Based on cloud computing and statistics theory, this paper proposes a reasonable analysis method for big data of film and television. The method selects Hadoop open source cloud platform as the basis, combines the MapReduce distributed programming model and HDFS distributed file storage system and other key cloud computing technologies. In order to cope with different data processing needs of film and television industry, association analysis, cluster analysis, factor analysis, and K-mean + association analysis algorithm (...) training model were applied to model, process, and analyze the full data of film and TV series. According to the film type, producer, production region, investment, box office, audience rating, network score, audience group, and other factors, the film and television data in recent years are analyzed and studied. Based on the study of the impact of each attribute of film and television drama on film box office and TV audience rating, it is committed to the prediction of film and television industry and constantly verifies and improves the algorithm model. (shrink)

Lockheed Martin Corp. has funded research to generate a framework and methodology for developing semantic reasoning applications to support the discipline oflntelligence Analysis. This chapter outlines that framework, discusses how it may be used to advance the information sharing and integrated analytic needs of the Intelligence Community, and suggests a system I software architecture for such applications.

As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their (...) overarching AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. (shrink)

Criminal intelligence data poses problems for conventional database technology. It has little structure or homogeneity and queries may involve looking for unknown associations between entities; such open-ended queries cannot be made in current systems. Finally, the data must be presented in an intuitively simple fashion for both investigative and evidential purposes. We discuss a database system which uses a labelled graph as its data model. This approach obviates the need for schema design, allows queries which look for associations between (...) entities to be implemented and provides the basis for a natural visual representation of the data. (shrink)

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...) interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...) as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction, as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings. (shrink)

This study focuses on the influence of the quality of services received by thalassotherapy customers on their global satisfaction and the relationship between this and the word of mouth. This study uses a hybrid SEM—classification tree analysis. The empirical findings reveal a significant relationship between the quality of each offered service and global satisfaction. This study contributes to identify tourist’s satisfaction or delight on received thalasso services through a proposed methodology. The main contribution of this work consists of the (...) proposal of a methodology to identify objectively through the opinion of tourists if they were satisfied or had reached delight. This work demonstrates, confirming what has been found in previous literature, that global satisfaction is related to the different experiences provided by the service. Thus, all hypotheses are accepted, supporting the hypotheses that relate the pool, the staff, the treatments, and the environment to satisfaction. In addition, the hypotheses that link satisfaction with the word of mouth are also supported. This theoretical implication has important practical implications for managers of the type of facilities such as those studied in this paper, since it shows that it is not enough to do well in one of the services provided if the environment or the interaction with the staff is not right. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...) inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Artificial Intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this chapter AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...) inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This chapter offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (...) (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (shrink)

The diversities in the natural, social, and human environment of various regions often lead to the differences in their regional economic development level and industrial structure and layout; moderate regional differences can mobilize economic vitality and improve development efficiency, but excessive differences may lead to social instability or even turbulence. Intelligent algorithms or their improved and hybrid algorithms can recently achieve more suitable solutions to practical problems of nonlinear, discrete, nondifferentiable, and multiple constraints. Therefore, this paper's main point is on (...) the analysis of regional economic development differences based on intelligent hybrid algorithms. On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of regional economic development differences analysis, elaborated the development background, current status, and future challenges of intelligent hybrid algorithms, introduced the methods and principles of principal component distance weighting algorithm and sequential quadratic programming algorithm, constructed a basic model for regional economic development differences based on intelligent hybrid algorithm, conducted the construction of analysis index system and the hybrid of intelligence algorithm, analyzed the regional economic development differences based on intelligent hybrid algorithm, performed the principal component analysis and time-space change analysis of regional economic development, and finally carried out a simulation experiment and its result analysis. The study results show that the intelligent hybrid algorithm can simulate the intelligent behavior of certain groups in nature when analyzing the differences in regional economic development, so that it has essentially parallelism, high accuracy, and convergence speed. The study results of this paper provide a reference for further researches on the regional economic development differences analysis based on intelligent hybrid algorithm. (shrink)

This paper examines the role of machine functionalism, as one of the most popular positions within the philosophy of mind, in the context of the development of artificial intelligence. Our analysis starts from the idea that machine functionalism is a theory that is largely consistent with the principles behind the strong AI thesis. However, we will see that there is a convincing counter-argument against such claims, and we will problematize this issue. Also, by testing ChatGPT, as the most (...) popular publicly available AI tool, we will make an effort to figure out whether the strong AI thesis could currently even be considered a potentially sustainable principle. Since ChatGPT fails the Turing test our conclusion is that the strong AI thesis cannot be upheld even in principle, implying that the current state of this AI tool does not yet provide strong enough arguments in favor of machine functionalism. (shrink)

We examined a large set of conditional inference data compiled from several previous studies and asked three questions: How is normative performance related to intelligence? Does negative conclusion bias stem from Type 1 or Type 2 processing? Does implicit negation bias stem from Type 1 or Type 2 processing? Our analysis demonstrated that rejecting denial of the antecedent and affirmation of the consequent inferences was positively correlated with intelligence, while endorsing modus tollens inferences was not; that the (...) occurrence of negative conclusion bias was related to the extent of Type 2 processing; and that the occurrence of implicit negation bias was not related to the extent of Type 2 processing. We conclude that negative conclusion bias is, at least in part, a product of Type 2 processing, while implicit negation bias is not. (shrink)

This work intends to solve the problem that the traditional education system cannot reasonably adjust the educational integration of children with the arrival of labor force in a short time, and support the education of migrant children in the education policy to integrate them into the local educational environment as soon as possible. Firstly, this work defines the surplus labor force and MC. Secondly, the principles of Artificial Intelligence and Deep Learning are introduced. Thirdly, it analyzes the education of (...) MC and relevant policies, and the data of the education effect of MC are collected and the evaluation effect model is built. Finally, the evaluation model of MC’s education effect is applied to test the effect of EP. The results show that using AI technology combined with DL technology to model the education effect of MC can establish an effective and accurate evaluation model of the education effect of MC, effectively evaluate the impact of local education policies on the education of MC, and give an effective effect analysis of relevant education policies in each period. The result of Adaptive Resonance Theory –Back Propagation algorithm is 65 ∼ 96%, which is much higher than the efficiency of traditional algorithms. This shows that the education integration evaluation model of MC based on AI technology and DL technology can effectively and accurately evaluate the integration effect of MC on the local education system, and then provide reference for local and even national adjustment of education policies. The results provide a new idea for the application of new technology in EP. (shrink)

I discuss some of the speculations proposed by Stewart ( 2010a ). These include the following propositions: the cooperation at larger and larger scales, the existence of larger scale processes, the enhancement of the tuning as the universe cycle repeats, the transmission between universes and the motivations to produce a new universe.

Corporate governance delivers feasible and controlled company operations using a group of common shareholders and appropriate policies. The roles and responsibilities of the shareholders suggest and improve corporate development through monotonous and independent rights. The implication of artificial intelligence provides knowledgeable insights for decision-making and control management. This article introduces a Mutual Consent-based Governance Regulation Model for dissimilarity mitigation in corporate rule implications. The proposed model exploits transfer learning for balanced rule implication and decision-making. The learning states are defined (...) based on mutual agreement, individual interest, and operational features. Based on the governance policies, the above rules are employed without hindering the pioneer regulations implemented in different periods. Therefore, artificial intelligence technology is utilized for prompt and swift governance decisions in delivering special rights for consumers and shareholders. The performance of this model is validated and verified using data sources related to governance policies from a real-time industry. The impact of varying policy features with dissimilarity is analyzed for varying occurrences. The analysis is given based on the considered data sources for which the classification and its impact over reports, sharing, voting, complaint, and market are analyzed. The availability before and after the proposed improves the above metrics by 10.48, 10.65, 9.78, 13.39, and 9.26%. (shrink)

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

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

With the progress of social production, the competition for talents among enterprises is fierce, and the market often lacks capable leaders, which leads to the lack of management of enterprise employees and cannot bring more economic benefits to enterprises. Traditional leaders make subordinate employees work actively and achieve the common goal of the enterprise by exerting their own leadership characteristics and observing their subordinates, but they cannot take care of the psychological state of each employee, resulting in the employee's work (...) efficiency is not very high. In recent years, charismatic leadership has become an important economic leader in the new era, and the theoretical spirit of charismatic leadership can well guide employees to work actively. Artificial intelligence affective computing can well identify the psychological state of the subject, and the combination of artificial intelligence affective computing and charismatic leadership can achieve effective management of employees through the predictive analysis of employees' psychological state. This paper compares the psychological state prediction analysis of employees' work attitudes between charismatic leaders based on artificial intelligence affective computing and traditional leaders through experiments. The results show that: charismatic leaders based on artificial intelligence affective computing predictive analytics can improve sensitivity to employee needs, resulting in an 8.2% increase in employee trust in leadership, a 4.4% increase in employee commitment to achieving organizational goals, and a 19.3% increase in employee job satisfaction. The psychological state prediction analysis of charismatic leaders based on artificial intelligence affective computing on employees' work attitudes can improve the work efficiency of employees and the economic benefits of enterprises. (shrink)

This multilevel meta-analysis examines whether emotional intelligence can be enhanced through training and identifies training effects’ determinants. We identified 24 studies containing 28 samples aiming at increasing individual-level EI among healthy adults. The results revealed a significant moderate standardized mean change between pre- and post-measurement for the main effect of EI training, and a stable pre- to follow-up effect. Additionally, the type of EI model, dimensions of the four branch model, length, and type of publication turned out to (...) be significant moderators. The results suggest that EI trainings should be considered effective interventions. (shrink)

This research assessed how the performance and team skills of three-person teams working with an Intelligent Team Tutoring System on a virtual military surveillance task were affected by feedback privacy, participant role, task experience, prior team experience, and teammate familiarity. Previous work in Intelligent Tutoring Systems has focused on outcomes for task skill training for individual learners. As research extends into intelligent tutoring for teams, both task skills and team skills are necessary for good team performance. This work includes a (...) brief review of previous research on ITTSs, feedback, teams, and teamwork, including the recounting of two categories of a framework of teamwork performance, Communication and Cognition, which are relevant to the present study. This research examines the effects of an intelligent agent, as well as features of the team, its members, and the task being undertaken, on team communication and team situation awareness. Thirty-seven teams of three participants, each at their own computer running a multiplayer surveillance simulation, were given just-in-time private or public performance feedback during four 5-min trials. In the fourth trial, two of the three participants switched roles. Feedback type, teamwork experience, and teammate familiarity had no statistically significant effect on communication or team situation awareness. However, higher levels of role experience and task experience showed significant and medium-sized effects on communication performance. Results, based on performance data and structured interview responses, also revealed areas of improvement in future feedback design and a potential benchmark for feedback frequency in an action-oriented serious game-based ITTS. Among the conclusions are six design objectives for future ITTSs, establishing a foundation for future research on designing effective ITTSs that train interpersonal skills to nascent teams. (shrink)

The artificial intelligence models with machine learning that exhibit the best predictive accuracy, and therefore, the most powerful ones, are, paradoxically, those with the most opaque black-box architectures. At the same time, the unstoppable computerization of advanced industrial societies demands the use of these machines in a growing number of domains. The conjunction of both phenomena gives rise to a control problem on AI that in this paper we analyze by dividing the issue into two. First, we carry out (...) an epistemological examination of the AI’s opacity in light of the latest techniques to remedy it. And second, we evaluate the rationality of delegating tasks in opaque agents. (shrink)

Deep learning and artificial intelligence are jointly applied to concrete piano teaching for children to comprehensively promote modern piano teaching and improve the overall teaching quality. First, the teaching environment and the functions of the intelligent piano are expounded. Then, a piano note onset detection method is proposed based on the convolution neural network. The network can analyze the time-frequency of the input piano music signal by transforming the original time-domain waveform of the piano music signal into the frequency (...) distribution varying with time. Besides, it can detect the note onset at a stable state after 8 × 104 iterations. Moreover, an intelligent piano teaching method is designed to teach Jingle Bells for 40 preschool children aged 4–6 years. Finally, a questionnaire survey is performed to investigate the teaching situation, including the learning interest and learning effect of children and learning feedback from parents. The results show that 80% of children like smart music scores, 82% of children like intelligent piano lessons with games, and 84% of children can learn actively in the intelligent piano class. Besides, 85% of parents believe that their children are more interested in learning piano. In general, the intelligent piano teaching method effectively combines DL with AI to realize the overall optimization of piano performance. It is widely favored by preschool children and their parents and plays an important role in improving the interest of preschool children in piano learning. (shrink)

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

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

Not long ago, I was perusing a commentary on Verdi’s Aida, and came across the following observation: the music toward the end of the Nile Scene, in which Aida and Radames resolve to flee Egypt, is the same as that of Radames’s entrance earlier.

With the continuous development of the era of big data, community management plays an important role in people’s mental health. Improve people’s mental health through the use of big data to improve governance of the community. To solve the problem, sequence segmentation is used in feature extraction, histogram absolute difference calculation and K-means intelligent algorithm, to analyze the existing problems one by one. Research shows that it is possible to systematically govern the community through big data and intelligent computing, so (...) that community residents can live a higher quality of life. In order to get rid of psychological problems, it can be solved by establishing special psychological support institutions in the community and strengthening the role of the government in community management. With the continuous development of big data, the application of big data and intelligence in community governance and mental health community is a trend. With the continuous progress of society, it also brings pressure to people, which leads to the decline of people’s mental health quality. We need to do something to improve community governance and people’s mental health. (shrink)

Dragon boat sport is a traditional activity in China. In recent years, dragon boat sport has become more and more popular around the world. In order to face more challenges, it is urgent for athletes to enhance their own strength. Scientific training methods are particularly important for athletes, and accurate training data are the basis to support scientific training. Traditional mathematical statistic methods neither can sample signals accurately nor can they do real-time analysis and feedback the characteristics to each (...) athlete. In this paper, we use the wearable device with a triaxial accelerometer and heart rate sensor builtin to sample the speed signals and heart rate signals of athletes in various stages of men’s 1000m straight race. Based on the complex network theory, we regard the 23 dragon boat athletes in the dragon boat race as 23 nodes so as to establish a network with 23 nodes and reflect the importance of nodes by measuring the impact of node deletion on the results of the race. The neural network multilayer perceptron model is used for training to obtain the optimal combined value with speed and heart rate for each race stage. The optimal value will be used in the simulated race as the target value to verify if it can help to improve the training efficiency. Experimental results show that the optimal value obtained by this method has a positive effect on the results of the dragon boat race which is beneficial to sports training and tactics planning. (shrink)

Philosophical and sociological approaches in technology have increasingly shifted toward describing AI (artificial intelligence) systems as ‘(moral) agents,’ while also attributing ‘agency’ to them. It is only in this way – so their principal argument goes – that the effects of technological components in a complex human-computer interaction can be understood sufficiently in phenomenological-descriptive and ethical-normative respects. By contrast, this article aims to demonstrate that an explanatory model only achieves a descriptively and normatively satisfactory result if the concepts of (...) ‘(moral) agent’ and ‘(moral) agency’ are exclusively related to human agents. Initially, the division between symbolic and sub-symbolic AI, the black box character of (deep) machine learning, and the complex relationship network in the provision and application of machine learning are outlined. Next, the ontological and action-theoretical basic assumptions of an ‘agency’ attribution regarding both the current teleology-naturalism debate and the explanatory model of actor network theory are examined. On this basis, the technical-philosophical approaches of Luciano Floridi, Deborah G. Johnson, and Peter-Paul Verbeek will all be critically discussed. Despite their different approaches, they tend to fully integrate computational behavior into their concept of ‘(moral) agency.’ By contrast, this essay recommends distinguishing conceptually between the different entities, causalities, and relationships in a human-computer interaction, arguing that this is the only way to do justice to both human responsibility and the moral significance and causality of computational behavior. (shrink)

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

Increasing attention is paid to ethical issues and values when designing and deploying artificial intelligence (AI). However, we do not know how those values are embedded in artificial artefacts or how relevant they are to the population exposed to and interacting with AI applications. Based on literature engaging with ethical principles and moral values in AI, we designed an original survey instrument, including 15 value components, to estimate the importance of these values to people in the general population. The (...) article is based on representative surveys conducted in Estonia, Germany, and Sweden (_n_ = 4501), which have varying experiences with implementing AI. The factor analysis showed four underlying dimensions of values embedded in the design and use of AI: (1) protection of personal interests to ensure social benefit, (2) general monitoring to ensure universal solidarity, (3) ensuring social diversity and social sustainability, and (4) efficiency. We found that value types can be ordered along the two dimensions of resources and change. The comparison between countries revealed that some dimensions, like social diversity and sustainability evaluations, are more universally valued among individuals, countries, and domains. Based on our analysis, we suggest a need and a framework for developing basic values in AI. (shrink)

Biological systems exhibit complexity at all levels of organization. It has recently been argued by Michael Behe that at the biochemical level a type of complexity exists--irreducible complexity--that cannot possibly have arisen as the result of natural, evolutionary processes and must instead be the product of (supernatural) intelligent design. Recent work on self-organizing chemical reactions calls into question Behe's analysis of the origins of biochemical complexity. His central interpretative metaphor for biochemical complexity, that of the well-designed mousetrap that ceases (...) to function if critical parts are absent, is undermined by the observation that typical biochemical systems exhibit considerable redundancy and overlap of function. Real biochemical systems, we argue, manifest redundant complexity--a characteristic result of evolutionary processes. (shrink)

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

Artificial Intelligence (AI) in the 21st century is no longer perceived as a purely technological phenomenon, more and more becoming a social and humanitarian phenomenon that develops in a complex context of cultural, value, philosophical, and ethical aspects of human life. The impact of AIrelated technologies on contemporary society is still difficult to assess fully, which does not prevent enthusiastic researchers and political leaders from attempting to define a value framework that will ensure the use of AI for societal (...) development. As interest in AI grows, more and more technologically advanced countries in the world are creating their own strategies for the development and use of this technological marvel of the 21st century. These pioneering documents often seem vague and indefinite, but nevertheless they allow us to assess how the political and scientific and technological elites of these countries see the value orientations of AI technology development, both nationally and internationally. The article presents a philosophical analysis of the value orientations of AI technology development in the USA and China – modern scientific and technological leaders in this field – on the basis of strategic documents defining the development and application of AI in these countries from the position of post-non-classical scientific rationality. The authors of the article conclude that, at the contemporary post-non-classical stage of science development, the value component is not only one of the integral components of scientific and technological activities but may be decisive in determining the goals and objectives of high-tech development at the state level. (shrink)

As more national governments adopt policies addressing the ethical implications of artificial intelligence, a comparative analysis of policy documents on these topics can provide valuable insights into emerging concerns and areas of shared importance. This study critically examines 57 policy documents pertaining to ethical AI originating from 24 distinct countries, employing a combination of computational text mining methods and qualitative content analysis. The primary objective is to methodically identify common themes throughout these policy documents and perform a (...) comparative analysis of the ways in which various governments give priority to crucial matters. A total of nineteen topics were initially retrieved. Through an iterative coding process, six overarching themes were identified: principles, the protection of personal data, governmental roles and responsibilities, procedural guidelines, governance and monitoring mechanisms, and epistemological considerations. Furthermore, the research revealed 31 ethical dilemmas pertaining to AI that had been overlooked previously but are now emerging. These dilemmas have been referred to in different extents throughout the policy documents. This research makes a scholarly contribution to the expanding field of technology policy formulations at the national level by analyzing similarities and differences among countries. Furthermore, this analysis has practical ramifications for policymakers who are attempting to comprehend prevailing trends and potentially neglected domains that demand focus in the ever-evolving field of artificial intelligence. (shrink)

Nowadays, new directions for the development of artificial intelligence (AI) have emerged, the task has been set to develop artificial general intelligence (AGI), which is able to go beyond the narrow AI, gain a high degree of autonomy, independently solve problems in different environmental conditions and thus have the ability to perform the functions of natural intelligence. In this regard, important philosophical, theoretical, and methodological questions arise concerning the definition and evaluation of the social significance of new (...) AI achievements, especially regarding the correlation of their socio-humanitarian and technological aspects. It is necessary to overcome a purely technocratic approach, which usually ignores the negative consequences of digitalization, the possible risks and threats of AI development. These difficulties are conditioned by the paradigm gap between the system of concepts used to describe technologies and the systems of concepts specific to socio-humanitarian descriptions and explanations. The so-called ontological paradox arises during digital transformation and the introduction of AI into social systems. An ontological paradox is also an epistemological paradox, since any statement of an ontological type presupposes its epistemological justification. To overcome this gap, V.E. Lepskiy proposes the conception of self-developing polysubjective environments – cybernetics of the third order. This conception allows to create a conceptual “bridge” between two systems of definitions that do not have direct logical connections between them. A productive tool for this can be the information approach, which is widely used to solve such interdisciplinary problems. This makes possible to theoretically correctly connect technological and socio-humanitarian descriptions in a single conceptual structure and to analyze main socio-humanitarian criteria for evaluating digital innovations. The article discusses in detail the main provisions of the information approach and its application for the development of AGI systems, the socio-humanitarian assessment of AI autonomous development, and the resolution of security issues. (shrink)

Emotional intelligence is an emerging field since the 1990s due to its important outcomes for employees. This study is a psychometric meta-analysis examining the links between emotional intelligence and organizational commitment, organizational citizenship behavior, job satisfaction, job performance, and job stress of employees. In this meta-analysis, carefully selected studies on emotional intelligence since the origin of the concept in 1990 were included along with studies examining its outcomes. For this analysis, three streams of emotional (...) intelligence, consistent with previous meta-analyses, were considered: ability, self-report, and mixed emotional intelligence. This meta-analysis is an attempt to add to the literature by analyzing the relationships between emotional intelligence and selected employee outcomes over a period of time beginning in 1990. The three streams of emotional intelligence were separately analyzed to examine their relationship with employee outcomes. These outcomes were included in the study based on select research studies. Our study results showed that emotional intelligence and its three streams were positively related to organizational commitment, organizational citizenship behavior, job satisfaction, and job performance and negatively related to job stress. (shrink)

In July 2017, China’s State Council released the country’s strategy for developing artificial intelligence, entitled ‘New Generation Artificial Intelligence Development Plan’. This strategy outlined China’s aims to become the world leader in AI by 2030, to monetise AI into a trillion-yuan industry, and to emerge as the driving force in defining ethical norms and standards for AI. Several reports have analysed specific aspects of China’s AI policies or have assessed the country’s technical capabilities. Instead, in this article, we (...) focus on the socio-political background and policy debates that are shaping China’s AI strategy. In particular, we analyse the main strategic areas in which China is investing in AI and the concurrent ethical debates that are delimiting its use. By focusing on the policy backdrop, we seek to provide a more comprehensive and critical understanding of China’s AI policy by bringing together debates and analyses of a wide array of policy documents. (shrink)