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In both public and private sectors, critical technology-based tasks, such as innovation, forecasting, and road-mapping, are faced with unmanageable complexity due to the ever-expanding web of technologies which can range into thousands. This context cannot be easily handled manually or with efficient speed. However, more precise and insightful answers are expected. These answers are the fundamental challenge addressed by tech-mining. For tech-mining, discovering the associations among them is a critical task. These associations are used to form a weighted directed graph of technologies called “association tech-graph” which is used for technology development, trend analysis, policymaking, strategic planning, and innovation. In this article, we present a novel method to build an artificial intelligence (AI) agent for automatic association discovery among technologies in a way that matches the quality of the human experts. To this end, neural network-based word embedding methods are exploited to represent technology terms as vectors, and their associations are calculated using similarity measures. To increase the accuracy of the vectors, several crawlers are built to acquire more appropriate training data. Furthermore, we introduce a validation method to measure the accuracy of the AI agent compared to human intelligence, which allows us to discuss the drawbacks of both approaches.

The need for advanced automation and artificial intelligence (AI) in various fields, including text classification, has dramatically increased in the last decade, leaving us critically dependent on their performance and reliability. Yet, as we increasingly rely more on AI applications, their algorithms are becoming more nuanced, more complex, and less understandable precisely at a time we need to understand them better and trust them to perform as expected. Text classification in the medical and cybersecurity domains is a good example of a task where we may wish to keep the human in the loop. Human experts lack the capacity to deal with the high volume and velocity of data that needs to be classified, and ML techniques are often unexplainable and lack the ability to capture the required context needed to make the right decision and take action. We propose a new abstract configuration of Human-Machine Learning (HML) that focuses on reciprocal learning, where the human and the AI are collaborating partners. We employ design-science research (DSR) to learn and design an application of the HML configuration, which incorporates software to support combining human and artificial intelligences. We define the HML configuration by its conceptual components and their function. We then describe the development of a system called Fusion that supports human-machine reciprocal learning. Using two case studies of text classification from the cyber domain, we evaluate Fusion and the proposed HML approach, demonstrating benefits and challenges. Our results show a clear ability of domain experts to improve the ML classification performance over time, while both human and machine, collaboratively, develop their conceptualization, i.e., their knowledge of classification. We generalize our insights from the DSR process as actionable principles for researchers and designers of 'human in the learning loop' systems. We conclude the paper by discussing HML configurations and the challenge of capturing and representing knowledge gained jointly by human and machine, an area we feel has great potential.

The fifth industrial revolution brings in massive advantages, providing candidates with a more personalized experience in their job search. Industry 5.0 recognizes the power of industry in achieving societal goals beyond jobs and growth to become a resilient provider of prosperity by directing production towards respecting the boundaries of our planet and placing the well-being of the industry worker at the center of the production process. Contrary to the trends in Industry 4.0 toward technology, dehumanization, technological advancement and innovation best practices, Industry 5.0 will bend back toward serving humanity. At workplaces, this industrial revolution will shed greater light on the human intelligence than ever. The challenge now is to examine the influence of soft skills to enhance the workforce in order to prepare them for Industry 5.0. Emotional intelligence is a soft skill. The purpose of this study is to examine the influence of emotional intelligence on enhancing the workforce for Industry 5.0. A total of 110 executives took part in this study. Findings suggest that emotional intelligence does influence the workforce to perform better. Emotional recognition and expression and emotions direct cognition were found to have a greater impact on the performance.

One crucial characteristic of scientifically literate individuals is making informed decisions in socioscientific issues (SSI). Participants’ reasoning patterns and their risk perceptions shape their decisions. Thus, determining participants’ informal reasoning patterns along with their risk perceptions while making decisions in SSI becomes important. This study fulfills this important point by exploring pre-service science teachers’ informal reasoning patterns and their risk perceptions in an SSI topic, specifically gene therapy. Eleven pre-service science teachers enrolling in two different public universities participated in the study voluntarily. The study was designed as a basic qualitative approach. The data were collected by semi-structured interviews focusing on the use of gene therapy in Huntington’s disease and human intelligence cases. The results revealed that pre-service science teachers made decisions by using one (rationalistic, emotive, or intuitive) or more informal reasoning patterns together. Moreover, their risk perceptions were found to be based on the potential and severity of effects on humanity and society, participants’ morals and values, side effects, and a general concern born out of fear. In addition to their risk perceptions regarding gene therapy, they referred to positive aspects of technology, negative aspects of technology, and a two-edged sword implying positive and negative aspects of technology as a whole while making decisions. These results altogether pin the importance of including multiple forms of informal reasoning and risk perceptions in the pre-service science teacher education programs.

The article notes that today the global problem is the almost complete absence of normative legal regulation of the functioning and activities of artificial intelligence and standardization in this area should be implemented at the global level. However, the world community is just beginning to realize the real and potential nuances of the influence of fully automated systems on vital areas of social relations, on the growth of ethical, social and legal problems associated with this trend. The authors poses the question of who will directly be responsible for the wrong decision implemented in life proposed by “artificial intelligence” and various options for answering it are proposed. Only a conscious subject can be the subject of responsibility, and since weak systems do not have autonomy, on them, i.e. artificial intelligence cannot be blamed. Measures of legal liability are simply not applicable to it, for example, the elementary impossibility of artificial intelligence to recognize the consequences of its harmful actions. In conclusion, it is proved that with all its development and the speed of information processing, many times exceeding even the potential capabilities of a person, artificial intelligence remains a program with material and technical support tied to it. Only a person is responsible for the actions of mechanisms, is tested for strength. As for the direct responsibility of artificial intelligence, in the current legal and social conditions, the question of its hypothetical responsibility is of a dead-end nature, since the measures of legal responsibility are simply inapplicable to it, for example, it is elementary for artificial intelligence to realize the consequences of its harmful actions. Even if artificial intelligence can simulate human intelligence, it will not be self-aware, and therefore artificial intelligence can in no way claim any special fundamental rights

Incremental implicit theories are associated with a belief regarding it is possible to improve one’s intelligence or ability through efforts. Previous studies have demonstrated that incremental implicit theories contributed to better academic achievement and positive youth development. Our study aimed to examine whether incremental implicit theories of morality significantly influenced change in students’ engagement in voluntary service activities. In our study, 54 Korean college students for Study 1 and 180 Korean 8th graders for Study 2 were recruited to conduct two two-wave studies. We surveyed participants’ implicit theories of morality and participation in voluntary service activities. The effect of implicit theories of morality on change in service engagement was analyzed through regression analysis. In Study 1, the moral growth mindset significantly moderated longitudinal change in service engagement. In Study 2, the moral growth mindset significantly influenced engagement in art-related activities, while it significantly moderated change in engagement in youth-related activities.

There are three theories of human intelligence, namely Intellectual Quotient (IQ), Emotional Quotient (EQ), and Spiritual Quotient (SQ). In its subsequent development, following the SQ era that considered the God Spot in the human brain as a source of intelligence, the concept of the Heart’s Code (HC) indicates that the source of intelligence lies in the heart, not the brain. The SQ model proposed by Zohar-Marshall and the HC model suggested by Pearsall only touched the biological and psychological realms, namely the material brain and the material heart. Both have yet to touch upon the transcendental level of divinity i.e. the spiritual brain and the spiritual heart. Using Thomas Kuhn’s scientific revolution approach, the current article intends to prove that the source of intelligence is not the brain but the ruh (the soul). When God has perfected the creation of man by blowing ruh in him, the sense of hearing subsequently radiates through the ears, sight through the eyes, smell through the nose, speech through the mouth, taste through the tongue, and intelligence through the brain. As a consequence, the brain is but a tool; it is not a source of intelligence. If IQ, EQ, and SQ are regarded as intelligence models originating from the human mind, which is certainly artificial in nature, then Ruhani Quotient (RQ) is an intelligence model originally created by God. Ruhani Quotient (RQ), which is based on ruh, has implications on new studies pertaining to ‘ruhiology.’

The present essay compares two books dealing with the evolution of human mental abilities. Agustín Fuentes’ The Creative Spark focuses on creativity. Fuentes argues that creativity is the central element that makes human uniqueness, and highlights continuity between modern examples of creativity and early forms of human creative behaviour. Mark Maslin’s The Cradle of Humanity discusses the role of East Africa’s climate in increasing the intelligence of humans. To understand this role, Maslin combines geological and climatic data with the latest discoveries in human evolution and palaeontology. The essay compares the books’ content as well as their tone, and concludes on whether they might inspire future research on human evolution.

Purpose The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network. Design/methodology/approach The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions. Findings The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages. Research limitations/implications The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study. Originality/value Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value.

With the widespread use of online social networks, billions of pieces of information are generated every day. How to detect new topics quickly and accurately at such data scale plays a vital role in information recommendation and public opinion control. One of the basic research tasks of topic detection is how to represent a topic. The existing topic representation models do not focus on how to select better differentiated words to represent topics, are still computer-centered, and do not effectively combine human intelligence and artificial intelligence (AI). To solve these problems, this article proposes a word-distributed sensitive topic representation model (WDS-LDA) based on hybrid human-AI (H-AI). The basic idea is that the distribution of words within a topic or among different topics has a great influence on the selection of topic expression words. If a word is evenly distributed among all documents of a certain topic, it indicates that the word is the common word of all documents in the topic, and it is more suitable to represent this topic. If a word is more evenly distributed among various topics, it indicates that the word is a common word of all topics, and cannot be used for the purpose of distinguishing among topics, becoming less suitable to represent any topic. At the same time, the human cognitive ability and cognitive models are introduced into topic representation based on H-AI. We introduce the user's modification of topic expression words into the topic model representation so that the topic model can learn human wisdom and become more and more accurate. Therefore, three different weights are introduced: inside weight; outside weight; and manual adjustment weight. The inside weight describes the uniform distribution of a word in the given topic, the outside weight describes the uniform distribution of a word in all topics, and the manual adjustment weight reflects whether a word is suitable as a representative vocabulary in the past manual adjustment. Tests using Sina microblog's actual data sets show that the WDS-LDA algorithm makes the representative words more important, the distinction among different topic words higher, and effectively improves the precision of subsequent algorithms, such as topic detection and topic evolutionary analysis using the topic model. This work was supported in part by NSFC under Grant 61972106, Grant U1636215, Grant 61871140, Grant 61572153, and Grant 61872420, in part by the National Key research and Development Plan under Grant 2019QY1406 and Grant 2018YFB0803504, in part by the Guangdong Province Key Research and Development Plan under Grant 2019B010136003 and Grant 2019B010137004

The verses of the Al-Quran which talk about the potential of learning and neuroscience, describe the activity of the mind and the brain as a learning instrument to understand, study and analyze, these signals can be traced through key terminology related to human brain activity. The terms tafakkur, tadabbur, ta'aqqul are theological foundations that describe the potential for human learning in a Neouroscience perspective. The brain is the center of human intelligence which controls the entire nervous system in capturing learning activities. with the power of the human brain can find various things that can facilitate human life. Cues of potential learning by maximizing brain nerve function (Neuroscience) can be traced to, QS Asy-Shams Verses 7-9, QS. An-Nahl 78, QS Ar-Rum 8, QS Al-Baqarah 219 and QS. Muhammad 24. The potential for human learning that is implemented in Islamic education, must develop a variety of potentials, so that the implementation of Islamic education can maximize the development of a comprehensive potential, such as Tarbiyah Imaniyah, Khuluqiyah, Tarbiyah, Jismiyah, Tarbiyah Aqliyah, Nafsiyah Ijtima'iyah. By maximizing the development of the potential, it will produce quality Islamic education output.

21st-century knowledge economy driven modern curriculum needs students to perceive complex dimensions of knowledge to be intellectually competent [1]The authors have observed that animation is an excellent way of presenting academics in a less complicated form to students as the concepts can be presented lively and engaging students visually. It has been found out that the platform and the learning atmosphere impact on data mining [2]This study was conducted with the main objective to assess the impact of using 2D animation as an effective teaching tool and to evaluate the most effective learning atmosphere for undergraduate studies. The authors have incorporated a qualitative approach to systematically investigate in-depth the effective use of 2D animation as a teaching tool. The authors have selected 180 business management undergraduate students as the sample of this study.The sample was divided in to two groups where each group comprised of 90 students. One group of students were taught using the 2D animated videos using animated characters relevent to the course module and the other group of students were taught using only the presentation slides created throughMicrosoft power point using only text and images. Through thematic analysis and participant observations, it was found out that there is a direct effect of using animated characters as a teaching tool and it was found out that using 2D animations add more value to the role of a lecturer when delivering through online platforms. This study's findings contribute towards emphasising how effective and innovative teaching techniques can be developed using 2D animations in a classroom environment. Thereby, through positive enhancement of the next generation of leaders' knowledge and attitudes in our country will increase the human intelligence assets in the knowledge-driven economy.

Purpose This paper aims to present an exploration of possible associations between the Jungian archetypes frequently used in marketing and three well-known products based on artificial intelligence (AI), namely, Sophia, Alexa and Articoolo. Design/methodology/approach The study conducted emotionalist interviews to gather thick data from 11 participants on how they conceptualize these AI-based products. In the absence of any existing relevant hypotheses, this paper attempts to build theory using a case study approach and qualitative analysis of interview narratives. Findings Despite the human attributes ascribed to these products, participants were principally concerned with their purpose, efficiency and the degree of trust which they felt could be accorded to the product. Anthropomorphism emerged as significant with participants making some associations with common archetypes traditionally exploited in marketing and this suggests a possible means of enhancing consumer trust in AI products. Originality/value Little research has been conducted on the marketing of AI and this study presents a timely identification of some potentially significant issues. As AI is intended to mimic some aspects of human intelligence, the role of the archetype in creating a personality to enhance trust may prove crucial in securing consumer confidence.

Artificial intelligence (AI) is essentially the simulation of human intelligence. Today’s AI can only simulate, replace, extend, or expand part of human intelligence. In the future, the research and development of cutting-edge technologies such as brain-computer interface (BCI) together with the development of the human brain will eventually usher in a strong AI era, when AI can simulate and replace human’s imagination, emotion, intuition, potential, tacit knowledge, and other kinds of personalized intelligence. Breakthroughs in algorithms represented by cognitive computing promote the continuous penetration of AI into fields such as education, commerce, and medical treatment to build up AI service space. As to human concern, namely, who controls whom between humankind and intelligent machines, the answer is that AI can only become a service provider for human beings, demonstrating the value rationality of following ethics.

Ethical analyses of biomedical human enhancement often consider the issue of authenticity — to what degree can the accomplishments of those utilizing biomedical enhancements (including cognitive or athletic ones) be considered authentic or worthy of praise? As research into Brain-Computer Interface (BCI) technology progresses, it may soon be feasible to create a BCI device that enhances or augments natural human intelligence through some invasive or noninvasive biomedical means. In this article we will (1) review currently existing BCI technologies and to what extent these can be said to enhance or augment the capabilities of the respective users, (2) describe one hypothetical type of BCI device that could augment or enhance a specific aspect of human knowledge — namely, mathematical ability, and (3) relate these concepts to the active externalism view of the extended mind as espoused by Clark and Chalmers in order to (4) argue that knowledge of mathematics derived from the usage of a BCI and the application thereof constitutes authentic knowledge and achievement.

The singularity of artificial intelligence (AI), which transcends human intelligence to play the role of God, is imminent. In this context, the Chinese judicial system has gained some latecomer advantage, with the help of information technology, the Internet, big data, cloud computing, and AI to improve the efficiency and transparency of case handling. The trial process has undergone extensive and profound qualitative mutations. This represents a challenge to the institutional arrangements of the modern rule of law. At this stage, we should adopt a cautious and prudent attitude towards the design and application of legal-expert systems as well as machine learning. Especially from the aspect of computer sentencing, it is even more necessary to avoid a rush for quick results, and there is no need to completely exclude the judge’s discretion and free evaluation of the evidence through inner conviction. The finality of the judicial power is destined to choose a correct final solution through a debate on the survival of the fittest mechanism. In the face of such a modern rule-of-law system, big data, cloud computing, information technology, and AI are just auxiliary means to achieve legal justice. It is impossible to put the cart before the horses. This is a basic principle that we should always bear in mind.

É irrefutável que softwares de inteligência artificial, cada vez mais, produzem conteúdo que antes era apena afeto aos seres humanos. Desde 1970 existem obras artísticas criadas por inteligências artificiais e, inclusive, em formato que é possível considera-las originais e criativas. Tal fato ensejou o enfrentamento teórico sobre a (im)possibilidade de tais obras serem protegidas por direitos autorais. Existem, pelo menos, três correntes teóricas sobre o tema: a primeira atribui direitos autorais diretamente à inteligência artificial, a partir da criação de uma personalidade eletrônica, ou desenvolvendo uma coautoria com a inteligência artificial; a segunda atribui os direitos autorais ao programador do software ou à empresa por trás do investimento, e a terceira defende que não há que se falar em direito autoral neste caso, pertencendo a obra ao domínio público. A discussão do tema enfrenta questões enraizadas sobre a forma de compreensão do mundo pelo ser humano, de grande complexidade, relacionadas a problemas de ordem filosófica, psicológica, social e também jurídica. E é por esta razão que nenhuma das correntes teóricas apresentadas conseguem solucionar de forma plena todos os desafios impostos ao Direito Autoral, já que o cerne para solução do tema proposto é a compreensão da própria inteligência humana e suas limitações. Para a realização da análise teórica, a partir de pesquisa exploratória e bibliográfica, partiu-se de casos concretos, utilizando-se, portanto, do método indutivo para elaboração do trabalho. Palavras-chave: Inteligência artificial. Obras intelectuais. Direito Autoral.

O objetivo deste artigo é abordar o brincar enquanto essência da criança e o brinquedo material ou materializado condutor dessa ação, envolvidos por afetos, culturas e épocas. Para tal, foi realizada uma revisão de literatura com contribuições de autores da historiografia, sobre a infância; da filosofia com as percepções de Platão; da arqueologia, que identificou o brincar em achados pré-históricos, a exemplo das artes rupestres; da psicologia e as suas observações do brincar, enquanto predisposição hereditária e da sua relação com a cognição, bem como da psicanálise que, na mesma época observou no brincar conteúdos inconscientes. Para neurociência esse comportamento compreende as regiões mais antigas do cérebro (regiões subcorticais), que influenciam a estruturação das regiões neocorticais, responsáveis pela inteligência humana. O diálogo multidisciplinar amplia o olhar sobre a natureza do brincar e suas características, seus aspectos históricos e culturais, origem ancestral e envolvimento com a complexa estrutura cerebral relacionada à inteligência.

The articles in this special section focus on developments in the area of hybrid human artificial intelligence. Humans want machines to be intelligent, with the machines serving them as much as possible. Yet they are concerned that these machines with full autonomy may one day outperform them and become too powerful to be controlled. The blend of desire and fear has led to this emerging futuristic research area, hybrid human-artificial intelligence.

We are currently experiencing a new revolution, which is related to the Internet, nanotechnology, biotechnology and robotics. Artificial intelligence is based on intelligent algorithms or learning algorithms similar to human intelligence, technologies make it possible for computer systems to acquire independence, self-adaptive reconfiguration. The greater the autonomy of AI, robots, and androids, the less they depend on manufacturers, owners, and users.The fact that the new generation of robots will coexist with humans should be taken into account in legislation, it should adapt and regulate issues of great legal significance, namely: who takes responsibility for the actions or inaction of intelligent robots? What is their legal status? Should they have a special regime of rights and obligations? How to resolve ethical conflicts related to their behavior?The analysis of legislation and doctrine in Latin America has revealed some trends in the use of AI.1. The use of AI in various spheres of public life causes legal problems in terms of guaranteeing human rights, as evidenced by the analysis of the constitutions of Brazil, Mexico and Argentina. For example, article 8 of the American Convention on Human Rights states: "Everyone has the right to have his case heard, with appropriate guarantees and within a reasonable period of time, before a competent, independent and impartial court convened in advance by law in support of any criminal charge brought against him or to determine his rights or obligations of a civil, labour, financial or any other nature."2. The similarity of AI and human intelligence raises the question of legal personality of AI, granting AI rights. The civil and commercial code of Argentina departs from the category of "human person" and establishes the term "legal persons": "all persons to whom the legal system grants the ability to acquire rights are legal persons for the purpose of fulfilling their purpose and obligations".The line between things and people is becoming more blurred, technology and a more sensitive view of other living beings lead to doubt whether man is the sole subject of law.

Background:The ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term “intelligence” does not best represent the technological needs of advancing society, because it is “wisdom”, rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW).Methods:We examine the constructs of human intelligence and human wisdom in terms of their basic components, neurobiology, and relationship to aging, based on published empirical literature. We review the development of AI as inspired and driven by the model of human intelligence, and consider possible governing principles for AW that would enable humans to develop computers which can operationally utilize wise principles and result in wise acts. We review relevant examples of current efforts to develop such wise technologies.Results:AW systems will be based on developmental models of the neurobiology of human wisdom. These AW systems need to be able to a) learn from experience and self-correct; b) exhibit compassionate, unbiased, and ethical behaviors; and c) discern human emotions and help the human users to regulate their emotions and make wise decisions.Conclusions:A close collaboration among computer scientists, neuroscientists, mental health experts, and ethicists is necessary for developing AW technologies, which will emulate the qualities of wise humans and thus serve the greatest benefit to humanity. Just as human intelligence and AI have helped further the understanding and usefulness of each other, human wisdom and AW can aid in promoting each other’s growth

Artificial intelligence is regarded in the context of the tasks that are delegated to it during the development of technical projects and the features of the implementation of tasks that must be performed in real time without the possibility of interruption. The relevance of the study is determined by the fact that artificial intelligence sees as its main task the formalisation of decision-making with little or no human involvement. The basis of the methodological search are biological and prognostic methods. The current stage of development of socio-humanitarian technologies, and in particular, systems with artificial intelligence, prompts people to conduct such socio-technical projects, for the implementation of which the properties of the human biological brain are no longer enough. The result of research on artificial intelligence is the desire to understand the work of the human brain, to reveal the secrets of human consciousness and the problem of creating machines with a certain level of human intelligence. The novelty of the study is determined by the fact that the understanding of artificial intelligence is primarily aimed at creating an environment that can distinguish artificial intelligence from the entire array of technological devices not only as a platform of knowledge and program code. The practical significance of the study is determined by the necessity for standardisation and the formation of attitudes and the acceptability of the use of artificial intelligence in tasks that will subsequently affect social development.

International audience; The default mode network (DMN) is believed to subserve the baseline mental activity in humans. Its higher energy consumption compared to other brain networks and its intimate coupling with conscious awareness are both pointing to an unknown overarching function. Many research streams speak in favor of an evolutionarily adaptive role in envisioning experience to anticipate the future. In the present work, we propose a process model that tries to explain how the DMN may implement continuous evaluation and prediction of the environment to guide behavior. The main purpose of DMN activity, we argue, may be described by Markov Decision Processes that optimize action policies via value estimates based through vicarious trial and error. Our formal perspective on DMN function naturally accommodates as special cases previous interpretations based on (1) predictive coding, (2) semantic associations, and (3) a sentinel role. Moreover, this process model for the neural optimization of complex behavior in the DMN offers parsimonious explanations for recent experimental findings in animals and humans.

Rapport is an integral part of interviewing, viewed as fundamental to the success of intelligence elicitation. One collection capability is human intelligence (HUMINT), the discipline charged with eliciting intelligence through interactions with human sources, such as covert human intelligence sources (CHIS). To date, research has yet to explore the perceptions and experiences of intelligence operatives responsible for gathering HUMINT within England and Wales. The present study consisted of structured interviews with police source handlers (N = 24). Rapport was perceived as essential, especially for maximising the opportunity for intelligence elicitation. Participants provided a range of rapport strategies while highlighting the importance of establishing, and maintaining, rapport. The majority of participants believed rapport could be trained to some degree. Thus, rapport was not viewed exclusively as a natural skill. However, participants commonly perceived some natural attributes are required to build rapport that can be refined and developed through training and experience.

To a greater extent than in other technical domains, research and progress in Artificial Intelligence has always been entwined with the fictional. Its language echoes strongly with other forms of cultural narratives, such as fairytales, myth and religion. In this essay we present varied examples that illustrate how these analogies have guided not only readings of the AI enterprise by commentators outside the community but also inspired AI researchers themselves. Owing to their influence, we pay particular attention to the similarities between religious language and the way in which the potential advent of greater than human intelligence is presented contemporarily. We then move on to the role that fiction, science fiction most of all, has historically played and is still playing in the discussion of AI by influencing researchers and the public, shifting the weights of different scenarios in our collectively perceived probability space. We sum up by arguing that the lore surrounding AI research, ancient and modern, points to the ancestral and shared human motivations that drive researchers in their pursuit and fascinate humanity at large. These points of narrative entanglement where AI meets the wider culture should serve to amplify the call to engage ourselves with the discussion of the potential destination of this technology.

Reviews and meta-analyses have proved to be fundamental to establish neuroscientific theories on intelligence. The prediction of intelligence using invivo neuroimaging data and machine learning has become a widely accepted and replicated result. We present a systematic review of this growing area of research, based on studies that employ structural, functional, and/or diffusion MRI to predict intelligence in cognitively normal subjects using machine learning. We systematically assessed methodological and reporting quality using the PROBAST and TRIPOD in 37 studies. We observed that fMRI is the most employed modality, resting-state functional connectivity is the most studied predictor. A meta-analysis revealed a significant difference between the performance obtained in the prediction of general and fluid intelligence from fMRI data, confirming that the quality of measurement moderates this association. Studies predicting general intelligence from Human Connectome Project fMRI averaged r = 0.42 (CI95% = [0.35, 0.50]) while studies predicting fluid intelligence averaged r = 0.15 (CI95% = [0.13, 0.17]). We identified virtues and pitfalls in the methods for the assessment of intelligence and machine learning. The lack of treatment of confounder variables and small sample sizes were two common occurrences in the literature which increased risk of bias. Reporting quality was fair across studies, although reporting of results and discussion could be vastly improved. We conclude that the current literature on the prediction of intelligence from neuroimaging data is reaching maturity. Performance has been reliably demonstrated, although extending findings to new populations is imperative. Current results could be used by future works to foment new theories on the biological basis of intelligence differences., Intelligence, 93, ISSN:0160-2896

“Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never ...

Today, creativity is vital for building a successful career ladder. The evolving digital technologies contribute to the achievement of new goals, which gives the employee the opportunity to realize their potential. At the same time, the development of artificial intelligence transforms the workspace, setting the boundaries for workers’ creativity. The introduction of these technologies can have serious consequences for employees, thus, people can abandon solving analytical and creative tasks, delegating them to artificial intelligence. This is a serious threat to the anthropocentricity of society. Creativity enables human intelligence to compete with artificial intelligence, which means that the development of the creative abilities of future specialists is very important for preserving the anthropocentrism of society. The law should contribute to minimizing these risks. Since most professionals are involved in labor relations, labor laws can help develop creativity. For example, digital control restricts the employee's right for privacy, while creativity is a skill better developed by a free person. Therefore, it is necessary to limit the use of digital sensors and neurosensors to monitor employees on a legislative level.

On the internet, artificial intelligence has grown to become a program with codes and algorithms that learn and reprogram themselves to carry out pre-established tasks with greater efficiency; although this translates into improvements, the scope of the results and reprogramming are unknown to the programmer. Given the risk of deviation from pre-established objectives and ethical regulations, filters must be installed at the beginning, during and at the end of the process, as alarms for detecting deviations with bioethical implications. The interaction of human intelligence with artificial intelligence has had negative and positive disagreements. Initially, adapting regulations, labor laws and human rights was enough; now it is necessary for ethical standards to be established, such as those formulated in the Barcelona Declaration for the Proper Development and Usage of Artificial Intelligence in Europe.En internet ha crecido la inteligencia artificial hasta convertirse en un programa con códigos y algoritmos que aprenden y se reprograman para efectuar tareas preestablecidas con mayor eficiencia; si bien lo anterior se traduce en mejoría, el programador desconoce los alcances de los resultados y de la reprogramación. Ante el riesgo de desviación de los objetivos preestablecidos y de los reglamentos éticos, se tienen que implementar filtros al inicio, durante y al final del proceso, como alarmas cuando existan desviaciones con implicación bioética. La interacción de la inteligencia humana con la inteligencia artificial ha tenido desencuentros negativos y positivos. Al principio, bastó con adecuar normas, leyes laborales y derechos humanos; ahora se requiere establecer normas éticas, como las formuladas en la Declaración de Barcelona para el Adecuado Desarrollo y Uso de la Inteligencia Artificial en Europa.

The 21st century is marked by the rapid development of science and technology: robots are gradually entering all spheres of human life and activity, along with other mechanisms. In this regard, in society, in popular science literature, in the media, the question is increasingly being asked, can a robot, in particular with artificial intelligence, replace a person in performing professional activities? Variety of problem of the impact of the introduction of robots and artificial intelligence on the future lives and activities of mankind is highlighted in research, discussions, statements, public speeches by E. Musk, B. Pring, P. Ro e hrig, M. Frank, S. Hawking, M. Zuckerberg, etc. « Success in creating artificial intelligence could be the biggest event in the history of our civilization, or the worst. Computers can, in theory, emulate human intelligence, and exceed it. », - S. Hawking said. The purpose of the article: to carry out the psychological futurological forecast for the introduction of robots, artificial intelligence, in particular in the higher education system through the prism of the author's many years of psychological and pedagogical experience. The current trends in the achievements of scientific and technological progress are analyzed : every day all over the world there are news about examples of successful professional interaction between people and robots (robots Sofia, Grace, Aypera, student robot and much more). Conclusions: the probable possibility of professional competition between humans and robots is obviously a positive argument for obtaining higher education, as well as the ability to constantly learn independently, based on the knowledge, skills and abilities already acquired. The robotization of the educational system should lead to significant facilitation and simplification of the teacher's activities in the future, since all routine work can be put on robots, in turn, teachers will be able to fully devote themselves to pedagogical creativity. Keywords: robot, artificial intelligence, professional interaction between people and robots, higher education. Accepted : 04.10.2021 Reviewed : 14.10.2021 Published : 18.10.2021 DOI : http://doi.org/10.31108/3.2021.5.2. 7

Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector.

This article is qualitative-descriptive analytical research on multiple intelligences, a theory which Howard Gardner introduced. According to Howard Gardner's findings, the concept of multiple intelligences has been widely known and used in educational institutions. Multiple intelligences are also considered a theory that first recognized the diversity of human intelligence. With multiple intelligences, it can be said that no child is stupid. Therefore, each child is born with intelligence that is not always equal to each other. In Islam, the Quran is a complete guide for life. This research has discovered the powerful instruments to develop Qur'anic multiple intelligences in educational institutions through literature. With the thematic interpretation method (maudhui) approach, this study described the practical efforts, using the mindset of interpretation and reflection, to develop the concept of multiple intelligences based on the perspective of the Quran. After researching, collecting, and analyzing all terms in the Quran that relate to intelligence, it is found that the Quran is distinguishing the concept of multiple intelligences. It can be used further as a practical guide for educational institutions in developing the concept of multiple intelligences from the perspective of the Quran

Numerous technologies are being integrated to enhance the services and tourist experiences in the field of tourism in which a digital support is provided to travelers before during and after the travel activity. Artificial Intelligence is the human intelligence technology to perform particular tasks. Artificial Intelligence offers travel services that are automated, customized and insightful to make tourism as Digital Tourism. The application of artificial intelligence in people's life have a significant role and so this article focuses on how AI technology can lead to the next mile stone in the tourism industry. Here we studied on Chatbot a revolution that has emerged in Artificial Intelligence which can solve our queries easily. This study is structured into two phases, first Identifying the customer preferences on the destination Coimbatore, second phase is developing a chatbot on Coimbatore as a destination Ask me WHW(What, How, Where). Bot covers 3 A’s of Coimbatore-Access, Attraction and Accommodation The rapid digitalization and vast potential of technologies will help in tourism development which make travel ease and feasible. It also interacts with customers and function as a virtual tour guide.

Knowledge representation as expert system rules or using frames and variety of logics, played a key role in capturing explicit knowledge during the hay days of AI in the past century. Such knowledge, aligned with planning and reasoning are part of what we refer to as Symbolic AI. The resurgent AI of this century in the form of Statistical AI has benefitted from massive data and computing. On some tasks, deep learning methods have even exceeded human performance levels. This gave the false sense that data alone is enough, and explicit knowledge is not needed. But as we start chasing machine intelligence that is comparable with human intelligence, there is an increasing realization that we cannot do without explicit knowledge. Neuroscience (role of long-term memory, strong interactions between different specialized regions of data on tasks such as multimodal sensing), cognitive science (bottom brain versus top brain, perception versus cognition), brain-inspired computing, behavioral economics (system 1 versus system 2), and other disciplines point to need for furthering AI to neuro-symbolic AI (i.e., hybrid of Statistical AI and Symbolic AI, also referred to as the third wave of AI). As we make this progress, the role of explicit knowledge becomes more evident. I will specifically look at our endeavor to support human-like intelligence, our desire for AI systems to interact with humans naturally, and our need to explain the path and reasons for AI systems’ workings. Nevertheless, the variety of knowledge needed to support understanding and intelligence is varied and complex. Using the example of progressing from NLP to NLU, I will demonstrate the dimensions of explicit knowledge, which may include, linguistic, language syntax, common sense, general (world model), specialized (e.g., geographic), and domain-specific (e.g., mental health) knowledge. I will also argue that despite this complexity, such knowledge can be scalability created and maintained (even dynamically or continually). Finally, I will describe our work on knowledge-infused learning as an example strategy for fusing statistical and symbolic AI in a variety of ways.

The advancement of AI enables the evolution of machines from relatively simple automation to completely autonomous systems that augment human capabilities with improved quality and productivity in work and life. The singularity is near! However, humans are still vulnerable. The COVID-19 pandemic reminds us of our limited knowledge about nature. The recent accidents involving Boeing 737 Max passengers ring the alarm again about the potential risks when using human-autonomy symbiosis technologies. A key challenge of safe and effective human-autonomy teaming is enabling “trust” between the human-machine team. It is even more challenging when we are facing insufficient data, incomplete information, indeterministic conditions, and inexhaustive solutions for uncertain actions. This calls for the imperative needs of appropriate design guidance and scientific methodologies for developing safety-critical autonomous systems and AI functions. The question is how to build and maintain a safe, effective, and trusted partnership between humans and autonomous systems. This talk discusses a context-based and interaction-centred design (ICD) approach for developing a safe and collaborative partnership between humans and technology by optimizing the interaction between human intelligence and AI. An associated trust model IMPACTS (Intention, Measurability, Performance, Adaptivity, Communications, Transparency, and Security) will also be introduced to enable the practitioners to foster an assured and calibrated trust relationship between humans and their partner autonomous systems. A real-world example of human-autonomy teaming in a military context will be explained to illustrate the utility and effectiveness of these trust enablers.

Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a subtype of AI; it refers to the ability of computers to draw conclusions (ie, learn) from data without being directly programmed. ML builds from traditional statistical methods and has drawn significant interest in healthcare epidemiology due to its potential for improving disease prediction and patient care. This review provides an overview of ML in healthcare epidemiology and practical examples of ML tools used to support healthcare decision making at 4 stages of hospital-based care: triage, diagnosis, treatment, and discharge. Examples include model-building efforts to assist emergency department triage, predicting time before septic shock onset, detecting community-acquired pneumonia, and classifying COVID-19 disposition risk level. Increasing availability and quality of electronic health record (EHR) data as well as computing power provides opportunities for ML to increase patient safety, improve the efficiency of clinical management, and reduce healthcare costs.

This essay maps IBM’s attempts to construct a typology of high-tech ‘New Collar’ work and leverage policymaking outcomes to underwrite IBM corporate ventures capable of materializing this work. Through a discursive analysis of IBM corporate texts, webpages, and the 2017 New Collar Jobs Act, I argue for New Collar work to be understood through the lens of autonomy, as IBM recasts notions of ‘autonomous’ technology onto humans by downplaying dystopic associations of technological autonomy and transferring notions of autonomy to human workers. In doing so, I account for IBM’s use of ‘augmentation’ to situate human intelligence as the cognitive force uplifted by work performed with artificial intelligence. By pairing human augmentation with posthumanist conceptions of ‘distributed cognition’, IBM centers human intelligence through a redistributed cognition that reverses posthumanism’s decentering of human supremacy. Following from this, I unpack ‘New Collar’ as a reinvention of ‘white’ and ‘blue’ collar dichotomies and New Collar work as the grounds for tech workers to reinvent themselves. In this way, by minimizing the necessity of 4-year college degrees as pathways to economic and professional mobility, IBM constructs ‘New Collar’ with embedded notions of enlarged self-determination for applied worker intellect, vocational training, and employability. Under the aegis of creating, training, and employing New Collar workers, IBM pursues policy outcomes to underwrite corporate ventures related to New Collar work and bolster its institutional autonomy amidst marketplaces of cognitive capitalism. By outlining how tax relief provisions of the New Collar Jobs Act correlate with neoliberal ideologies of legislators and IBM investments in public–private vocational models and cybersecurity platforms, I account for IBM’s elongated ‘economy of learning’ that enables the company to more thoroughly capture, underwrite, and commodify New Collar cognition from training to market outputs.

Purpose The purpose of this paper is to underscore the need for developing a meta-intelligence in companies based on a conceptual framework for combining artificial and human intelligence. Design/methodology/approach This is a conceptual paper, which draws on the insights from extant theoretical and empirical research. Findings In light of a growing trend towards artificial intelligence (AI), most companies face substantial difficulties, which often derive from an excessive emphasis on merely replacing human intelligence by means of AI. To capture the complementary benefits of artificial and human intelligence beyond mere cost savings, firms do not only need to enhance their advanced analytics while continuing to develop their human intelligence. Rather, they additionally need a meta-intelligence for transforming their intelligence architecture in line with corporate strategy. Consequently, the firms need intelligence3 – comprising AI, human intelligence and the meta-intelligence. Originality/value The new concept of a meta-intelligence for renewing and recombining artificial and human intelligence helps to reconcile diverse findings in prior research. Without this meta-intelligence, most AI initiatives will be isolated endeavors, which may have positive effects but likely will not live up to the expectations.

Purpose The aim of this study is to develop a spiritual intelligence scale from an Islamic perspective. In addition, this research explores the relationship of spiritual intelligence from an Islamic perspective with emotional intelligence among the students of higher learning institutions in Malaysia. Design/methodology/approach Data were collected from 250 students from different higher learning institutions in Malaysia. Findings The findings of the study show the relationships of spiritual intelligence from an Islamic perspective and emotional intelligence. Statistically significant relationships were found between four dimensions of spiritual intelligence from an Islamic perspective (e.g. transcendental awareness, meaning of life, patience and forgiveness) and emotional intelligence. Originality/value The contribution of human intelligence in the development higher learning institution is remarkable. Most research found on spiritual intelligence is from traditional and Western perspective with very limited studies found from an Islamic perspective. The purpose of the current study is to construct a spiritual intelligence from an Islamic perspective and empirically validate the items. The study also looks for relationships of spiritual intelligence from an Islamic perspective and emotional intelligence among the students of higher learning institutions.

Ever since the inception of Machine Learning and Artificial Intelligence, the basic motto for most of research works has been to bring the machines at par with human intelligence. Designing new products and artifacts is one of the many fields where it is very difficult to enable computing machines replicate human creativity and innovativeness. Design processes in engineering fields as well as in arts follow methodical series of steps to create new products. Due to high demands of customized products and services, competitors tend to shorten the time-to-market periods, using advanced Computer-Aided Design programs. These programs play important roles to assist designers in digitizing blueprints and automating repetitive tasks. However, they fail to boost designer creativity by generating or suggesting new ideas or designs based on existing products or their variants. In order to boost creativity in the entertainment industry, we propose in this paper a new approach based on unsupervised learning techniques to create variants of a given artifact or product blueprints. Within the field of designing new cartoon characters, our proposed approach relies on Generative Adversarial Neural Networks [1] to create new anime or cartoon faces on their own without any human intervention. It learns features and characteristics from an image training dataset and combines them to create new features and thus builds a new image which is not present in the training dataset. This applied approach attempts to not only help artists and designers to have a preview of the possible new and unique avatars but also would prevent any copyright infringements.

In an effort to realize their dreams, people develop natural communication where it is possible to obtain a variety of resources. Nature is the guarantor of itsautopoesis, complexity of relationships and the development of intelligence. At the same time through culture, the development of digital technology, net­work communications, people enhances creative potential, expanding their own development opportunities. Modern world, full of dynamic change processes, formats, of a person, affecting him more than ever, but the man himself is com­mitted to manage its own natural capacity to master the digital technologies of communication, developing creative interaction, communication. One of the burn­ing issues is the resource base for the development of human intelligence, the human brain, its correlation with the morphological level of existence of the organism. In this communication the person that owns digital technology ac­tually creates a new cultural space, understood them very poorly. In the culture appeared logic, which carries risks, which creates the human experience of awareness of the external results of the technical creativity, but ignores, excludes the person. Such self-understanding gives rise to a contradiction when natural autopoiesis keeps the human intellect, and culture lays down the principle of the loss of valuable properties of individual. This crisis manifests itself in the spread in the world community of ideas of transhumanism, carrying a grow­ing disregard for the natural human intelligence, and the desire to develop each motive turning yourself into an object of experimentation, of self-transformation in a technical device. Creating the future through unique functional Hi-tech ex­pansion, man is able through the update technology, to create its own conditions of development, to find the update principles of development models for harmo­nization of relations in nature and culture.

There is a direct link between human intelligence and intelligence services. Intelligence is a high level dynamic knowing process, a decision-making support function. For its complexity, it is difficult to define, but its major attributes can be grasped. With openness of the political power, intelligence can produce added value. International “proliferation” of intelligence, the changing publicity do not narrow the leeway of services. Political decision-making will need intel-support in the future, too. For the intelligence service, the key to success resides in continuous observation of the changing environment, learning, organisational and information technology adaptation and identification of opportunities of serving national interests.

Being an aptitude, human intelligence needs to develop a lot of exercise and knowledge. The ability to understand, visualize and solve problems must be cultivated and rigorously guided. This paper presents a new integrated method of teaching the Technical Drawing and Infographics, with the purpose of training new students. The method is based on the observations of the teachers during the last years, their experience in education and the suggestions of the students. The results of applying this integrated method are quantifiable, leading to a better attendance at courses, towards 95%, at a much lower risk of school dropout and not least, creating bridges between abstract and reality.

Purpose The purpose of this paper is to address the possible future evolution of innovation from a human-only initiative, to human–machine co-innovation, to autonomous machine innovation and to arrive at a conceptual mind model that outlines the role of innovation regimes and innovation agents. Design/methodology/approach This is a concept paper where a theoretical “thought experiment” is done, using future thinking principles and data that originate from the literature. Findings A conceptual mind model is developed to facilitate a better understanding of complexity at the edge of innovation where intelligent machines will emerge as innovators of the cyber world. It was found that innovation will gradually evolve from a human-only activity, to human–machine co-innovation, to incidences of autonomous machine innovation, based on the growth of machine intelligence and the adoption of human–machine partnership management models in future. Research limitations/implications Very little information is available in the literature on intelligent machines doing innovation. The work is based on a theoretical approach that presents new concepts to be debated, but have not been tested in engineering and technology management practice, except for a conference presentation and academic discussion. Practical implications The current world view is that future “smartness” is only possible through the creative abilities that humans have, but as machines are entering the workplace and our daily lives, not only as static robots on a manufacturing line, but as intelligent systems with the potential to replace lawyers and accountants, doctors and teachers, companions and partners, their role in innovation in complex environments needs to be explored. Social implications Human–machine interaction is often an emotional social issue of concern in terms of the replacement of human intelligence with machine intelligence. It should be asked whether humans will or should remain in control of innovation? Artificial intelligence (AI) may complement and even substitute human intelligence, but huge value is embedded in the new goods, services and innovations AI will enable, especially in manufacturing, where value embedded in the project becomes complex and dynamic. Originality/value The thinking presented in this paper is original and should lead to debate to question the way innovation systems will work in future and inspires thinking about AI and innovation.

Artificial Intelligence (AI) is a rapidly growing field; one that is mysterious to the general public. The mention of the word AI fills the imaginations of many with thoughts of talking robots, jobs being replaced, and possibly even the destruction of mankind. Perhaps imaginations are running wild due to, perhaps driven by the loose definition of AI as systems able to perform tasks that normally require human intelligence that allows Hollywood to take some creative license. The experts in the field tend to work directly with AI and often for large companies, allowing for the imagination and news headlines to be where the public gets their information. Many wonder if this new technology is going to be an overall benefit to society or if it will bring unmitigated disaster. When the imagination runs wild, instead of understanding, news stories can perpetuate concerns and anxieties rather than hope and optimism.

Human intelligence plays a significant role in the operation of a multi-agent system. This study proposes a control framework that allows a human operator to collaboratively interact with a swarm robot to accomplish environmental exploration, detection, and coverage. A ri-limited Voronoi partition is proposed herein for improving the all-territory sensing range for coverage control. Subsequently, an interactive control framework and control algorithms are presented for an abstract task function that allows a human operator to control the movement of a swarm robot in a working environment. Environmental information is fed back to the master devices so that the human operator can realize the swarm robots coverage control situation. Stability and position tracking with static coverage control and input-to-state stability with dynamic coverage control of the human-swarm system are investigated. The efficiency and efficacy of the proposed system are validated via numerical examples and experiments.

Along with the increasing attention to artificial intelligence (AI), renewed emphasis or reflection on human intelligence (HI) is appearing in many places and at multiple levels. One of the foci is critical thinking. Critical thinking is one of four key 21st century skills – communication, collaboration, critical thinking and creativity. Though most people are aware of the value of critical thinking, it lacks emphasis in curricula. In this paper, we present a comprehensive definition of critical thinking that ranges from observation and inquiry to argumentation and reflection. Given a broad conception of critical thinking, a developmental approach beginning with children is suggested as a way to help develop critical thinking habits of mind. The conclusion of this analysis is that more emphasis should be placed on developing human intelligence, especially in young children and with the support of artificial intelligence. While much funding and support goes to the development of artificial intelligence, this should not happen at the expense of human intelligence. Overall, the purpose of this paper is to argue for more attention to the development of human intelligence with an emphasis on critical thinking.

Digital Linguistics (DL) is an interdisciplinary study that identifies human language as a digital evolution of mammal analog vocal sign communications, founded on the vertebrate spinal sign reflex mechanism. The author identifies the birth of linguistic humans at the time of the laryngeal descent, which provided vowel accented syllables containing logical properties of phonemes and morae. A character set and literacy is the second evolution. Written text is long lasting syllables in the brain of literate persons, and a civilization started as a linguistic phenomenon. At the end of their biological life, they can write their accumulated knowledge with a character set, so that subsequent generations can share their thoughts and experiences to develop further. In the 21st century, text is available in electronic form, which is interactive against keyword searches. It is time for linguistic humans to integrate disciplinary sciences and correct any errors to establish collective human intelligence. Piaget indicated that concepts can be manipulated correctly based on a group theory, which seems to be a base logic for intellectual evolution of linguistic humans as well as a tool for respectful and productive interdisciplinary discussions. [1][2]

Arange of issues, related to the use of cybernetics in economic research, technological development and educational programs for training specialists of management, has been considered. A large contribution of this science to the space exploration, designing counting machines, etc., – has been noticed. At the same time, focusing on management in systems, it did not pay enough attention to many important functions and specifics of socio-economic processes. Cybernetics tried to change some traditional ideas about the possibilities and methods of goal-setting in management of economic processes in the centrally planned Soviet economy, but these attempts were ineffective. More so, cybernetics was unable to affect the spiritual and moral sphere of human life and society, the content and development of such sciences as philosophy, sociology, political economy, etc.It has been shown, that the tendency to revise the fundamental provisions of the Humanities can lead and often leads to false conclusions, believing, that the qualitative differences between the system objects are insignificant. Agreeing, that setting limits to the possibilities of computer modeling in advance is impossible, it must be recognized, that the machines created by cybernetics, remain only an objectification – a “truncated” (incomplete) form of any kind of human activity, including management (purposing, selection of criteria, decision-making, etc.).The goal setting requires at least a normal human intelligence. At the same time, “individual survival” is not the main universal task: in natural selection, the survival of the species is often achieved by the death of a significant part of specimens.The article pays considerable attention to the cybernetic approach to the study of socio-economic processes. It is noted, that the thesis about cybernetically expedient functioning of any social systems (this point of view is shared by some specialists in cybernetics) contradicts common sense. Capitalism would have to be seen as a planned system, alien to the anarchy of production, and in fact as a system, which solves pre-set tasks corresponding to the interests of society. Therefore, according to the authors, the concept of self-governing system in the cybernetic sense is not applicable to a society with a market economy.