Background Nurses are the main protectors of goodness, honesty and morality in patient care. Conscience allows nurses to be understanding and careful while they provide patient care. In this research the researcher aimed to determine the relationship between conscientious intelligence levels and caring behaviours of nurses and to determine the factors affecting the conscientious intelligence levels and caring behaviours. Methods This research designed as a descriptive, cross-sectional and correlation study included 314 nurses working at three hospitals in eastern (...) Turkey. The data were collected by the researcher at a time when the nurses were available and not working. Written and oral informed consent was obtained from all the participants. Results A moderate significant positive correlation was observed between conscientious intelligence levels and caring behaviours of nurses. The length of service in nursing, sex and being pleased with the nursing profession were associated with conscientious intelligence levels and caring behaviours. Conclusion At the end of this research, it was determined that nurses with high conscientious intelligence had better caring behaviours. Although it is very important for nurses to be knowledgeable of and competent at providing care, taking their conscience into consideration in the care of his or her patients is more important. If a nurse is not pleased with the nursing profession, his or her behaviour should be monitored when he or she provides care for the patient. Persons without conscientious values should not be accepted into the nursing profession. (shrink)

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system’s ability to care for people with chronic and degenerative conditions, including Parkinson’s Disease (PD). This paper reports the themes and lessons derived from a qualitative study with people living with PD, family caregivers, and health care providers regarding the ethical dimensions of using AI to monitor, assess, and predict PD symptoms and progression. Thematic analysis identified ethical concerns at four (...) intersecting levels: personal, interpersonal, professional/institutional, and societal levels. Reflecting on potential benefits of predictive algorithms that can continuously collect and process longitudinal data, participants expressed a desire for more timely, ongoing, and accurate information that could enhance management of day-to-day fluctuations and facilitate clinical and personal care as their disease progresses. Nonetheless, they voiced concerns about intersecting ethical questions around evolving illness identities, familial and professional care relationships, privacy, and data ownership/governance. The multi-layer analysis provides a helpful way to understand the ethics of using AI in monitoring and managing PD and other chronic/degenerative conditions. (shrink)

here has been a large number of studies in neurological sciences on how human brain works, especially in reading and parallel information processing. So I think this statement is really sweeping. Perhaps it is better to knowledge the abilities of human brains and to comment on the limitations of the human brain. The book “Adapt” by Tim Hartford advocates micro-step changes. An important aspect in this area is to understand the processes involved behind the scenes so that it gives us (...) a better formulation of the creativity algorithms involved. I will try to put in some pointers on the depths to which higher level intelligence has been simulated by AI in the past years. Some of the higher level intelligence mechanisms such as creativity, dreams and logical thinking have been implemented in machines in certain ways. However, they are still not implemented in the way humans do the same. The exact mechanism in which these intelligence mechanisms are used by human brains is still way ahead of that done by computers. However, we now look at other aspects in them as well as other functions which might be explored in the years ahead in AI. (shrink)

High-level perception--”the process of making sense of complex data at an abstract, conceptual level--”is fundamental to human cognition. Through high-level perception, chaotic environmen- tal stimuli are organized into the mental representations that are used throughout cognitive pro- cessing. Much work in traditional artificial intelligence has ignored the process of high-level perception, by starting with hand-coded representations. In this paper, we argue that this dis- missal of perceptual processes leads to distorted models of human cognition. We (...) examine some existing artificial-intelligence models--”notably BACON, a model of scientific discovery, and the Structure-Mapping Engine, a model of analogical thought--”and argue that these are flawed pre- cisely because they downplay the role of high-level perception. Further, we argue that perceptu- al processes cannot be separated from other cognitive processes even in principle, and therefore that traditional artificial-intelligence models cannot be defended by supposing the existence of a --œrepresentation module--� that supplies representations ready-made. Finally, we describe a model of high-level perception and analogical thought in which perceptual processing is integrated with analogical mapping, leading to the flexible build-up of representations appropriate to a given context. (shrink)

Definition of the problem The umbrella term “explicability” refers to the reduction of opacity of artificial intelligence (AI) systems. These efforts are challenging for medical AI applications because higher accuracy often comes at the cost of increased opacity. This entails ethical tensions because physicians and patients desire to trace how results are produced without compromising the performance of AI systems. The centrality of explicability within the informed consent process for medical AI systems compels an ethical reflection on the trade-offs. (...) Which levels of explicability are needed to obtain informed consent when utilizing medical AI? Arguments We proceed in five steps: First, we map the terms commonly associated with explicability as described in the ethics and computer science literature, i.e., disclosure, intelligibility, interpretability, and explainability. Second, we conduct a conceptual analysis of the ethical requirements for explicability when it comes to informed consent. Third, we distinguish hurdles for explicability in terms of epistemic and explanatory opacity. Fourth, this then allows to conclude the level of explicability physicians must reach and what patients can expect. In a final step, we show how the identified levels of explicability can technically be met from the perspective of computer science. Throughout our work, we take diagnostic AI systems in radiology as an example. Conclusion We determined four levels of explicability that need to be distinguished for ethically defensible informed consent processes and showed how developers of medical AI can technically meet these requirements. (shrink)

Background Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are being increasingly introduced into various domains of health care for diagnostic, prognostic, therapeutic and other purposes. A significant part of the discourse on ethically appropriate conditions relate to the levels of understanding and explicability needed for ensuring responsible clinical decision-making when using AI-CDSS. Empirical evidence on stakeholders’ viewpoints on these issues is scarce so far. The present study complements the empirical-ethical body of research by, on the one hand, investigating the (...) requirements for understanding and explicability in depth with regard to the rationale behind them. On the other hand, it surveys medical students at the end of their studies as stakeholders, of whom little data is available so far, but for whom AI-CDSS will be an important part of their medical practice. Methods Fifteen semi-structured qualitative interviews (each lasting an average of 56 min) were conducted with German medical students to investigate their perspectives and attitudes on the use of AI-CDSS. The problem-centred interviews draw on two hypothetical case vignettes of AI-CDSS employed in nephrology and surgery. Interviewees’ perceptions and convictions of their own clinical role and responsibilities in dealing with AI-CDSS were elicited as well as viewpoints on explicability as well as the necessary level of understanding and competencies needed on the clinicians’ side. The qualitative data were analysed according to key principles of qualitative content analysis (Kuckartz). Results In response to the central question about the necessary understanding of AI-CDSS tools and the emergence of their outputs as well as the reasons for the requirements placed on them, two types of argumentation could be differentiated inductively from the interviewees’ statements: the first type, the clinician as a systemic trustee (or “the one relying”), highlights that there needs to be empirical evidence and adequate approval processes that guarantee minimised harm and a clinical benefit from the employment of an AI-CDSS. Based on proof of these requirements, the use of an AI-CDSS would be appropriate, as according to “the one relying”, clinicians should choose those measures that statistically cause the least harm. The second type, the clinician as an individual expert (or “the one controlling”), sets higher prerequisites that go beyond ensuring empirical evidence and adequate approval processes. These higher prerequisites relate to the clinician’s necessary level of competence and understanding of how a specific AI-CDSS works and how to use it properly in order to evaluate its outputs and to mitigate potential risks for the individual patient. Both types are unified in their high esteem of evidence-based clinical practice and the need to communicate with the patient on the use of medical AI. However, the interviewees’ different conceptions of the clinician’s role and responsibilities cause them to have different requirements regarding the clinician’s understanding and explicability of an AI-CDSS beyond the proof of benefit. Conclusions The study results highlight two different types among (future) clinicians regarding their view of the necessary levels of understanding and competence. These findings should inform the debate on appropriate training programmes and professional standards (e.g. clinical practice guidelines) that enable the safe and effective clinical employment of AI-CDSS in various clinical fields. While current approaches search for appropriate minimum requirements of the necessary understanding and competence, the differences between (future) clinicians in terms of their information and understanding needs described here can lead to more differentiated approaches to solutions. (shrink)

Both direct, and evolved, behavior-based approaches to mobile robots have yielded a number of interesting demonstrations of robots that navigate, map, plan and operate in the real world. The work can best be described as attempts to emulate insect level locomotion and navigation, with very little work on behavior-based non-trivial manipulation of the world. There have been some behavior-based attempts at exploring social interactions, but these too have been modeled after the sorts of social interactions we see in insects. (...) But thinking how to scale from all this insect level work to full human level intelligence and social interactions leads to a synthesis that is very different from that imagined in traditional Artificial Intelligence and Cognitive Science. We report on work towards that goal. (shrink)

In this research work, a user-friendly decision support framework is developed to analyze the behavior of Pakistani students in academics. The purpose of this article is to analyze the performance of the Pakistani students using an intelligent decision support system (DSS) based on the three-level machine learning (ML) technique. The neural network used a three-level classifier approach for the prediction of Pakistani student achievement. A self-recorded dataset of 1,011 respondents of graduate students of English and Physics courses are (...) used. The ten interviews along with ten questions were conducted to determine the perception of the individual student. The chi-squared ( χ ) \left(\chi ) test was applied to test statistical significancy of the questionnaire. The statistical calculations and computation of data were performed by using the statistical package of IBMM SPSS version 21.0. The seven different algorithms were tested to improve the data classification. The Java-based environment was used for the development of numerous prediction classifiers. C4.5 algorithm shows the finest accuracy, whereas Naïve Bayes (NB) algorithm shows the least. The results depict that the classifier’s efficiency was improved by using a three-level proposed scheme from 83.2% to 88.8%. This prediction has shown remarkable results when compared with the individual level classifier technique of ML. This improvement in the accuracy of DSSs is used to identify more efficiently the gray areas in the education stratum of Pakistan. This will pave a path for making policies in the higher education system of Pakistan. The presented framework can be deployed on different platforms under numerous operating systems. (shrink)

Following the studies of Araujo et al. (AI Soc 35:611–623, 2020) and Lee (Big Data Soc 5:1–16, 2018), this empirical study uses two scenario-based online experiments. The sample consists of 221 subjects from Germany, differing in both age and gender. The original studies are not replicated one-to-one. New scenarios are constructed as realistically as possible and focused on everyday work situations. They are based on the AI acceptance model of Scheuer (Grundlagen intelligenter KI-Assistenten und deren vertrauensvolle Nutzung. Springer, Wiesbaden, 2020) (...) and are extended by individual descriptive elements of AI systems in comparison to the original studies. The first online experiment examines decisions made by artificial intelligence with varying degrees of impact. In the high-impact scenario, applicants are automatically selected for a job and immediately received an employment contract. In the low-impact scenario, three applicants are automatically invited for another interview. In addition, the relationship between age and risk perception is investigated. The second online experiment tests subjects’ perceived trust in decisions made by artificial intelligence, either semi-automatically through the assistance of human experts or fully automatically in comparison. Two task types are distinguished. The task type that requires “human skills”—represented as a performance evaluation situation—and the task type that requires “mechanical skills”—represented as a work distribution situation. In addition, the extent of negative emotions in automated decisions is investigated. The results are related to the findings of Araujo et al. (AI Soc 35:611–623, 2020) and Lee (Big Data Soc 5:1–16, 2018). Implications for further research activities and practical relevance are discussed. (shrink)

Research into artificial intelligence has increased significantly in recent years. However, the fundamental question of what intelligence is and how it works remains open to some extent. Traditional definitions of intelligence are broad and lack clarity regarding its nature and mechanisms. The nature of consciousness is another matter that has been widely explored with multiple theories but for which we do not have a final agreed theory, especially in terms of its relation to intelligence. In this (...) work, we present a preliminary theory of the nature of intelligence and its working mechanisms. We contrast it against observations to show that our theory is consistent with observed reality. We also use our theory of intelligence to offer a theory on the nature of consciousness, as well as its relation to human understanding and intent. We then show that our theories can be consistent with the theory of evolution. Similarly, we explore examples of how our theory applies to specific cases to show its consistency across applications. Lastly, we outline how our theory can pave the way towards artificial general intelligence. Our theory is unproven. (shrink)

A large part of technological advances, especially in the field of industry, have been focused on the optimization of productive processes. However, the detection of anomalies has turned out to be a great challenge in fields like industry, medicine or stock markets. The present work addresses anomaly detection on a control level plant. We propose the application of different intelligent techniques, which allow to obtain one-class classifiers using real data taken from the correct plant operation. The performance of each (...) classifier is assessed and validated with real created faults, achieving successful overall results. (shrink)

Artificial intelligence is rapidly entering our daily lives in the form of driverless cars, automated online assistants and virtual reality experiences. In so doing, AI has already substituted human employment in areas that were previously thought to be uncomputerizable. Based on current trends, the technological displacement of labor is predicted to be significant in the future – if left unchecked this will lead to catastrophic societal unemployment levels. This paper presents a means to mitigate future technological unemployment through the (...) introduction of a Basic Income scheme, accompanied by reforms in school curricula and retraining programs. Our proposal argues that such a scheme can be funded by a special tax on those industries that make use of robotic labour; it includes a practical roadmap that would see a government take this proposal from the conceptual phase and implement it nationwide in the span of one decade. (shrink)

In the development of governmental policy for artificial intelligence that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, (...) elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: preliminary landscape assessments; multi-stakeholder participation and cross-sectoral feedback; and, mechanisms to support implementation and operationalizability. (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 (mediator) and emotional intelligence (moderator) 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)

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch (...) as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the design and evaluation of collective cognitive systems. For example, the notion of mandevillian intelligence forces us to take seriously the idea that the exploitation of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success. (shrink)

This article is the basis of an invited talk at KR-96 in 1996 November. It has been modified from the version that appeared in the preprints of that meeting. There is an html version, a.dvi version,.pdf version and a.ps version. Up to: Main McCarthy page Up to: Send comments to mccarthy @stanford.edu. I sometimes make changes suggested in them. - John McCarthy.

In this text, first published in 1993, Barrow decisively rejects the traditional assumption that intelligence has no educational significance and contends instead that intelligence is developed by the enlargement of understanding. Arguing that much educational research is driven by a concept of intelligence that has no obvious educational relevance, Dr Barrow suggests that this is partly due to a widespread lack of understanding about the nature and point of philosophical analysis, and partly due to a failure to (...) face up to the value judgements that are necessarily involved in analysing a concept such as intelligence. If intelligence is to be of educational significance, it must be understood in terms that allow it to be educable. Written by a philosopher of education, this study offers a reasoned and extended argument in favour of an original view of philosophical analysis. It focuses on the issue of intelligence from a philosophical perspective. It should be of interest to students of education, philosophy and the philosophy of education alike. (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design (...) of an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

In this paper, through the intelligent research of the whole process of logistics and distribution with the Internet of Things supply chain, we study how to improve the development of the cold chain, reduce the loss in circulation, improve the social and economic benefits, and carry out intelligent information collection, monitoring, management, and information tracing of the whole cold chain. This paper analyzes and empirically studies the impact of key technologies of the Internet of Things in cold chain coordination from (...) the perspective of building an intelligent cold chain coordination system with the Internet of Things technology. This paper analyzes the current situation of cold chain logistics and the impact that the application of IoT technology will have, explains that IoT technology can improve the intelligence level of the cold chain, and then introduces the application of intelligent cold chain logistics under IoT orientation, combining the process of cold chain logistics with the three-layer architecture of IoT technology. By extracting the key technologies of IoT perception layer, network layer, and intelligence layer, the intelligent cold chain coordination system based on IoT technology is constructed, and then, the correctness of the system is verified, to have some reference and evaluation for the cold chain construction. The system was then verified to have some reference and guidance significance for the construction and evaluation of the cold chain. The results of this paper are more accurate and more efficient. (shrink)

The current study investigated correlations among gifted students’ academic performance; emotional, social, analytical, creative, and practical intelligence; and their implicit theories of intelligence. Furthermore, it studied the effect of gender and grade on these variables. The participants included 174 gifted fifth and sixth grade students, comprising 53.4% male and 46.6% female. The following analytical, creative, and practical intelligence tests were administered: Aurora Battery, the emotional intelligence scale, the implicit theories of intelligence scale, and an assessment (...) scale of students’ performances. The results revealed significant correlations among academic performance, kinds of intelligence, and implicit theories of intelligence. There were no significant differences between the male and female students in these measures. There were, however, significant differences between the fifth and sixth grade students, with the sixth-grade students showing higher levels of all kinds of intelligence, except emotional intelligence. Moreover, the results indicated that the intelligence measures were non-significantly affected by either gender or gender–grade interaction. Overall, our results showed that most types of intelligence are related to giftedness, and that there were no gender differences among gifted students on measures of intelligence. (shrink)

The current study aimed at identifying the awareness level of artificial intelligence applications' risks among faculty members and its relation to the attitude towards digital culture at Imam Abdulrahman Bin Faisal University. The descriptive survey method was used. A questionnaire was designed to measure the awareness of the artificial intelligence applications' risks, and a scale for measuring the attitude towards digital culture. They were administered to a sample of [463] faculty members at Imam Abdulrahman Bin Faisal University. (...) The study concluded that there is an average awareness of the artificial intelligence applications' risks and the attitude towards digital culture among faculty members. A significant relationship was found out between awareness of the artificial intelligence applications' risks as a whole and the attitude towards digital culture. The results indicated that there are no differences in the awareness level of the artificial intelligence risks due to the variables of: gender, use duration of digital applications, and colleges. There are no differences in the variable of the attitude towards digital culture with its various dimensions: cognitive, psychomotor, and affective and its total score. The current study recommended designing a professional development plan for faculty members on the negative effects and risks of artificial intelligence, and launching an Arab platform based on artificial intelligence applications. (shrink)

In this paper, we examine the meta-ontology of AI systems with human-level intelligence, with us denoting such AI systems as AI E. Meta-ontology in philosophy is a discourse centered on ontology, ontological commitment, and the truth condition of ontological theories. We therefore discuss how meta-ontology is conceptualized for AI E systems. We posit that the meta-ontology of AI E systems is not concerned with computational representations of reality in the form of structures, data constructs, or computational concepts, while (...) the ontological commitment of AI E systems is directed toward what exists in the outside world. Furthermore, the truth condition of the ontology (which is meta-ontological assumption) of AI E systems does not require consistency with closed conceptual schema or ontological theories but rather with reality, or in other words, “what is the world” (Smith, 2019, p.57). In addition, the truth condition of AI E systems is verified through operational success rather than by coherence with theories. This work builds on ontological postulates about AI systems that were formulated by Brian Cantwell Smith (2019). (shrink)

Recently, Intelligent Tutoring Systems (ITS) got much attention from researchers even though ITS educational technology began in the late 1960s and ITS is just embryonic from laboratories into the field. In this paper we outline an intelligent tutoring system for teaching basics of the databases system called (MDB). The MDB was built as education system by using the authoring tool (ITSB). MDB contains learning materials as a group of lessons for beginner level which include relational database system and lessons (...) in the process to install and set up a database. MDB system has exams for each level of the Lessons. An evaluation was done to see the effectiveness the MDB among learners and instructors. The outcome of the evaluation was promising. (shrink)

A number of authors have agued the case that there is empirical evidence that the universe (or particular configurations within it) must be the outcome of intelligent design. Recent books by William Dembski and Dean Overman, though different in style and level of argumentation, reach a similar conclusion: the universe, or certain forms within it, cannot be explained without appeal to design as a mode of causation. But exactly what is the operative definition for intelligent design in these works? (...) And how convincing is their case for the necessity of appealing to this type of design in causal explanations? (shrink)

Intelligence, as measured by grades and/or standardized test scores, plays a principal role in the medical school admissions process in most nations. Yet while sufficient intelligence is necessary to practice medicine effectively, no evidence suggests that surplus intelligence beyond that threshold is correlated with providing higher quality medical care. This paper argues that using perceived measures of intelligence to distinguish between applicants, at levels that exceed the level of intelligence required to practice medicine, is (...) both unfair to applicants and fails to serve the interests of patients. (shrink)

ABSTRACTThe seeming distinction between motor and cognitive skills has hinged on the fact that the former are automatic and non-propositional, whereas the latter are slow and deliberative. Here, the physiological and behavioral phenomenon of long-latency stretch reflexes is used to show that “knowing-that” can be incorporated into “knowing-how,” either immediately or through learning. The experimental demonstration that slow computations can, with practice, be cached for fast retrieval, without the need for re-computation, dissolves the intellectualist/anti-intellectualist distinction: All complex human tasks, at (...) any level of expertise, are a combination of intelligent reflexes and deliberative decisions. (shrink)

In this article the central philosophical issues concerning human-level artificial intelligence (AI) are presented. AI largely changed direction in the 1980s and 1990s, concentrating on building domain-specific systems and on sub-goals such as self-organization, self-repair, and reliability. Computer scientists aimed to construct intelligence amplifiers for human beings, rather than imitation humans. Turing based his test on a computer-imitates-human game, describing three versions of this game in 1948, 1950, and 1952. The famous version appears in a 1950 article (...) in Mind, ‘Computing Machinery and Intelligence’ (Turing 1950). The interpretation of Turing's test is that it provides an operational definition of intelligence (or thinking) in machines, in terms of behavior. ‘Intelligent Machinery’ sets out the thesis that whether an entity is intelligent is determined in part by our responses to the entity's behavior. Wittgenstein frequently employed the idea of a human being acting like a reliable machine. A ‘living reading-machine’ is a human being or other creature that is given written signs, for example Chinese characters, arithmetical symbols, logical symbols, or musical notation, and who produces text spoken aloud, solutions to arithmetical problems, and proofs of logical theorems. Wittgenstein mentions that an entity that manipulates symbols genuinely reads only if he or she has a particular history, involving learning and training, and participates in a social environment that includes normative constraints and further uses of the symbols. (shrink)

This paper provides a philosophically informed and robust account of the global justice implications of Artificial Intelligence (AI). We first discuss some of the key theories of global justice, before justifying our focus on the Capabilities Approach as a useful framework for understanding the context-specific impacts of AI on low- to middle-income countries. We then highlight some of the harms and burdens facing low- to middle-income countries within the context of both AI use and the AI supply chain, by (...) analyzing the extraction of _materials_, which includes mineral extraction and the environmental harms associated with it, and the extraction of _labor_, which includes unethical labor practices, low wages, and the trauma experienced by some AI workers. We then outline some of the potential harms and benefits that AI poses, how these are distributed, and what global justice implications this has for low- to middle-income countries. Finally, we articulate the global justice significance of AI by utilizing the Capabilities Approach. We argue that AI must be considered from a global justice perspective given that, globally, AI puts significant downward pressure on several elements of well-being thereby making it harder for people to achieve threshold levels of the central human capabilities needed for a life of dignity. (shrink)

During 2018, as part of a research project funded by the Deviant Practice Grant, artist Bruno Moreschi and digital media researcher Gabriel Pereira worked with the Van Abbemuseum collection (Eindhoven, NL), reading their artworks through commercial image-recognition (computer vision) artificial intelligences from leading tech companies. The main takeaways were: somewhat as expected, AI is constructed through a capitalist and product-focused reading of the world (values that are embedded in this sociotechnical system); and that this process of using AI is an (...) innovative way for doing institutional critique, as AI offers an untrained eye that reveals the inner workings of the art system through its glitches. This paper aims to regard these glitches as potentially revealing of the art system, and even poetic at times. We also look at them as a way of revealing the inherent fallibility of the commercial use of AI and machine learning to catalogue the world: it cannot comprehend other ways of knowing about the world, outside the logic of the algorithm. But, at the same time, due to their “glitchy” capacity to level and reimagine, these faulty readings can also serve as a new way of reading art; a new way for thinking critically about the art image in a moment when visual culture has changed form to hybrids of human–machine cognition and “machine-to-machine seeing”. (shrink)

The world’s current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity. However, to date, considerations of the ethical implications (...) of using AI to achieve a transition to CE have been limited. This article addresses this gap. It outlines how AI is and can be used to transition towards CE, analyzes the ethical risks associated with using AI for this purpose, and supports some recommendations to policymakers and industry on how to minimise these risks. (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.

Although theory and research on emotional intelligence (EI) in the workplace has generated high expectations and promising findings, the gap between research and practice looms large. Several lines of inquiry point to the potential benefits of EI for leaders, teams, and organizations. Yet, assessing EI remains challenging, and research focusing on group and organizational levels of analysis is still scarce. In this review, I seek to bridge the gap between research and practice by considering a broader view of EI (...) and discussing research findings with a focus on implications for assessment and training. In particular, I discuss strategies to enhance the impact of EI and leadership training, and to drive results through well-integrated organizational development initiatives. (shrink)

We define a notion of the intelligence level of an idealized mechanical knowing agent. This is motivated by efforts within artificial intelligence research to define real-number intelligence levels of compli- cated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent to be the supremum of the computable ordinals that (...) have codes the agent knows to be codes of computable ordinals. We prove that if one agent knows certain things about another agent, then the former necessarily has a higher intelligence level than the latter. This allows our intelligence no- tion to serve as a stepping stone to obtain results which, by themselves, are not stated in terms of our intelligence notion (results of potential in- terest even to readers totally skeptical that our notion correctly captures intelligence). As an application, we argue that these results comprise evidence against the possibility of intelligence explosion (that is, the no- tion that sufficiently intelligent machines will eventually be capable of designing even more intelligent machines, which can then design even more intelligent machines, and so on). (shrink)

Publication date: 15 October 2018 Source: Author: Donovan A. McFarlane This paper examines the constructs “Level of Educational Attainment” and “Intelligence Quotient” using a Case Study Approach based in current United States political conflicts and debates between U.S. Representative Maxine Waters and U.S. President Donald Trump. Specifically, the researcher examines U.S. President Donald Trump’s claim that U.S. Representative Maxine Waters, a democratic member of the U.S. Congress from the State of California, is a “low IQ individual”. The researcher (...) examines IQ indicators and focuses on the Level of Educational Attainment of Trump and Waters by accessing, analyzing, and interpreting the most current vital data on Level of Educational Attainment at the post-secondary level, specifically examining both parties’ LEA in relation to the population samples within their age groups. Additionally, the researcher briefly looks at the life circumstances of both Donald Trump and Maxine Waters to make an educated conclusion about both leaders’ levels of intelligence and IQs. (shrink)

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

As the COVID-19 outbreak remains an ongoing issue, there are concerns about its disruption, the level of its disruption, how long this pandemic is going to last, and how innovative technological solutions like Artificial Intelligence (AI) and expert systems can assist to deal with this pandemic. AI has the potential to provide extremely accurate insights for an organization to make better decisions based on collected data. Despite the numerous advantages that may be achieved by AI, the use of (...) AI can be perceived differently by society, where moral and ethical issues may be raised, especially in regards to accessing and exploiting public data gathered from social media platforms. To better comprehend the concerns and ethical challenges, utilitarianism and deontology were used as business ethics frameworks to explore the aforementioned challenges of AI in society. The framework assists in determining whether the AI’s deployment is ethically acceptable or not. The paper lays forth policy recommendations for public and private organizations to embrace AI-based decision-making processes to avoid data privacy violations and maintain public trust. (shrink)

The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals (...) may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity. (shrink)

Traditionally, most of the research on occupational burnout has focused on organizational stressors, such as workload and time pressure, and has overlooked the emotional nature of customer service work and its effect on burnout. This study was designed to examine the effects of individuals’ affective traits and affective states on burnout. The main hypothesis of this study was that emotional intelligence acts as a moderator in the relationship between negative emotions felt by employees during their interactions with clients and (...) emotional exhaustion. A total of 137 service sector employees rated the extent to which they felt four positive emotions and four negative emotions while interacting with clients. The results indicated that negative affectivity was significantly associated with higher levels of emotional exhaustion, whereas high positive affectivity showed the reverse pattern. It was also observed that employees who declared greater intensity of negative emotions reported more symptoms of emotional exhaustion. However, as predicted, this effect was observed only among employees who were low in the trait of emotional intelligence. Negative emotions and emotional exhaustion were unrelated among employees who were high in trait emotional intelligence. (shrink)

The rapid development of programs based on the principles of machine learning (ML) and artificial intelligence (AI) signals significant changes in the components of education, namely in the provider, the tool of transmission, and the recipient of knowledge. Historical data analysis regarding the key functions of education serves as the basis for identifying fundamental innovations introduced through AI and ML. The impact of writing, printing, and the Internet has significantly altered the tool for knowledge transmission, influencing the volume of (...) information and the number of knowledge recipients. The implementation of AI and ML transforms not only the tool but also the provider of knowledge itself, which can become impersonal thanks to the corresponding computer programs. With the historically justified increase in the volume of knowledge possessed by humanity, there is a transformation observed in education systems. This is especially true for democratic societies, where the emphasis is increasingly shifting from providing a large amount of knowledge to developing critical thinking. It has been researched that programs based on AI and ML, applying linguistic models, are capable of effectively systematizing knowledge. This lays the foundation for personalizing the entire education process for a specific knowledge recipient, without burdening the provider. However, there have been cases when such imitation misleads scientists, who perceive it as attempts at communication between programs that have an equivalence to the human level. The conclusions drawn indicate a significant transformation of the education system caused by AI and ML-based programs. However, intelligent programs are unable to evolve into independent knowledge recipients due to their inability to consciously attribute meaning to information, transforming it into knowledge. (shrink)