attention -EA-, emotional clarity -EC-, and mood repair -MR) as mediating variables, self-esteem as the independent variable, and (...) STAI-S and STAI-T as the dependent ones. Our results confirmed that self-esteem scores explained and predicted both, STAI-S and STAI-T values (13% for STAI-S and 21% for STAI-T). This explanatory capacity is increased by 8% when accounting for all trait EI dimensions. Considering STAI-S, the results of the direct effects showed that a decrease in their levels is predicted through the increases in the levels of both, self-esteem and MR. Regarding STAI-T, the results of the direct effects showed that a decrease in their levels is predicted, in addition to an increment of self-esteem and MR values, by an increase of EC and a decrease of EA. Conversely, indirect effects revealed that higher levels of self-esteem were associated with worse scores in EA and worse MR, which in turn would enhance both STAI-S and STAI-T levels. Moreover, regarding STAI-T higher levels of self-esteem were associated with worse scores in EA and worse EC, therefore increasing STAI-T levels. As shown, the negative association found between self-esteem and EA becomes a key element. The effect of self-esteem on EA and the influence that the latter had on EC and MR exerts an indirect mediated effect with the power to invert the influence that self-esteem wields on both types of anxiety. In this sense, the apparent protective role of self-esteem changed, turning into a risk factor that promotes higher anxiety values. (shrink)

While the scientific discourse on astrobiology—the study of the origin, evolution, and distribution of life in the universe—leans toward optimism about the possibility of extraterrestrial life, optimistic thinking is tempered by the limits of evidence and observations gathered thus far. Most astrobiologists assume that “first contact” with extraterrestrial life, if it is ever to occur, will likely be the discovery of microbial life elsewhere in our solar system. But in popular culture, “first contact” tends to be characterized as contact with (...) extraterrestrial intelligence. This article will touch on theory and research relating to the origins and evolution of life and intelligence on Earth and speculation about extraterrestrial life and intelligence. (shrink)

We have examined the attitude and moral perception of 228 college students towards artificial intelligence in an international university in Japan. The students were asked to select a single most significant ethical issue associated with AI in the future from a list of nine ethical issues suggested by the World Economic Forum, and to explain why they believed that their chosen issues were most important. The majority of students chose unemployment as the major ethical issue related to AI. The (...) second largest group of students were concerned with ethical issues related to emotional AI, including the impact of AI on human behavior and emotion. The paper discusses the results in detail and concludes that, while policymakers must consider how to ameliorate the impact of AI on employment, AI engineers need to consider the emotional aspects of AI in research and development, as well. (shrink)