Some recent developments in Artificial Intelligence—especially the use of machine learning systems, trained on big data sets and deployed in socially significant and ethically weighty contexts—have led to a number of calls for “transparency”. This paper explores the epistemological and ethical dimensions of that concept, as well as surveying and taxonomising the variety of ways in which it has been invoked in recent discussions. Whilst “outward” forms of transparency may be straightforwardly achieved, what I call “functional” transparency about (...) the inner workings of a system is, in many cases, much harder to attain. In those situations, I argue that contestability may be a possible, acceptable, and useful alternative so that even if we cannot understand how a system came up with a particular output, we at least have the means to challenge it. (shrink)

This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral error; and (3) 'Human-Like (...) AMAs' programmed to understand and apply moral values in broadly the same way that we do, with a human-like moral psychology. Sections 2–4 then argue that each type of AMA generates unique control and alignment problems that have not been fully appreciated. Section 2 argues that Inhuman AMAs are likely to behave in inhumane ways that pose serious existential risks. Section 3 then contends that Better-Human AMAs run a serious risk of magnifying some sources of human moral error by reducing or eliminating others. Section 4 then argues that Human-Like AMAs would not only likely reproduce human moral failures, but also plausibly be highly intelligent, conscious beings with interests and wills of their own who should therefore be entitled to similar moral rights and freedoms as us. This generates what I call the New Control Problem: ensuring that humans and Human-Like AMAs exert a morally appropriate amount of control over each other. Finally, Section 5 argues that resolving the New Control Problem would, at a minimum, plausibly require ensuring what Hume and Rawls term ‘circumstances of justice’ between humans and Human-Like AMAs. But, I argue, there are grounds for thinking this will be profoundly difficult to achieve. I thus conclude on a skeptical note. Different approaches to developing ‘safe, ethical AI’ generate subtly different control and alignment problems that we do not currently know how to adequately resolve, and which may or may not be ultimately surmountable. (shrink)

The first issue of Artificial Intelligence and Law journal was published in 1992. This paper offers some commentaries on papers drawn from the Journal’s third decade. They indicate a major shift within Artificial Intelligence, both generally and in AI and Law: away from symbolic techniques to those based on Machine Learning approaches, especially those based on Natural Language texts rather than feature sets. Eight papers are discussed: two concern the management and use of documents available on the (...) World Wide Web, and six apply machine learning techniques to a variety of legal applications. (shrink)

For several years, scholars have (for good reason) been largely preoccupied with worries about the use of artificial intelligence and machine learning (AI/ML) tools to make decisions about us. Only recently has significant attention turned to a potentially more alarming problem: the use of AI/ML to influence our decision-making. The contexts in which we make decisions—what behavioral economists call our choice architectures—are increasingly technologically-laden. Which is to say: algorithms increasingly determine, in a wide variety of contexts, both the (...) sets of options we choose from and the way those options are framed. Moreover, artificial intelligence and machine learning (AI/ML) makes it possible for those options and their framings—the choice architectures—to be tailored to the individual chooser. They are constructed based on information collected about our individual preferences, interests, aspirations, and vulnerabilities, with the goal of influencing our decisions. At the same time, because we are habituated to these technologies we pay them little notice. They are, as philosophers of technology put it, transparent to us—effectively invisible. I argue that this invisible layer of technological mediation, which structures and influences our decision-making, renders us deeply susceptible to manipulation. Absent a guarantee that these technologies are not being used to manipulate and exploit, individuals will have little reason to trust them. (shrink)

This paper examines Augustine’s views on language, learning, and testimony in De Magistro. It is often held that, in De Magistro, Augustine is especially concerned with explanatory understanding (a complex cognitive state characterized by its synoptic nature and awareness of explanatory relations) and that he thinks testimony is deficient in imparting explanatory understanding. I argue against this view and give a clear analysis of the different kinds of cognitive state Augustine is concerned with and a careful examination of his (...) arguments concerning the deficiencies of testimony in producing these cognitive states. (shrink)

Understanding students’ psychological pressure and bad emotional reaction can solve psychological problems as soon as possible and avoid affecting students’ normal study life. With the improvement of global scientific and technological strength, and the step-by-step in-depth research on deep learning and computational intelligence optimization. Now, we have enough conditions to build a psychological and emotional data set for the field of education, and build a mental health stress detection model with emotional analysis function. In addition, a variety of (...) experimental methods are used for comparison, which shows the superior performance of the model in practical application scenarios. The results show that: the data set constructed for the model is reasonable. Psychological stress test shows that the tested college students are in good health and have no positive performance. Schools need to pay special attention to obsessive–compulsive disorder and interpersonal sensitivity, and the average values of both indicators are higher than 0.9. For the optimization of ant colony algorithm computational intelligence, both the stability and the average execution time of the algorithm are obviously higher than those of other algorithms. This model has obvious performance advantages after using this algorithm. Using loss function value to measure the difference between simulated emotion analysis and real value. The difference of most emotion tests is less than 3%; the accuracy difference between sadness and fear is about 7%. Although the final results prove the feasibility of this method, there are still some shortcomings to be optimized. (shrink)

ABSTRACT Early in Plato’s Euthydemus, sophistical arguments threaten the intelligibility of the process of learning. According to M. M. McCabe, Socrates resists the sophists’ arguments by resisting their problematic replacement model of change. The replacement model proposes that one item (e.g., an unlearned one) is simply replaced with a nonidentical item (e.g., a learned one). Socrates is said to endorse a rival metaphysics of temporally extended, teleologically structured activities. The rival model allows an enduring subject to survive ‘aspect changes’ (...) by occupying distinct stages in a continuous, unified process. McCabe may be right that Socrates presupposes or favors a metaphysics of continuous, end-oriented activities. If so, there are independent reasons to strive to understand the teleological structure of the activity of learning. Nevertheless, I am not convinced that Socrates relies on such a metaphysics to resist the learning arguments at 275d—278d. I argue that Socrates appeals, instead, to the complexity of the learning process to recognize two distinct, yet related, uses of the term ‘learning.’ In order to resist the sophists’ arguments, Socrates recommends attending to ‘the correctness of names’. Socrates’s disambiguating response is sufficient to dissolve the sophistical arguments while remaining compatible with a variety of metaphysics of individuals and activities. (shrink)

Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine (...) today. To develop this idea I will introduce the approach to artificial agency provided by Luciano Floridi. Simultaneously, I will situate this approach in the context of contemporary discussions regarding the nature of artificial agency. It is argued here that the IDSS possesses a specific sort of agency, includes several agent features (e.g. autonomy, interactivity, adaptability), and hence, performs an autonomous behavior, which may have a substantial moral impact on the patient’s well-being. It follows that, through the technology of artificial neural networks combined with ‘deep learning’ mechanisms, the IDSS tool achieves a specific sort of independence (autonomy) and may possess a certain type of moral agency. Second, I will provide a conceptual framework for the ethical evaluation of the moral impact that the IDSS may have on the doctor’s decision-making and, consequently, on the patient’s wellbeing. This framework is the Object-Oriented Model of Moral Action developed by Luciano Floridi. Although this model appears in many contemporary discussions in the field of information and computer ethics, it has not yet been applied to the medical domain. This paper addresses this gap and seeks to reveal the hidden potentialities of the OOP model for the field of medical diagnosis. (shrink)

Over the past two decades an increasing number of research papers have signalled growing interest in more responsible, sustainable and ethical modes of management education. This systematic literature review of peer-reviewed publications on, and allied to, the concept of responsible management learning and education confirms that scholarly interest in the topic has accelerated over the last decade. Rather than assuming that RMLE is one thing, however, this review proposes that the literature on responsible management education and learning can (...) be divided into four distinct categories: Teaching Responsible Management; Organizing for Responsible Education; Responsible Individual Learning, and; Responsible Organizational Learning. Although the literature on RMLE has grown, work on how managers learn responsible management in organizational or workplace settings, particularly without the intervention of external educational providers, is minimal. The Special Issue of the Journal of Business Ethics is the first to address this significant lacuna. The vast majority of published peer-reviewed research is related to organizational provider-centric organizing for responsible management education. Each category is explored and the implications of organizing the literature this way for the field of RMLE are discussed. Finally, an agenda for future research and theory development on RMLE is proposed. (shrink)

The purpose of this study was to examine the role of personality traits on academic performance. Furthermore, this study also aims at exploring the effects of virtual experience and emotional intelligence between personality traits and academic performance of the students. The findings imply that personality traits are the strong predictors of better academic performance. However, several personality traits do not have a positive impact on the academic performance. The study further suggests that students who have emotional abilities and virtual (...) experience are more likely to perform well in their academics. The population of this research consists of students in various colleges and universities in developing regions. Thus, the sample consists of bachelor's and master's students. Existing scales are adopted with minor changes to make it more suitable and understandable within the study context. A total of 319 questionnaires were distributed. Among these 365 questionnaires, 234 questionnaires were received and further used for the purpose of data analysis. This shows an encouraging response from the targeted sample. Education and productivity of the students are influenced by their personality as well as their emotional intelligence abilities. The findings imply that being extrovert is a strong predictor of student achievement and should be prioritized in intervention strategies. This personality feature is responsible for performance in addition to virtual learning experience. Despite its low overall relative value, agreeableness is a significant driver of student achievement. Along with ability and aptitude assessments, personality evaluations might be utilized as a secondary screening tool to identify adolescents at risk of underperformance and academic performance failure. Therefore, learning emotional skills would be beneficial to cope the modern challenges of the competitive educational environment. Virtual experience and being emotionally sound can help students to learn quickly and to be more adaptive into the new world of digitalization. The conclusions of the current study have significant consequences for educators and policymakers. They must accept that boosting emotional intelligence levels through teaching or training is a significant objective of contemporary education. The emotional intelligence abilities of the students related to culture may be shown in a variety of ways, from expectations toward students to interpersonal interactions with students, and from teaching techniques to evaluation methods. (shrink)

We present a novel methodology for building humanlike artificially intelligent systems. We take as a model the only existing systems which are universally accepted as intelligent: humans. We emphasize building intelligent systems which are not masters of a single domain, but, like humans, are adept at performing a variety of complex tasks in the real world. Using evidence from cognitive science and neuroscience, we suggest four alternative essences of intelligence to those held by classical AI. These are the parallel (...) themes of development, social interaction, embodiment, and integration. Following a methodology based on these themes, we have built a physical humanoid robot. In this paper we present our methodology and the insights it affords for facilitating learning, simplifying the computation underlying rich behavior, and building systems that can scale to more complex tasks in more challenging environments. (shrink)

ABSTRACT: This article addresses two main concerns: first, the relation between the truth/falsehood and purity/impurity criteria as applied to pleasure, and, second, the status of our pleasures of learning. In addressing the first, I argue that Plato keeps the truth/falsehood and purity/impurity criteria distinct in his assessment of pleasures and thus leaves room for the possibility of hybrid pleasures in the form of true impure pleasures and false pure pleasures. In addressing the second issue, I show that Plato's view (...) is perfectly able to accommodate an understanding of our pleasures of learning as pure pleasures even if such pleasures are preceded by awareness of a lack (ignorance).RÉSUMÉ: Cet article aborde deux concepts principaux: premièrement, la relation entre les critères de vérité/fausseté et de pureté/impureté appliqués au plaisir, et deuxièmement, le statut de notre plaisir d'apprendre. En abordant le premier concept, j'argumente que Platon tient distincts les critères de vérité/fausseté et de'pureté Iimpureté dans son évaluation du plaisir, laissant ouverte la possibilité de plaisirs hybrides sous forme de vrais plaisirs impurs et faux plaisirs purs. En abordant le deuxième concept, je montre que le point de vue de Platon est parfaitement capable d'accommoder la compréhension de nos plaisirs d'apprendre comme plaisirs purs si de tels plaisirs sont précédés par la conscience d'un manque (ignorance). (shrink)

In this article, I establish a theory of knowledge approach for evaluating the use of computers for educational purposes at the university. In so doing, I trace part of the history of the “enabling factor” of Artificial Intelligence in this sector, an important element that has been integrated into everyday learning environments. The result of my reflection is a dialogical structure, directly inspired by past technology assessment research, which illustrates the conceptual advancement of researchers in the field of (...) learning technologies. The notions covered have implications in future policy-related discourse with regards to education. (shrink)

Abstract:Artificial intelligence is profoundly transforming the world in various spheres and already finding its way into educational institutions. This essay aims to examine whether the Deweyan ideal of education can be achieved through such digital means. By analyzing how both the aims and means of education, as defined by Dewey, can be understood in the context of learning with artificial intelligence, the inherent differences of both educational approaches are brought out. It becomes apparent that important concepts that (...) characterize successful education for Dewey, such as intrinsic inquiry, experience-based schooling, and thinking as the method for learning, do not go hand in hand with intelligent teaching systems. (shrink)

Over the last two decades the traditional conception of intelligence and other mental powers as stable individual assets has been challenged by approaches in psychology emphasising context and ‘situated cognition’. This paper argues that the debate should not be seen as an empirical dispute, and relates it to discussions in philosophy of mind between methodological solipsists and varieties of externalists. In the light of this I argue that attempts to conceptualise the identity over time of mental powers qua (...) individual assets run into intractable difficulties. Hence ‘individual asset’ views of many abilities should be abandoned. Implications for education policy particularly in regard to assessment are explored. (shrink)

Over the last two decades the traditional conception of intelligence and other mental powers as stable individual assets has been challenged by approaches in psychology emphasising context and ‘situated cognition’. This paper argues that the debate should not be seen as an empirical dispute, and relates it to discussions in philosophy of mind between methodological solipsists and varieties of externalists. In the light of this I argue that attempts to conceptualise the identity over time of mental powers qua (...) individual assets run into intractable difficulties. Hence ‘individual asset’ views of many abilities should be abandoned. Implications for education policy particularly in regard to assessment are explored. (shrink)

The application of machine learning and artificial intelligence in healthcare domains has received much attention in recent years, yet significant questions remain about how these new tools integrate into frontline user workflow, and how their design will impact implementation. Lack of acceptance among clinicians is a major barrier to the translation of healthcare innovations into clinical practice. In this systematic review, we examine when and how clinicians are consulted about their needs and desires for clinical AI tools. Forty-five (...) articles met criteria for inclusion, of which 24 were considered design studies. The design studies used a variety of methods to solicit and gather user feedback, with interviews, surveys, and user evaluations. Our findings show that tool designers consult clinicians at various but inconsistent points during the design process, and most typically at later stages in the design cycle. We also observed a smaller amount of studies adopting a human-centered approach and where clinician input was solicited throughout the design process. A third of all studies reported on clinician trust in clinical AI algorithms and tools. The surveyed articles did not universally report validation against the “gold standard” of clinical expertise or provide detailed descriptions of the algorithms or computational methods used in their work. To realize the full potential of AI tools within healthcare settings, our review suggests there are opportunities to more thoroughly integrate frontline users’ needs and feedback in the design process. (shrink)

The phrase ‘mathematical foundation’ has shifted in meaning since the end of the nineteenth century. It used to mean a consistent general theory in mathematics, based on basic principles and ideas to which the rest of mathematics could be reduced. There was supposed to be only one foundational theory and it was to carry the philosophical weight of giving the ultimate ontology and truth of mathematics. Under this conception of ‘foundation’ pluralism in foundations of mathematics is a contradiction.More recently, the (...) phrase has come to mean a perspective from which we can see, or in which we can interpret, much of mathematics; it has lost the realist-type metaphysical, essentialist importance. The latter has been replaced with an emphasis on epistemology. The more recent use of the phrase shows a lack of concern for absolute ontology, truth, uniqueness and sometimes even consistency. It is only under the more modern conception of ‘foundation’ that pluralism in mathematical foundations is conceptually possible.Several problems beset the pluralist in mathematical foundations. The problems include, at least: paradox, rampant relativism, loss of meaning, insurmountable complexity and a rising suspicion that we can say anything meaningful about truth and objectivity in mathematics. Many of these are related to each other, and many can be overcome, explained, accounted for and dissolved by concentrating on crosschecking, fixtures and rigour of proof. Moreover, apart from being a defensible position, there are a lot of advantages to pluralism in foundations. These include: a sensitivity to the practice of mathematics, a more faithful account of the objectivity of mathematics and a deeper understanding of mathematics.The claim I defend in the paper is that we stand to learn more, not less, by adopting a pluralist attitude. I defend the claim by looking at the examples of set theory and homotopy type theory, as alternative viewpoints from which we can learn about mathematics. As the claim is defended, it will become apparent that ‘pluralism in mathematical foundations’ is neither an oxymoron, nor a contradiction, at least not in any threatening sense. On the contrary, it is the tension between different foundations that spurs new developments in mathematics. The tension might be called ‘a fruitful meta-contradiction’.I take my prompts from Kauffman’s idea of eigenform, Hersh’s idea of thinking of mathematical theories as models and from my own philosophical position: pluralism in mathematics. I also take some hints from the literature on philosophy of chemistry, especially the pluralism of Chang and Schummer. (shrink)

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession of a few general and uniform principles. The paper also provides a unifying thread to a variety of recent approaches to natural language comprehension. We conclude (...) with a brief discussion of how Artificial Intelligence may have a radical impact on education if the principles which it utilizes to explore the representation and use of knowledge are made available to the student to use in his own learning experiences. (shrink)

Test domains for AI can have a deep impact on research. The polyflap domain is proposed for testing complex AI theories about architectures, mechanisms and forms of representation involved in features of human and animal intelligence that evolved to enable perception, action, and learning in diverse environments containing things that we can perceive and manipulate, and many complex processes involving objects that differ in shape, materials, causal properties, and relations to one another. We need a test environment that (...) is rich enough to provide some of that variety of structures, processes and affordances, yet simple enough to be within reach of robotics research in the not too distant future. (shrink)

We argued [Since this argument appeared in other journals, I am reprising it here, almost verbatim.] (Fulda in J Law Info Sci 2:230–232, 1991/AI & Soc 8(4):357–359, 1994) that the paradox of the preface suggests a reason why machines cannot, will not, and should not be allowed to judge criminal cases. The argument merely shows that they cannot now and will not soon or easily be so allowed. The author, in fact, now believes that when—and only when—they are ready they (...) actually should be so allowed, in the interests of justice. Both the original argument applied and this detailed reconsideration applies exclusively to trial courts, and both specifically exclude(d) sentencing. The argument highlights some key relevant differences between minds and machines and attempts, also, to explain why automation is of far greater import for the first-level justice system (trial courts) than for higher courts. A final section discusses why sentencing was, is, and should be excluded. (shrink)

Epistemics as a whole would have a larger scope, encompassing secondary as well as primary individual epistemology and social epistemology in addition. There are a variety of terms of intellectual evaluation, many of interest to epistemology. The ones most commonly used in the discipline are ‘justified’ and ‘rational.’ Another central term of intellectual appraisal, which oddly has received only scant attention in the field, is ‘intelligent.’ Epistemology should be concerned with this range of intellectual assessments. Ethics distinguishes consequentialist and deontological (...) types of theories, and epistemology can utilize the distinction. Which cognitive processes are available, and which are to be approved, are matters that can only be settled with the help of cognitive science. An important distinction drawn in Epistemology and Cognition is the distinction between processes and methods of belief formation. Processes are basic psychological operations, either innate parts of our cognitive architecture or merely the results of maturation as opposed to learning. (shrink)

Artificial Intelligence (AI), especially of the machine learning (ML) variety, is used by health care organizations to assist with a number of tasks, including diagnosing patients and optimizing operational workflows. AI products already proliferate the health care market, with usage increasing as the technology matures. Although AI may potentially revolutionize health care, the use of AI in health settings also leads to risks ranging from violating patient privacy to implementing a biased algorithm. This chapter begins with a broad (...) overview of health care AI and how it is currently used. We then adopt a “lifecycle” approach to discussing issues with health care AI. We start by discussing the legal and ethical issues pertaining to how data to build AI are gathered in health care settings, focusing on privacy. Next, we turn to issues in algorithm development, especially algorithmic bias. We then discuss AI deployment to treat patients, focusing on informed consent. Finally, we will discuss existing oversight mechanisms for health AI in the United States: liability and regulation. (shrink)

Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and ‎Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part (...) of general intelligence. Emotional intelligence can be defined as an ability of a human to perceive oneself and interact with others with the help of obtained and processed emotional information. Language acquisition is mediated by the necessity to communicate with others. Consequently, the ability to manage the process of communication is of utmost importance in learning a language. Virtual learning environment reduces dramatically the immediate interaction of the participants of the process of education. It undoubtedly affects the process of acquisition and demands to reconsider the distribution of different learning activities. (shrink)

Position papers on artificial intelligence (AI) ethics are often framed as attempts to work out technical and regulatory strategies for attaining what is commonly called trustworthy AI. In such papers, the technical and regulatory strategies are frequently analyzed in detail, but the concept of trustworthy AI is not. As a result, it remains unclear. This paper lays out a variety of possible interpretations of the concept and concludes that none of them is appropriate. The central problem is that, by (...) framing the ethics of AI in terms of trustworthiness, we reinforce unjustified anthropocentric assumptions that stand in the way of clear analysis. Furthermore, even if we insist on a purely epistemic interpretation of the concept, according to which trustworthiness just means measurable reliability, it turns out that the analysis will, nevertheless, suffer from a subtle form of anthropocentrism. The paper goes on to develop the concept of strange error, which serves both to sharpen the initial diagnosis of the inadequacy of trustworthy AI and to articulate the novel epistemological situation created by the use of AI. The paper concludes with a discussion of how strange error puts pressure on standard practices of assessing moral culpability, particularly in the context of medicine. (shrink)

Judgments concerning animals have arisen across a variety of established practice areas. There is, however, no publicly available repository of judgments concerning the emerging practice area of animal protection law. This has hindered the identification of individual animal protection law judgments and comprehension of the scale of animal protection law made by courts. Thus, we detail the creation of an initial animal protection law repository using natural language processing and machine learning techniques. This involved domain expert classification of 500 (...) judgments according to whether or not they were concerned with animal protection law. 400 of these judgments were used to train various models, each of which was used to predict the classification of the remaining 100 judgments. The predictions of each model were superior to a baseline measure intended to mimic current searching practice, with the best performing model being a support vector machine (SVM) approach that classified judgments according to term frequency—inverse document frequency (TF-IDF) values. Investigation of this model consisted of considering its most influential features and conducting an error analysis of all incorrectly predicted judgments. This showed the features indicative of animal protection law judgments to include terms such as ‘welfare’, ‘hunt’ and ‘cull’, and that incorrectly predicted judgments were often deemed marginal decisions by the domain expert. The TF-IDF SVM was then used to classify non-labelled judgments, resulting in an initial animal protection law repository. Inspection of this repository suggested that there were 175 animal protection judgments between January 2000 and December 2020 from the Privy Council, House of Lords, Supreme Court and upper England and Wales courts. (shrink)

Written by leading researchers in educational and social psychology, learning science, and neuroscience, this edited volume is suitable for a wide-academic readership. It gives definitions of key terms related to motivation and learning alongside developed explanations of significant findings in the field. It also presents cohesive descriptions concerning how motivation relates to learning, and produces a novel and insightful combination of issues and findings from studies of motivation and/or learning across the authors' collective range of scientific (...) fields. The authors provide a variety of perspectives on motivational constructs and their measurement, which can be used by multiple and distinct scientific communities, both basic and applied. (shrink)

While an increasing number of organizations have introduced artificial intelligence as an important facilitating tool for learning online, the application of artificial intelligence in e-learning has become a hot topic for research in recent years. Over the past few decades, the importance of online learning has also been a concern in many fields, such as technological education, STEAM, AR/VR apps, online learning, amongst others. To effectively explore research trends in this area, the current state (...) of online learning should be understood. Systematic bibliometric analysis can address this problem by providing information on publishing trends and their relevance in various topics. In this study, the literary application of artificial intelligence combined with online learning from 2010 to 2021 was analyzed. In total, 64 articles were collected to analyze the most productive countries, universities, authors, journals and publications in the field of artificial intelligence combined with online learning using VOSviewer through WOS data collection. In addition, the mapping of co-citation and co-occurrence was explored by analyzing a knowledge map. The main objective of this study is to provide an overview of the trends and pathways in artificial intelligence and online learning to help researchers understand global trends and future research directions. (shrink)

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic (...) Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks. (shrink)

This study investigates the use of musical intelligence to improve the English pronunciation of Chinese third level students. It is relevant for a human-centred systems engineering approach to cross-cultural interaction. Language learning is important as valid communication can help interactions and cultural understanding between countries, this also may benefit international stability. There are natural barriers between the English and Chinese language which are reflected in teaching approaches. The teaching of English in Chinese classrooms is removed from real-world English (...) learning environments. The academic environments and approaches focus on the learning of grammar, spelling and writing with little real-life conversation and interaction with native English speakers. English language learning in China is from a more academic perspective rather than practical utilisation. Correct pronunciation and accent is therefore diminished. This study demonstrates that a musical intelligence e-Learning approach can benefit Chinese English language students. (shrink)

Artificial Neural Networks have reached “grandmaster” and even “super-human” performance across a variety of games, from those involving perfect information, such as Go, to those involving imperfect information, such as “Starcraft”. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong—an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, automated credit-scoring (...) processes “discriminate” on gender, etc.—there are often significant financial, legal, and brand consequences, and the incident becomes major news. As Judea Pearl sees it, the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” —the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for theNew York Times: “we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets—often using an approach known as ‘Deep Learning’—and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space, and causality.” In this paper, foregrounding what in 1949 Gilbert Ryle termed “a category mistake”, I will offer an alternative explanation for AI errors; it is not so much that AI machinery cannot “grasp” causality, but that AI machinery (qua computation) cannot understand anything at all. (shrink)

The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal (...) precedents, the practice of software engineering, historical attitudes towards technological innovation and a sustained technical analysis of the models themselves. This paper queries the location and nature of substantive artistic work in the developmental stages of an AI-generated image, offering critiques of existing assumptions and posing questions for future research. The emergence of convincing AI creative output, artistic or literary, has significant long-term implications for the humanities, including the need for re-appraisal of foundational ideas about authorship and creativity in general. The effects of artificial intelligence, whether generalised or task-specific, cannot be ignored or displaced now that easy-access, scalable image and text production is a reality. (shrink)

Historically, the dispute between empiricists and nativists in philosophy and cognitive science has concerned human and animal minds (Margolis and Laurence in Philos Stud: An Int J Philos Anal Tradit 165(2): 693-718, 2013, Ritchie in Synthese 199(Suppl 1): 159–176, 2021, Colombo in Synthese 195: 4817–4838, 2018). But recent progress has highlighted how empiricist and nativist concerns arise in the construction of artificial systems (Buckner in From deep learning to rational machines: What the history of philosophy can teach us about (...) the future of artificial intelligence. Oxford University Press.). This paper uses nativism and empiricism to address questions about the nature of artificial intelligence and its trajectory. It begins by defining the nativism/empiricism debate in terms of the generality of a system. Nativist systems have initial states with domain-specific features; empiricist systems have initial states with only domain-general features. With the debate framed in this way, it then explores a variety of arguments for nativism and empiricism in AI. These arguments revolve around two different questions which must be distinguished: whether nativism the only possible approach to developing human-level AI (HLAI); and whether nativism is the most practical approach to developing HLAI. On the first question, it argues that nativism is quite clearly not the only possible approach to developing HLAI, as is sometimes suggested. It argues that existing arguments for the necessity of nativism are unconvincing, because they analogize from poverty of the stimulus arguments about humans, while AIs often have access to much more data than humans. Then it argues that the case of evolution gives us a compelling argument against nativism. On the second, practical question, the paper argues that there is a tradeoff between the advantages of encoding innate machinery directly, and the advantages of evolving or learning it. However, as the past decade has shown, empiricism is a much more viable path to greater capability levels, given the ‘bitter lesson’ (Sutton in _Reinforcement Learning: An Introduction_. MIT press.) that encoding the ‘correct’ knowledge in AI systems is perennially outperformed by more empiricist methods that leverage large-scale data and computation. (shrink)

Written by leading researchers in educational and social psychology, learning science, and neuroscience, this edited volume is suitable for a wide-academic readership. It gives definitions of key terms related to motivation and learning alongside developed explanations of significant findings in the field. It also presents cohesive descriptions concerning how motivation relates to learning, and produces a novel and insightful combination of issues and findings from studies of motivation and/or learning across the authors' collective range of scientific (...) fields. The authors provide a variety of perspectives on motivational constructs and their measurement, which can be used by multiple and distinct scientific communities, both basic and applied. (shrink)

The article summarizes the theoretical and methodological knowledge about ecotourism as one of the viable types of tourism in the postmodern era, clarifies the patterns of its formation and development, a variety of approaches to its interpretation, interaction with other types of tourism, features of motivation and management in ecotourism. On the basis of the generalized data a number of perspective educational conditions is modeled: the orientation of the maintenance of pedagogical education on formation of steady positive motivation; updating the (...) content of professional training; availability of educational and methodical support; interrelation of competence, system and personal-activity approaches. Diagnostic methods relevant for postmodern education are selected: methods of diagnosing students' learning motivation; methods of diagnosis of value orientations in career; tests to determine the levels of formation of the components of professional competence. It is proved that the professional training of teachers who are able to use ecological tourism in their professional activities at a high level is one of the important conditions for increasing the interest of children and young people in physical education, tourism and sports, ensuring the necessary physical activity, developing, maintaining and strengthening their health, adaptation to the flexible postmodern society. (shrink)

Mankind’s research on marketing has a history of hundreds of years, and it has been fruitful in continuous summary and research. Now the theory of marketing has gradually penetrated into the minds of every company and even individual. A successful marketing strategy is the inevitable result of scientific planning and effective implementation. However, the current marketing strategy has gradually failed to meet the needs of corporates. In order to find the best solution for corporate marketing strategy, we built a simulation (...) environment based on mobile computing and machine learning and compared the differences by simulating several companies of the same size in this city. The results of the study found that intelligent marketing based on machine learning is more suitable for enterprises than general marketing strategies. The efficiency of enterprises has increased by about 20%, and the income of enterprises has increased by more than 30% compared with traditional marketing strategies. This shows that the intelligent marketing strategy based on mobile computing and machine learning to build a simulated environment plays an extremely important role in the peculiarities. (shrink)

Between 1900 and 1925, the American economy witnessed a remarkably successful effort to upgrade competition through associations. Unlike the prevailing interpretation of American industrialization, in which associations fell prey to antitrust and collective action problems, we find many associations that reinvented themselves from cartels to developmental associations. This transition marked two previously unrecognized varieties in economic institutions. In the first, associations joined markets and corporate hierarchies to create variety in American capitalism. In the second, associations used deliberation, cost accounting, (...) and benchmarking to enhance productivity and create varieties of collective governance. This article explains the origins of developmental associations, outlines their principles, traces their implementation in the commercial printing industry, and surveys their distribution and performance effects across 344 industries. Based on these findings, we revise conventional institutionalist assumptions about order and agency to make room for institutional diversity and actors’ capacities for reflexivity and learning. (shrink)

Through an international case study, this paper illustrates how a conversation method was used effectively to address a cross-cultural ethics problem. The method included as moments in one continuous process three different dimensions of postmodernism-Gadamer reconstruction, Derrida deconstruction, and Rorty neopragmatism. In addition to including different dimensions of postmodernism, the method combines effective mutual learning and effective action. Strengths and limitations of the approach are discussed. The article demonstrates how it can be beneficial to build bridges between and within (...) the postmodernism and organization ethics literatures. Also, the article demonstrates how postmodernism can be positively ethical and not necessarily aethical or nihilistic. (shrink)

Forms of justification for inductive machine learning techniques are discussed and classified into four types. This is done with a view to introduce some of these techniques and their justificatory guarantees to the attention of philosophers, and to initiate a discussion as to whether they must be treated separately or rather can be viewed consistently from within a single framework.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are 'black boxes'. The initial response in the literature was a demand for 'explainable AI'. However, recently, several authors have suggested that making AI more explainable or 'interpretable' is likely to be at the cost of the accuracy of these systems and that prioritising interpretability in medical AI may constitute a 'lethal prejudice'. In this paper, we defend the value of (...) interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realised. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems , may itself constitute a form of lethal prejudice that may diminish the benefits of AI to - and perhaps even harm - patients. (shrink)

Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and ‎Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part (...) of general intelligence. Emotional intelligence can be defined as an ability of a human to perceive oneself and interact with others with the help of obtained and processed emotional information. Language acquisition is mediated by the necessity to communicate with others. Consequently, the ability to manage the process of communication is of utmost importance in learning a language. Virtual learning environment reduces dramatically the immediate interaction of the participants of the process of education. It undoubtedly affects the process of acquisition and demands to reconsider the distribution of different learning activities. (shrink)

This article explores Academic Service Learning as a teaching method which bridges the gap between academic requirements for learning and the need of society to have individuals willing to give their time and effort to benefit others in need. Students as part of a course learning requirement engaged in a consulting project whereby a non-profit organization was advised on both short term and long term planning. Students were exposed to the operational needs of the organization as well (...) as the dependency of the needy on their services. A pre- and post- survey was administered which focused on any perceived changes in Emotional Intelligence experienced by the students upon completion of the project. The results indicated that student’s EI was affected by the learning project in terms of how they feel about themselves and their overall effort levels. (shrink)

Context: Over a thirteen-year period Ernst von Glasersfeld directly answered a wide diversity of questions posed to him on the Oikos web site. Purpose: This is the fourth and final article in a series that is based on a selection from all of the questions posed in the thirteen-year period and is aimed at giving prominence to key aspects of his radical constructivist approach. Method: This article deals with the issue of “change,” divided into the two main themes of (i) (...) viability as defined by von Glasersfeld and (ii. the processes of personal learning and change. Implications: This ultimate article of this series offers an important source of original material for those readers who are seeking to elaborate their understanding of radical constructivism. (shrink)

Connectionist models provide a promising alternative to the traditional computational approach that has for several decades dominated cognitive science and artificial intelligence, although the nature of connectionist models and their relation to symbol processing remains controversial. Connectionist models can be characterized by three general computational features: distinct layers of interconnected units, recursive rules for updating the strengths of the connections during learning, and “simple” homogeneous computing elements. Using just these three features one can construct surprisingly elegant and powerful (...) models of memory, perception, motor control, categorization, and reasoning. What makes the connectionist approach unique is not its variety of representational possibilities or its departure from explicit rule-based models, or even its preoccupation with the brain metaphor. Rather, it is that connectionist models can be used to explore systematically the complex interaction between learning and representation, as we try to demonstrate through the analysis of several large networks. (shrink)