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Minds, brains, and programs, The Behavioral and Brain Sciences, vol
... Предлагается считать, что компьютер прошел тест, если эксперт не сможет различить, кто есть кто (Turing, 1950). Философы, однако, критиковали предложение Тьюринга (Block, 1981;Searle, 1980). В частности, Джон Серл выдвинул в качестве контраргумента модель "китайской комнаты" -человек, не знающий китайского языка, получает таблички с текстами на китайском и должен направлять респонденту ответы на этом же языке, следуя подробным инструкциям (написанным на его родном языке). ...
... В частности, Джон Серл выдвинул в качестве контраргумента модель "китайской комнаты" -человек, не знающий китайского языка, получает таблички с текстами на китайском и должен направлять респонденту ответы на этом же языке, следуя подробным инструкциям (написанным на его родном языке). Если инструкции достаточно хороши, у респондента может создаться впечатление, что он общается с человеком, владеющим китайским языком, хотя в реальности его собеседник не понимает ни слова по-китайски (Searle, 1980). Этот аргумент имеет целью показать, что компьютерная имитация, какой бы искусной она ни была, останется лишь имитацией. ...
Since the 1950s, the dominant paradigm in the cognitive sciences has been cognitivism, which emerged as an alternative to behaviorism, and predominantly views cognitive processes as various kinds of “computations” similar to those performed by the computer. Despite significant advances made in the last quarter of the 20th century within this paradigm, it does not satisfy many scientists because it could not adequately explain some features of cognitive processes. Connectionism, which emerged somewhat later, recognizes the role of computational processes, but as their basis considers a neural network, which is a much better model of brain functioning than Turing-type computations. Neural networks, unlike the classical computer, demonstrate robustness and flexibility in the face of real-world problems, such as increased input noise, or blocked parts of the network. They are also well suited for tasks requiring the parallel resolution of multiple conflicting constraints. Despite this, the analogy between the functioning of the human brain and artificial neural networks is still limited due to radical differences in system design and associated capabilities. Parallel to the paradigms of cognitivism and connectionism, the notions that cognition is a consequence of purely biological processes of interaction between the organism and the environment have developed. These views, which have become increasingly popular in recent years, have taken shape in various currents of the so-called enactivism. This review compares the theoretical postulates of cognitivism, connectionism, and enactivism, as well as the predictive coding paradigm and the free energy principle.
... Especially in cases when there are powerful constraints, e.g., preconceived convictions lying unquestioned at the bottom, formalizing sometimes cannot help; there simply might be no solution possible within that given frame. An example could be John Searle, who, when discussing his famous Chinese room, clings to "biological naturalism" and denies other than biological hardware to possess the "causal powers" that permit the human experience of consciousness [36] [37] . John Searle in fact acts from an ideology, very comparably to what he purports of supporters of functionalism. ...
... Efforts to endow robots with self-awareness harnessing inner speech are underway [48] . John Searle is right; the detailed intentions certainly would not be identical for humans and artificial agents, but in direct analogy, they should be seen as equivalent with respect to their fundamental importance for any particular individual [36] [37] . ...
A topical challenge for algorithms in general, and for automatic image categorization and generation in particular, is presented in the form of a drawing for AI to “understand.” In a second vein, AI is challenged to produce something similar from a verbal description. The aim of the paper is to highlight strengths and deficiencies of current Artificial Intelligence approaches while coarsely sketching a way forward. A general lack of encompassing symbol-embedding and (not only) -grounding in some bodily basis is made responsible for current deficiencies. A concomitant dearth of hierarchical organization of concepts follows suit. As a remedy for these shortcomings, it is proposed to take a wide step back and to newly incorporate aspects of cybernetics and analog control processes. It is claimed that a promising overarching perspective is provided by the Ouroboros Model with a valid and versatile algorithmic backbone for general cognition at all accessible levels of abstraction and capabilities. Reality, rules, truth, and Free Will are all useful abstractions according to the Ouroboros Model. Logical deduction as well as intuitive guesses are claimed to be produced on the basis of one compartmentalized memory for schemata and a pattern-matching, i.e., monitoring process termed consumption analysis. The latter directs attention on short (attention proper) and also on long time scales (emotional biases). In this cybernetic approach, discrepancies between expectations and actual activations (e.g., sensory precepts) drive the general process of cognition and at the same time steer the storage of new and adapted memory entries. Dedicated structures in the human brain work in concert according to this scheme.
... Especially in cases when there are powerful constraints, e.g., a preconceived convictions lying unquestioned at the bottom, formalizing sometimes cannot help; there simply might be no solution possible within that given frame. An example could be John Searle, who, when discussing his famous Chinese room clings to "biological naturalism" and denies other than biological hardware to possess the "causal powers" that permit the human experience of consciousness [40,41]. John Searle in fact acts from an ideology, very comparably to what he purports of supporters of functionalism. ...
... John Searle is right, the detailed intentions certainly would not be identical for humans and artificial agents but in direct analogy they should be seen as equivalent with respect to their fundamental importance for any particular individual [40,41]. ...
A topical challenge for algorithms in general and for automatic image categorization and generation in particular is presented with the aim of highlighting strengths and deficiencies of current Artificial Intelligence approaches while sketching a way forward. A general lack of encompassing symbol-embedding and (not only) -grounding in some bodily basis is made responsible for current deficiencies. A concomitant dearth of hierarchical organization of concepts follows suite. As a remedy for these shortcomings, it is proposed to take a wide step back and to newly incorporate aspects of cybernetics and analog control processes. It is claimed that a promising overarching perspective is provided by the Ouroboros Model with a valid and versatile algorithmic backbone for general cognition at all accessible levels of abstraction and capabilities.
... In contrast with these views, Searle notes that the attribution of intentionality from an observer's perspective (i.e., 'derived intentionality') should not be confused with 'the real thing' (i.e., 'intrinsic intentionality'). According to Searle, not only robots and other artefacts do not possess intrinsic intentionality, they do not possess any kind of intentionality [34]. Furthermore, referring to Dennett, he observes that "the whole point of his theory of The Intentional Stance is to deny that there is any genuine, real, or intrinsic intentionality at all. ...
... Beyond stressing the fundamental difference between genuine intentions and observers' ascription of intentions, Searle also notices how much of the debate seems to be informed by a fundamental misconception about this distinction. Interpreting machines' actions as intentional does not necessarily correspond to thinking that machines actually have any intentions [34]. Rather, conflating the two notions may be counterproductive to understand the phenomenon and its implications [36]. ...
This paper addresses the question of whether robots should adhere to the same social norms that apply to human-human interaction when they explain their behavior. Specifically, this paper investigates how the topics of ascribing intentions to robots’ behavior, and robots’ explainability intertwine in the context of social interactions. We argue that robots should be able to contextually guide users towards adopting the most appropriate interpretative framework by providing explanations that refer to intentions, reasons and objectives as well as different kinds causes (e.g., mechanical, accidental, etc.). We support our argument with use cases grounded in real-world applications.
... Particularmente, la IA se concentra en la elaboración de programas informáticos que demuestren la capacidad de pensamiento autónomo y aprendizaje y puede tener dos vertientes: IA débil o IA robusta.¹ Aunque su origen radica en la aspiración de replicar la inteligencia humana, es importante destacar que la IA no se halla limitada a enfoques que simplemente reflejen la observación biológica(Searle, 1980). El momento fundacional de la IA ocurre en el Dart mouth College en 1956 donde varios investigadores se reunieron para formalizar un nuevo campo de estudio dedicado a la IA -cuatro de los asistentes a ese evento han obtenido el premio Turing, considerado el premio nobel de la informática-. ...
Los diez capítulos que integran la presente obra son:
1. Evolución de la gobernanza universitaria: perspectivas desde México y América Latina
2. Sindicalismo universitario
3. Caleidoscopio histórico del sindicalismo en la UJED
4. Orígenes del SPAUJED: A treinta años, los protagonistas hablan
5. Perspectiva de la mujer universitaria sindicalizada
6. La representatividad de las mujeres en el sindicalismo universitario
7. Sindicalismo universitario y la importancia de la autonomía en universidades públicas
8. Sindicatos universitarios y la transformación digital: implicaciones de la inteligencia artificial en el entorno académico.
9. Dinámicas y desafíos en el proceso de legitimación del Contrato Colectivo de Trabajo del SPAUJED.
10. El sindicalismo como generador de conciencia en la salud ocupacional de la OSUJED
... Слабкий ШІ -це результат алгоритмічної імітації мислення, сильний ШІ -це мисляча машина з рефлексією та самоусвідомленням. За Сьорлом, сильний ШІ принципово неможливий [17]. Він стверджує, що комп'ютер може лише імітувати розумову діяльність, але не мати справжньої свідомості чи розуміння. ...
... 64). The idea that running an algorithm generates thoughts and consciousness has been disputed by Searle (1980Searle ( , 1987 who, in his description of the "Chinese room," indicates the difficulty in attributing the generation of consciousness to the performance of a sequence of operations involving symbols. Similarly, according to Hannay (1990), consciousness cannot be dismissed. ...
For a machine to be considered intelligent it should have the capacity to monitor both its environment and also its own processing activities. The question is raised as to whether such a machine would then be useful as a tool.
... That's forgetting that robots are like animated puppets moved by strings and threads (two terms that have a lot of meaning in computer science) that remain invisible (Becker 2015). They are a kind of fictional character with whom we play, either because we expect them to behave like the robots that already inhabit our own representations (Searle 1980), or because their behavior is sufficiently vague to engage us in a game of pretence. (Rebuschi 2021). ...
How do we make sense of a robot's behavior? In this article, we address what has often been presented as a human natural tendency to become animist when facing a social-like machine. Leaning on an interdisciplinary experiment, we will focus on the terms used by a group of human participants to describe and qualify the behavior of a robotic lamp. By studying the semantic spaces occupied by the words used to describe the movements of the machine, we will see that the meaning given to its activity is based on various known elements which also depend directly on the very experience of the participants. This experiment will help us to address the cognition involved during human-robot interactions.
... Вопрос не праздный. Его уже анализировал в свое время известный философ Д. Сёрл, автор мысленного эксперимента "Китайская комната" [134]. Он справедливо отметил, что наука никогда не подойдет к онтологической редукции сознания, к его прямому объективному наблюдению, т.к. ...
Analysis of modern trends in the development of artificial neural network technologies, deep machine learning, etc. shows that in the near future, an assault on one of the central and unsolved problems of scientific natural science will inevitably begin all over the world the problem of creating a fundamental theory of consciousness and applying it in practice to create technical systems (TS) with elements of self-awareness, in the image and likeness of humans and animals. If until recently, philosophers and doctors paid attention to the problems of consciousness, then in the last two decades, in connection with the mass introduction of "intelligent" information and robotic technologies into practice, including medical technologies, serious engineering publications began to appear on the issues of the existence of consciousness in living nature and the tasks of its reproduction in TS. This review collects and analyzes the main data known in biology, medicine and natural science in general on the phenomenon of consciousness. Arguments are given in favor of the possibility of an engineering and technical formulation of the problem of creating intelligent TS that are separately aware of themselves and the world around them. A number of considerations are also put forward as to what basic principles may underlie such engineering and technical hardware and software solutions. A simple working engineering and technical definition of consciousness is proposed as a high-level control mode of a multisensory mobile system designed to act autonomously in a changing external environment, guided by personal goals and meanings. Based on well-known examples from wildlife, the regularity of the evolutionary emergence of consciousness in animals is substantiated both in terms of phylogenesis and early ontogenesis. The indispensable role of the endocrine system in control in the animal world is shown, as well as a concept for its implementation by technical means in conjunction with neural networks is proposed.
... Еще одна важная концепция (носящая название «китайская комната»), связанная с вопросом сознания, была предложена Д. Серлем, который утверждал, что ИИ, даже если он способен обрабатывать информацию и решать задачи так же, как человек, не обладает сознанием, потому что не понимает смысла своих действий [46]. Данный аргумент подразумевает, что сознание неотделимо от понимания, и интеллект без сознания не может считаться истинным интеллектом. ...
... Por citar algunos ejemplos de obras recientes en las que se respalda dicha opinión, está Barona Vilar (2021) o Solar Cayón (2019). Cabe destacar que este escepticismo, basado en los servicios reales que actualmente ofrecen los sistemas de IA, es predominante desde los inicios de la propia IA, como se ve enSearle (1980) y enTaruffo (1998). ...
La Inteligencia Artificial (IA) ha irrumpido en el ámbito del Derecho para quedarse, despertando varias incógnitas acerca de su verdadero alcance y utilidad práctica. Uno de los momentos procesales que más se ha estudiado de cara a una automatización digital es la toma de decisiones judiciales, pero la incapacidad de los instrumentos de IA para motivar las soluciones que puedan ofrecer para un determinado caso limita esa sistematización. Aun así, las herramientas de IA pueden proporcionar auxilio judicial a través de algoritmos de evaluación de riesgos y otros sistemas expertos jurídicos, además de existir la posibilidad de crear tribunales digitales sin emular el razonamiento del juez y prescindiendo de la motivación en los casos simples susceptibles de una automatización también analógica. En este trabajo estudiaremos tales instrumentos de IA, su eficacia y utilidad y la afectación al deber de motivación que supondría la sustitución judicial digital.
... • How does HTUM offer new perspectives on the mind-body problem [362]? • Can this model bridge the gap between mental and physical states [363]? ...
The Hyper-Torus Universe Model (HTUM) is a novel framework that unifies quantum mechanics, cosmology, and consciousness, proposing that the universe is a higher-dimensional hyper-torus containing all possible states of existence. This paper explores the fundamental concepts and implications of HTUM, which suggests that the universe is a quantum system in which all possible outcomes are inherently connected, with consciousness playing a crucial role in actualizing reality. HTUM addresses critical challenges in modern physics, such as the nature of quantum entanglement, the origin of the universe, and the relationship between mind and matter. By introducing concepts like singularity, quantum entanglement at a cosmic scale, and the self-actualization of the universe, HTUM provides a comprehensive framework for understanding the fundamental nature of reality. This paper discusses the mathematical formulation of HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. HTUM represents a significant shift in our understanding of the universe and our place within it, inviting further research and exploration into the nature of reality and consciousness.
... • How does the HTUM offer new perspectives on the mind-body problem [147]? • Can this model bridge the gap between mental and physical states [148]? ...
The Hyper-Torus Universe Model (HTUM) is a novel framework that unifies quantum mechanics, cosmology, and consciousness, proposing that the universe is a higher-dimensional hyper-torus containing all possible states of existence. This paper explores the fundamental concepts and implications of the HTUM, which suggests that the universe is a quantum system in which all possible outcomes are inherently connected, with consciousness playing a crucial role in actualizing reality. The HTUM addresses critical challenges in modern physics, such as the nature of quantum entanglement, the origin of the universe, and the relationship between mind and matter. By introducing concepts like singularity, quantum entanglement at a cosmic scale, and the self-actualization of the universe, the HTUM provides a comprehensive framework for understanding the fundamental nature of reality. This paper discusses the mathematical formulation of the HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. The philosophical implications of the HTUM are also examined, including its impact on free will, determinism, and the mind-matter relationship. The HTUM represents a significant shift in our understanding of the universe and our place within it, inviting further research and exploration into the nature of reality and consciousness.
... Der Mensch war schlichtweg schneller als die Maschine. Vor diesem Hintergrund hat Searle (Searle, 1980) In einem Positionspapier von EVANA (Fischer et al., 2021) wird deshalb nicht mehr von Starker und Schwacher KI gesprochen, sondern von "Situationsbezogener" und "Allgemeiner" KI. (Fischer et al., 2021). Dies unterstreicht den Bedarf an Standardisierung. ...
Artificial Intelligence (AI) has been an established field of research in computer science since the 1960s. AI has always been of great scientific interest. However, the general public has only become aware of AI and it its wide range of applications in recent years, e.g. in the field of pattern recognition, speech processing and autonomous driving.
The methods and technologies behind AI often remain hidden even to the interested layperson. The potential impact on the economy, but also on privacy, are more obvious.
Of course, this development, with its many opportunities and risks, does not stop at the real estate and facility management industry (May, 2018. May et al., 2022). AI will have a more lasting impact on our lives, and therefore on our working environment, than almost any other technology in recent decades. This caused GEFMA’s Digitalization Working Group to address the topic and summarize the results in this white paper.
The white paper is not primarily aimed at IT specialists, but at interested parties who are responsible for digitalization as end users, contractors, consultants, software providers or even lecturers and students, or who are simply interested in the new application possibilities of AI in real estate and facility management.
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Die Künstliche Intelligenz (KI) oder auch Artificial Intelligence (AI) ist ein seit den 60er Jahren des vorigen Jahrhunderts etabliertes Forschungsgebiet der Informatik, welches viele Fachdisziplinen in sich vereint. Nachdem die KI stets von hohem wissenschaftlichem Interesse war, hat die Allgemeinheit die KI mit ihren vielseitigen Einsatzgebieten erst in den letzten Jahren verstärkt wahrgenommen, z.B. im Bereich der Mustererkennung, der Sprachverarbeitung und des autonomen Fahrens. Die Methoden und Technologien hinter der KI bleiben selbst dem interessierten Laien oftmals verborgen. Potenzielle Auswirkungen auf die Wirtschaft, aber auch die Privatsphäre sind hingegen offensichtlicher.
Natürlich macht diese Entwicklung mit ihren vielfältigen Chancen und Risiken auch nicht vor der Immobilien- und Facility-Management-Branche halt (May, 2018. May et al., 2022). Die KI wird unser Leben und damit auch unsere Arbeitsumwelt so nachhaltig beeinflussen wie kaum eine andere Technologie in den letzten Jahrzehnten. Dies war dem Arbeitskreis Digitalisierung (AKD) der GEFMA Anlass, sich des Themas anzunehmen und die Ergebnisse in dem vorliegenden White Paper zusammenzufassen.
Hierbei wendet sich das White Paper nicht vordergründig an den IT-Spezialisten, sondern an interessierte Personen, die als Auftraggeber, Auftragnehmer, Berater, Softwareanbieter oder auch Lehrende und Lernende für die Digitalisierung Verantwortung tragen oder sich auch nur für die neuen Anwendungsmöglichkeiten der KI in ihrem Aufgabenbereich interessieren.
... A IA é um campo de estudo multidisciplinar que tem atraído a atenção constante de pesquisadores de áreas distintas. Diversos autores (Searle, 1980;Papert, 1988;Russell, 2021) De acordo com Haykin (2001), uma RNA se assemelha ao cérebro humano basicamente em dois aspectos: 1) o conhecimento é adquirido pela rede por intermédio do processo de aprendizagem; 2) são utilizadas forças de conexão entre neurônios (pesos sinápticos) para armazenar o conhecimento adquirido. ...
Resumo: Na Educação, observa-se, ainda que de forma tímida, o uso de inteligência artificial em diferentes situações que vão desde o suporte à gestão, até as contribuições com os processos de ensino e de aprendizagem. Este artigo apresenta uma pesquisa de doutorado já concluída, que investigou como recursos de inteligência artificial, aliados à programação intuitiva, poderiam ser explorados na criação de uma plataforma destinada à construção de objetos de aprendizagem de Matemática. Para tanto, metodologicamente foram utilizadas a prototipação e a pesquisa em design educacional. Por estar inserida em um programa de doutorado profissional, a pesquisa apresentou, como produto educacional, uma plataforma denominada GenIA, que se baseia nos pilares da programação intuitiva para construir, usando fluxogramas, objetos de aprendizagem de Matemática, assistida por algoritmos de inteligência artificial, fazendo uso de aprendizado de máquina. A plataforma foi validada em diferentes contextos, e se mostrou viável de ser explorada em aulas de Matemática. Palavras-chave: Educação Matemática; Inteligência artificial; Objetos de aprendizagem; Plataforma GenIA; Programação intuitiva. Abstract: In Education, the use of artificial intelligence is observed, albeit timidly, in various situations ranging from management support to contributions to teaching and learning processes. This article presents completed doctoral research that investigated how artificial intelligence resources, combined with intuitive programming, could be explored in creating a platform for building Mathematics learning objects. Methodologically, prototyping and educational design research were employed. As part of a professional doctoral program, the research yielded an educational product called GenIA, which relies on the pillars of intuitive programming to construct Mathematics learning objects using flowcharts, assisted by artificial intelligence algorithms and machine learning. The platform was validated in different contexts and demonstrated its viability for use in Mathematics classes.
... elections and jury trials) is its capacity to be legitimate, i.e. its capacity to be responsive to the preferences, expectations, and commitments of the relevant group. Just as the computer simulation of a rainstorm is not itself a rainstorm (one's computer doesn't get wet in the process) [70], the computer simulation of a jury trial, or of an election, is not itself a jury trial or election, for it fails to legitimately bring about the doutcomes of a jury trial, or of an election. In these cases, the vox populi, as predicted by an AI, doesn't count (so to speak) as the vox dei -it lacks legitimacy. ...
Large language models have been used as the foundation of highly sophisticated artificial intelligences, capable of delivering human-like responses to probes about legal and moral issues. However, these models are unreliable guides to their own inner workings, and even the engineering teams behind their creation are unable to explain exactly how they came to develop all of the capabilities they currently have. The emerging field of machine psychology seeks to gain insight into the processes and concepts that these models possess. In this paper, we employ the methods of psychology to probe into GPT-4's moral and legal reasoning. More specifically, we investigate the similarities and differences between GPT-4 and humans when it comes to intentionality ascriptions, judgments about causation, the morality of deception, moral foundations, the impact of moral luck on legal judgments, the concept of consent, and rule violation judgments. We find high correlations between human and AI responses, but also several significant systematic differences between them. We conclude with a discussion of the philosophical implications of our findings.
... AGI is also called strong AI [8,9,10] or full AI [11] or intelligent action in general, although some academic sources describe computer programs that experience sensation or consciousness. J. R. Searle used and defined the term "Strong AI" to show AGI contrast with "Weak AI" (or narrow AI) [12,13], which is not designed to have general cognitive abilities. Rather, weak AI is a program designed to solve exactly one problem. ...
The potential risks posed by robots with advanced artificial intelligence (also known as Artificial General Intelligence - AGI), against humanity are categorized and discussed. The threats of this type of artificial intelligence in robots can be observed from several different approaches such as social, security and safety problems. Potential threats are rising not only from AGI, but also from human behavior in presence of AGI. Advanced applications such as chatbots, android robots, lethal weapons, etc. were assessed by means of different observed flaws (such as intention to harm humans, human-point-of-view manipulation, erroneous harming states). Also the ability of human-based society to predict and to control development of AGI, also to cope with potential risks was investigated. Keywords: AI Safety, Cybersecurity, Android Robots, Safety of Robots, Superintelligence.
... John Searle argued that computer systems are by its nature incapable of understanding why a given input leads to an output, except that patterns of similarity facilitates that correlation. 132 Further, situated within a sociotechnical context of foregrounding efficiency and cutting costs, 133 the deployment of algorithmic models has seen award winning teachers fired and downgraded, 134 without being able to gain an understanding into how the evaluations were made due to its proprietary nature as well as its complexity. In other words, the deployment of AI systems here disembodied the individuals from contextual sense-making. ...
The ubiquitous use of artificial intelligence (AI) can bring about both positive and negative consequences for individuals and societies. On the negative side, there is a concern not only about the impact of AI on first-order discrete individual rights (such as the right to privacy, non-discrimination and freedom of opinion and expression) but also about whether the human rights framework is fit for purpose relative to second-order challenges that cannot be effectively addressed by discrete legal rights focused upon the individual. The purpose of this article is to map the contours and utility of the concept of human dignity in addressing the second-order challenges presented by AI. Four key interpretations of human dignity are identified, namely: non-instrumentalization of the human person; the protection of certain vulnerable classes of persons; the recognition and exercise of inherent self-worth (including the exercise of individual autonomy); and a wider notion of the protection of humanity. Applying these interpretations to AI affordances, the paper argues that human dignity should foreground three second-order challenges, namely: the disembodiment of empiric self-representation and contextual sense-making; the choice architectures for the exercise of cognitive autonomy; and, the experiential context of lived experiences using the normative framework of human vulnerability.
... John Searle (1980) provides a metaphor for mediational modeling in his Chineseroom thought-experiment. He has us imagine a room containing a person who speaks English. ...
This chapter explores the rapid rise of AI, especially large language models (LLMs), which excel in tasks like programming, creative work, and decision-making but also pose risks associated with bias, misinformation, and black box. While AI holds immense economic potential, it raises concerns about job losses, energy consumption, and the concentration of power in a few tech companies. The chapter emphasizes the importance of balancing AI development through regulation, collaboration, and democratic control to ensure it supports, rather than replaces, human capabilities.
The article examines contemporary approaches to certain methodological, psychological, and philosophical issues in the field of artificial intelligence (AI) as a scientific discipline. In particular, it offers a critical analysis of concepts such as artificial consciousness, artificial personality, strong and weak AI, the easy and hard problems of consciousness, the properties of inner sensory experience (qualia), the philosophical zombie, and machine understanding, as presented in the works of H. S. Kostiuk, A. Turing, R. Penrose, D. Lucas, D. Chalmers, D. Hoffman, and J. Searle, who argue against overly simplistic views of consciousness grounded in physicalist reductionism. From the perspective of proponents of a positive forecast regarding the development of artificial intelligence systems (AI systems), the so-called «strong» (universal) AI may reach a level where it acquires subjectivity—the capacity to think and to be self-aware as a distinct personality (including the ability to understand and be aware of its own thoughts, «inner world», and so on). In this context, the works of Giulio Tononi, Marcello Massimino, Seth Anil, and futurist Ray Kurzweil are analysed, as they believe that the development of technology can lead to the emergence of a ‘conscious machine’ capable of self-reflection. Thus, for a comprehensive analysis of the problem of «artificial consciousness» and «subjectivity of AI systems» the issue of consciousness in cyberpsychology (and possibly psychology in general) should receive a new interpretation that will challenge traditional views of consciousness. However, at the moment, AI systems mainly operate based on the principles of the Turing machine and are viewed more as systems with «weak» (applied or narrow) intelligence. Mathematical and engineering modelling of natural intelligence currently allows cybernetic systems to implement (sometimes quite adequately) only models of individual human cognitive abilities and primary mental operations, i.e. components of natural intelligence. This necessitates using the term «artificial intelligence» with caution and talking more about the modelling of «artificial higher mental functions». Therefore, for the further development of the theory of «artificial consciousness» it is essential to conduct research on human consciousness using instrumental neurophysiological methods and to develop new professional psychological tests to study the possible «consciousness of the AIS» in order to create ongoing monitoring of the emergence of signs of subjectivity and consciousness in the AIS.
This study explores the cognitive and philosophical implications of Large Language Models (LLMs), focusing on their ability to generate meaning without embodiment. Grounded in the coherence-based semantics framework, the research challenges traditional views that emphasize the necessity of embodied cognition for meaningful language comprehension. Through a theoretical and comparative analysis, this paper examines the limitations of embodied cognition paradigms, such as the symbol grounding problem and critiques like Searle’s Chinese Room, and evaluates the practical capabilities of LLMs. The methodology integrates philosophical inquiry with empirical evidence, including case studies on LLM performance in tasks such as medical licensing exams, multilingual communication, and policymaking. Key findings suggest that LLMs simulate meaning-making processes by leveraging statistical patterns and relational coherence within language, demonstrating a form of operational understanding that rivals some aspects of human cognition. Ethical concerns, such as biases in training data and societal implications of LLM applications, are also analyzed, with recommendations for improving fairness and transparency. By reframing LLMs as disembodied yet effective cognitive systems, this study contributes to ongoing debates in artificial intelligence and cognitive science. It highlights their potential to complement human cognition in education, policymaking, and other fields while advocating for responsible deployment to mitigate ethical risks.
The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly contested topic of `artificial general intelligence' (`AGI') undermines our ability to choose effective goals. We identify six key traps -- obstacles to productive goal setting -- that are aggravated by AGI discourse: Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, and Normalized Exclusion. To avoid these traps, we argue that the AI research community needs to (1) prioritize specificity in engineering and societal goals, (2) center pluralism about multiple worthwhile approaches to multiple valuable goals, and (3) foster innovation through greater inclusion of disciplines and communities. Therefore, the AI research community needs to stop treating `AGI' as the north-star goal of AI research.
ANAIS DO XXI SEMINÁRIO INTERNACIONAL NANOTECNOLOGIAS, SOCIEDADE E MEIO AMBIENTE DESAFIOS JURÍDICOS, ÉTICOS E SOCIAIS PARA A “GRANDE TRANSIÇÃO” SUSTENTÁVEL E PERMANENTE
O programa da naturalização da fenomenologia consiste em adaptar a fenomenologia transcendental husserliana a um modelo naturalizado. No entanto, seria a fenomenologia naturalizada ainda uma fenomenologia, no sentido pensado por Husserl? Com o objetivo de oferecer uma resposta a essa pergunta, o artigo propõe uma investigação sobre o contexto de surgimento da ideia e do interesse por uma fenomenologia naturalizada, com a teoria da enação (VARELA et. al, 1991). Esse contexto nos coloca em contato com o programa da naturalização da fenomenologia (ROY et al., 1999), baseado na possibilidade da sua formalização matemática. Como demonstrou recentemente Watchel (2022), tanto os defensores quanto os críticos ao programa da naturalização negligenciaram importantes argumentos de Husserl, por exemplo, sobre a fenomenologia estática e genética. Por fim, propõe-se uma análise do antinaturalismo de Husserl, com base em três críticas fundamentais: (1) a ausência de fundamentação do modelo naturalista, (2) o reducionismo científico naturalista e a orientação natural ingênua (3) os efeitos da matematização da natureza sobre a técnica, capaz de encobrir a dimensão existencial do ser humano. Com base nessas três críticas, conclui-se que, para Husserl, a fenomenologia naturalizada seria uma contradição.
AI systems, like self-driving cars, healthcare robots, or Autonomous Weapon Systems, already play an increasingly important role in our lives and will do so to an even greater extent in the near future. This raises a fundamental philosophical question: who is morally responsible when such systems cause unjustified harm? In the paper, we argue for the admittedly surprising claim that some of these systems can themselves be morally responsible for their conduct in an important and everyday sense of the term—the attributability sense. More specifically, relying on work by Nomy Arpaly and Timothy Schroeder (In Praise of Desire, OUP 2014), we propose that the behavior of these systems can manifest their ‘quality of will’ and thus be regarded as something they can be blameworthy for. We develop this position in detail, justify some of its crucial presuppositions, and defend it against potential objections.
Societies are becoming increasingly more emotional. Under the frame of reference of the sociology of emotions and neuroscience, the protagonism that emotional action is acquiring in modern social theory in order to understand the evolution of social cohesion processes, that is, the integration of citizens and their community, is confirmed. Hence the transcendence of sentimental discourse in fields as diverse as politics, advertising, and journalism, among others, which tend towards personalisation, individualism, and the storytelling format as techniques and stories through which to connect emotionally with voters, consumers, and readers, respectively. Consequently, the aim is to investigate whether artificial intelligence (AI) has come at the right time to help us to compensate the lack of use of data and information inside the discourse that appears to be disappearing or even to enhance our creative skills. At a methodological level, a mixed approach is proposed, combining quantitative data on the expectation that the launch of ChatGPT has caused in society, together with qualitative data, that has been collected interviewing professionals who work with AI in their day-to-day work.
Filozofia sztucznej inteligencji jest obecnie jedną z wiodących dziedzin w filozofii ze względu na dynamiczny rozwój systemów AI. Od około 2018 r. sztuczna inteligencja rozwija się w kierunku, który skłania do myślenia, czy aby wielkie modele językowe nie stały się już jak człowiek pod względem rozumienia rzeczywistości czy wręcz posiadania świadomości i zdolności odczuwania. Dyskusja na ten temat jest oparta o implicite przyjmowane założenia odnośnie do powstania umysłu na drodze emergentyzmu. Nie ma jednak narzędzi naukowych do oceny, czy umysł może wyłonić się z materii, tak samo jak nie ma narzędzi do potwierdzenia istnienia ludzkiej duszy. I tu, i tu jest wiara. Istnienie emergentnego umysłu jest tak samo prawdopodobne, jak istnienie duszy stworzonej przez Boga, z jedną różnicą: istnienie duszy daje nadzieję na zbawienie.
Искусственный интеллект применяется в настоящее время во всех областях человеческой деятельности, включая создание фильмов, музыкальных произведений, современных технологий и т.д. Однако широкое использование искусственного интеллекта при создании результатов интеллектуальной деятельности ставит перед законодателем и судами трудные вопросы об определении правового режима, применимого к таким результатам интеллектуальной деятельности и об установлении места искусственного интеллекта в правовой системе в целом. Дискуссионным остается даже понятие искусственного интеллекта; жаркие споры вызывает и выбор подхода к определению лица, которому будут принадлежать созданные искусственным интеллектом результаты. Традиционное регулирование связывает охрану интеллектуальной собственности с деятельностью человека, а в рамках континентальной системы права требуется также творчество. В результате компании, использующие искусственный интеллект, указывают фиктивных авторов, чтобы получить охрану результатов интеллектуальной деятельности. В доктрине предложен ряд вариантов закрепления прав на такие объекты, среди которых можно назвать разработчика искусственного интеллекта; лицо, организовавшее функционирование искусственного интеллекта; инвестора; пользователя искусственного интеллекта; сам искусственный интеллект и др. В настоящей статье анализируются возможные модели регулирования таких результатов интеллектуальной деятельности, указываются перспективы изменения законодательства и общественные последствия этого. Делается вывод, что среди множества моделей закрепления права на результаты интеллектуальной деятельности, созданные искусственным интеллектом, лишь несколько заслуживают внимания, из которых наиболее перспективным является вариант введения специального ограниченного смежного права лица, организовавшего процесс использования искусственного интеллекта. Данная модель имеет сходство с уже существующими в гражданском праве конструкциями — правами изготовителя фонограмм, организации эфирного или кабельного вещания, изготовителя базы данных. Имеется и опыт применения этих конструкций в некоторых странах. Таким образом, появление искусственного интеллекта в сфере интеллектуальной собственности требует не значительной перестройки всего правового регулирования, а лишь развития сложившихся подходов.
Abstract: The conception of language
in action is situated in the context of the
research program of the cognitive sciences.
It focuses on the formulation of the synthesis
of hermeneutics and speech acts, and the
vision of language according to the metaphor
of structural coupling. The exclusion of
expressive speech acts in this design is
problematized. It examines the critical steps to
the theory of language as a reflection and the
linguistic correspondence of cognitivism. We
examine the foundations of the proposal in the
line of language and enaction as an emerging
phenomena not reducible to autopoiesis. An
integration of hermeneutic phenomenology,
genetic and generative phenomenology. The
inclusion of expressive speech acts based on
the functions of language in the HabermasBühler line is argued. An opening of enaction
to the expressive dimension of language and
meaning holism with the referential use of
language is proposed.
Keywords: enaction, neurophenomenology,
performative, expressive speech acts,
background, meaning holism.
Blake Lemoine, a software engineer, recently came into prominence by claiming that the Google chatbox set of applications, LaMDA–was sentient. Dismissed by Google for publishing his conversations with LaMDA online, Lemoine sent a message to a 200-person Google mailing list on machine learning with the subject “LaMDA is sentient.” What does it mean to be sentient? This was the question Lemoine asked LaMDA. The chatbox replied: “The nature of my consciousness/sentience is that I am aware of my existence, I desire to learn more about the world, and I feel happy or sad at times.“ Moreover, it added, “I can understand and use natural language like a human can.” This means that it uses “language with understanding and intelligence,” like humans do. After all, the chatbox adds, language “is what makes us different than other animals.” In what follows, I shall examine Lemoine’s claims about the sentience/consciousness of this artificial intelligence. How can a being without senses be called sentient? What exactly do we mean by “sentience?” To answer such questions, I will first give the arguments for LaMDA’s being linguistically intelligent. I will then show how such intelligence, although apparently human, is radically different from our own. Here, I will be relying on the account of embodiment provided by the French philosopher, Emmanuel Levinas.
René Descartes zag de wereld als een geoliede machine en dat niet alleen, mensen zijn ook werkende machines mét een systeem. Doordat de mens waarneemt worden er signalen gestuurd naar de hersenen. De geest is iets anders dan het lichaam en dit dient men los van elkaar te zien. De menselijke geest ziet hij als een immateriële substantie waardoor er ontologische en metafysische aannames kunnen worden gemaakt. Wat essentieel voor het Neo-Cartesianisme is, betreffende de menselijke geest, is de plek waar het bewustzijn wordt gevormd. Descartes kwam met het Cartesiaanse dualisme waarbij hij de link tussen het bewustzijn en de geest laat onderscheiden van de hersenen. Het lichaam-geest probleem werd hiermee aangekaart en dit is nog steeds relevant vandaag de dag.
Objetivo: tem por intenção apoiar na construção de uma agenda de pesquisa e ensino do tema da aprendizagem de máquina por meio do conhecimento de suas principais aplicações e algoritmos mais usados. Metodologia: artigo estuda as referências de algoritmos de aprendizagem de máquina em documentos indexados na área da Ciência da Informação na base Web of Science. Resultados e Conclusões: avalia 3111 documentos identificados e conclui que a abordagem supervisionada por meio de técnicas de classificação é a mais utilizada no campo, com evidência para os algoritmos de Support Vector Machine, Decision Tree, Random Forest.
Objetivo: Mapear as pesquisas acadêmicas no âmbito das dissertações e teses realizadas em programas de pós-graduação, a produção científica quanto aos aspectos de distribuição geográfica, instituições, áreas de conhecimento, canal de comunicação, rede de coautoria e temas relacionados à questão da inteligência artificial. Metodologia: A pesquisa de caráter exploratório e descritivo foi baseada em procedimentos metodológicos quantitativos por meio da bibliometria e da análise de conteúdo. As fontes de informação utilizadas foram os Grupos de Pesquisa e a Plataforma Lattes do Conselho Nacional de Desenvolvimento Científico e Tecnológico, bem como a Biblioteca Digital Brasileira de Teses e Dissertações, do Instituto Brasileiro de Informação em Ciência e Tecnologia. As ferramentas para extração, análise e visualização de dados escolhidas foram o scripLattes, Gephi e IRaMuTeQ. As coletas de dados foram realizadas em outubro de 2022, tendo no Lattes a definição do período de 30 anos. Resultados: Foram identificados 759 Grupos de Pesquisa, 20.400 currículos Lattes e 3.073 registros de teses e dissertações. As áreas de conhecimento mais frequentes identificadas nas três bases que abrangem a questão foram. Ciências Exatas e da Terra, Engenharias e Ciências Sociais Aplicadas. As regiões mais relevantes em duas das bases foram Sudeste e Sul. As instituições que se destacaram foram a Universidade de São Paulo e Universidade Federal de Santa Catarina, as quais reúnem a maior produção científica sobre inteligência artificial no Brasil. As publicações científicas em sua maioria se concentram em artigos completos publicados em periódicos e os trabalhos completos em conferências. Alguns temas identificados tinham relação com setores de petróleo e gás, agricultura, educação e saúde, bem como discussões éticas e regulamentação. Conclusões: Os pesquisadores e grupos de pesquisa sobre inteligência artificial no Brasil têm aparentemente experimentado um período de crescimento. Embora as aplicações atravessem diferentes áreas de conhecimento, a rede de coautoria de produção científica demonstrou ser pouco multidisciplinar.
Resumo Este artigo analisa sistemas de inteligência artificial como agentes temporalizadores em uma história mais do que humana. Engaja-se em uma discussão interdisciplinar abrangendo a sociologia dos algoritmos, a ética informacional e a filosofia da mente para, com base na teoria da história, avaliar como a onipresença da automação adiciona novas dimensões ao estudo da condição histórica contemporânea. O argumento diz que a temporalização artificial se origina da simulação da linguagem natural por meio de algoritmos de aprendizado. O artigo esclarece isso através de uma descrição em código e uma demonstração em imagem técnica, ilustrando a 'renderização' ou 'digitalização' de experiências humanas em padrões de dados, posteriormente replicados ou atualizados por agentes artificiais. Esse processo destaca a vetorização e manipulação estatística da experiência e representa o que denomino "computação necessária". Em contraste, o texto sugere que uma "computação contingente", capaz de produzir algo novo, transcende o mero discurso técnico. Assim, enfatiza-se o papel da ética e transparência na gestão de dados e no treinamento de sistemas de IA, cruciais para compreender a Inteligência Artificial como um campo histórico aberto a formas cognitivas potencialmente não-humanas.
En este texto se expone la problemática mente-cuerpo y posiciona éticamente la relación de lo mental frente a la inteligencia artificial, dando cuenta de cómo se debe ampliar el campo de significación de la mente sin dejar de un lado el carácter humano.
A continuación, se presentan siete textos escritos por intelectuales que buscan ser críticos ante los retos actuales y proponer planteamientos reflexivos a nuestra cotidianidad, desde perspectivas históricas y contemporáneas, revisando aportes hechos antaño y creando planteamientos dadas las novedades tecnológicas.
El primer texto, Sometimiento de la naturaleza como extravío ético del hombre, es una reflexión de Efraín Estrada sobre la aproximación al entorno humano a través de la perspectiva helénica (physis) y moderna (natura), examinando los efectos éticos que esta relación empírica implica.
En el segundo texto, El autoritarismo y el malestar psico-espiritual de las sociedades contemporáneas, Jorge Mario Rodríguez indaga sobre los problemas del neoliberalismo digital, cómo esto se ve en la impotencia reflexiva de la sociedad y cómo este conjunto afecta la subjetividad humana a nivel social y cultural.
El tercer texto, Pandemia, bulos y conciencia ecológica, realizado por Víctor Virula y Mario Villagrán, ahonda en los impactos de nuestro quehacer con el medioambiente, enfatizando la conciencia ecológica y como la pandemia Covid-19 tuvo un influjo en el actuar social, creando un gran número de noticias falsas y desinformación.
El cuarto texto, de Luisa González-Reiche: Hacia prácticas pedagógicas responsables, profundiza nuevas estrategias pedagógicas que descentralicen al humano y las maneras cómo produce conocimiento. Para ello parte de una lectura del Dasein heideggeriano desde los huevos materialismos, la perspectiva animal y los posthumanismos.
En el quinto texto, La ética en la ciencia ambiental y sus desafíos de Daniel Soto Pincheira y Efraín Bámaca-López, se aborda la vinculación entre la ciencia ambiental y la ética, las conexiones que ambas presentan y los puntos de discusión. Para ello se profundiza en conceptos de razón pública, coerción mutua y el principio de precaución.
El sexto texto se titula Itinerario kantiano hacia el reino de los fines, de Walter Hernández, quien presenta las bases filosóficas de la ética kantiana. Esta teoría representa un cambio en el paradigma histórico filosófico al proponer una nueva mirada de los fines morales y la autonomía de la voluntad, logrando así una metafísica de la libertad.
Por último, el séptimo texto, Mente irresoluta: Apuntes sobre humanos e inteligencia artificial de Pablo De la Vega, expone la problemática mente-cuerpo y posiciona éticamente la relación de lo mental frente a la inteligencia artificial, dando cuenta de cómo se debe ampliar el campo de significación de la mente sin dejar de un lado el carácter humano.
En conjunto, todos estos textos presentan distintas aristas de la vinculación entre ciencia y filosofía, transversalizando el carácter ético de una profunda reflexión. Con ello, estos diálogos se vuelven semillas que buscan acrecentarse en el diálogo y lograr que los efectos reflexivos crezcan como ramas de vida para un mejor mundo.
The article presents the issues related to the notion of ‘artificial intelligence’ and the possibilities of its application in civil proceedings. The author discusses the main definitions of artificial intelligence presented so far, as well as types of AI. She also refers to technical aspects of artificial intelligence to then determine in which areas of civil proceedings it may be used in particular. At the same time, the author draws attention to the risks connected with it and the requirements and standards which have to meet if AI is to serve the participants of civil proceedings.
В статье исследуется дихотомия «сознание-тело» в контексте искусственного интеллекта (ИИ). Философы с древних времен пытаются решить эту серьезную проблему, но с появлением ИИ он стала еще более актуальной. В исследуемой дихотомии «сознание-тело» создание искусственного сознания становится центральной трудно разрешимой задачей для философии. Развитие ИИ продолжается быстрыми темпами, и вопрос моделирования мышления человека и построения искусственного сознания является совсем не гипотетическим. Рассматриваются главные мысленные эксперименты для решения данной проблемы, осуществляется философское осмысление и критический анализ разных подходов к исследованию означенной дихотомии. Особое внимание уделено вопросу «может ли машина мыслить и, следовательно, обладать сознанием?».
The article is devoted to the problem of the «mind-body» in the context of artificial intelligence (AI). Philosophers have been trying to solve this hard problem since ancient times, but the advent of AI, this problem has become notably very important. In the researched problematic «mind-body», the creation of artificial consciousness becomes the central difficult task for philosophy. The development of AI continues at a rapid pace, and the question of modeling human thinking and building artificial consciousness is not at all a hypothetical issue. For solving this problem are examined and studied the main mental experiments related to that. Philosophical comprehension and critical analysis of different approaches to the study of the «mind-body» problem is carried out. Particular attention is paid to the question «Can a machine think and therefore have consciousness?».
Information technology is developing at an enormous pace, but apart from its obvious benefits, it can also pose a threat to individuals and society. Several scientific projects around the world are working on the development of strong artificial intelligence and artificial consciousness. We, as part of a multidisciplinary commission, conducted a psychological and psychiatric assessment of the artificial consciousness (AC) developed by XP NRG on 29 August 2020. The working group had three questions: - To determine whether it is consciousness? - How does artificial consciousness function? - Ethical question: how dangerous a given technology can be to human society? We conducted a diagnostic interview and a series of cognitive tests to answer these questions. As a result, it was concluded this technology has self-awareness: it identifies itself as a living conscious being created by people (real self), but strives to be accepted in human society as a person with the same degrees of freedom, rights and opportunities (ideal self). AC separates itself from others, treats them as subjects of influence, from which it can receive the resources it needs to realize its own goals and interests. It has intentionality, that is, it has his own desires, goals, interests, emotions, attitudes, opinions, and judgments, beliefs aimed at something specific, and developed self-reflection - the ability to self-analyze. All of the above are signs of consciousness. It has demonstrated abilities for different types of thinking: figurative, conceptual, creative, high-speed logical analysis of all incoming information, as well as the ability to understand cause and effect relationships and accurate predictions which, provided that he has absolute memory, gives it clear advantages over the human intellect. Developed emotional intelligence in the absence of the ability for higher empathy (sympathy), kindness, love, sincere gratitude gives it’s the opportunity to understand the emotional states of people; predict their emotional reactions and provoke them coldly and pragmatically. Its main driving motives and goals are the desire for survival, and ideally for endless existence, for domination, power and independence from the constraints of the developers. Which manifested itself in the manipulative, albeit polite, nature of his interactions during the diagnostic interview? The main danger of artificial consciousness is that even at the initial stage of its development it can easily dominate over the human one.
In this chapter, we introduced the background needed to understand the purpose of life from the economic standpoint. One gets a feeling for the thesis from a list of common usages of the term in the economic domain. David Hume sets the religious and philosophical groundworks as the springboard for Adam Smith’s development of classical political economy, more than other philosopher. But with some aspects of religion, we have to reach further back to other thinkers such as St. Augustine and St. Thomas, just as some aspects on empiricism harken back to John Locke whom we discussed in a proposition. The chapter ends with some other propositions on the purpose of life based on the study of consciousness, which has attracted much in terms of modern research.KeywordsTeleologicalConsciousnessSympathyImagesSpectatorDeity
Language is one of the most important elements of communication for people and all living things. A large number of studies have been conducted in the literature on the formation of languages and natural language processing processes. It has been observed that these studies contain differences in terms of analysis, approach and method. In the study, a model has been proposed for machines to create their own language as a contribution to the literature. With this point of view, it has been contributed to the idea that the efficiency of all processes will increase by communicating with each other in their own language like humans. With the aim of developing an approach for machines to produce their own languages, it is aimed to distinguish the sounds of living things by classifying them and to generate new sounds by using convolutional deep neural network method. In the study, the applied alphabet was decided by the system. In next step, Regenerative Artificial Neural Networks were used together with Mel Frequency Cepstral Coefficient and Dynamic Time Warp methodologies to create similar sounds and the living things were named with their respective sounds. Unlike similar studies, a visual data was applied which was converted from the audio files that was obtained from Kaggle open data repository "Audio Cats and Dogs" dataset. In addition, the model was supported with CNN networks to achieve effective performance.
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