Human Thinking Research Articles

Little Things Matter a Lot: The Significance of Implicit Bias, Practically & Legally

Abstract Skeptics point out that measures of implicit bias can only weakly predict discrimination. And it is true that under current technologies, the degree of correlation between implicit bias (for example, as measured by the Implicit Association Test) and discriminatory judgment and behavior is small to moderate. In this essay, I argue that these little effects nevertheless matter a lot, in two different senses. First, in terms of practical significance, small burdens can accumulate over time to produce a large impact in a person's life. When these impacts are integrated not only over time but double integrated over large populations, these little things become even more practically significant. Second, in terms of legal significance, an upgraded model of discrimination that incorporates implicit bias has started to reshape antidiscrimination law. This transformation reflects a commitment to “behavioral realism”: a belief that the law should reflect more accurate models of human thinking and behavior.

How many heuristics are enough? Testing a parsimonious theory of possibility generation in problem-solving

Despite widespread recognition of the need for general-purpose mechanisms in unified theories of cognition, accounts of human thinking often propose that performance is best explained by task- or problem-specific knowledge and heuristics, elements found even in theories proposing general-purpose mechanisms. Here, we argue that many of the effects explained by task- or problem-specific knowledge or heuristics can be better explained by two general mechanisms: maximisation of progress and learning from experience. In Experiment 1, performance on the Taxicab problem, variously described as requiring or not requiring insight, was unaffected by removal of content presumed to trigger a problem-specific heuristic. In Experiment 2, the order of move selection in the Hobbits and Orcs problem, usually described as a transformation problem that does not require insight to solve, was successfully modelled by a maximisation heuristic with conceptual encoding of intermediate states, irrespective of problem context. In Experiment 3, solution rates to the eight-coin puzzle, a problem generally accepted as requiring insight to solve, were increased by cueing moves. A parsimonious theory, based on progress maximisation plus conceptual learning during solution, appears sufficient to model performance across a wide range of problems.

Narrative strategy of life story in the literature of Margaret Atwood

The subject of the research in this article is the narrative strategy of life description in the work of Margaret Atwood. Margaret Atwood (b. 1939) is a well–known modern Canadian writer, poet, and literary critic. The work of M. Atwood is considered in three main directions: the search for Canadian identity in the works of M. Atwood; the women's question and theories of feminism in the works of M. Atwood and speculative (conceptual) fiction in the works of M. Atwood. It is these three areas that the largest number of scientific papers about the Canadian writer are devoted to. Based on the life and creative path of M. Atwood, these three highways are justified. But behind them, the basis of the writer's work is lost – the narrative structure, to the study of which M. Atwood devoted many of her literary works. Based on the best practices of foreign and domestic narrative researchers, as well as on the research of M. Atwood herself, in this article we describe how a multi-level narrative of biography unfolds in the writer's fiction, implying a division into narrative layers. Each narrative layer is responsible for a certain time: the past, the present and the timelessness. The relevance and novelty of this article lies in an attempt to describe the narratives of M. Atwood, in isolation from the three main paths, and highlight the features of the narrative of the biography, which is key to the author's works. Thanks to the strategy of biography, the Canadian writer explores the nature of human memory, thinking, and fantasy. By placing the main character, the narrator, at the center of the narrative, M. Atwood allows her characters to independently analyze their own actions, their past, which brings her characters closer to real people. The characters of the writer, like real people, have general ideas about how a story should be built, a story and use literary techniques in talking about themselves. But, gradually opening up, the characters are the narrators of M. Atwood turns to a frank conversation, discarding literary decorations. The approach to the work of M. Atwood from the point of view of narrative, narratology helps to open new facets in the work of the famous author, to emphasize and actualize many artistic features of M. Atwood's books. Atwood, who remain in the shadows with a cultural and ideological approach.

How Text-to-Image Generative AI Is Transforming Mediated Action.

This article examines the intricate relationship between humans and text-to-image generative models (generative artificial intelligence/genAI) in the realm of art. The article frames that relationship in the theory of mediated action-a well-established theory that conceptualizes how tools shape human thoughts and actions. The article describes genAI systems as learning, cocreating, and communicating, multimodally capable hybrid systems that distill and rely on the wisdom and creativity of massive crowds of people and can sometimes surpass them. Those systems elude the theoretical description of the role of tools and locus of control in mediated action. The article asks how well the theory can accommodate both the transformative potential of genAI tools in creative fields and art, and the ethics of the emergent social dynamics it generates. The article concludes by discussing the fundamental changes and broader implications that genAI brings to the realm of mediated action and, ultimately, to the very fabric of our daily lives.

Integrating artificial intelligence and adult dental age estimation in forensic identification: A literature review

Age estimation is crucial in various forensic fields, including forensic medicine, anthropology, and demographic studies. Adult dental age estimation is affected by multiple factors, resulting in discrepancies between dental age and chronological age. The development of artificial intelligence (AI) technology has led to extensive investigations in forensic sciences, encompassing several areas such as facial recognition, age, sex identification, and DNA analysis. Adult age estimation methods commonly used include the pulp-tooth ratio approach, the Harris & Nortje method, and the Van Heerden method. AI approaches such as Fuzzy Logic (FL), Evolutionary Computing (EC), and Machine Learning (ML) are being extensively applied. These techniques use algorithms to imitate human thinking and behavior. Deep learning techniques, explicitly using deep convolutional neural networks (DCNN), enable age estimation by segmenting images and making measurements, replicating the cognitive processes of radiologists when computing indices such as the third molar maturity (I3M) index. Also, DCNNs automatically optimize teeth segmentation in dental X-ray images, improving image refining and analysis efficiency. AI integration in forensic dentistry improves the precision and effectiveness of dental data processing while significantly accelerating individual identification procedures. Incorporating this technology shows potential for enhancing the caliber and dependability of evidence in forensic investigations.

About One Linguistic Problem

Introduction. The article continues a series of publications on R-linguistics and is dedicated to the ternary hypothesis and the problem of modeling the world associated with it. The essence of the ternary hypothesis is based on the assumption that any natural language does not use verbs with arity (valency) above three. This hypothesis creates an epistemological problem, the essence of which lies in the mismatch between the constraints of the dimensionality of thinking and the dimensionality of some phenomena and processes of the surrounding world. The indicated problem is directly related to language, since language reflects human thinking and the structure of the world model.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations for verbs with high valence, the categorization axioms formulated earlier in the series are used.Results and discussion. It has been shown that cases of multiple indirect objects are related to data dependencies in the sentence. Methods of categorization have been developed for ternary relations and relations with higher arity. It has been demonstrated that even in this case, all conditional categorizations and conditional verbs can be reduced to a single categorization.Conclusion. The ternary hypothesis and the ternary problem are formulated. Based on the study of data dependencies, it is shown that the ternary hypothesis is most likely true for all natural languages. Based on the study of methods of categorizing relations with arity higher than three, it is demonstrated that in this case linguistic spaces show stability regardless of the location of categories in the sentence, which makes it possible to describe highdimensional interactions using subordinate clauses. Thus, the appearance of subordinate clauses in all languages of the world is associated with the need to describe highdimensional interactions in the world model human.

Новые образы социальной реальности в цифровую эпоху

The process of increasing complexity of social reality must be seen as historically conditioned. The develop-ment of techniques and technologies that shape both human thinking and life is recognized as a major deter-minant of changing social reality. The main event of recent decades has certainly been digitalization, whose transformative impact on society and its institutions has been so great that a new term has appeared – the “digi-tal age”. Social reality in the digital age is being transformed by social media and virtual or augmented realities. The birth of digital reality from the spontaneous interaction of diverse realities has poorly predicted social and existential consequences. The real driver accelerating the formation of digital reality is the digitalization of the administrative and bureaucratic component of public administration. The most notable here are the provision of public services in digital format, the transfer of intradepartmental and interdepartmental interactions to electron-ic document management, a significant transformation in the nature and quality of feedback, and the manipu-lation of large amounts of data. In the process of digitalization, a reality is born that cannot be reduced to any kind of previously known realities. It is not described in ontological terms of virtuality and human existence manifests itself in it.

Conceptualizing Discussions on the Dark Web: An Empirical Topic Modeling Approach

Social networks on the Internet have become a home that attracts all types of human thinking to exchange knowledge and ideas and share businesses. On the other hand, it has also become a source for researchers to analyze this knowledge and frame it in patterns that define types of thoughts circulating on these networks and representing the communities around them. In particular, some social networks on the Dark Web attract a special kind of thinking centered around the malicious and illegal activities disseminated on websites and marketplaces on the Dark Web. These networks involve discussions to exchange and discourse information, tips, and advice on performing such business. Studying social networks on the Dark Web is still in its infancy. In this paper, we present a methodology for analyzing the content of social networks on the Dark Web using topic modeling methods. We demonstrate the needed stages for the topic modeling process, beginning with data preprocessing and feature extraction to topic modeling algorithms. We utilize and discuss the following four topic models: LDA, CTM, PAM, and PTM. We discuss the following four topic coherence measures as evaluation metrics: UMass, UCI, CNPMI, and CV, demonstrating the selection of the best number of topics for each model according to the most coherent produced topics. Furthermore, we discuss the limitations, challenges, and future work. Our proposed approach highlights the ability to discover the latent thematic patterns in conversations and messages in the common language used in social networks on the Dark Web, constructing topics as groups of terms and their associations. This paper provides researchers with a leading methodology for analyzing thought patterns on the Dark Web.

ARTIFICIAL INTELLIGENCE, PROBLEMS AND PROSPECTS

The article discusses the concept of “artificial intelligence”, its problems and prospects. Artificial intelligence is the property of artificial intelligent systems to perform creative functions that are traditionally considered the prerogative of humans. the science and technology of creating intelligent machines, especially intelligent computer programs. The article discusses the main characteristics of artificial intelligence. Features and examples of the implementation of artificial intelligence technologies in the modern foreign educational space are shown. The history of artificial intelligence as a new scientific direction begins in the middle of the 20th century. By this time, many prerequisites for its origin had already been formed: among philosophers there had long been debates about the nature of man and the processes of cognition of the world, neurophysiologists and psychologists developed a number of theories regarding the work of the human brain and thinking, economists and mathematicians asked questions about optimal calculations and the presentation of knowledge about the world in in a formalized form; finally, the foundation of the mathematical theory of computing - the theory of algorithms - was born and the first computers were created. The formation of modern computer technologies has created a large number of cases that are related to: • human speech, the ability to learn to recognize and synthesize it; • development of technical vision mechanisms that will be able to recognize people’s faces; • the ability to teach cars to drive independently without human intervention, etc. [1]. Such systems that demonstrate and follow human behavior are called artificial intelligence. The study of artificial intelligence is an important direction in modern science. Artificial intelligence is a technology that contains a set of tools that help a computer, based on the studied data, provide answers to questions, and also draw conclusions based on this. Today, AI is essential for a wide range of industries, including healthcare, retail, manufacturing, and even government. But there are ethical challenges with AI, and as always, these options need to be out of options to ensure AI doesn't do more harm than good. Here are some of the biggest ethical challenges of AI. Keywords: Artificial intelligence, computer, robot, thinking, awareness, personality, society, humanity, problems, prospects, future.

Relevancy and Outlook of the Technology-Enhanced Education within Digital Contents, Resources and Tools

Digital technology has become one of the most dictating determinants of this modern age; technology is gradually taking wider roles in every aspect of human activity and practice; education, teaching, and learning have centrally been apt to a wide range of changeability: technology-enhancement has facilitated the emergence of new concepts in education; technology- enhancement has also incorporated new roles for teachers, students, learning content, pedagogy, learning resources, instructional media and tools; as a consequence, the aim of this study was to investigate the relevancy and outlook of such a technology –enhanced education within the three domains of digital content, digital resources, and, digital tools. To achieve the aim of this study, a juxtaposed qualitative approach was followed to reveal and then describe such relevancy and outlook; the available literature has profoundly been surveyed to support the argument and the investigative range of this study; consequently, three essays, which are separate in form, but interrelated in their thematic topicality, have investigated three related issues: the first is why technology enhancement has dictated itself to the educational system, and how it has been changing the whole educational system; the second is why and how digital content can be an unavoidable digital resource and why there is a call to exploit digital contents and digital resources; the third is how digital tools, "Grammarly" as an example, bears some functional limitations that can cast some uncertainty over the degree of dependability that they are supposed to record. Accordingly, this study has generally concluded that technology enhancement, digital contents, digital resources, and digital tools are advantageous and exploitable as long as they are exploited rationally and reasonably; technology enhancement should be understood as an extension and not as a substitution to traditional educational practices; the study also concluded that the overdependence on technological and digital solutions could cast various risks on Human Intelligence (HI), thinking, attitudes, and behavior. This study comes up with various recommendations.

Coccyx Terminate by Artificial Intelligence

Being the most successful Artificial Intelligence automate mathematical used for human intelligence. This paper focuses on establishing the conceptual foundation of the structure and processes of human thinking systems. The conceptualization of component of the complexity-intelligence strategy. In this analysis, the human thinking system is perceived to be comprised of two components namely, the energy–matter subsystem and the physical symbol subsystem. The general procedure in which the human mind handles and exploits one or more physical symbol systems is analysed. Subsequently, the boundaries and objectives of human thinking systems as information processing systems, and the necessity of artificial information systems are conceived as four postulates. My research over on various Otsu algorithms and AI with Coccyx. Here i used information from the four human senses, vision, hearing, touch and think. Also some ways those sensory AI modalities mimic the senses, and offer benefits in both new and current applications. Key Words: Human Thinking system, intelligent microfluidic chip. Coccyx, Artificial Intelligence

Get To Know The History And Function Of The West Javanese Angklung Musical Instrument

West Java is a collection of various types of very beautiful nature with enchanting cultural attractions. The diversity of existing cultures is shown through the diversity of arts that are staged. This art is an expression of human thoughts, feelings, and ideas that differ from their environment and experience. Along with the development of the times, the growing diversity of art created by humans, as well as various forms of types of works of art, Artworks are one of the cultural products of a nation, which is priceless. Angklung is a popular traditional musical instrument from West Java. Angklung musical instruments have been known by the Sundanese people since the royal era, and have grown in popularity since November 2010, when Angklung was listed as Masterpieces of the Oral and Intangible Heritage of Humanity by UNESCO.

Artificial Intelligence - Digital Limiter of Consciousness

Translation as one of the types of human activity is related to topical philosophical issues, including transhumanism, as well as the need for its application in modern technologies for creating a man-machine and the upcoming AI singularity. The accuracy and unambiguity of language content is the foundation of AI software. For a specialized technical translation, this is an undeniable advantage in terms of the speed and efficiency of the process. The reduction of heterogeneity and polysemy of any language as a reflection of the activity of human consciousness to unambiguous definitions is an absolute limiter of creative mental activity. Specific examples of the intervention of an automatic editor in the process of individual activity of an AI user demonstrate real conflict situations. According to the author, translation is a universal property of human thinking, and cognitive processes are generated by the activity of the brain, and not exclusively by its structure. Combinatorial thinking is unique to humans. Reflection - the subject's appeal to himself - is one of the most important acts of consciousness, which makes it possible for an individual translation of thoughts into their native and any other language.

ON THE INCOMPATIBILITY OF SELF-SUFFICIENT ADVERSARIALISM WITH OBJECTIVE TRUTH IN THE ADVERSARIAL CODE OF CRIMINAL PROCEDURE OF THE RUSSIAN FEDERATION

Purpose of the study. For the author, the purpose of the study is to recognize materialist dialectics, as an objective law, as a truly scientific methodology, since dialectics is global, universal - it inevitably manifests itself in the world, nature and in human thinking; its rules and logic must be taken into account in criminal proceedings. Dialectics is inextricably linked with objective truth. The objective-true model of the criminal process corresponds to the scientific requirements of dialectics, in contrast to the current adversarial criminal process in Russia with its self-sufficient adversarialism, excluding objectivity and truth - a process that does not take into account the scientific requirements of dialectics about the inadmissibility of erasing differences between opposites, such as truth and error, goal and means, form and content, probability and reliability, presumption of innocence and presumption of guilt, inevitability of responsibility and impunity. Hence, it is impossible to erase the differences between formal legal and objective truths, between adversarial and objective-true models of criminal proceedings. At the same time, the objective-true model of the criminal process is a higher type of process than the adversarial criminal process with its “right of the powerful”. The purpose of the study also includes solving in the well-known legal dictum that “no case of crime should go unsolved”, the requirement for reliable, objective-true solving of each crime (counteracting the crime) and the requirement for the inevitability of punishment for the crime, which has an important preventive, proactive meaning for crime. Conclusions. As a result of the research, the author comes to the following conclusions: materialist dialectics is the science of the general laws of motion of both the objective world and human thinking; its rule about the inadmissibility of erasing the distinction between opposites should also be applied in criminal proceedings. The objective-true model of criminal proceedings, in contrast to the current adversarial Code of Criminal Procedure of the Russian Federation, meets the scientific requirements of materialist dialectics and represents a higher type of criminal process. The legislator in the adversarial Code of Criminal Procedure of the Russian Federation, contrary to the requirements of dialectics, erases the distinction between form and content, goal and means, turning adversarialism (that is, a means) into an end in itself of the process, which excludes objective truth. An attempt to combine formal legal truth with objective truth in the adversarial Code of Criminal Procedure of the Russian Federation seems to be an unscientific approach, since it is necessary to observe a rigid alternative: either formal truth (legal, procedural, judicial, “the truth of the winner of the argument of the parties”), or objective truth. A third is not given. The well-known legal provision that “no case of crime should go unsolved” contains not only the requirement for the need to reliably disclose every crime (counteracting the crime), but also has an important preventive, proactive meaning, leading to a reduction in crime. The modern adversarial Code of Criminal Procedure of the Russian Federation does not provide for such a requirement for the inevitability of responsibility of the perpetrators.

Selection of a Neural Network Architecture for Implementation of Cognitive Functions of Network Software for Control of a Group of Interacting Small Space Vehicles

The purpose of the research is to substantiate and select the architecture of a neural network for the possibility of implementing the cognitive functions of network software for controlling a grouping of interacting small spacecraft.Methods are based on the concepts of AI theory for managing the grouping of small spacecraft - the use of adaptive methods and tools that allow making decisions, similar to the mechanisms of human thinking. With regard to space communication systems with a heterogeneous structure, AI methods and technologies are aimed at the processes of predicting the state in communication channels between network nodes and automatic reconfiguration of the network of devices based on the learning processes of a neural network (NN).Results. In the learning and forecasting mode, it is necessary to use time series of parameters and coordinates of specific pairs of small spacecraft with non-zero line of sight. Especially for time series analysis, recurrent neural networks (RNN) are used, in particular, LSTM. The idea of RNN operation is to use as input data for the current forecast not only the state vectors of the SVs and their coordinates, but also the previous value of the communication quality, actual or predictive. The paper shows that the onboard computing power of a separate MSC does not allow performing forecasting and training on board. Therefore, a dedicated ground segment of forecasting and monitoring is required, which will collect a posteriori information, periodically train the cognitive model, use it to predict the quality of communication, and transmit the results to the network nodes to build data transmission routes.Conclusion. The analysis of modern solutions and the choice of neural network architecture for the implementation of the cognitive functions of the network software for controlling the grouping of interacting small spacecraft showed that the neural networks of the Transformer architecture, which are based on the mechanism of internal attention, most fully meet the requirements of the project. The Transformer architecture allows using the entirety of a priori data, has a high learning and forecasting speed.

EKSPLORASI ETNOMATEMATIKA DALAM AL-QUR’AN SEBAGAI SUMBER BELAJAR

Mathematics is one of the subject areas taught from elementary school to high school and even to universities. Mathematics is also one of the subjects that is considered difficult by many students, but mathematics is very important in improving human thinking and this science also plays a very important role in everyday life. Through this ethnomathematics exploration, students will find it easier and more enjoyable to learn mathematics from the Qur’an. Mathematics has a close relationship with the Qur’an without us realizing it, such as odd numbers, even numbers, and prime numbers listed in surah Al-kahf verse 22, verse 25, Al-ankabut verse 14, Al-baqarah verse 261, and annisa’ verse 11-12. The purpose of this research is to describe and elaborate mathematics learning in number theory contained in the Qur’an. The method in this research is using qualitative method which is done by observation and literature study. From this research, it is known that there is a relationship between the words of God contained in the Qur’an and the concept of mathematics, and it is proven that always math lessons can solve all problems in Islam. This research is expected to facilitate the learning of mathematics and can show that there is a connection with the Qur’an. Thus later mathematics lessons are not only as ordinary subjects, but can also be seen in religion, so the researcher took the title Exploration of Ethnomathematics in the Qur’an as a learning resource.Keywords: exploration, ethnomathematics, Qur’an

Investment Analysis of Artificial Intelligence

As the core technology of the new round of social change, artificial intelligence is promoting the upgrading of traditional industries and driving the rapid development of the "unmanned economy," which will have an extremely important impact on the fields of intelligent transportation, smart home, and intelligent medical care. With the arrival of the information age, through coding, programmed machines can complete the tasks that humans can not complete which is intelligence. Today's artificial intelligence allows people to witness real intelligence: let the machine be automatic, through simulation of human thinking and learning ability, to complete many complex tasks and decision-making, with the data, arithmetic, and algorithms to achieve continuous breakthroughs. Additionally, artificial intelligence may even enter an eternal spring. The foreseeable is that AI will reshape human life in the future, and the era of AI with infinite possibilities will come in full swing. The factors that make artificial intelligence worthwhile for people to invest in are crucial. In recent years, people have devoted a lot of time and effort to the invention of artificial intelligence in order to make life more convenient, make people's travel easier, and reduce a lot of unnecessary expenses as well and save a lot of time. Besides, the development of human beings has always been inseparable from artificial intelligence. Every stage of development is improved by technology. However, the emergence of artificial intelligence will undoubtedly improve our lives and enhance our quality of life. More precisely, AI has liberated a large amount of labor and enhanced the way of human thinking.

Creating Public Awareness of Renewable Energy by Combining a Photovoltaic System and Nature

Energy is seemingly permanently andnearly everywhere in the western world available to theend consumer. While a majority of the western civilizationis aware of the downsides of fossil energy sources and is fa-voring renewable energy sources, the energy consumptionis still increasing. The situation is quite clear to the ex-perts in the field, but further awareness in the public mustbe created. Therefore this paper addresses a method ofcreating this awareness: installations that stimulate con-versations of renewable energy.A solar tree was developed and built to serve young peoplewith an AC outlet at a rock festival. The tree was real-ized under mechanical constraints and considerations ofthe electrical network to allow energy storage and conver-sion. This paper will introduce the principle of provotypes,which are provoking human thinking toward environmen-tal friendly technology. The mechanical requirements andthe developed solution is shown, before providing inten-sive insight into the electrical configuration, consisting ofa battery, photovoltaic cells and a DC-AC converter. Fur-thermore a low complexity charge controller is presented.The resulting solar tree is capable of attracting peoplesattention, surviving in harsh environments and providingpower up to around100 W.

Chain of Thought Utilization in Large Language Models and Application in Nephrology.

Chain-of-thought prompting enhances the abilities of large language models (LLMs) significantly. It not only makes these models more specific and context-aware but also impacts the wider field of artificial intelligence (AI). This approach broadens the usability of AI, increases its efficiency, and aligns it more closely with human thinking and decision-making processes. As we improve this method, it is set to become a key element in the future of AI, adding more purpose, precision, and ethical consideration to these technologies. In medicine, the chain-of-thought prompting is especially beneficial. Its capacity to handle complex information, its logical and sequential reasoning, and its suitability for ethically and context-sensitive situations make it an invaluable tool for healthcare professionals. Its role in enhancing medical care and research is expected to grow as we further develop and use this technique. Chain-of-thought prompting bridges the gap between AI's traditionally obscure decision-making process and the clear, accountable standards required in healthcare. It does this by emulating a reasoning style familiar to medical professionals, fitting well into their existing practices and ethical codes. While solving AI transparency is a complex challenge, the chain-of-thought approach is a significant step toward making AI more comprehensible and trustworthy in medicine. This review focuses on understanding the workings of LLMs, particularly how chain-of-thought prompting can be adapted for nephrology's unique requirements. It also aims to thoroughly examine the ethical aspects, clarity, and future possibilities, offering an in-depth view of the exciting convergence of these areas.

Basic questions of the philosophy of artificial intelligence

The object of the study is a special branch of scientific knowledge, formed at the intersection of interests of various humanitarian disciplines – the philosophy of artificial intelligence; the subject of the study is the problems it considers. The author identifies the main traditional questions that the philosophy of artificial intelligence tried to answer earlier. Such questions in the earlier stages of the development of science were concentrated around the possibility of artificial intelligence to become aware of itself, learn to think, feel and create like a person. Scientists since the 1960s interested in the problems of equality of natural and artificial intelligence, the ability of a computer to show benevolence or hostility towards its creators. The research was carried out using a historical and philosophical analysis of issues in the philosophy of artificial intelligence, the method of interpretive synthesis, etc. Systemic-structural, dialectical, cultural-historical, value-based, interdisciplinary approaches to the problem were used. The scientific novelty of the research lies in identifying the problems of the philosophy of artificial intelligence that are relevant at this stage of development of this scientific field. It is noted that the dynamics of the philosophy of artificial intelligence are significantly influenced by the fact that “strong” artificial intelligence has not been created for several decades. This has caused a transformation in the research field of the philosophy of artificial intelligence, and at the moment this branch of scientific knowledge is considering new questions, including why it is not possible to create “strong” AI that completely replicates human thinking; can a computer think, albeit differently, than a human; what is the difference between human and machine thinking; who should be responsible for the decisions and actions of artificial intelligence, and etc. The issues facing the philosophy of artificial intelligence are constantly updated.