The famous advaitic expressions -/- Brahma sat jagat mithya jivo brahma eva na apraha and Asti bhaati priyam namam roopamcheti amsa panchakam AAdya trayam brahma roopam tato dwayam jagat roopam -/- will be analyzed through physics and electronics and interpreted. -/- Four phases of mind, four modes of language acquisition and communication and seven cognitive states of mind participating in human cognitive and language acquisition and communication processes will be identified and discussed. -/- Implications and application of such (...) an identification and analysis to the fields of cognitive sciences, mind-machine modeling, natural language comprehension field of artificial intelligence and physiological psychology will be hinted. A comprehensive modern scientific understanding of human consciousness, mind and mental functions will be presented. (shrink)

A model of human consciousness is presented here in terms of physics and electronics using Upanishadic awareness. The form of Atman proposed in the Upanishads in relation to human consciousness as oscillating psychic energy-presence and its virtual or unreal energy reflection maya, responsible for mental energy and mental time-space are discussed. Analogy with Fresnel’s bi-prism experimental set up in physical optics is used to state, describe and understand the form, structure and function of Atman and maya, the ingredients of human (...) consciousness. A description of phases of mind in terms of conscious states and transformation of mental energy is given. Four states of consciousness and four modes of language communication and understanding processes are also given. Implications of above scientific awareness of Upanishadic wisdom to the modern scientific fields of physiological psychology, cognitive sciences, mind-machine modeling and natural language comprehension are suggested. -/- . (shrink)

Soonya Vaada, the prime and significant contribution to Indian philosophical thought from Buddhism will be scientifically developed and presented. How this scientific understanding helped to sow seeds of origin of rationalism and its development in Buddhist thought and life will be delineated. Its role in the shaping of Buddhist and other Indian philosophical systems will be discussed. Its relevance and use in the field of cognitive science and development of theories of human consciousness and mind will be put forward. (...) The idea of absence as zero in number system, vacuum in physics and other natural sciences and state of absence of cognition in mind machine modeling will be presented. The use of significance of Soonya Vaada in philosophy, rational social life, natural sciences and technology, mathematics and cognitive science will be comprehensively discussed and a model for human cognition and communication will be arrived at. -/- . (shrink)

Sabdabrahma Siddhanta, popularized by Patanjali and Bhartruhari will be scientifically analyzed. Sphota Vada, proposed and nurtured by the Sanskrit grammarians will be interpreted from modern physics and communication engineering points of view. Insight about the theory of language and modes of language acquisition and communication available in the Brahma Kanda of Vakyapadeeyam will be translated into modern computational terms. A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension and communication process forming (...) the basis to develop software for relevant mind-machine modeling will be presented. The implications of such a model to artificial intelligence and cognitive sciences will be discussed. The essentiality and necessity of a physics, communication engineering , biophysical and biochemical insight as both complementary and supplementary to using mathematical and computational methods in delineating the theory of Sanskrit language is put forward. Natural language comprehension as distinct and different from natural language processing is pointed out. (shrink)

Ideas about human consciousness and mental functions will be analyzed and developed using cognitive science information available in the Upanishads, Brahmajnaana, Advaita and Dvaita schools of thought. -/- The analysis and development so done will be used to theorize and give scheme of human language acquisition and communication process clubbing with Sabdabrahma Siddhanta/Sphota Vaada which put forward infrasonic wave oscillator issuing pulses in infrasonic range and are reflected as brain waves. -/- Thus a brain-wave modulation/demodulation model of human language acquisition (...) and communication will be advanced and put forward. Application of this study in mind-machine modeling, natural language comprehension field of artificial intelligence will also be hinted. -/- . (shrink)

Matthias Mahlmann’s Mind and Rights (M&R) argues that the mentalist theory of moral cognition—premised on an approach to the mind most closely associated with generative linguistics—is the appropriate lens through which to understand moral judgment’s roots in the mind. Specifically, he argues that individuals possess an inborn moral faculty responsible for the principled generation of moral intuitions. These moral intuitions, once sufficiently abstracted, generalized, and universalized by individuals, gave rise to the idea of human rights embodied in (...) such conventions as the Universal Declaration of Human Rights. I am sympathetic to the fundamentals of this argument, particularly in the link between Universal Moral Grammar and the idea of human rights. I thus take my comments on M&R as an opportunity to preempt a topical challenge to the mentalist theory arising in statistical machine learning. Using M&R’s analytical theory of morality alongside the mentalist approach, I emphasize—through this preempted challenge—the significance of strong generative capacity in the moral domain, the distinction between actual acquisition of cognitive abilities and simulation of acquisition, and what Mahlmann calls the theory-dependence of data interpretation in machine learning modeling. (shrink)

A cognitive science perspective of yoga system of thought will be developed in conjugation with the Samkhya Darsana. This development will be further advanced using Advaita Vedanta and will be translated into modern scientific terms to arrive at an idea about cognition process. The stalling of the cognitive process and stilling the mind will be critically discussed in the light of this perspective. This critical analysis and translation into cognitive science and modern scientific terms will be presented together with (...) its implications and applications to the disciplines of mind-machine modeling, natural language comprehension branch of artificial intelligence and physiological psychology. (shrink)

A biophysical and biochemical perspective of Brahmajnaana will be advanced by viewing Upanishads and related books as “Texts of Science on human mind”. A biological and cognitive science insight of Atman and Maya, the results of breathing process; constituting and responsible for human consciousness and mental functions will be developed. The Advaita and Dvaita phases of human mind, its cognitive and functional states will be discussed. These mental activities will be modeled as brain-wave modulation and demodulation processes. The (...) energy-forms and their transformations as ideas/moods/experiences/thoughts/feelings/utterances/knowing/perception/experience/mood; and a theory of human cognition and communication will be advanced. The sameness of these and processes taking place and steps involved in human language acquisition and communication processes will be highlighted taking ideas from Sabdabrahma Siddhanta and Sphota Vaada, for which the basis is Brahmajnaana only. In fine, a physiological psychological and neurological model of human consciousness and function of mind based on Indian spiritual thought will be derived and discussed using concepts from modern science and technology. The application of these derivations in the fields of physiological psychology, mind-machine modeling, natural language comprehension branch of artificial intelligence and neurology to model and imitate human mental functions will be hinted. -/- . (shrink)

Descartes famously constructed a language test to determine the existence of other minds. The test made critical observations about how humans use language that purportedly distinguishes them from animals and machines. These observations were carried into the generative (and later biolinguistic) enterprise under what Chomsky in his Cartesian Linguistics, terms the “creative aspect of language use” (CALU). CALU refers to the stimulus-free, unbounded, yet appropriate use of language—a tripartite depiction whose function in biolinguistics is to highlight a species-specific form of (...) intellectual freedom. This paper argues that CALU provides a set of facts that have significant downstream effects on explanatory theory-construction. These include the internalist orientation of linguistics, the invocation of a competence-performance distinction, and the postulation of a generative language faculty that makes possible—but does not explain—CALU. It contrasts the biolinguistic approach to CALU with the recent wave of enthusiasm for the use of Transformer-based Large Language Models (LLMs) as tools, models, or theories of human language, arguing that such uses neglect these fundamental insights to their detriment. It argues that, in the absence of replication, identification, or accounting of CALU, LLMs do not match the explanatory depth of the biolinguistic framework, thereby limiting their theoretical usefulness. (shrink)

The concept developed in relation to Atman as infrasonic bio-mechanical oscillatorwill be used to delineate the physicochemical nature of thoughts and ideas. The insight available in the Upanishads, the Brahma Sutras, the Vishnu Sahasranaama and LalitaSahasranaama will be used to further and advance the understanding of mechanical, biochemical and electro-chemical nature of human thoughts and ideas. The conceptual clarity about these mental processes will be presented. A pictorial diagram of nature and forms of energy transformations involved in thought processes and (...) idea generations will be given. Implications and application of this insight to the disciplines of physiological psychology and mind-machine modeling will be hinted. (shrink)

In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...) to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year. (shrink)

-/- Explaining Consciousness and the Mind-Body Problem Through the Universal Law of Balance -/- Introduction -/- The nature of consciousness and its relationship with the body has been one of the greatest mysteries in philosophy and science. The mind-body problem questions how subjective experience (mind) arises from physical matter (body), while modern neuroscience, quantum mechanics, and artificial intelligence seek to understand the origins of conscious thought. -/- Angelito Malicse’s universal formula, rooted in the universal law of balance (...) in nature, provides a powerful framework for understanding consciousness as an emergent property of equilibrium. If all human decision-making follows natural laws, then consciousness itself—both individual and collective—must also follow the same principles of balance. This essay explores how this perspective can unify philosophical theories, be tested scientifically, and guide the development of artificial intelligence. -/- The Mind-Body Problem and the Universal Formula -/- Historically, the mind-body problem has been debated through dualism, materialism, and panpsychism. -/- 1. Dualism, proposed by René Descartes, suggests that the mind and body are separate substances. However, if consciousness emerges from a balance of biological, cognitive, and environmental factors, then mind and body are not separate but rather two interdependent systems working in harmony. -/- 2. Materialism, the view that consciousness is purely a result of physical processes in the brain, can also be explained through the universal formula. If the brain maintains a homeostatic equilibrium of neural activity, then conscious thought can be seen as a function of maintaining that balance. -/- 3. Panpsychism, the idea that consciousness is a fundamental property of the universe, aligns with the universal formula if all systems—atomic, biological, and cognitive—follow the same balancing principles. -/- Thus, the universal law of balance in nature can unify these perspectives by suggesting that consciousness is a product of equilibrium across multiple levels of reality. -/- Testing the Universal Formula in Neuroscience -/- If consciousness emerges from a balance between the brain, body, and environment, then this should be observable in biological experiments. -/- Brain-Body Synchronization -/- Neuroscientists have found that consciousness is deeply linked to bodily processes such as heartbeat rhythms, breathing patterns, and gut microbiome activity. When these systems are in balance, cognitive clarity and emotional stability increase. Disruptions—such as stress, disease, or neurological disorders—cause imbalances that affect perception and decision-making. -/- Scientific Test: Using fMRI and EEG, researchers can measure how homeostasis in the body correlates with stable brain activity and conscious awareness. If maintaining balance improves cognition, this supports the universal formula’s application to consciousness. -/- Feedback Loops in Decision-Making -/- Cognitive science shows that human thought follows a feedback mechanism—our brain constantly adjusts decisions based on past experiences and environmental input. If the universal formula is correct, then consciousness itself is a continuous process of maintaining equilibrium in decision-making. -/- Scientific Test: Experiments with brain-machine interfaces (BMIs) could simulate disruptions in decision-making balance and measure how the mind adapts. -/- Quantum Mechanics and Consciousness -/- Some scientists propose that consciousness operates at the quantum level, where thought processes may resemble wave superpositions and collapses. -/- Quantum Decision Theory -/- The human brain does not always process information in a straightforward way; rather, it often considers multiple possibilities before reaching a conclusion. This mirrors quantum physics, where particles exist in superposition until they interact with an observer. If consciousness follows the universal law of balance, then the brain may hold multiple mental states in balance before making a final decision. -/- Scientific Test: Studies in quantum cognition compare human decision-making with quantum probability models. If human thought aligns with quantum systems, it suggests that mental balance follows the same natural laws as physical balance in the universe. -/- Microtubule Consciousness Hypothesis -/- Some researchers, such as Roger Penrose and Stuart Hameroff, suggest that tiny structures within neurons (microtubules) generate consciousness through quantum coherence. If consciousness is a process of balance, then maintaining coherence within these structures might regulate awareness. -/- Scientific Test: If external stimuli can enhance or disrupt microtubule coherence, then altering quantum balance should affect conscious states. -/- Artificial Intelligence and the Simulation of Conscious Balance -/- If the universal formula is truly fundamental to consciousness, then AI systems that mimic this balance should develop self-regulating awareness. -/- AI Homeostasis and Adaptive Learning -/- Unlike traditional AI, which follows strict programming, an AI system designed to maintain balance between inputs, processing, and decision-making could behave in a way similar to biological consciousness. This would involve: -/- Self-regulating feedback loops that adjust based on new information. -/- Adaptive responses to environmental changes, like a human mind maintaining homeostasis. -/- Pattern recognition based on equilibrium, where the AI finds optimal solutions by balancing multiple factors. -/- Scientific Test: Developing AI models that learn through balance, rather than rigid programming, could demonstrate whether consciousness emerges from self-regulating equilibrium. -/- Conclusion: A New Understanding of Consciousness -/- The universal law of balance in nature provides a unifying framework for explaining consciousness, bridging philosophy, neuroscience, quantum mechanics, and artificial intelligence. If all decision-making follows natural balance, then consciousness itself is not an isolated phenomenon but a result of maintaining equilibrium across multiple dimensions—biological, cognitive, and universal. -/- By testing this theory scientifically—through brain-body synchronization, quantum cognition, and AI balance modeling—we may uncover the fundamental principles governing human awareness. This could lead to breakthroughs in mental health, decision science, and artificial intelligence, transforming how we understand both human and machine intelligence. -/- Thus, Angelito Malicse’s universal formula may hold the key to one of the greatest mysteries of existence: the true nature of consciousness itself. -/- . (shrink)

This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical systems, which (...) I call "cognitive systems". The goal of a cognitive study is to specify a dynamical model of a cognitive system, and then use this model to produce a detailed account of the specific cognitive abilities of that system. The dynamical approach does not limit a-priori the form of the dynamical models which cognitive science may consider. In particular, this approach is compatible with both computational and connectionist modeling, for both computational systems and connectionist networks are special types of dynamical systems. ;To substantiate these methodological claims about cognitive science, I deal first with two questions in two different fields: What is a computational system? What is a dynamical explanation of a deterministic process? ;Intuitively, a computational system is a deterministic system which evolves in discrete time steps, and which can be described in an effective way. In chapter 1, I give a formal definition of this concept which employs the notions of isomorphism between dynamical systems, and of Turing computable function. In chapter 2, I propose a more comprehensive analysis which is based on a natural generalization of the concept of Turing machine. ;The goal of chapter 3 is to develop a theory of the dynamical explanation of a deterministic process. By a "dynamical explanation" I mean the specification of a dynamical model of the system or process which we want to explain. I start from the analysis of a specific type of explanandum--dynamical phenomena--and I then use this analysis to shed light on the general form of a dynamical explanation. Finally, I analyze the structure of those theories which generate explanations of this form, namely dynamical theories. (shrink)

The concepts developed using Upanishadic insight regarding human consciousness, mind and mental processes and their applications in information acquisition and transmission by, through and in human body will be used to model human cognitive processes. A sequential reversible process by the stepwise transformation of (i) infrasonic form of energy and transformation of information already stored in (ii) biochemical form within as memory, and retrieved as inner mental world into (iii) electrochemical and then into (iv) mechanical form while communicating and (...) the reverse of it as the (i) input stimuli from outside world as light, sound, chemical, mechanical and heat forms, into (ii) electrochemical, (iii) biochemical and finally into (iv) infra sonic form while acquiring and understanding processes is put forward and discussed. Comparisons will be made between energy transformations in electronics communication processes and these psychic energy transformations that give rise to cognitive processes. This comparison gives an insight and theory of origin, structure, function and cessation of human mental functions. A comparative diagram that describes application of infrasonic energy transformations associated with bionics as biochemical, electrochemical and mechanical forms will be given. (shrink)

Four modes of language acquisition and communication are presented translating ancient Indian expressions on human consciousness, mind, their form, structure and function clubbing with the Sabdabrahma theory of language acquisition and communication. The modern scientific understanding of such an insight is discussed. . A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension and communication process forming the basis to develop software for relevantmind-machine modeling will be presented. The implications (...) of such a model to artificial intelligence and cognitive sciences will be discussed. The essential nature and necessity of a physics, communication engineering , biophysical and biochemical insight as both complementary and supplementary to using mathematical and computational methods in delineating the theory of language processing in humans is put forward. (shrink)

In conceptual modeling (CM) as a subdiscipline of software engineering, current proposed ontologies (categorical analysis of entities) are typically established through whole adoption of philosophical theories (e.g. Bunge’s). In this paper, we pursue an interdisciplinary research approach to develop a diagrammatic-based ontological foundation for CM using philosophical ontology as a secondary source. It is an endeavor to escape an offshore procurement of ontology from philosophy and implant it in CM. In such an effort, the CM diagrammatic language plays an (...) important role in contrast to dogmatic philosophical languages’ obsession with abstract entities. Specifically, this paper is about developing a descriptive (in contrast to formal) ontology that a modeler accepts as a supplementary account of reality when using thinging machines (TMs; i.e. a reality that uncovers the ontology of things that TM modeling discusses or “talks about,” akin to the ontology of natural language). Although existence is a well-established notion, we defend subsistence (Stoic term) as a supplementary mode of reality (e.g. reflection of event). The aim here is aligned toward developing CM notions and processes that are firm enough. Classical analysis of being per se (e.g. identity, substance, classes, objects) is de-emphasized in this work; nevertheless, philosophical concepts form an acknowledged authority to compare to. As a case study, such a methodology is applied to the notion of information that provides a common-sense understanding of the world. This application would enhance understanding of the TM methodology and clarify some of the issues that shed light on the question of the nature of information as an important concept in software engineering. Information is defined as about events; that is, it is about existing things. It is viewed as having a subsisting nature that exists only through being “carried on” by other things. The results seem to indicate a promising approach to define information and understand its nature. (shrink)

In this essay, it is argued that naturalism of an even moderate sort speaks strongly against a certain widely held thesis about the human mental (and cognitive) architecture: that it is divided into two distinct levels, the personal and the subpersonal, about the former of which we gain knowledge in a manner that effectively insulates such knowledge from the results of scientific research. -/- An empirically motivated alternative is proposed, according to which the architecture is, so to speak, flattened from (...) above. On this flattened view, although the states and processes typically associated with the personal level likely appear in our best models of the production of human behavior, they appear alongside states and processes normally associated with the subpersonal level. Moreover, the success of such models depends nowise on a levels-based distinction between the various causal contributors. It is argued that the flattened view has methodological implications of significant import. (shrink)

We explore the question of whether machines can infer information about our psychological traits or mental states by observing samples of our behaviour gathered from our online activities. Ongoing technical advances across a range of research communities indicate that machines are now able to access this information, but the extent to which this is possible and the consequent implications have not been well explored. We begin by highlighting the urgency of asking this question, and then explore its conceptual underpinnings, in (...) order to help emphasise the relevant issues. To answer the question, we review a large number of empirical studies, in which samples of behaviour are used to automatically infer a range of psychological constructs, including affect and emotions, aptitudes and skills, attitudes and orientations (e.g. values and sexual orientation), personality, and disorders and conditions (e.g. depression and addiction). We also present a general perspective that can bring these disparate studies together and allow us to think clearly about their philosophical and ethical implications, such as issues related to consent, privacy, and the use of persuasive technologies for controlling human behaviour. (shrink)

Predictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a nor- mative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., repre- sentational versus non-representational. Here we argue that these different interpre- tations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to dis- (...) tinguish four main notions of representation, which focus on organizational, struc- tural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that tradition- ally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demon- strates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what represen- tations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate. (shrink)

Until recently philosophy of physics has been overshadowed by the idea that the important philosophical issues that can be derived from physics are related only to fundamental theories, such as quantum mechanics and relativity. Applied fields of physics were deemed as unimportant. The argument for such a position lays in thinking that these applied fields of physics depend in their theoretical representations on fundamental theories and hence are reducible to these fundamental theories. It would be hard to defend such a (...) position, keeping in mind that applied fields of physics have a life of its own totally separate from fundamental physics and have in fact a lot to say to philosophers. The field of polymers is one of the branches of applied physics that has a lot to say to philosophers. It is a field of physics where theoreticians failed to present a coherent theory that can capture the different ways polymers can be built. This paper examines the difficulties that keep theoreticians away from having such a theory, revealing what kind of philosophical lessons polymers might have. The main thesis is: even in the cases where a theory predict the possibility of developing a specific type of polymers that was not previously known, the exact model that represent the outcome polymer theoretically will not be even in principle derivable from the theory that predicted its existence in the first place. (shrink)

In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. Carter contrasts functionalism with (...) reductive materialism, highlighting how the former accommodates the concept of artificial minds. He also emphasizes the significance of computationalism, which combines functionalism with computational theory to provide a robust explanation for mental processes. The book further discusses formal systems, the role of register machines in computation, and the inherent challenges in AI research, particularly in developing natural language processing systems. Carter’s work underscores the limitations of current computational models of cognition while remaining hopeful that advances in neuroscience may lead to stronger AI systems in the future. (shrink)

Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid.

his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor (...) is the main goal of this article. The statement is substantiated that the invention of mechanical computing devices, having a long history in the European engineering tradition, formed the prerequisites for the emergence of machine functionalism in the modern philosophy of mind. The idea of multiple implementation stems from the principle that a formal symbol system prescribes rules for the use of rational abstractions through the physical architecture of a computational engine. The article considers the reasons for the conceptual shift and reveals the semantic foundations for the metaphorical transfer of the properties of abstract objects from the theory of automata to the field of modern philosophy of mind. The criticism and ways of protecting the philosophical program of machine functionalism are analyzed by changing the content of the metaphor “Mind as machine”. The reasons for the stability of the information-computer approach in cognitive sciences are also disclosed and explained. (shrink)

Philosophical questions about minds and computation need to focus squarely on the mathematical theory of Turing machines (TM's). Surrogate TM's such as computers or formal systems lack abilities that make Turing machines promising candidates for possessors of minds. Computers are only universal Turing machines (UTM's)—a conspicuous but unrepresentative subclass of TM. Formal systems are only static TM's, which do not receive inputs from external sources. The theory of TM computation clearly exposes the failings of two prominent critiques, Searle's Chinese room (...) (1980) and arguments from Gödel's Incompleteness theorems (e.g., Lucas, 1961; Penrose, 1989), both of which fall short of addressing the complete TM model. Both UTM-computers and formal systems provide an unsound basis for debate. In particular, their special natures easily foster the misconception that computation entails intrinsically meaningless symbol manipulation. This common view is incorrect with respect to full-fledged TM's, which can process inputs non-formally, i.e., in a subjective and dynamically evolving fashion. To avoid a distorted understanding of the theory of computation, philosophical judgments and discussions should be grounded firmly upon the complete Turing machine model, the proper model for real computers. (shrink)

The continued development of General Circulation Models (GCMs) towards increasing resolution and complexity is a predominantly chosen strategy to advance climate science, resulting in channelling of research and funding to meet this aspiration. Yet many other modelling strategies have also been developed and can be used to understand past and present climates, to project future climates and ultimately to support decision-making. We argue that a plurality of climate modelling strategies and an equitable distribution of funding among them would be an (...) improvement on the current predominant strategy for informing policy making. To support our claim, we use a philosophy of science approach to compare increasing resolution and complexity of General Circulation Models with three alternate examples: the use of machine learning techniques, the physical climate storyline approach, and Earth System Models of Intermediate Complexity. We show that each of these strategies prioritises a particular set of methodological aims, among which are empirical agreement, realism, comprehensiveness, diversity of process representations, inclusion of the human dimension, reduction of computational expense, and intelligibility. Thus, each strategy may provide adequate information to support different specific kinds of research and decision questions. We conclude that, because climate decision-making consists of different kinds of questions, many modelling strategies are all potentially useful, and can be used in a complementary way. (shrink)

This paper concerns the Black Box. It is not the engineer’s black box that can be opened to reveal its mechanism, but rather one whose operations are inferred through input from (and output to) a companion observer. We are observers ourselves, and we attempt to understand minds through interactions with their host organisms. To this end, Ranulph Glanville followed W. Ross Ashby in elaborating the Black Box. The Black Box and its observer together form a system having different properties than (...) either component alone, making it a greater Black Box to any further-external observer. How far into this greater box can a further-external observer probe? The answer is crucial to understanding Black Boxes, and so an answer is offered here. It employs von Foerster’s machines, abstract entities having mechano-electrical bases, just like putative Black Boxes. Von Foerster follows Turing, Ashby, E. F. Moore, and G. H. Mealy in recognizing archetype machines that he calls trivial (predictable) and non-trivial (non-predictable). It is argued here that non-trivial machines are the only true Black Boxes. But non-trivial machines can be concatenated from trivial machines. Hence, the utter core of any greater Black Box (a non-trivial machine) may involve two (or more) White Boxes (trivial machines). This is how an unpredictable thing emerges from predictable parts. Interactions of White Boxes—of trivial machines—may be the ultimate source of the mind. Keywords: . (shrink)

This paper focuses on the research field of machine ethics and how it relates to a technological singularity—a hypothesized, futuristic event where artificial machines will have greater-than-human-level intelligence. One problem related to the singularity centers on the issue of whether human values and norms would survive such an event. To somehow ensure this, a number of artificial intelligence researchers have opted to focus on the development of artificial moral agents, which refers to machines capable of moral reasoning, judgment, and (...) decision-making. To date, different frameworks on how to arrive at these agents have been put forward. However, there seems to be no hard consensus as to which framework would likely yield a positive result. With the body of work that they have contributed in the study of moral agency, philosophers may contribute to the growing literature on artificial moral agency. While doing so, they could also think about how the said concept could affect other important philosophical concepts. (shrink)

"Data mining is not an invasion of privacy because access to data is only by machines, not by people": this is the argument that is investigated here. The current importance of this problem is developed in a case study of data mining in the USA for counterterrorism and other surveillance purposes. After a clarification of the relevant nature of privacy, it is argued that access by machines cannot warrant the access to further information, since the analysis will have to be (...) made either by humans or by machines that understand. It concludes that the current data mining violates the right to privacy and should be subject to the standard legal constraints for access to private information by people. (shrink)

In 1949, the Department of Philosophy at the University of Manchester organized a symposium “Mind and Machine” with Michael Polanyi, the mathematicians Alan Turing and Max Newman, the neurologists Geoff rey Jeff erson and J. Z. Young, and others as participants. Th is event is known among Turing scholars, because it laid the seed for Turing’s famous paper on “Computing Machinery and Intelligence”, but it is scarcely documented. Here, the transcript of this event, together with Polanyi’s original statement (...) and his notes taken at a lecture by Jeff erson, are edited and commented for the fi rst time. Th e originals are in the Regenstein Library of the University of Chicago. Th e introduction highlights elements of the debate that included neurophysiology, mathematics, the mind-body-machine problem, and consciousness and shows that Turing’s approach, as documented here, does not lend itself to reductionism. (shrink)

The purpose of this essay is to determine the domain of validity of the notions developed in Machine Ethics [ME]. To this aim, I analyse the epistemological and methodological presuppositions that lie at the root of such technological project. On this basis, I then try and develop the theoretical means to identify and deconstruct improper applications of these notions to objects that do not belong to the same epistemic context, focusing in particular on the extent to which ME is (...) supposed to feedback onto moral philosophy. By highlighting the inadequacy of many approaches to the supposed philosophical implications of ME, I wish to redirect attention to its actual scope and to stress its relevance for the social acceptance of autonomous technologies. The essay is structured as follows. After a brief introduction (§ 1), in § 2 I shed light upon the link between the current trend of robotic development toward greater degrees of autonomy and the corresponding need for artificial moral agents that fuels research in ME. I then present the epistemological profile of ME in § 3, focusing on its main component, i.e., the modelling of human moral agency in the language of robotics and computer science. In § 4 I deal with cases in which such model is brought to bear on human ethics and moral philosophy as well, whilst in § 5 I develop a criticism of this extension based on an account of the actual epistemological relations that obtain between philosophical and technological knowledge in the context of the ME project. In § 6 I discuss the role that the ordinary use of language plays in the process of extending machinerelated notions to other domains of knowledge and, finally, I clarify what the appropriate scope of machine ethics is notwithstanding its many utopian or dystopian misinterpretations. (shrink)

This paper is an expanded written version of my reply to Rosanna Keefe’s paper ‘Modelling higher-order vagueness: columns, borderlines and boundaries’ (Keefe 2015), which in turn is a reply to my paper ‘Columnar higher-order vagueness, or Vagueness is higher-order vagueness’ (Bobzien 2015). Both papers were presented at the Joint Session of the the Aristotelian Society and the Mind Association in July, 2015. At the Joint Session meeting, there was insufficient time to present all of my points in response to (...) Keefe’s paper. In addition, the audio of the session, which is available online, becomes inaudible at the beginning of my reply to Keefe’s comments due to a technical defect. The following is a full version of my remarks. (shrink)

The mind-body problem is one of the important topics in philosophy of mind and cognitive science. Following the analytical tradition of linguistic and logical analysis, we focus on two aspects of the mind- body problem: one is around Gödel's incompleteness theorem, and the other is on cognitive logic, especially on the question of whether Epistemological Arithmetic and machines are private. In the former case, in response to the popular view that the Gödel Incompleteness Theorem supports dualism in (...) the mind-body problem, H. Putnam constructs a counter-argument that defends the computationalist agenda: the equivalence of mind and Turing machine. In this regard, the paper discusses Putnam's line of analysis and then argues that it is unsound. In the latter case, the paper examines in detail the cognitive form of the expression of privateness and concludes, together with recent results in EA, that the existence of privateness in Turing machines is logically untenable and, therefore, we argue that the mind is not equivalent to a machine in terms of cognitive ability and privateness, i.e., the computationalist agenda is not valid. (shrink)

This special issue, which includes papers first presented at two workshops on ‘Memory, Mind, and Media’ in Sydney on November 29–30 and December 2–3, 2004, showcases some of the best interdisciplinary work in philosophy and psychology by memory researchers in Australasia (and by one expatriate Australian, Robert Wilson of the University of Alberta). The papers address memory in many contexts: in dance and under hypnosis, in social groups and with siblings, in early childhood and in the laboratory. Memory is (...) taken as a test case for evaluating the optimistic vision of a new kind of cognitive science defended by Andy Clark. Clark (2001:154) argues: Much of what matters about human intelligence is hidden not in the brain, nor in the technology, but in the complex and iterated interactions and collaborations between the two ... The study of these interaction spaces is not easy, and depends both on new multidisciplinary alliances and new forms of modelling and analysis. The pay-off, however, could be spectacular: nothing less than a new kind of cognitive scientific collaboration involving neuroscience, physiology, and social, cultural, and technological studies in about equal measure. So the central motivation is to investigate critically how well the case of memory would fit the extended mind’ thesis put forward by Clark and Chalmers (Clark and Chalmers 1998; Clark 1997, 2006)—according to which mental states and processes can spread across the.. (shrink)

The mental risk poses a high threat to the individuals, especially overseas demographic, including expatriates in comparison to the general Arab demographic. Since Arab countries are renowned for their multicultural environment with half of the population of students and faculties being international, this paper focuses on a comprehensive analysis of mental health problems such as depression, stress, anxiety, isolation, and other unfortunate conditions. The dataset is developed from a web-based survey. The detailed exploratory data analysis is conducted on the dataset (...) collected from Arab countries to study an individual’s mental health and indicative help-seeking pointers based on their responses to specific pre-defined questions in a multicultural society. The proposed model validates the claims mathematically and uses different machine learning classifiers to identify individuals who are either currently or previously diagnosed with depression or demonstrate unintentional “save our souls” (SOS) behaviors for an early prediction to prevent risks of danger in life going forward. The accuracy is measured by comparing with the classifiers using several visualization tools. This analysis provides the claims and authentic sources for further research in the multicultural public medical sector and decision-making rules by the government. (shrink)

The paper develops two related thought experiments exploring variations on an ‘animat’ theme. Animats are hybrid devices with both artificial and biological components. Traditionally, ‘components’ have been construed in concrete terms, as physical parts or constituent material structures. Many fascinating issues arise within this context of hybrid physical organization. However, within the context of functional/computational theories of mentality, demarcations based purely on material structure are unduly narrow. It is abstract functional structure which does the key work in characterizing the respective (...) ‘components’ of thinking systems, while the ‘stuff’ of material implementation is of secondary importance. Thus the paper extends the received animat paradigm, and investigates some intriguing consequences of expanding the conception of bio-machine hybrids to include abstract functional and semantic structure. In particular, the thought experiments consider cases of mind-machine merger where there is no physical Brain-Machine Interface: indeed, the material human body and brain have been removed from the picture altogether. The first experiment illustrates some intrinsic theoretical difficulties in attempting to replicate the human mind in an alternative material medium, while the second reveals some deep conceptual problems in attempting to create a form of truly Artificial General Intelligence. (shrink)

Conceptual modeling of a portion of the world is a necessary prerequisite to set the stage and define software system boundaries. In this context, one of the challenges is to provide a unified framework to create a comprehensive representation of the targeted domain. According to many researchers, conceptual model (CM) development is a hard task, and system requirements are difficult to collect, causing many miscommunication problems. Accordingly, CMs require more than modeling ability alone: they first require an understanding (...) of the targeted domain that the model attempts to represent. Accordingly, a preconceptual modeling (pre-CM) stage is intended to address ontological issues before typical CM development is initiated. It involves defining a portion of reality when entities and processes are differentiated and integrated as unified wholes. This pre-CM phase forms the focus of research in this paper. The purpose is not show how to model; rather, it is to demonstrate how to establish a metaphysical basis of the involved portion of reality. To demonstrate such a venture, we employ the so-called thinging machine (TM) modeling that has been proposed as a high-level CM. A TM model integrates staticity and dynamism grounded in a fundamental construct called a thimac (things/machine). It involves two modes of reality, existence (events) and subsistence (regions: roughly, specifications of things and processes). Currently, the dominant approach in CM has evolved to limit its scope of application to develop ontological categorization (types of things). In contrast, advocates of TM modeling have pursued a broader metaphysical study of the nature of the domain’s things and processes beyond categorization. In the TM approach, pre-CM metaphysics is viewed as a part and parcel of CM itself. The general research problem is how to map TM constructs to what is out there in the targeted domain. Discussions involve the nature of thimacs (things and processes) and subsistence and existence as they are superimposed over each other in reality. Specifically, we make two claims, (i) the perceptibility of regions as a phenomenon and (ii) the distinctiveness of existence as a construct for events. The results contribute to further the understanding of TM modeling in addition to introducing some metaphysical insights. (shrink)

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.

Scientists and philosophers alike debate whether various systems such as plants and bacteria exercise cognition. One strategy for resolving such debates is to ground claims about nonhuman cognition in evidence from mathematical models of cognitive capacities. In this article, I show that proponents of this strategy face two major challenges: demarcating phenomenological models from process models and overcoming underdetermination by model fit. I argue that even if the demarcation problem is resolved, fitting a process model to behavioral data is, on (...) its own, not strong evidence for any cognitive process, let alone processes shared with humans. (shrink)

Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching (...) 97.23%. The model's success is attributed to its ability to effectively leverage attributes related to eating habits, physical condition, and demographic factors. Feature importance analysis reveals key factors contributing to accurate predictions. This paper contributes to the field of health analytics by demonstrating the effectiveness of Random Forest in predicting and categorizing health risks. The insights gained from this research have the potential to inform personalized health interventions and contribute to the advancement of precision health strategies. Furthermore, the study highlights the importance of leveraging machine learning techniques for health risk assessment in diverse populations. (shrink)

The scope of Platonism is extended by introducing the concept of a “Platonic computer” which is incorporated in metacomputics. The theoretical framework of metacomputics postulates that a Platonic computer exists in the realm of Forms and is made by, of, with, and from metaconsciousness. Metaconsciousness is defined as the “power to conceive, to perceive, and to be self-aware” and is the formless, con-tentless infinite potentiality. Metacomputics models how metaconsciousness generates the perceived actualities including abstract entities and physical and nonphysical realities. (...) It is postulated that this is achieved via digital computation using the Platonic computer. The introduction of a Platonic computer into the realm of Forms thus bridges the “inverse explanatory gap” and therefore solves the “inverse hard problem of consciousness” in the philosophy of mind. (shrink)

This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst (...) models of mind. The last developments in the field of deep learning gave rich empirical material for cognitive sciences. Multilayered networks, mathematical models of associative dynamics of learning, self-organizing neuronets and all that allow to explain the principles of human conceptual organizing and after this to emulate these processes in computer systems. At all engineering achievements of this technology there is a traditional criticism from representatives of cognitive psychology who cannot accept a thesis about learning ability of a neuronet on the basis of redistribution of scales. Process of learning of natural intelligence, according to cognitive models, happens due to attraction of knowledge broadcast in a symbolical form (mental representations, concepts) at the expense of the systems of output knowledge expressed in the propositional contents. Some philosophical aspects of «neural metaphor» in modern cognitive sciences create the problem field which demands comprehensive understanding, the first step towards which is taken in this work. (shrink)

This Essay discusses whether U.S. law is ready for artificial intelligence (“AI”) which is headed down the road of blurring the line between human and machine minds. Perhaps the most high-profile and recent examples of AI are Large Language Models (“LLMs”) such as ChatGPT and Google Gemini that can generate written text, reason and analyze in a manner that seems to mimic human capabilities. U.S. law is based on English common law, which in turn incorporates Christian principles that assume (...) the dominance and uniqueness of humankind. U.S. law assumes human communication skills are accompanied by attributes such as consciousness and Free Will (“FW”) that, in turn, underpin critical legal concepts such as mens rea – i.e., intent. Philosophers and others generally agree that consciousness is necessary for FW. On the assumption that human beings possess consciousness that supports FW, the law thereafter deems human beings capable of acting with legal consequences, from entering into contracts to committing crimes. With a focus on LLMs, the Essay suggests that U.S. law may struggle to respond to AI because the technology disrupts the law’s assumptions regarding the uniqueness of human traits and abilities such as consciousness, FW, written communications and reasoning. (shrink)

Given the personal acquaintance between Alan M. Turing and W. Ross Ashby and the partial proximity of their research fields, a comparative view of Turing’s and Ashby’s work on modelling “the action of the brain” (letter from Turing to Ashby, 1946) will help to shed light on the seemingly strict symbolic/embodied dichotomy: While it is clear that Turing was committed to formal, computational and Ashby to material, analogue methods of modelling, there is no straightforward mapping of these approaches onto symbol-based (...) AI and embodiment-centered views respectively. Instead, it will be demonstrated that both approaches, starting from a formal core, were at least partly concerned with biological and embodied phenomena, albeit in revealingly distinct ways. (shrink)

Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.

Review of: Margaret A. Boden, Mind as Machine: A History of Cognitive Science, 2 vols, Oxford: Oxford University Press, 2006, xlvii+1631, cloth $225, ISBN 0-19-924144-9. - Mind as Machine is Margaret Boden’s opus magnum. For one thing, it comes in two massive volumes of nearly 1700 pages, ... But it is not just the opus magnum in simple terms of size, but also a truly crowning achievement of half a century’s career in cognitive science.

The mind-body problem is intuitively familiar, as mental and physical entities mysteriously interact. However, difficulties arise when intertwining concepts of the self with mental and physical traits. To avoid confusion, I propose instead focusing on three categories, with the mental matching the mind and physical the body with respect to raw inputs and outputs. The third category, the self, will experience and measure the others. With this new classification, we can see difficulties clearly, specifically five questions covering interaction (...) and correlation. We break down the problem using both existing theories and a hypercube topology representing the solution. We show any satisfactory theory must explain both spatial interaction and content correlation, and that we cannot escape our topology, whatever our preferred fundamental substance and mind-body movement permutation. We conclude by looking outside the hypercube, noting how solutions such as existential monism, priority monism, and will-based cosmic-idealism avoid the dangers involved. (shrink)

Intellectualists about knowledge how argue that knowing how to do something is knowing the content of a proposition (i.e, a fact). An important component of this view is the idea that propositional knowledge is translated into behavior when it is presented to the mind in a peculiarly practical way. Until recently, however, intellectualists have not said much about what it means for propositional knowledge to be entertained under thought's practical guise. Carlotta Pavese fills this gap in the intellectualist view (...) by modeling practical modes of thought after Fregean senses. In this paper, I take up her model and the presuppositions it is built upon, arguing that her view of practical thought is not positioned to account for much of what human agents are able to do. (shrink)