Pub Date : 2024-07-12DOI: 10.17726/philit.2024.1.6
P. N. Baryshnikov
This article examines the nature of scientific knowledge generated by Large Language Models (LLMs) and assesses their impact on scientific discoveries and the philosophy of science. LLMs, such as GPT‑4, are advanced deep learning algorithms capable of performing various natural language processing tasks, including text generation, translation, and data analysis. The study aims to explore how these technologies influence the scientific research process, questioning the classification and validity of AI‑assisted scientific discoveries. The methodology involves a comprehensive review of existing literature on the application of LLMs in various scientific fields, coupled with an analysis of their ethical implications. Key findings highlight the benefits of LLMs, including accelerated research processes, enhanced accuracy, and the ability to integrate interdisciplinary knowledge. However, challenges such as issues of reliability, the ethical responsibility of AI‑generated content, and environmental concerns are also discussed. The paper concludes that while LLMs significantly contribute to scientific advancements, their use necessitates a reevaluation of traditional concepts in the philosophy of science and the establishment of new ethical guidelines to ensure transparency, accountability, and integrity in AI‑assisted research. This balanced approach aims to harness the potential of LLMs while addressing the ethical and practical challenges they present.
{"title":"What is scientific knowledge produced by Large Language Models?","authors":"P. N. Baryshnikov","doi":"10.17726/philit.2024.1.6","DOIUrl":"https://doi.org/10.17726/philit.2024.1.6","url":null,"abstract":"This article examines the nature of scientific knowledge generated by Large Language Models (LLMs) and assesses their impact on scientific discoveries and the philosophy of science. LLMs, such as GPT‑4, are advanced deep learning algorithms capable of performing various natural language processing tasks, including text generation, translation, and data analysis. The study aims to explore how these technologies influence the scientific research process, questioning the classification and validity of AI‑assisted scientific discoveries. The methodology involves a comprehensive review of existing literature on the application of LLMs in various scientific fields, coupled with an analysis of their ethical implications. Key findings highlight the benefits of LLMs, including accelerated research processes, enhanced accuracy, and the ability to integrate interdisciplinary knowledge. However, challenges such as issues of reliability, the ethical responsibility of AI‑generated content, and environmental concerns are also discussed. The paper concludes that while LLMs significantly contribute to scientific advancements, their use necessitates a reevaluation of traditional concepts in the philosophy of science and the establishment of new ethical guidelines to ensure transparency, accountability, and integrity in AI‑assisted research. This balanced approach aims to harness the potential of LLMs while addressing the ethical and practical challenges they present.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"20 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.17726/philit.2024.1.5
A. B. Khomyakov, P. Chizhik
The article presents a new method for obtaining analogues of words, characterized by simplicity and the absence of the need for preliminary training on large data as in existing methods. In the method under study, analogues are determined by their syntactic predicates using methods of distributive semantics. In the study, analogues of adjectives, nouns and verbs were obtained and analyzed. This made it possible to obtain a result that is not inferior to the results obtained using the most popular neural network approach as word2vec when qualitatively comparing analogues. The demonstrated method shows that obtaining analogues is possible using methods of distributive semantics using a more interpretable method, which opens up the possibility of studying semantic analogy. This method also allows you to identify analogues on a specific topic. Based on the experimental results obtained, an original definition of analogues and cognitive schemes is formulated. The article also analyzes and substantiates the possibility of a new approach for creating artificial intelligence systems based on the researched method. According to the authors, this provides significant advantages for the creation of such systems. In particular, the proposed method allows for broader generalizations over orders of magnitude smaller data, as well as learning during use, which is not possible for neural networks.
{"title":"A new way of finding analogues as an opportunity to study language, thinking and build artificial intelligence systems","authors":"A. B. Khomyakov, P. Chizhik","doi":"10.17726/philit.2024.1.5","DOIUrl":"https://doi.org/10.17726/philit.2024.1.5","url":null,"abstract":"The article presents a new method for obtaining analogues of words, characterized by simplicity and the absence of the need for preliminary training on large data as in existing methods. In the method under study, analogues are determined by their syntactic predicates using methods of distributive semantics. In the study, analogues of adjectives, nouns and verbs were obtained and analyzed. This made it possible to obtain a result that is not inferior to the results obtained using the most popular neural network approach as word2vec when qualitatively comparing analogues. The demonstrated method shows that obtaining analogues is possible using methods of distributive semantics using a more interpretable method, which opens up the possibility of studying semantic analogy. This method also allows you to identify analogues on a specific topic. Based on the experimental results obtained, an original definition of analogues and cognitive schemes is formulated. The article also analyzes and substantiates the possibility of a new approach for creating artificial intelligence systems based on the researched method. According to the authors, this provides significant advantages for the creation of such systems. In particular, the proposed method allows for broader generalizations over orders of magnitude smaller data, as well as learning during use, which is not possible for neural networks.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"143 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.17726/philit.2024.1.2
L. A. Bukreeva, L. Velis
In this research work, an analysis of collocations associated with the concepts of “smell”, “aroma”, “stench” and “stench” in the Russian and English languages was carried out using quantitative methods and automatic language processing on the basis of the National Corpus of the Russian Language (NCRL), corpus English (COCA) and the Mannheim Corpus for German. The obtained statistical indicators make it possible to identify the peculiarities of the use of adjectives, verbs and nouns that reflect the attitude to olfactory experience in English, Russian and German. The results allow us to compare descriptions of odors in different cultures and identify trends in the assessment of olfactory impressions. Patterns in the compatibility of olfactory vocabulary also indicate the tendency of keywords to acquire a positive or negative emotional connotation due to collocates.
{"title":"Quantitative analysis of olfactory vocabulary based on the example of Russian, English and German languages","authors":"L. A. Bukreeva, L. Velis","doi":"10.17726/philit.2024.1.2","DOIUrl":"https://doi.org/10.17726/philit.2024.1.2","url":null,"abstract":"In this research work, an analysis of collocations associated with the concepts of “smell”, “aroma”, “stench” and “stench” in the Russian and English languages was carried out using quantitative methods and automatic language processing on the basis of the National Corpus of the Russian Language (NCRL), corpus English (COCA) and the Mannheim Corpus for German. The obtained statistical indicators make it possible to identify the peculiarities of the use of adjectives, verbs and nouns that reflect the attitude to olfactory experience in English, Russian and German. The results allow us to compare descriptions of odors in different cultures and identify trends in the assessment of olfactory impressions. Patterns in the compatibility of olfactory vocabulary also indicate the tendency of keywords to acquire a positive or negative emotional connotation due to collocates.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"96 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.17726/philit.2024.1.1
K. V. Kasparyan, M. Rutkovskaya, I. N. Kolesnikov
This article is devoted to the study of the specific features of the display of social networks and computer technologies in the late 70s of the XX – early 20s of the XXI century in the fantastic Star Wars universe created by American filmmaker D. Lucas. In this scientific work, the authors argue for the relevance and scientific novelty of the problem under consideration. The study examines the peculiarities of the influence of social networks and computer technologies in modern conditions. The article provides a justification for the need to analyze the reflection of this issue in fantasy art as an auxiliary factor in the development of the prognostic function of science. This paper provides a reasoned explanation of the choice of the Star Wars universe as an object of research, taking into account its importance in the fantasy genre, as well as in order to refute stereotypes according to which Star Wars is a collection of entertainment materials in which there is completely no semantic load. The authors analyze the fundamental differences in the coverage of the studied problem in such genres of art as literature and cinema in the context of Star Wars. The article examines the features of the evolution of the display of cybernetic technologies and communication network platforms in the Star Wars universe in the mid‑1970s – early 2020s, as a reflection of the real development of scientific and technological progress, as well as an example of the impact of political, socio‑economic and moral factors on the use of online platforms and computer technology during the period under study. In this article, using the example of the Star Wars universe, the features of the transformation of the role of specialists in the field of high technology through the prism of the attitude of artists to them – more specifically, writers and cinematographers – are also considered. The article also examines the moral and ethical aspect of the use of computer technology and social networks, considered by artists who have made a significant contribution to the development of the fantastic epic of Star Wars.
{"title":"The mapping of social networks and computer technology in the star wars universe in 1977-2023: a historical retrospective","authors":"K. V. Kasparyan, M. Rutkovskaya, I. N. Kolesnikov","doi":"10.17726/philit.2024.1.1","DOIUrl":"https://doi.org/10.17726/philit.2024.1.1","url":null,"abstract":"This article is devoted to the study of the specific features of the display of social networks and computer technologies in the late 70s of the XX – early 20s of the XXI century in the fantastic Star Wars universe created by American filmmaker D. Lucas. In this scientific work, the authors argue for the relevance and scientific novelty of the problem under consideration. The study examines the peculiarities of the influence of social networks and computer technologies in modern conditions. The article provides a justification for the need to analyze the reflection of this issue in fantasy art as an auxiliary factor in the development of the prognostic function of science. This paper provides a reasoned explanation of the choice of the Star Wars universe as an object of research, taking into account its importance in the fantasy genre, as well as in order to refute stereotypes according to which Star Wars is a collection of entertainment materials in which there is completely no semantic load. The authors analyze the fundamental differences in the coverage of the studied problem in such genres of art as literature and cinema in the context of Star Wars. The article examines the features of the evolution of the display of cybernetic technologies and communication network platforms in the Star Wars universe in the mid‑1970s – early 2020s, as a reflection of the real development of scientific and technological progress, as well as an example of the impact of political, socio‑economic and moral factors on the use of online platforms and computer technology during the period under study. In this article, using the example of the Star Wars universe, the features of the transformation of the role of specialists in the field of high technology through the prism of the attitude of artists to them – more specifically, writers and cinematographers – are also considered. The article also examines the moral and ethical aspect of the use of computer technology and social networks, considered by artists who have made a significant contribution to the development of the fantastic epic of Star Wars.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"136 52","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.17726/philit.2024.1.4
I. F. Mikhailov
The paper discusses different approaches to the concept of recursion and its evolution from mathematics to cognitive studies. Such approaches are observed as: self‑embedded structures, multiple hierarchical levels using the same rule, and embedding structures within structures. The paper also discusses the concept of meta‑recursion. Examining meta‑recursion may enable understanding of the ability to apply recursive processes to multilayered hierarchies, with recursive procedures acting as generators. These types of recursive processes could be the fundamental elements of general cognition. The paper also briefly discusses the role of probability in current recursive approaches to cognition. It is conjenctured that the hierarchical mechanism of cognition demonstrates a kind of meta‑recursion in the sense that recursive neural loops may support some primitive recursive cognitive processes, which in turn account for recursiveness of language grammars, space orientation, social cognition, etc. The study indicates that using multiple approaches to understand the phenomenon of recursion can provide a more complete understanding of the complexity of recursion, as it plays a significant role in fields like language, mathematics, and cognitive science.
{"title":"The Concept of Recursion in Cognitive Studies. Part I: From Mathematics to Cognition","authors":"I. F. Mikhailov","doi":"10.17726/philit.2024.1.4","DOIUrl":"https://doi.org/10.17726/philit.2024.1.4","url":null,"abstract":"The paper discusses different approaches to the concept of recursion and its evolution from mathematics to cognitive studies. Such approaches are observed as: self‑embedded structures, multiple hierarchical levels using the same rule, and embedding structures within structures. The paper also discusses the concept of meta‑recursion. Examining meta‑recursion may enable understanding of the ability to apply recursive processes to multilayered hierarchies, with recursive procedures acting as generators. These types of recursive processes could be the fundamental elements of general cognition. The paper also briefly discusses the role of probability in current recursive approaches to cognition. It is conjenctured that the hierarchical mechanism of cognition demonstrates a kind of meta‑recursion in the sense that recursive neural loops may support some primitive recursive cognitive processes, which in turn account for recursiveness of language grammars, space orientation, social cognition, etc. The study indicates that using multiple approaches to understand the phenomenon of recursion can provide a more complete understanding of the complexity of recursion, as it plays a significant role in fields like language, mathematics, and cognitive science.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"18 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.17726/philit.2024.1.3
V. Y. Filimonov
Today, large language models are very powerful, informational and analytical tools that significantly accelerate most of the existing methods and methodologies for processing informational processes. Scientific information is of particular importance in this capacity, which gradually involves the power of large language models. This interaction of science and qualitative new opportunities for working with information lead us to new, unique scientific discoveries, their great quantitative diversity. There is an acceleration of scientific research, a reduction in the time spent on its implementation – the freed up time can be spent both on solving new scientific problems and on scientific creativity, which, although it may not necessarily lead to a specific solution to a particular scientific problem, but is able to demonstrate the beauty of science in various disciplinary areas. As a result, the interaction of large language models and scientific information is at the same time a research for solutions to scientific problems, scientific problems, and scientific creativity. Solving scientific problems requires the ability to efficiently process big data, which cannot be done without an effective method – one of the significant methods was the Transformer architecture, introduced in 2017 and comprehensively integrated into the GPT‑3 model, which, as of September 2020, was the largest and most advanced language model in the world. Therefore, GPT‑3 can be called the basis of most scientific developments carried out in the context of using large language models. The interaction of science and large language models has become a factor in the emergence of a large number of questions, among which are: «Is the result of data analysis new knowledge?», «What are the prospects for scientific creativity in the era of big computing?». Currently, these issues are extremely important, because they allow us to develop the foundations for effective human‑computer interaction. Therefore, this study analyzes the issues presented.
{"title":"Large language models and their role in modern scientific discoveries","authors":"V. Y. Filimonov","doi":"10.17726/philit.2024.1.3","DOIUrl":"https://doi.org/10.17726/philit.2024.1.3","url":null,"abstract":"Today, large language models are very powerful, informational and analytical tools that significantly accelerate most of the existing methods and methodologies for processing informational processes. Scientific information is of particular importance in this capacity, which gradually involves the power of large language models. This interaction of science and qualitative new opportunities for working with information lead us to new, unique scientific discoveries, their great quantitative diversity. There is an acceleration of scientific research, a reduction in the time spent on its implementation – the freed up time can be spent both on solving new scientific problems and on scientific creativity, which, although it may not necessarily lead to a specific solution to a particular scientific problem, but is able to demonstrate the beauty of science in various disciplinary areas. As a result, the interaction of large language models and scientific information is at the same time a research for solutions to scientific problems, scientific problems, and scientific creativity. Solving scientific problems requires the ability to efficiently process big data, which cannot be done without an effective method – one of the significant methods was the Transformer architecture, introduced in 2017 and comprehensively integrated into the GPT‑3 model, which, as of September 2020, was the largest and most advanced language model in the world. Therefore, GPT‑3 can be called the basis of most scientific developments carried out in the context of using large language models. The interaction of science and large language models has become a factor in the emergence of a large number of questions, among which are: «Is the result of data analysis new knowledge?», «What are the prospects for scientific creativity in the era of big computing?». Currently, these issues are extremely important, because they allow us to develop the foundations for effective human‑computer interaction. Therefore, this study analyzes the issues presented.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"18 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.17726/philit.2023.2.4
N. V. Makeeva
The paper aims to discuss the results of testing a neural network which classifies the vowels of the vocalic system with the [ATR] (Advanced Tongue Root) contrast based on the data of Akebu (Kwa family). The acoustic nature of the [ATR] feature is yet understudied. The only reliable acoustic correlate of [ATR] is the magnitude of the first formant (F1) which can be also modulated by tongue height, resulting in significant overlap between high [-ATR] vowels and mid [+ATR] vowels. Other acoustic metrics which had been associated with the [ATR], such as F1 bandwidth (B1), relative intensity of F1 to F2 (A1-A2), etc., are typically inconsistent across vowel types and speakers. The values of four metrics – F1, F2, A1-A2, B1 – were used for training and testing the neural network. We tested four versions of the model differing in the presence of the fifth variable encoding the speaker and the number of hidden layers. The models which included the variable encoding the speaker achieved slightly higher accuracy, whereas the precision and recall metrics of the three-layer model were generally higher than those with two hidden layers.
本文旨在讨论基于 Akebu（Kwa 语系）数据对神经网络进行测试的结果，该网络利用 [ATR]（高级舌根）对比对发声系统的元音进行分类。ATR]特征的声学性质尚未得到充分研究。与[ATR]声学相关的唯一可靠指标是第一共振（F1）的大小，它也会受到舌高的调节，从而导致高[-ATR]元音和中[+ATR]元音之间的显著重叠。其他与[ATR]相关的声学指标，如 F1 带宽（B1）、F1 与 F2 的相对强度（A1-A2）等，在不同元音类型和说话者之间通常是不一致的。F1、F2、A1-A2、B1 这四个指标的值被用于训练和测试神经网络。我们测试了四种不同版本的模型，它们的区别在于是否存在编码说话人的第五个变量以及隐藏层的数量。包含对说话者进行编码的变量的模型准确率略高，而三层模型的精确度和召回率指标则普遍高于有两个隐藏层的模型。
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Pub Date : 2023-12-18DOI: 10.17726/philit.2023.2.1
N. V. Bhatti
Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part of general intelligence. Emotional intelligence can be defined as an ability of a human to perceive oneself and interact with others with the help of obtained and processed emotional information. Language acquisition is mediated by the necessity to communicate with others. Consequently, the ability to manage the process of communication is of utmost importance in learning a language. Virtual learning environment reduces dramatically the immediate interaction of the participants of the process of education. It undoubtedly affects the process of acquisition and demands to reconsider the distribution of different learning activities.
加德纳的多元智能理论得到了进一步的发展，侧重于人类认知活动的研究。因此，情商的概念，也就是本文的主题，是由约翰?梅尔（John D. Mayer）、彼得-萨洛维（Peter Salovey）和丹尼尔-戈尔曼（Daniel Goleman）提出的。一般智力可以定义为进行抽象推理以理解含义、识别两个概念之间的异同和进行概括的能力。情商不是一般智力的一部分。情商可以定义为人借助获得和处理的情感信息来认识自己和与他人互动的能力。语言的习得是以与他人交流的必要性为中介的。因此，管理交流过程的能力对语言学习至关重要。虚拟学习环境大大减少了教育过程参与者之间的直接互动。这无疑会影响学习过程，并要求重新考虑不同学习活动的分配。
{"title":"Emotional intelligence and the second language acquisition in virtual learning environment","authors":"N. V. Bhatti","doi":"10.17726/philit.2023.2.1","DOIUrl":"https://doi.org/10.17726/philit.2023.2.1","url":null,"abstract":"Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part of general intelligence. Emotional intelligence can be defined as an ability of a human to perceive oneself and interact with others with the help of obtained and processed emotional information. Language acquisition is mediated by the necessity to communicate with others. Consequently, the ability to manage the process of communication is of utmost importance in learning a language. Virtual learning environment reduces dramatically the immediate interaction of the participants of the process of education. It undoubtedly affects the process of acquisition and demands to reconsider the distribution of different learning activities.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"49 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.17726/philit.2023.2.3
M. N. Korsakova-Krein
The development of the mind follows the path of biological evolution towards the accumulation and transmission of information with increasing efficiency. In addition to the cognitive constants of speech (Solntsev, 1974), which greatly improved the transmission of information, people have created computing devices, from the abacus to the quantum computer. The capabilities of computers classified as artificial intelligence are developing at a rapid pace. However, at the present stage, artificial intelligence (AI) lacks an emotion module, and this makes AI fundamentally different from human intelligence, since the life of the mind in humans cannot be separated from their feelings (Damasio, 2010; Panksepp, 1997). Consciousness itself is formed through the sensory and motor systems, that is, it is embodied (Foglia & Wilson, 2013), which means that our mental life is inseparable from our sensory motor experience (Wellsby & Pexman, 2014). Evolutionarily, our minds rely on ancient survival mechanisms that influence our decisions and choices. Hence, for example, the question whether the choice of Artificial Intelligence will always be favorable for humanity.
{"title":"Artificial Intelligence and Emotions","authors":"M. N. Korsakova-Krein","doi":"10.17726/philit.2023.2.3","DOIUrl":"https://doi.org/10.17726/philit.2023.2.3","url":null,"abstract":"The development of the mind follows the path of biological evolution towards the accumulation and transmission of information with increasing efficiency. In addition to the cognitive constants of speech (Solntsev, 1974), which greatly improved the transmission of information, people have created computing devices, from the abacus to the quantum computer. The capabilities of computers classified as artificial intelligence are developing at a rapid pace. However, at the present stage, artificial intelligence (AI) lacks an emotion module, and this makes AI fundamentally different from human intelligence, since the life of the mind in humans cannot be separated from their feelings (Damasio, 2010; Panksepp, 1997). Consciousness itself is formed through the sensory and motor systems, that is, it is embodied (Foglia & Wilson, 2013), which means that our mental life is inseparable from our sensory motor experience (Wellsby & Pexman, 2014). Evolutionarily, our minds rely on ancient survival mechanisms that influence our decisions and choices. Hence, for example, the question whether the choice of Artificial Intelligence will always be favorable for humanity.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"13 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139172823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.17726/philit.2023.2.10
P. N. Baryshnikov
Science as a social institution today is experiencing a phase of profound transformation. Objects, methods, research technological tools, methods of institutional communication and mechanisms for commercializing new knowledge are changing. The creation of new interdisciplinary communication platforms is more relevant today than ever before. This review pro[1]vides key information about the First Conference «Mind, Body, Intelligence, Language in the Age of Cognitive Technologies». The organizers created an event that brought together IT developers, academic researchers, and business representatives.
{"title":"Mind, body, intelligence amd language in the era of cognitive technologies. Brief overview of the MBIL 2023 conference","authors":"P. N. Baryshnikov","doi":"10.17726/philit.2023.2.10","DOIUrl":"https://doi.org/10.17726/philit.2023.2.10","url":null,"abstract":"Science as a social institution today is experiencing a phase of profound transformation. Objects, methods, research technological tools, methods of institutional communication and mechanisms for commercializing new knowledge are changing. The creation of new interdisciplinary communication platforms is more relevant today than ever before. This review pro[1]vides key information about the First Conference «Mind, Body, Intelligence, Language in the Age of Cognitive Technologies». The organizers created an event that brought together IT developers, academic researchers, and business representatives.","PeriodicalId":398209,"journal":{"name":"Philosophical Problems of IT & Cyberspace (PhilIT&C)","volume":"122 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139176115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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