With the noted intelligence failures prior to the September 11 attacks and the 2003 Iraq War, the US intelligence community has recognized the need to acquire new, outside expertise to mitigate against future intelligence breakdowns. This recent attention on intelligence outreach provides Science and Technology Studies scholars with an opportunity to consider the role they might play in these efforts, as well as the various opportunities and difficulties that can shape these relationships, and the types of (...) knowledge that can be produced and known from engagements with these secret communities. This paper provides a reflection on how two STS scholars have attempted to intervene into intelligence and the lessons learned. (shrink)

The article proposes a universal dual-axis intelligent systems assessment scale. The scale considers the properties of intelligent systems within the environmental context, which develops over time. In contrast to the frequent consideration of the “mind” of artificial intelligent systems on a scale from “weak” to “strong”, we highlight the modulating influences of anticipatory ability on their “brute force”. In addition, the complexity, the ”weight“ of the cognitive task and the ability to critically assess it beforehand determine the actual set (...) of cognitive tools, the use of which provides the best result in these conditions. In fact, the presence of ”common sense“ options is what connects the ability to solve a problem with the correct use of such an ability itself. The degree of ”correctness“ and ”adequacy“ is determined by the combination of a suitable solution with the temporal characteristics of the event, phenomenon, object or subject under study. The proposed approach can be applied in the evaluation of various intelligent agents in different contexts including AI and humans performing complex domain-specific tasks with high uncertainty. (shrink)

Over the past ten years, we have worked in a collaboration between educators and computer scientists at the University of Illinois to imagine futures for education in the context of what is loosely called “artificial intelligence.” Unhappy with the first generation of digital learning environments, our agenda has been to design alternatives and research their implementation. Our starting point has been to ask, what is the nature of machine intelligence, and what are its limits and potentials in education? (...) This paper offers some tentative answers, first conceptually, and then practically in an overview of the results of a number of experimental implementations documented in greater detail elsewhere. Our key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence. However, within the limits that we describe in this paper, it offers the potential to transform education in ways that—counterintuitively perhaps—make education more human, not less. (shrink)

Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on old-fashioned (...) programming). Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing. (shrink)

Estimation of discharge flowing through rivers is an important aspect of water resource planning and management. The most common way to address this concern is to develop stage-discharge relationships at various river sections. Various computational techniques have been applied to develop discharge ratings and improve the accuracy of estimated discharges. In this regard, the present study explores the application of the novel hybrid multigene genetic programming-generalized reduced gradient technique for estimating river discharges for steady as well as unsteady flows. It (...) also compares the MGGP-GRG performance with those of the commonly used optimization techniques. As a result, the rating curves of eight different rivers were developed using the conventional method, evolutionary algorithm, the modified honey bee mating optimization algorithm, artificial neural network, MGGP, and the hybrid MGGP-GRG technique. The comparison was conducted on the basis of several widely used performance evaluation criteria. It was observed that no model outperformed others for all datasets and metrics considered, which demonstrates that the best method may be different from one case to another one. Nevertheless, the ranking analysis indicates that the hybrid MGGP-GRG model overall performs the best in developing stage-discharge relationships for both single-value and loop rating curves. For instance, the hybrid MGGP-GRG technique improved sum of square of errors obtained by the conventional method between 4.5% and 99% for six out of eight datasets. Furthermore, EA, the MHBMO algorithm, and artificial intelligence models performed satisfactorily in some of the cases, while the idea of combining MGGP with GRG reveals that this hybrid method improved the performance of MGGP in this specific application. Unlike the black box nature of ANN, MGGP offers explicit equations for stream rating curves, which may be counted as one of the advantages of this AI model. (shrink)

Over the past ten years, we have worked in a collaboration between educators and computer scientists at the University of Illinois to imagine futures for education in the context of what is loosely called “artificial intelligence.” Unhappy with the first generation of digital learning environments, our agenda has been to design alternatives and research their implementation. Our starting point has been to ask, what is the nature of machine intelligence, and what are its limits and potentials in education? (...) This paper offers some tentative answers, first conceptually, and then practically in an overview of the results of a number of experimental implementations documented in greater detail elsewhere. Our key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence. However, within the limits that we describe in this paper, it offers the potential to transform education in ways that—counterintuitively perhaps—make education more human, not less. (shrink)

Our study explores the relationships between psychological and driving-related personality traits, fluid intelligence and cognitive abilities for drivers whose driving licence has been revoked due to intoxicated driving (alcohol and/or drugs). We were able to show that highly significant impacts on cognitive functions derive from the participants’ age and fluid intelligence. In addition, driving-related personality traits such as emotional instability, a sense of responsibility and self-control contributed significantly to some of the cognitive abilities that are important for fitness (...) to drive. Additionally, the mediating effects of fluid intelligence in the model are discussed. Traffic psychologists can use this knowledge in their assessment of drivers, mainly regarding the possible compensation of cognitive deficits regarding the fitness to drive. (shrink)

Today, intelligence in all walks of life is developing at an unexpectedly fast speed. The complexity of the Internet of Things big data system of intelligent parks is analyzed to unify the information transmission of various industries, such as smart transportation, smart library, and smart medicine, thereby diminishing information islands. The traditional IoT systems are analyzed; on this basis, a relay node is added to the transmission path of the data information, and an intelligent park IoT big data system (...) is constructed based on relay cooperation with a total of three hops. Finally, the IoT big data system is simulated and tested to verify its complexity. Results of energy efficiency analysis suggest that when the power dividing factor is 0.5, 0.1, and 0.9, the energy efficiency of the IoT big data system first increases and then decreases as α0 increases, where the maximum value appears when α0 is about 7 J. Results of outage probability analysis demonstrate that the system’s simulation result is basically the same as that of the theoretical result. Under the same environment, the more hop paths the system has, the more the number of relays is; moreover, the larger the fading index m, the better the system performance, and the lower the outage possibility. Results of transmission accuracy analysis reveal that the IoT big data system can provide a result that is the closest to the actual result when the successful data transmission probability is 100%, and the parameter λ values are between 0.01 and 0.05; in the meantime, the delay of successful data transmission is reduced gradually. In summary, the wireless relay cooperation transmission technology can reduce the outage probability and data transmission delay probability of the IoT big data system in the intelligent park by adding the multihop path, thereby improving the system performance. The above results can provide an experimental basis for exploring the complexity of IoT systems in intelligent parks. (shrink)

Building on nearly eighty years of scientific work, The Handbook of Emotional Intelligence is the first definitive resource that brings together a stellar panel of academics, researchers, and practitioners, in the field. Sweeping in scope, the text presents information on the most important conceptual models, reviews and evaluates the most valid and reliable methods for assessing emotional intelligence, and offers specific guidelines for applying the principles of Emotional Intelligence in a variety of settings.

We describe an approach that enables a more complete evaluation of the validity of emotional intelligence measures. We argue that a source of evidence for validity is often overlooked by researchers and test developers, namely, evidence based on response processes. This evidence can be obtained through a definition of the ability, a description of the mental processes that operate when a person uses the ability, the development of a theory of response behaviour that links variation in the construct with (...) variation on the responses to the items of a measure, and a test of the theory of response behaviour through one or more strategies that we describe. (shrink)

We developed an on-line intelligent argumentation system which facilitates stakeholders in exchanging dialogues. It provides decision support by capturing stakeholders’ rationale through arguments. As part of the argumentation process, stakeholders tend to both polarise their opinions and form polarisation groups. The challenging issue of assessing argumentation polarisation had not been addressed in argumentation systems until recently. Arvapally, Liu, and Jiang [, ‘Identification of Faction Groups and Leaders in Web-Based Intelligent Argumentation System for Collaborative Decision Support’, in Proceedings of International Conference (...) on Collaborative Technologies and Systems] earlier developed a method to identify polarisation groups. These groups, however, tend to overlap to a certain degree; each stakeholder may be a member of multiple polarisation groups to varied degrees. Quantifying stakeholders’ membership in multiple polarisation groups is an important issue in the argumentation for collaborative decision-making, which is not addressed earlier. We present a novel approach using fuzzy clustering algorithm to address this issue in this article. The method is evaluated using data sets produced from the discussions of 24 stakeholders. Experimental results indicate that our method is effective for both identifying polarisation groups and quantifying stakeholders’ degree of membership in each polarisation group. (shrink)

The traditional evaluation methods of foreign language communication skills cannot deal with emotional information in the process of communication. Psychologists believe that a real personalized evaluation system should be smart. Based on the emotion network technology of artificial emotion intelligence, aiming at the shortcomings of the traditional evaluation system, this paper puts forward a new language ability evaluation system with certain emotion judgment function. The system can easily obtain and identify emotions in foreign communication, and can also carry out (...) individual learning at the cognitive and emotional levels on the basis of comprehensive analysis of emotions and communication effects. (shrink)

Artificial intelligence is a cutting-edge technology that has been widely applied in tourism operations. To enhance tourists' experience, many tourism suppliers introduced AI devices to interact with tourists. Previous studies classified AI devices as task- and social- oriented based on their functions; however, current models that explain customers' intention to use AI devices did not reflect the discrepancy between the two different types. Therefore, this paper attempts to fill this gap by proposing a theoretical model for the use of (...) task-oriented AI devices. Based on the multi-stage appraisal framework and the Structural Equation Modeling analysis, this paper presents the following findings: utilitarian motivation, interaction convenience, and task-technology fit are the factors appraised in the first stage; perceived competence and flow experience are the factors appraised in the second stage; utilitarian motivation, interaction convenience, and task-technology fit are positively associated with perceived competence. Perceived competence positively influences flow experience, which further affects customers' switching intention from task-oriented AI devices to human service; the serial mediating effect of perceived competence and flow experience between the stimulus mentioned in the first appraisal stage and the switching intention is confirmed. This study reveals the underlying psychological mechanism when customers use task-oriented AI devices, and it provides a theoretical framework for task-oriented AI device adoption. (shrink)

This paper discusses how John Dewey’s notion of intelligent habit could contribute to technology ethics. For Dewey, intelligent (i.e., desirable) habits are reflective – arising from inquiry into the appropriate courses of action in each situation – and flexible – easily adaptable to the changing circumstances. We should strive to develop intelligent habits as they are the best tools for the achievement of our goals and are necessary for individual and societal flourishing. I argue that Dewey’s notion of intelligent habit (...) makes it possible to identify the impact of technology on users’ identity and self-determination, advocate for the extension of user choice and malleability of technologies, and analyse the connections between the epistemic dimension of technology and users’ ability to flourish. (shrink)

There is a debate about the measure of IQ in children with ADHD. Some studies report that, compared to static assessment procedures, dynamic assessment of intelligence can better measure cognitive modifiability and plasticity. The present study was designed to examine children belonging to different ADHD subtypes in terms of both static and dynamic measures. Thirty-four children were compared to a sample of 27 typically developing children. Results indicate that only the inattentive and the combined subtypes, compared with (...) the normative sample, show lower IQ scores. The ADHD-I group presents generally low WISC scores and ADHD-H presents generally high WISC scores. Moreover, the ADHD-C group shows a low static score and a high dynamic score, indicating a wide breadth of Vygotskian children’s zone of proximal development. Static and dynamic measurements together can indeed be considered a comprehensive examination of intelligence levels in ADHD children and may be essential in predicting learning capacities. (shrink)

Organizations are making massive investments in artificial intelligence, and recent demonstrations and achievements highlight the immense potential for AI to improve organizational and human welfare. Yet realizing the potential of AI necessitates a better understanding of the various ethical issues involved with deciding to use AI, training and maintaining it, and allowing it to make decisions that have moral consequences. People want organizations using AI and the AI systems themselves to behave ethically, but ethical behavior means different things to (...) different people, and many ethical dilemmas require trade-offs such that no course of action is universally considered ethical. How should organizations using AI—and the AI itself—process ethical dilemmas where humans disagree on the morally right course of action? Though a variety of ethical AI frameworks have been suggested, these approaches do not adequately address how people make ethical evaluations of AI systems or how to incorporate the fundamental disagreements people have regarding what is and is not ethical behavior. Drawing on moral foundations theory, we theorize that a person will perceive an organization’s use of AI, its data procedures, and the resulting AI decisions as ethical to the extent that those decisions resonate with the person’s moral foundations. Since people hold diverse moral foundations, this highlights the crucial need to consider individual moral differences at multiple levels of AI. We discuss several unresolved issues and suggest potential approaches for thinking about conflicts in moral judgments concerning AI. (shrink)

This article examines the potential implications of the implementation of artificial intelligence in health care for both its delivery and the medical profession. To this end, the first section explores the basic features of AI and the yet theoretical concept of autonomous AI followed by an overview of current and developing AI applications. Against this background, the second section discusses the transforming roles of physicians and changes in the patient–physician relationship that could be a consequence of gradual expansion of (...) AI in health care. Subsequently, an examination of the responsibilities physicians should assume in this process is explored. The third section describes conceivable practical and ethical challenges that implementation of a single all-encompassing AI healthcare system would pose. The fourth section presents arguments for regulation of AI in health care to ensure that these applications do not violate basic ethical principles and that human control of AI will be preserved in the future. In the final section, fundamental components of a moral framework from which such regulation may be derived are brought forward, and some possible strategies for building a moral framework are discussed. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of (...) a ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism (...) or utilitarianism, that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelli-gence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies. (shrink)

The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework (...) developed by the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers. (shrink)

Definition of the problem In medicine, as well as in other disciplines, computer science expertise is becoming increasingly important. This requires a culture of interdisciplinary assessment, for which medical ethics committees are not well prepared. The use of big data and artificial intelligence (AI) methods (whether developed in-house or in the form of “tools”) pose further challenges for research ethics reviews. Arguments This paper describes the problems and suggests solving them through procedural changes. Conclusion An assessment that (...) is interdisciplinary from the outset appears to be more suitable than having two commissions with different expertise. However, this would require that the composition of medical ethics committees be altered. In addition, the article recommends initial measures to be taken during research ethics reviews of big data and AI projects in order to consolidate the review process and ensure standardization of the criteria. (shrink)

The proposed European Artificial Intelligence Act (AIA) is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can (and should) be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the _conformity assessments_ that providers of high-risk AI systems are expected to conduct, (...) and the _post-market monitoring plans_ that providers must establish to document the performance of high-risk AI systems throughout their lifetimes. We argue that the AIA can be interpreted as a proposal to establish a Europe-wide ecosystem for conducting AI auditing, albeit in other words. Our analysis offers two main contributions. First, by describing the enforcement mechanisms included in the AIA in terminology borrowed from existing literature on AI auditing, we help providers of AI systems understand how they can prove adherence to the requirements set out in the AIA in practice. Second, by examining the AIA from an auditing perspective, we seek to provide transferable lessons from previous research about how to refine further the regulatory approach outlined in the AIA. We conclude by highlighting seven aspects of the AIA where amendments (or simply clarifications) would be helpful. These include, above all, the need to translate vague concepts into verifiable criteria and to strengthen the institutional safeguards concerning conformity assessments based on internal checks. (shrink)

Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, (...) that they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human-level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power-seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate. (shrink)

Chat Generative Pre-Trained Transformer (ChatGPT) has been a growing point of interest in medical education yet has not been assessed in the field of bioethics. This study evaluated the accuracy of ChatGPT-3.5 (April 2023 version) in answering text-based, multiple choice bioethics questions at the level of US third-year and fourth-year medical students. A total of 114 bioethical questions were identified from the widely utilised question banks UWorld and AMBOSS. Accuracy, bioethical categories, difficulty levels, specialty data, error analysis and character count (...) were analysed. We found that ChatGPT had an accuracy of 59.6%, with greater accuracy in topics surrounding death and patient–physician relationships and performed poorly on questions pertaining to informed consent. Of all the specialties, it performed best in paediatrics. Yet, certain specialties and bioethical categories were under-represented. Among the errors made, it tended towards content errors and application errors. There were no significant associations between character count and accuracy. Nevertheless, this investigation contributes to the ongoing dialogue on artificial intelligence’s (AI) role in healthcare and medical education, advocating for further research to fully understand AI systems’ capabilities and constraints in the nuanced field of medical bioethics. (shrink)

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation (...) of the ITS was done by a group of students and teachers. The results were acceptable. (shrink)

The transformers that drive chatbots and other AI systems constitute large language models (LLMs). These are currently the focus of a lively discussion in both the scientific literature and the popular media. This discussion ranges from hyperbolic claims that attribute general intelligence and sentience to LLMs, to the skeptical view that these devices are no more than “stochastic parrots”. I present an overview of some of the weak arguments that have been presented against LLMs, and I consider several of (...) the more compelling criticisms of these devices. The former significantly underestimate the capacity of transformers to achieve subtle inductive inferences required for high levels of performance on complex, cognitively significant tasks. In some instances, these arguments misconstrue the nature of deep learning. The latter criticisms identify significant limitations in the way in which transformers learn and represent patterns in data. They also point out important differences between the procedures through which deep neural networks and humans acquire knowledge of natural language. It is necessary to look carefully at both sets of arguments in order to achieve a balanced assessment of the potential and the limitations of LLMs. (shrink)

This paper describes an Intelligent Tutoring System for helping users with ADO.NET called ADO-Tutor. The Intelligent Tutoring System was designed and developed using (ITSB) authoring tool for building intelligent educational systems. The user learns through the intelligent tutoring system ADO.NET, the technology used by Microsoft.NET to connect to databases. The material includes lessons, examples, and questions. Through the feedback provided by the intelligent tutoring system, the user's understanding of the material is assessed, and accordingly can be guided to different difficulty (...) level of exercises and/or the lessons. The Intelligent Tutoring System was evaluated by a group of users and the results were more than satisfactory in terms of the quality of the material and the design of the system. (shrink)

The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk prediction. A secondary aim is to review assessment tools that have been developed to prevent biases in AI systems. In addition, we provide a conceptual clarification for some terms related to biases in this particular context. We focus mainly on (...) nonracial biases that may be less considered when addressing biases in AI systems in the existing literature. In the manuscript, we found that the existence of bias in AI systems used for COVID-19 can result in algorithmic justice and that the legal frameworks and strategies developed to prevent the apparition of bias have failed to adequately consider social determinants of health. Finally, we make some recommendations on how to include more diverse professional profiles in order to develop AI systems that increase the epistemic diversity needed to tackle AI biases during the COVID-19 pandemic and beyond. (shrink)

Adaptive Intelligence is a dramatic reappraisal and reframing of the concept of human intelligence. In a sweeping analysis, Robert J. Sternberg argues that we are using a fatally-flawed, outdated conception of intelligence; one which may promote technological advancement, but which has also accelerated climate change, pollution, the use of weaponry, and inequality. Instead of focusing on the narrow academic skills measured by standardized tests, societies should teach and assess adaptive intelligence, defined as the use of collective (...) talent in service of the common good. This book describes why the outdated notion of intelligence persists, what adaptive intelligence is, and how it could lead humankind on a more positive path. (shrink)

The science of consciousness has made great strides in recent decades. However, the proliferation of competing theories makes it difficult to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, agents artificial systems are capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial (...) systems. With these challenges in mind, I propose that we look for ecumenical heuristics for artificial consciousness to enable us to make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such heuristics should have three main features: they should be (i) intuitively plausible, (ii) theoretically-neutral, and (iii) scientifically tractable. I claim that the concept of general intelligence — understood as a capacity for robust, flexible, and integrated cognition and behavior — satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious. -/- . (shrink)

Artificial intelligence (AI) national strategies provide countries with a framework for the development and implementation of AI technologies. Sixty countries worldwide published their AI national strategies. The majority of these countries with more than 70% are developed countries. The approach of AI national strategies differentiates between developed and developing countries in several aspects including scientific research, education, talent development, and ethics. This paper examined AI readiness assessment in a developing country (Palestine) to help develop and identify the main (...) pillars of the AI national strategy. AI readiness assessment was applied across education, entrepreneurship, government, and research and development sectors in Palestine (case of a developing country). In addition, it examined the legal framework and whether it is coping with trending technologies. The results revealed that Palestinians have low awareness of AI. Moreover, AI is barely used across several sectors and the legal framework is not coping with trending technologies. The results helped develop and identify the following five main pillars that Palestine’s AI national strategy should focus on: AI for Government, AI for Development, AI for Capacity Building in the private, public and technical and governmental sectors, AI and Legal Framework, and international Activities. (shrink)

The article examines the problem of ensuring the political stability of a democratic social system with a shortage of a vital commodity (like vaccine against COVID-19). In such a system, members of society citizens assess the authorities. Thus, actions by the authorities to increase the supply of this commodity can contribute to citizens' approval and hence political stability. However, this supply is influenced by random factors, the actions of competitors, etc. Therefore, citizens do not have sufficient information about all the (...) possibilities of supplying, and it is difficult for them to make the right decisions. Such citizen unawareness can be exploited by unscrupulous politicians to achieve personal targets. Therefore, it is necessary to organize public control to motivate politicians to use all available opportunities in supplying. The goal of the paper is to build such a digital mechanism of public control of the politicians by citizens, which would best assess and stimulate the activities of the authorities to improve the supply of a vital commodity. In the age of artificial intelligence, such digital public control in the face of uncertainty can be based on digital machine learning. In addition, it is necessary to take into account and model the activities of politicians associated with the presence of their own targets that do not coincide with public ones. Such politicians can use the learning of citizens for their own targets. The objective of the article is to build an optimal digital mechanism of public control in a two-level model of a democratic social system—a digital society. At its top level, there is the Citizen, who gives an assessment for the Politico located at the lower level. In turn, the Politico can influence the supplying of a vital commodity. Political stability is guaranteed if the Citizen regularly approves of the Politico’s actions to increase this supply. However, the Politico may not use the opportunities available to him to offer a commodity to achieve a personal target. To avoid this, the Politico’s control mechanism is proposed. It includes the procedure for digital learning of the Citizen, as well as a procedure for assessing the Politico activity. Sufficient conditions have been found for the synthesis of such the Politico’s control mechanism, at which stochastic possibilities of increasing the supply of a vital commodity are used. The example of such the Politico’s control mechanism is considered on the case of supply of the COVID-19 vaccine in England. (shrink)

Although theory and research on emotional intelligence 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)

Although the concept of “AI governance” is frequently used in the debate, it is still rather undertheorized. Often it seems to refer to the mechanisms and structures needed to avoid “bad” outcomes and achieve “good” outcomes with regard to the ethical problems artificial intelligence is thought to actualize. In this article we argue that, although this outcome-focused view captures one important aspect of “good governance,” its emphasis on effects runs the risk of overlooking important procedural aspects of good AI (...) governance. One of the most important properties of good AI governance is political legitimacy. Starting out from the assumptions that AI governance should be seen as global in scope and that political legitimacy requires at least a democratic minimum, this article has a twofold aim: to develop a theoretical framework for theorizing the political legitimacy of global AI governance, and to demonstrate how it can be used as a compass for critially assessing the legitimacy of actual instances of global AI governance. Elaborating on a distinction between “governance by AI” and “governance of AI” in relation to different kinds of authority and different kinds of decision-making leads us to the conclusions that much of the existing global AI governance lacks important properties necessary for political legitimacy, and that political legitimacy would be negatively impacted if we handed over certain forms of decision-making to artificial intelligence systems. (shrink)

People have various desires, but it is a contested moral issue when a desire becomes of such importance that it legitimizes a moral claim on others. This paper explores how the normative significance of desire satisfaction can be assessed and argues that a normatively significant desire can constitute a pro tanto obligation to help satisfy it. The paper presents a framework that relates the normative significance of a given desire to the general goal of living a reasonably valuable life and (...) inquires how the latter can be given determinate content without excluding a heterogeneity of the personal good. The paper contends that the set of possibly normatively significant desires is thus restricted by considerations about intelligibility, adequacy, and replaceability, which are mediated by societal background theories. (shrink)

Artificial Intelligence (AI) is set to bring changes to legal systems. These technologies may have positive practical implications when it comes to access, efficiency, and accuracy in Justice. However, there are still many uncertainties and challenges associated with the implementation of AI in the legal space. In this research, we surveyed Judges on critical challenges related to the Judging Profession in the AI paradigm; Automated Adjudication; and Legal Principles. Our results suggest that (i) Judges are hesitant about changes in (...) their profession. They signal the need for adequate training that fosters legal literacy in AI, but are less open to changes in legal writing or their social and institutional role; (ii) Judges believe higher levels of automation only lead to fair outcomes if used in earlier phases of adjudication; (iii) Judges believe and are concerned about AI leading to Techno-Legal Positivism; and (iv) Judges consider that Legal AI technologies may have a positive impact in some legal principles, as long as everyone has equal access to those technologies and cybersecurity and judge on the loop safeguards are in place; and (v) Judges are strongly concerned about the de-humanization of Justice. They consider that assessing evidence, analyzing arguments, and deciding on a legal case should be inherently human. By surveying these practitioners, we aim to foster a responsible, inclusive, and transparent innovation in Justice. (shrink)

An investigation into the assessment of the moral components which were developed by John Wilson, is reported. Tests fox the classroom measurement of two components were developed. The components were; PHIL(CC), the claiming of concern for other persons as an overriding, universal, and prescriptive principle in moral decision making; and; GIG, knowledge of factual information which is relevant in making moral decisions which subjects face. The test development exercise was undertaken at a time when public interest in moral education (...) was growing. The recent demand for moral education in Auckland is reviewed. Over the last fifteen years, since the Currie Commission Report, reports by committees investigating the purposes of schools have increasingly emphasised moral and social education as school objectives. The Department of Education appeared to be sympathetic towards the cause of moral education. The submissions made by the public during the Educational Development Conference suggested that, in general, parents and citizens were prepared to consider innovative programmes in social or moral education, although there was little agreement on what form such training or education should take. A number of teachers were supporters of moral education. The primary purpose in constructing tests for Wilson's components was to provide an instrument which would assist in the evaluation of moral education curriculum projects in Auckland secondary schools. Evidence concerning descriptive, content, domain selection, construct and concurrent validity is presented. Kuder-Richardson, retest and criterion-referenced reliability studies were undertaken. It is claimed that an instrument with sufficient validity and reliability has bean produced for the summative evaluation of curriculum projects, and the diagnostic investigation of class groups using the test as a criterion-referenced measure. Auckland intermediate and secondary school pupils were surveyed, using the tests produced and punch card recording in an attempt to identify significant variables. Over 1,100 children completed the tests under controlled conditions. Significant variables identified using the test for PHIL(CC) were socio-economic level for twelve-year-old children, and intelligence for sixteen-year-old children. The effect of schooling appeared to be significant at all levels. Age does not appear to markedly increase children's concern for others. Age was related to performance in the knowledge test. Older children knew more. Other significant variables for GIG were socio-economic level (middle levels performed better) and the effects of schooling. There was some evidence that females know more than males. In both tests it appears that there is considerable interaction between the variables. Suggestions for the further development of the tests are given. (shrink)

Christopher Peacocke has recently made an important and insightful effort to fashion a non-verificationist method for distinguishing sense from nonsense. The argument is subtle and complex, and varies somewhat with each of his three target ‘spurious hypotheses’: that if a perfect fission of one person into two were to occur, one and only one of the resulting persons would be identical with the original; that another person’s visual experience can be qualitatively different from your own when you are both seeing (...) the same object, even though your relevant brain states are physically identical and so are your environmental conditions; and that the entire material universe is moving undetectably at a particular uniform velocity with respect to absolute space. My own assessment of his efforts is that they are most successful against the third of these hypotheses, and that this is a function of the fact that of the three, it alone clearly employs a problematic concept- that of absolute location. However, my purpose here is not to engage in a comprehensive evaluation of Peacocke’s project; it is rather to defend the extreme inverted spectrum hypothesis against his attack. I shall argue not only that his argument against EISH fails, but that he is himself independently committed to its intelligibility. Beyond that, I shall point out some striking and, to my mind, welcome consequences of his plausible claims concerning the relations between his own proposal and certain other views concerning content theory; the consequences in question depend both on his positive proposal and on my reasons for rejecting his argument against the extreme inversion hypothesis. (shrink)

The currently developing fields of Ambient Intelligence and Persuasive Technology bring about a convergence of information technology and cognitive science. Smart environments that are able to respond intelligently to what we do and that even aim to influence our behaviour challenge the basic frameworks we commonly use for understanding the relations and role divisions between human beings and technological artifacts. After discussing the promises and threats of these technologies, this article develops alternative conceptions of agency, freedom, and responsibility that (...) make it possible to better understand and assess the social roles of Ambient Intelligence and Persuasive Technology. The central claim of the article is that these new technologies urge us to blur the boundaries between humans and technologies also at the level of our conceptual and moral frameworks. (shrink)

Hospitality industry plays a crucial role in the development of tourism. Predicting the future demand of a hotel is a key step in the process of hotel revenue management. Hotel passenger flow prediction plays an important role in guiding the formulation of hotel pricing and operating strategies. On the one hand, hotel passenger flow prediction can provide decision support for hotel managers and effectively avoid the waste of hotel resources and loss of revenue caused by the loss of customers. On (...) the other hand, it is the guarantee of the priority occupation of business opportunities by hotel enterprises, which can help hotel enterprises adjust their operation strategies reasonably to better adapt to the market situation. In addition, hotel passenger flow prediction is helpful to judge the overall operating condition of the hotel industry and assess the risk level of the hotel project to be built. Hotel passenger flow is affected by many factors, such as weather, environment, season, holidays, economy, and emergencies, and has the characteristics of complex nonlinear fluctuation. The existing demand predicting methods include linear methods and nonlinear methods. The linear prediction methods rely on the stability of environment and time series, so they cannot completely simulate the complex nonlinear fluctuations characteristics of hotel passenger flow. Traditional nonlinear prediction methods need to improve the prediction accuracy, and they are difficult to deal with the increasing data of hotel passenger flow. Based on the above analysis, this paper constructs a deep learning prediction model based on Long Short-Term Memory to predict the number of actual monthly arrival bookings. The number of actual monthly arrival bookings can reflect the actual monthly passenger flow of a hotel. The prediction model can effectively reduce the loss caused by cancellation or nonarrival of bookings due to various reasons and improve the hotel revenue. The experimental part of this paper is based on the booking demand dataset of a resort hotel in Portugal from July 1, 2015, to August 31, 2017. Artificial neural network and support vector regression are built as benchmark models to predict the number of actual monthly arrival bookings of this hotel. The experimental results show that, compared with the benchmark models, the LSTM model can effectively improve the prediction ability and provide necessary reference for the hotel's future pricing decision and operation mode arrangement. (shrink)

In this paper, we designed and developed an intelligent tutoring system for teaching Photoshop. We designed the lessons, examples, and questions in a way to teach and evaluate student understanding of the material. Through the feedback provided by this tool, you can assess the student's understanding of the material, where there is a minimum overshoot questions stages, and if the student does not pass the level of questions he is asked to return the lesson and read it again. Eventually this (...) administration is a special teacher for the students and can continue with him until he fully understands the lesson without weariness or boredom, regardless of the level of student. (shrink)

This article considers how professional knowledge should be assessed. It is maintained that the assessment of professional know-how raises distinctive issues from the assessment of know-how more generally. Intellectualist arguments which suggest that someone's giving an account of how to F should suffice for attributing to them knowledge of how to F are set out. The arguments fail to show that there is no necessary distinction between two kinds of know-how, namely the ability to F and knowing that (...) w is a way to F, such that the latter is more fundamental. The consequences of this failure for our understanding of professional assessment are then considered. The issue of the assessment of tacit knowledge is then addressed. It is concluded that there is no context-dependent codifiable or articulable propositional knowledge of how to F which could be substituted for being able to F and that therefore tacit knowledge can only be assessed in performance. The parallel with Gettier cases is reviewed and it is concluded that the provenance of accounts of and justifications for the attribution of know-how are not matters of indifference to its assessment. Finally, the question of evaluability or what Ryle would have called the applicability of intelligence epithets is discussed in relation to its relevance to our procedures for assessing practical knowledge. Once again, it is concluded that excellent performance is necessary to attribute excellence in know-how. However, the ability to give an account of how and why an agent would do something in hypothetical circumstances is also very important for the assessment of professional knowledge. (shrink)