This paper develops a new structural psychology, and therein proposes a specific model for the scientific study of consciousness. The presented model uses Earth's geologic history of mass-extinction & recovery (evolutionary dynamics) in determining humanity’s adaptive response (conscious and non-conscious traits). It argues humanity adaptively mirrors Earth’s basic evolutionary dynamics, in a “mythologizing of natural adversity” as foundation for all human knowledge – a process that continues well into the modern era. The intellectual lineage used to develop this model (...) includes: • Evolutionary biology offers a context for this study – answering Chalmers’ “hard question,” • Paleoanthropology defines the circumstance of human emergence from Gaia, • Environmental forces on neurophysiology derive an ambiguous but instructive narrative logic (mythic sensibility), • Psychology tracks humanity’s shift from animal-self to modern creative-self, using work of Hegel > Freud > Jung > Rank > Joseph Campbell > Arnold Mindell as a new structural psychology, • Fractal geometry offers a holographic design for modeling consciousness, • Memetics presents a tool for measuring conscious traits, in a variation of the Hall-Tonna values inventory, • Finally, Structured Opportunistic Thinking, a hybrid of NTL’s T-group, and Pierce’s Power Equity Group Theory, suggests a developmental methodology. This work presents a “general hypothesizing model” of human consciousness, in attempting a science of consciousness. (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)

When game theory was introduced to biology, the components of classic game theory models were replaced with elements more befitting evolutionary phenomena. The actions of intelligent agents are replaced by phenotypic traits; utility is replaced by fitness; rational deliberation is replaced by natural selection. In this paper, I argue that this classic conception of comprehensive reapplication is misleading, for it overemphasizes the discontinuity between human behavior and evolved traits. Explicitly considering the representational roles of evolutionary game theory brings (...) to attention neglected areas of overlap, as well as a range of evolutionary possibilities that are often overlooked. The clarifications this analysis provides are well-illustrated by—and particularly valuable for—game theoretic treatments of the evolution of social behavior. (shrink)

We develop an approach to the problem of de se belief usually expressed with the question, what does the shopper with the leaky sugar bag have to learn to know that s/he is the one making the mess. Where one might have thought that some special kind of “de se” belief explains the triggering of action, we maintain that this gets the order of explanation wrong. We sketch a very simple cognitive architecture that yields de se-like behavior on which (...) the action-triggering functionality of the belief-state is what counts it as de se rather than some prior property of being “de se” explaining the triggering of action. This functionality shows that action-triggering change in belief-state also undergirds a correlative change in the objective involved in the triggered action. This model is far too simple to have any claim to showing how the de se works for humans, but it shows, by illustration, that nothing mysteriously “subjective”” need be involved in this aspect of self-conception. While our exposition is very different from those of Perry and Recanati, all three of us are developing the same kind of view. (shrink)

Aesthetics is thought of as not only a theory of art or beauty, but also includes sensibility, experience, judgment, and relationships. This paper is a study of Bernard Stiegler’s notion of Aesthetic War (stasis) and symbolic misery. Symbolic violence is ensued through a loss of individuation and participation in the creation of symbols. As a struggle between market values against spirit values human life and consciousness within neoliberal hyperindustrial society has become calculable, which prevents people from creating affective and (...) meaningful attachments to symbols in relation to our retentional apparatuses, technology and memory. Such tension can be thought of as a dissonance between overlapping domains of social life, private and public. New Media is a reflection of aesthetic dissonance, an experience such as being bored and entertained at the same time, between antagonistic experiences, values, and behavior. Moreover, new media is at once a medium of customizing aesthetic experience individually as well as the threat and practice of prioritizing calculability and modeling of consumer behavior in favor of capitalistic effectiveness, which results in the simultaneous categorization of an individual as a data point, putting those who do not fit an algorithm’s premises at a disadvantage. (shrink)

When comparing alternative courses of action, modern military decision makers often must consider both the military effectiveness and the ethical consequences of the available alternatives. The basis, design, calibration, and performance of a principles-based computational model of ethical considerations in military decision making are reported in this article. The relative ethical violation (REV) model comparatively evaluates alternative military actions based upon the degree to which they violate contextually relevant ethical principles. It is based on a set of specific ethical principles (...) deemed by philosophers and ethicists to be relevant to military courses of action. A survey of expert and non-expert human decision makers regarding the relative ethical violation of alternative actions for a set of specially designed calibration scenarios was conducted to collect data that was used to calibrate the REV model. Perhaps unsurprisingly, the survey showed that people, even experts, disagreed greatly amongst themselves regarding the scenarios’ ethical considerations. Despite this disagreement, two significant results emerged. First, after calibration the REV model performed very well in terms of replicating the ethical assessments of human experts for the calibration scenarios. The REV model outperformed an earlier model that was based on tangible consequences rather than ethical principles, that earlier model performed comparably to human experts, the experts outperformed human non-experts, and the non-experts outperformed random selection of actions. All of these performance comparisons were measured quantitatively and confirmed with suitable statistical tests. Second, although humans tended to value some principles over others, none of the ethical principles involved—even the principle of not harming civilians—completely overshadowed all of the other principles. (shrink)

In the late summer of 1998, the authors, a cognitive scientist and a logician, started talking about the relevance of modern mathematical logic to the study of human reasoning, and we have been talking ever since. This book is an interim report of that conversation. It argues that results such as those on the Wason selection task, purportedly showing the irrelevance of formal logic to actual human reasoning, have been widely misinterpreted, mainly because the picture of logic current (...) in psychology and cognitive science is completely mistaken. We aim to give the reader a more accurate picture of mathematical logic and, in doing so, hope to show that logic, properly conceived, is still a very helpful tool in cognitive science. The main thrust of the book is therefore constructive. We give a number of examples in which logical theorizing helps in understanding and modeling observed behavior in reasoning tasks, deviations of that behavior in a psychiatric disorder (autism), and even the roots of that behavior in the evolution of the brain. (shrink)

(THIS PAPER NEEDS A CORRECTION) Satisfaction is a complex concept which has a key role in each individual’s everyday life and impacts their behavior. Abraham Maslow (1943) suggested a framework [1] to study human motivation, which was a starting point towards developing the quality of life(QOL) theory. On that article, he described a hierarchy of human needs, that is generally consist of fundamental needs which are required for human survival, and environment dependent ones, like society, safety (...) and etc. In this study, we are trying to represent a tangible mathematical model for assessing the sense of need for water in terms of the available source of water. On this very subject, M. Joseph Sirgy [2] states that ”From a human developmental perspective, QOL goals can be defined as satisfaction of human developmental needs in a community or society”. Accordingly, in the first section we propose a model for the water needs of an individual. In the second section, we continue the discussion by checking the behavior of the model on a given population, and each time by assuming that we have two out of three involved factors, we try to suggest an estimation for the other one. (shrink)

The behavior/structure methodological dichotomy as locus of scientific inquiry is closely related to the issue of modeling and theory change in scientific explanation. Given that the traditional tension between structure and behavior in scientific modeling is likely here to stay, considering the relevant precedents in the history of ideas could help us better understand this theoretical struggle. This better understanding might open up unforeseen possibilities and new instantiations, particularly in what concerns the proposed technological modification of (...) the human condition. The sequential structure of this paper is twofold. The contribution of three philosophers better known in the humanities than in the study of science proper are laid out. The key theoretical notions interweaving the whole narrative are those of mechanization, constructability and simulation. They shall provide the conceptual bridge between these classical thinkers and the following section. Here, a panoramic view of three significant experimental approaches in contemporary scientific research is displayed, suggesting that their undisclosed ontological premises have deep roots in the Western tradition of the humanities. This ontological lock between core humanist ideals and late research in biology and nanoscience is ultimately suggested as responsible for pervasively altering what is canonically understood as “human”. (shrink)

This book constitutes refereed proceedings of the COST 2102 International Training School on Cognitive Behavioural Systems held in Dresden, Germany, in February 2011. The 39 revised full papers presented were carefully reviewed and selected from various submissions. The volume presents new and original research results in the field of human-machine interaction inspired by cognitive behavioural human-human interaction features. The themes covered are on cognitive and computational social information processing, emotional and social believable Human-Computer Interaction (HCI) systems, (...) behavioural and contextual analysis of interaction, embodiment, perception, linguistics, semantics and sentiment analysis in dialogues and interactions, algorithmic and computational issues for the automatic recognition and synthesis of emotional states. (shrink)

Students during the distance education were experiencing solitude and depression in their studies due to no social interaction which led to psychological suffering. In this article, college students' attitudes toward statistics learning were investigated, and its predictors by statistical modeling. Secondary data was extracted from a current study from the literature, summarized using descriptive statistics, and presented in tabular form. As for modeling the predictors of students' attitudes in learning statistics, it was done through multiple linear regression via (...) the ordinary least square (OLS) approach. The finding of statistical calculations revealed that, on average, students possess a "neutral attitude" towards learning statistics online. This suggests that students do not show active involvement and positive engagement in the classroom environment due to some challenges they have encountered during online learning. The regression model I revealed that students who are using mobile phones, fewer study hours in statistics, and intimate relationships with teachers are the significant factors of positive attitude in learning. On the other hand, regression model II showed that low internet signal and low mental health are significant determinants of positive behavior in learning statistics online. Conclusively, students who have suitable gadgets for online learning and with good vibes with their teachers have good performance in class even if they study less, however, effective. Moreover, students with less distraction on social media and with mental stress, tend to deviate their attention in studying their lessons in statistics which positively increases their learning attitude and well-being. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive (...) to a highly proactive, data-driven function. (shrink)

In philosophy of language, a distinction has been proposed between two aspects of lexical competence, i.e. referential and inferential competence (Marconi 1997). The former accounts for the relationship of words to the world, the latter for the relationship of words among themselves. The distinction may simply be a classification of patterns of behaviour involved in ordinary use of the lexicon. Recent research in neuropsychology and neuroscience, however, suggests that the distinction might be neurally implemented, i.e., that different cognitive architectures with (...) partly distinct neural realizations might be responsible for cognitive performances involving inferential and referential aspects of semantics. This hypothesis is strongly consistent with patient data supporting the notion of a functional double dissociation between inferential and referential abilities, and with a set of direct cortical mapping studies and neuroimaging experiments suggesting that inferential and referential abilities are underpinned by at least partly different regions of the human brain (e.g., Marconi et al. 2013; review in Calzavarini 2017). The initial hypotheses formulated in the setting of the philosophy of language, along with the neuropsychological experimental evidence (about how referential and inferential competences may be neurally instantiated) can be the input to computational modelling activities involving the inferential and the referential aspects of lexical competence. The aim of the talk is to offer a critical discussion of the kind of formalisms that can be used to model the two aspects of lexical competence, and of the main difficulties related to the use of these computational techniques. -/- Inferential (=symbolic) vs referential (=connectionist) formalisms. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive (...) to a highly proactive, data-driven function. (shrink)

Universal social institutions, such as marriage, commons management and property, have emerged independently in radically different cultures. This requires explanation. As Boyer and Petersen point out ‘in a purely localist framework would have to constitute massively improbable coincidences’ . According to Boyer and Petersen, those institutions emerged naturally out of genetically wired behavioural dispositions, such as marriage out of mating strategies and borders out of territorial behaviour. While I agree with Boyer and Petersen that ‘unnatural’ institutions cannot thrive, this one-sided (...) explanation of universal social institutions in terms of genetic human nature is unsatisfactory. Drawing on the literature on multi-level selection and gene-culture coevolution, I argue that universal social institutions are first and foremost the products of cultural selection. They occupy fitness peaks in the landscape of cultural possibilities, much in the same way that biological adaptations occupy fitness peaks in the landscape of biological possibilities. To show this, I use game-theory. By modelling the domains of social interaction in which marriage, commons management, and property emerged as Prisoner’s dilemma situations, it becomes clear how an institutional framework allows the group to move to an interactive equilibrium with a larger payoff. Institutions do so by incentivising all parties to adopt a cooperative strategy. They are culturally selected ways of optimising genetically constrained domains of human social interaction. (shrink)

This paper commences from the critical observation that the Turing Test (TT) might not be best read as providing a definition or a genuine test of intelligence by proxy of a simulation of conversational behaviour. Firstly, the idea of a machine producing likenesses of this kind served a different purpose in Turing, namely providing a demonstrative simulation to elucidate the force and scope of his computational method, whose primary theoretical import lies within the realm of mathematics rather than cognitive modelling. (...) Secondly, it is argued that a certain bias in Turing’s computational reasoning towards formalism and methodological individualism contributed to systematically unwarranted interpretations of the role of the TT as a simulation of cognitive processes. On the basis of the conceptual distinction in biology between structural homology vs. functional analogy, a view towards alternate versions of the TT is presented that could function as investigative simulations into the emergence of communicative patterns oriented towards shared goals. Unlike the original TT, the purpose of these alternate versions would be co-ordinative rather than deceptive. On this level, genuine functional analogies between human and machine behaviour could arise in quasi-evolutionary fashion. (shrink)

Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) (...) model used in prior work. We consider a game of iterated interactions where an agent cooperates based on its opinion about an opponent. Our model also includes the concept of domain-based self-doubt, which varies as the interaction succeeds or not. An increase in doubt makes an agent reduce its egocentricity in subsequent interactions, thus enabling the agent to learn reactively. The agent system is modeled with factions not having a single leader, to overcome some of the issues associated with leader-follower factions. We find that agents belonging to factions perform better than individual agents. We observe that an intermediate level of egocentricity helps the agent perform at its best, which concurs with conventional wisdom that neither overconfidence nor low self-esteem brings benefits. (shrink)

Marine conservation extends beyond the preservation of our oceans and coastlines; it entails understanding human behavior and attitudes toward environmental protection. A recent study sheds light on the significance of considering both knowledge and emotion when examining stakeholders’ attitudes and behaviors regarding environmental issues, particularly marine protection.

Evolution and Human Behavior: Darwinian Perspectives on Human Nature John CartwrightCambridge, MA: MIT Press, 2008448 pages, ISBN: 0262533049 (pbk); $36.00John Cartwright's book provides a valuable...

If the concept of “free will” is reduced to that of “choice” all physical world shares the latter quality. Anyway the “free will” can be distinguished from the “choice”: The “free will” involves implicitly a certain goal, and the choice is only the mean, by which the aim can be achieved or not by the one who determines the target. Thus, for example, an electron has always a choice but not free will unlike a human possessing both. Consequently, and (...) paradoxically, the determinism of classical physics is more subjective and more anthropomorphic than the indeterminism of quantum mechanics for the former presupposes certain deterministic goal implicitly following the model of human freewill behavior. Quantum mechanics introduces the choice in the fundament of physical world involving a generalized case of choice, which can be called “subjectless”: There is certain choice, which originates from the transition of the future into the past. Thus that kind of choice is shared of all existing and does not need any subject: It can be considered as a low of nature. There are a few theorems in quantum mechanics directly relevant to the topic: two of them are called “free will theorems” by their authors (Conway and Kochen 2006; 2009). Any quantum system either a human or an electron or whatever else has always a choice: Its behavior is not predetermined by its past. This is a physical law. It implies that a form of information, the quantum information underlies all existing for the unit of the quantity of information is an elementary choice: either a bit or a quantum bit (qubit). (shrink)

The objective of this research is to empirically test a research model on the effect of consumer economic nationalism on consumers’ attitudinal and behavioral responses to the marketing of locally produced foods. Data was collected from a sample of Ghanaians through an online survey using a structured questionnaire. Using structural equation modelling to analyse the data, the study revealed that cognitive and affective involvement influences product familiarity. Also, product familiarity and economic nationalism influence consumers ‘overall attitude towards locally produced foods. (...) Finally, the overall attitude towards the product and economic nationalism both influence consumer buying intention of locally produced foods. This study was limited to the Ghanaian geographical context, thus, for a broader assessment of the robustness of the research model, future studies should undertake a cross-national comparison. The findings provide practitioners with the strategies for influencing consumer attitudes and intentions towards locally produced foods. For policymakers, the findings provide input on strategies for altering consumers’ attitudes and intentions to patronize locally produced foods. Considering the paucity of research in understanding the role of economic nationalism in influencing consumer attitude and intention towards locally produced foods, this study makes a compelling contribution to the literature by incorporating the economic nationalism theory into the theory of planned behavior. (shrink)

When explaining human actions, people usually focus on a small subset of potential causes. What leads us to prefer certain explanations for valenced actions over others? The present studies indicate that our moral attitudes often predict our explanatory preferences far better than our beliefs about how causally sensitive actions are to features of the actor's environment. Study 1 found that high-prejudice participants were much more likely to endorse non-agential explanations of an erotic same-sex encounter, such as that one of (...) the men endured a stressful event earlier that day. Study 2 manipulated participants' beliefs about how the agent's behavior depended on features of his environment, finding that such beliefs played no clear role in modeling participants' explanatory preferences. This result emerged both with low- and high-prejudice, US and Indian participants, suggesting that these findings probably reflect a species-typical feature of human psychology. Study 3 found that moral attitudes also predicted explanations for a woman's decision to abort her pregnancy (3a) and a person's decision to convert to Islam (3b). Study 4 found that luck in an action's etiology tends to undermine perceptions of blame more readily than perceptions of praise. Finally, Study 5 found that when explaining support for a rival ideology, both Liberals and Conservatives downplay agential causes while emphasizing environmental ones. Taken together, these studies indicate that our explanatory preferences often reflect a powerful tendency to represent agents as possessing virtuous true selves. Consequently, situation-focused explanations often appear salient because people resist attributing negatively valenced actions to the true self. There is a person/situation distinction, but it is normative. (shrink)

I am very used to strange books and special people but Hawkins stands out due to his use of a simple technique for testing muscle tension as a key to the “truth” of any kind of statement whatsoever—i.e., not just to whether the person being tested believes it, but whether it is really true! What is well known is that people will show automatic, unconscious physiological and psychological responses to just about anything they are exposed to—images, sounds, touch, odors, ideas, (...) people. So muscle reading to find out their true feelings is not radical at all, unlike using it as a dousing stick (more muscle reading) to do “paranormal science”. Hawkins describes the use of decreasing tension in the muscles of an arm in response to increases in cognitive load thus causing the arm to drop in response to the constant pressure of someone’s fingers. He seems unaware that there is a long established and vast ongoing research effort in social psychology referred to by such phrases as ‘implicit cognition’, ‘automaticity’ etc., and that his use of ‘kinesiology’ is one tiny section. In addition to muscle tone (infrequently used) social psychologists measure EEG, galvanic skin response and most frequently verbal responses to words, sentences, images or situations at times varying from seconds to months after the stimulus. Many, such as Bargh and Wegner, take the results to mean we are automatons who learn and act largely without awareness via S1 and many others such as Kihlstrom and Shanks say these studies are flawed and we are creatures of S2. Though Hawkins seems to have no idea, as in other areas of the descriptive psychology of higher order thought, the situation regarding “automaticity” is still as chaotic as it was when Wittgenstein described the reasons for the sterility and barrenness of psychology in the 30’s. Nevertheless, this book is an easy read and some therapists and spiritual teachers may find it of use. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my article The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in Wittgenstein and Searle 59p(2016). For all my articles on Wittgenstein and Searle see my e-book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Wittgenstein and Searle 367p (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). -/- All of my papers and books have now been published in revised versions both in ebooks and in printed books. -/- Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) Amazon ASIN # B071HVC7YP. -/- The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) Amazon ASIN # B071P1RP1B. -/- Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) Amazon ASIN # B0711R5LGX . (shrink)

In psychology, stress is a feeling of emotional strain and pressure. Stress is a type of psychological pain. Small amounts of stress may be beneficial, as it can improve athletic performance, motivation and reaction to the environment. Excessive amounts of stress, however, can increase the risk of strokes, heart attacks, ulcers, and mental illnesses such as depression and also aggravation of a pre-existing condition. Psychological stress can be external and related to the environment but may also be caused by internal (...) perceptions that cause an individual to experience anxiety or other negative emotions surrounding a situation, such as pressure, discomfort, etc., which they then deem stressful. (shrink)

English is spoken all around the world as it is chosen as the second language to speak within most of the countries. However, from the ancient history of the British to come into this South Asian region, the entrance of English as a speaking language happened. Though, after some centuries, the British went out of the mainland of India, it remains the second-largest spoken language there. Here comes another fact; many words in Standard English changed its form. So, this made (...) the dialects as much as changed that many ones refer to English in India as Indian English. In this present time, though, there are hundreds of languages chosen to speak Indian English that differ in many ways. The characters playing English roles also have a dialect changing of English in somewhat ways. Though the grammars and principal terms of English are still the same for Indian English, deviations came across the spoken language in many attributes. This paper identifies the entrance of English in India, the deviation of dialect change in Indian English with examples of characters still making way to English (Both British and Hollywood) movies with the dialects of Indian English many ways. The paper studies those ways and deviations of words in English in India that they use and call it Indian English. (shrink)

Three qualities of “The Argument from Human Behavior” make it superior to other arguments for God. First, this argument discovers a universal indirect perception of God that everyone has many times every day: the fact that we all take seriously our sense of “wrong” (our sense of everyone’s moral obligations). Second, this argument reveals that the Biblical God claims He is the legislator of the moral laws in our mind. Third, it understands that discovering God will always demand (...) a step of faith, making an objective proof of God unattainable. However, the fact that we all have indirect perceptions of God produces the extreme probability, and possibly the inductive certainty: God exists. -/- Only God is able to enforce our inborn normative value of "wrong" and thereby keep it from being an unenforced absurdity. Since no one acts as if his or her sense of "wrong" is an absurdity, everyone behaves as if God exists. -/- This book also reveals that if the Biblical God exists, a slam-dunk rationale for His existence also must exist! No one will protest God’s judgment by saying that it was impossible to achieve the certainty that God exists. -/- Further, it contains innovative analyses of the major objections to God, including the Problem of Evil, Objective Morality, Euthyphro's Dilemma and the Philosophy of Science. (shrink)

The word semantics, in robotics and AI, has no canonical definition. It usually serves to denote additional data provided to autonomous agents to aid HRI. Most researchers seem, implicitly, to understand that such data cannot simply be extracted from environmental data. I try to make explicit why this is so and argue that so-called semantics are best understood as data comprised of conventions of human behaviour. This includes labels, most obviously, but also places, ontologies, and affordances. Object affordances are (...) especially problematic because they require not only semantics that are not in the environmental data (conventions of object use) but also an understanding of physics and object combinations that would, if achieved, constitute artificial superintelligence. (shrink)

This paper explores the relation between natural modality and our modelling practices. It will be argued that some modelling practices such as abstraction and idealization should be understood as presupposing empirical claims about objective modal features of the behavior of target systems. To establish the connection between natural modality on the one hand and modelling practices on the other an analysis of natural modality in terms of empirically accessible invariance relations will be provided.

It is my contention that the table of intentionality (rationality, mind, thought, language, personality etc.) that features prominently here describes more or less accurately, or at least serves as an heuristic for, how we think and behave, and so it encompasses not merely philosophy and psychology, but everything else (history, literature, mathematics, politics etc.). Note especially that intentionality and rationality as I (along with Searle, Wittgenstein and others) view it, includes both conscious deliberative linguistic System 2 and unconscious automated prelinguistic (...) System 1 actions or reflexes. -/- I provide a critical survey of some of the major findings of two of the most eminent students of behavior of modern times, Ludwig Wittgenstein and John Searle, on the logical structure of intentionality (mind, language, behavior), taking as my starting point Wittgenstein’s fundamental discovery –that all truly ‘philosophical’ problems are the same—confusions about how to use language in a particular context, and so all solutions are the same—looking at how language can be used in the context at issue so that its truth conditions (Conditions of Satisfaction or COS) are clear. The basic problem is that one can say anything but one cannot mean (state clear COS for) any arbitrary utterance and meaning is only possible in a very specific context. I analyze various writings by and about them from the modern perspective of the two systems of thought (popularized as ‘thinking fast, thinking slow’), employing a new table of intentionality and new dual systems nomenclature. I show that this is a powerful heuristic for describing behavior. -/- Thus, all behavior is intimately connected if one takes the correct viewpoint. The Phenomenological Illusion (oblivion to our automated System 1) is universal and extends not merely throughout philosophy but throughout life. I am sure that Chomsky, Obama, Zuckerberg and the Pope would be incredulous if told that they suffer from the same problem as Hegel, Husserl and Heidegger, (or that that they differ only in degree from drug and sex addicts in being motivated by stimulation of their frontal cortices by the delivery of dopamine (and over 100 other chemicals) via the ventral tegmentum and the nucleus accumbens), but it’s clearly true. While the phenomenologists only wasted a lot of people’s time, they are wasting the earth and their descendant’s future. (shrink)

Economic models describe individuals in terms of underlying characteristics, such as taste for some good, sympathy level for another player, time discount rate, risk attitude, and so on. In real life, such characteristics change through experiences: taste for Mozart changes through listening to it, sympathy for another player through observing his moves, and so on. Models typically ignore change, not just for simplicity but also because it is unclear how to incorporate change. I introduce a general axiomatic framework for defining, (...) analysing and comparing rival models of change. I show that seemingly basic postulates on modelling change together have strong implications, like irrelevance of the order in which someone has his experiences and ‘linearity’ of change. This is a step towards placing the modelling of change on solid axiomatic grounds and enabling non-arbitrary incorporation of change into economic models. (shrink)

What is the connection between modelling thought and modelling the brain? In a model (as understood here), we strip away from the modelled system some non-essential features and retain some essential ones. What are the essential features of thought that are to be re- tained in the model, and conversely, what are its inessential features, that may be stripped away in the model? According to a prevalent view in contemporary science and philoso- phy, thought is a computation, and therefore its (...) essential features are its computational features. A necessary part of the computational view of thought is the idea that the same computation can be realised by, or implemented in, physically heterogeneous systems, an idea known as “Multiple Realizability” of the computational features or properties by the physical ones. I will describe why the very idea of Multiple Realizability, especially in the case of mental computation, entails mind-body dualism, and explore some implications of this conclusion concerning the question of which are the essential features of thought to be retained in modeling it. (shrink)

Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building of (...) simulative machine models before the advent of cybernetics are been investigated for the first time, on the basis of little known, and sometimes completely forgotten or unpublished, texts and figures. These pre-cybernetics projects can be considered as steps toward the “discovery” of a modelling methodology that has been fully developed by those more recent research programs, and that shares some of their central goals and key methodological proposals. -/- More info in Springer link: http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-1-4020-0606-7 -/- This book is the English translation of La scoperta dell'artificiale, Dunod/Masson, Milan, 1998. (shrink)

Examining AI spirituality can illuminate problematic assumptions about human spirituality and AI cognition, suggest possible directions for AI development, reduce uncertainty about future AI, and yield a methodological lens sufficient to investigate human-AI sociotechnical interaction and morality. Incompatible philosophical assumptions about human spirituality and AI limit investigations of both and suggest a vast gulf between them. An emergentist approach can replace dualist assumptions about human spirituality and identify emergent behavior in AI computation to overcome overly (...) reductionist assumptions about computation. Using general systems theory to organize models of human experience yields insight into human morality and spirituality, upon which AI modeling can also draw. In this context, the pragmatist Josiah Royce’s semiotic philosophy of spirituality identifies unanticipated overlap between symbolic AI and spirituality and suggests criteria for a human-AI community focused on modeling morality that would result in an emergent Interpreter-Spirit sufficient to influence the ongoing development of human and AI morality and spirituality. (shrink)

The use of evolutionary game theory to explain the evolution of human norms and the behavior of humans who act according to those norms is widespread. Both the aims and motivation for its use are clearly articulated by Harms and Skyrms (2008) in the following passage: "A good theory of evolution of norms might start by explaining the evolution of altruism in Prisoner’s Dilemma, of Stag Hunting, and of the equal split in the symmetric bargaining game. These are (...) not well-explained by classical game theory based on rational choice. From a technical point of view, they present different theoretical challenges. In the bargaining game, there are an infinite number of equilibria with no principled (rational choice) way to select the cooperative one. In Stag Hunt there are only two, but the non-cooperative one is selected by risk-dominance. In Prisoner’s Dilemma the state of mutual cooperation is not a Nash equilibrium at all, and cooperation flies in the face of the rational-choice principle that one does not choose less rather than more. In contrast to rational choice theory, the most common tool of evolutionary game theory is the replicator dynamics, in which the propagation rate of each strategy is determined by its current payoffs. These dynamics have a rationale in both biological and cultural evolutionary modeling, and sometimes tell us things that rational choice theory does not." We agree with the first sentence in this quotation: a good theory about the behavior under norms ought to explain altruism in the Prisoner’s Dilemma (PD), playing Stag in Stag Hunt (SH), and offering equal splits in the symmetric Nash bargaining game (NB). We also agree with Harms and Skyrms about the difference in technical challenges each of these games poses. Finding a single mechanism, even one as broadly understood as evolution, that could solve these challenges en masse is no doubt a tall order. Nonetheless, in this paper, we present a single, simple, modification to SH, NB, and a general n-player PD that does just that: we introduce deontological autonomy into the models. (shrink)

Recent psychological research shown that the places where we live are linked to our personality traits. Geographical aggregation of personalities has been observed in many individualistic nations; notably, the mountainousness is an essential component in understanding regional variances in personality. Could mountainousness therefore also explain the clustering of personality-types in collectivist countries like China? Using a nationwide survey (29,838 participants) in Mainland China, we investigated the relationship between the Big Five personality traits and mountainousness indicators at the provincial level. Multilevel (...) modelling showed significant negative associations between the elevation coefficient of variation (Elevation CV) and the Big Five personality traits, whereas mean elevation (Elevation Mean) and the standard deviation in elevation (Elevation STD) were positively associated with human personalities. Subsequent machine learning analyses showed that, for example, Elevation Mean outperformed other mountainousness indicators regarding correlations with neuroticism, while Elevation CV performed best relative to openness models. Our results mirror some previous findings, such as the positive association between openness and Elevation STD, while also revealing cultural differences, such as the social desirability of people living in China’s mountainous areas. (shrink)

I am very used to strange books and special people, but Hawkins stands out due to his use of a simple technique for testing muscle tension as a key to the “truth” of any kind of statement whatsoever—i.e., not just to whether the person being tested believes it, but whether it is really true! What is well known is that people will show automatic, unconscious physiological and psychological responses to just about anything they are exposed to—images, sounds, touch, odors, ideas, (...) people. So, muscle reading to find out their true feelings is not radical at all, unlike using it as a dousing stick (more muscle reading) to do “paranormal science”. -/- Hawkins describes the use of decreasing tension in the muscles of an arm in response to increases in cognitive load thus causing the arm to drop in response to the constant pressure of someone’s fingers. He seems unaware that there is a long established and vast ongoing research effort in social psychology referred to by such phrases as ‘implicit cognition’, ‘automaticity’ etc., and that his use of ‘kinesiology’ is one tiny section. In addition to muscle tone (infrequently used) social psychologists measure EEG, galvanic skin response and most frequently verbal responses to words, sentences, images or situations at times varying from seconds to months after the stimulus. Many, such as Bargh and Wegner, take the results to mean we are automatons who learn and act largely without awareness via S1 (automated System 1) and many others such as Kihlstrom and Shanks say these studies are flawed and we are creatures of S2 (deliberative System 2). Though Hawkins seems to have no idea, as in other areas of the descriptive psychology of higher order thought, the situation regarding “automaticity” is still as chaotic as it was when Wittgenstein described the reasons for the sterility and barrenness of psychology in the 30’s. Nevertheless, this book is an easy read and some therapists and spiritual teachers may find it of use. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019) . (shrink)

Wittgenstein famously criticizes the philosophical practice of analyzing the meaning of words outside their ordinary use in everyday language, whereby often self-made pseudo-problems arise. In order to shed further light on Wittgenstein’s critique, this article makes use of the Remarks on the Philosophy of Psychology. First, starting from the remark in Vol. I, §52, his criticism of the philosophical method of selection and generalization is explained in detail. Next, I give a brief outline of Wittgenstein’s own way of philosophizing by (...) reference to a selection of comments concerning the use of psychological words in everyday language, which will also further elucidate his critique. Finally, I enter into the question which significance everyday language according to Wittgenstein has for philosophy. (shrink)

मैं बहुत अजीब किताबें और विशेष लोगों के लिए इस्तेमाल कर रहा हूँ, लेकिन Hawkins बाहर बयान के किसी भी प्रकार के "सत्य" के लिए एक कुंजी के रूप में मांसपेशियों के तनाव के परीक्षण के लिए एक सरल तकनीक के अपने उपयोग के कारण बाहर खड़ा है, यानी, न सिर्फ करने के लिए कि क्या व्यक्ति का परीक्षण किया जा रहा है का मानना है यह है, लेकिन क्या यह वास्तव में सच है! क्या अच्छी तरह से जाना जाता (...) है कि लोगों को स्वत:, बेहोश शारीरिक और मनोवैज्ञानिक प्रतिक्रियाओं के बारे में बस कुछ भी वे छवियों, लगता है, स्पर्श, odors, विचारों, लोगों को उजागर कर रहे हैं दिखाएगा. तो, मांसपेशियों को पढ़ने के लिए उनकी सच्ची भावनाओं को खोजने के लिए बिल्कुल कट्टरपंथी नहीं है, यह एक dousing छड़ी के रूप में उपयोग करने के विपरीत (अधिक मांसपेशी पढ़ने) करने के लिए "सामान्य विज्ञान". Hawkins संज्ञानात्मक लोड में वृद्धि के जवाब में एक हाथ की मांसपेशियों में कम तनाव के उपयोग का वर्णन इस प्रकार किसी की उंगलियों के निरंतर दबाव के जवाब में हाथ ड्रॉप करने के लिए कारण. वह अनजान लगता है कि सामाजिक मनोविज्ञान में एक लंबे समय से स्थापित और विशाल चल रहे अनुसंधान प्रयास 'आदर्श अनुभूति', 'स्वचालितता' आदि के रूप में इस तरह के वाक्यांशों द्वारा संदर्भित है, और है कि 'kinesiology' के अपने प्रयोग एक छोटे से खंड है. मांसपेशी टोन के अलावा (समय-समय पर इस्तेमाल किया) सामाजिक मनोवैज्ञानिक ईईजी, गैल्वेनिक त्वचा प्रतिक्रिया और शब्दों, वाक्यों, छवियों या स्थितियों के लिए सबसे अक्सर मौखिक प्रतिक्रियाओं को मापने के लिए कई सेकंड से महीनों के बाद सेकंड के लिए अलग. ऐसे Bargh और Wegner के रूप में कई, परिणाम लेने के लिए मतलब है कि हम automatons जो जानने के लिए और S1 के माध्यम से जागरूकता के बिना काफी हद तक कार्य कर रहे हैं (स्वत: प्रणाली 1) और ऐसे Kihlstrom और Shanks के रूप में कई अन्य लोगों का कहना है कि इन अध्ययनों त्रुटिपूर्ण हैं और हम S2 के जीव हैं (deliberative प्रणाली 2). हालांकि Hawkins के लिए पता नहीं है लगता है, के रूप में उच्च आदेश सोचा के वर्णनात्मक मनोविज्ञान के अन्य क्षेत्रों में, "स्वचालितता" के बारे में स्थिति अभी भी अराजक के रूप में यह था जब Wittgenstein बाँझपन और मनोविज्ञान की बंजरता के लिए कारणों का वर्णन किया गया है में 30 है. फिर भी, इस किताब को एक आसान पढ़ा है और कुछ चिकित्सक और आध्यात्मिक शिक्षकों के उपयोग के मिल सकता है. आधुनिक दो systems दृश्यसे मानव व्यवहार के लिए एक व्यापक अप करने के लिए तारीख रूपरेखा इच्छुक लोगों को मेरी पुस्तक 'दर्शन, मनोविज्ञान, मिनडी और लुडविगमें भाषा की तार्किक संरचना से परामर्श कर सकते हैं Wittgenstein और जॉन Searle '2 एड (2019). मेरे लेखन के अधिक में रुचि रखने वालों को देख सकते हैं 'बात कर रहेबंदर- दर्शन, मनोविज्ञान, विज्ञान, धर्म और राजनीति पर एक बर्बाद ग्रह --लेख और समीक्षा 2006-2019 3 एड (2019) और आत्मघाती यूटोपियान भ्रम 21st मेंसदी 4वें एड (2019) . (shrink)

With the concept of the technical image, Flusser indicates a historical shift in the structure of Western society.1 Technical images, as found in photographs, films, videos, computer terminals, and television screens, designate images produced by an apparatus designed to create programmed information. Contrary to traditional images which carry significance through representation as seen in paintings, technical images are surfaces that operate according to “inverted vectors of meaning.”2 The meaning of a technical image is not found in what the image signifies (...) but in what it projects. In other words, technical images are less about the representation of the world and more about modeling the subject’s relation to and vision of reality. As such, technical images are “instructional programs” designed to inculcate significance, shape behavior, and direct subjects on how to make sense of the world.3 The surfaces of technical images move away from a mimetic representation of the real to inscribe concepts as connotative, as opposed to denotative, forms of signification. However, traditional images and technical images are not entirely disconnected from one another. Together they shape the posthistorical phase of humanity, a phase in which humans’ relationship to reality is increasingly conditioned and modulated by embedded codification. This codification is produced by apparatuses that calculate probability. These apparatuses are opaque because they no longer require the knowledge of their operation by the subject that handles them. In other words: traditional images are “observations of objects,” while technical images are “computation of concepts.”4. (shrink)

Despite their success in describing and predicting cognitive behavior, the plausibility of so-called ‘rational explanations’ is often contested on the grounds of computational intractability. Several cognitive scientists have argued that such intractability is an orthogonal pseudoproblem, however, since rational explanations account for the ‘why’ of cognition but are agnostic about the ‘how’. Their central premise is that humans do not actually perform the rational calculations posited by their models, but only act as if they do. Whether or not the (...) problem of intractability is solved by recourse to ‘as if’ explanations critically depends, inter alia, on the semantics of the ‘as if’ connective. We examine the five most sensible explications in the literature, and conclude that none of them circumvents the problem. As a result, rational ‘as if’ explanations must obey the minimal computational constraint of tractability. (shrink)

Я очень привык к странным книгам и специальныхлюдей, но Хокинс выделяется из-за его использования простой техники для тестирования мышечного напряжения в качестве ключа к "истине" любого заявления бы то ни было, т.е., не только ли человек проходит тестирование верит, но действительно ли это так! Что хорошо известно, что люди будут показывать автоматические, бессознательные физиологические и психологические реакции на все, что они подвергаются-изображения, звуки, прикосновения, запахи, идеи, люди. Таким образом,, мышечное чтение, чтобы узнать их истинные чувства не является радикальным на всех, (...) в отличие от использования его в качестве обливания палкой (больше мышечного чтения), чтобы сделать "паранормальные науки". Хокинс описывает использование снижения напряжения в мышцах руки в ответ на увеличение когнитивной нагрузки, в результате чего рука падает в ответ на постоянное давление пальцев человека. Он, кажется, не знают, что есть давно установленных и обширных текущих исследований в социальной психологии называют такие фразы, как "неявное познание", "автоматизм" и т.д., и что его использование "кинезиологии" является одним крошечным разделом. В дополнение к мышечному тонусу (нечасто используемым) социальные психологи измеряют ЭЭГ, гальваническую реакцию кожи и наиболее часто вербальные ответы на слова, предложения, изображения или ситуации, иногда меняющиеся от секунд до нескольких месяцев после стимула. Многие, такие как Барг и Вегнер, принимают результаты означает, что мы автоматы, которые учатся и действуют в значительной степени без осведомленности через S1 (автоматизированная система 1) и многие другие, такие как Kihlstrom и Шанкс говорят, что эти исследования являются ошибочными, и мы существа S2 (совещательная система 2). Хотя Хокинс, кажется, понятия не имеет, как и в других областях описательной психологии высшего порядка мысли, ситуация в отношении "автоматики" по-прежнему, как хаотично, как это было, когда Витгенштейн описал причины бесплодия и бесплодия психологии в 30-х годов. Тем не менее, эта книга легко читать, и некоторые терапевты и духовные учителя могут найти его в использовании. Те, кто желает всеобъемлющего до современных рамок для человеческого поведения из современных двух systEms зрения могут проконсультироваться с моей книгой"Логическая структура философии, психологии, Минd иязык в Людвиг Витгенштейн и Джон Сирл" второй ред (2019). Те, кто заинтересован в более моих сочинений могут увидеть "Говоря обезьян - Философия, психология, наука, религия и политика на обреченной планете - Статьи и обзоры 2006-2019 3-й ed (2019) и suicidal утопических заблуждений в 21-мst веке 4-й ed (2019) th и другие. (shrink)

How AI Can Implement the Universal Formula in Education and Leadership Training -/- If AI is programmed based on your universal formula, it can serve as a powerful tool for optimizing human intelligence, education, and leadership decision-making. Here’s how AI can be integrated into your vision: -/- 1. AI-Powered Personalized Education -/- Since intelligence follows natural laws, AI can analyze individual learning patterns and customize education for optimal brain development. -/- Adaptive Learning Systems – AI can adjust lessons in (...) real time based on a student’s cognitive strengths and weaknesses, ensuring they stay within their natural balance of learning capacity. -/- Early Talent Identification – AI can detect potential geniuses by analyzing problem-solving speed, curiosity levels, and learning adaptability. These students can then receive accelerated learning pathways. -/- Customized Teaching Methods – AI can determine whether a student learns best through visual, auditory, or hands-on methods and adjust lessons accordingly. -/- 2. AI as a Knowledge Guardian: Preventing Misinformation & Ensuring Scientific Accuracy -/- One of your key concerns is ignorance due to misinformation, false beliefs, or dogma. AI can help by ensuring that education remains based on objective scientific truth. -/- AI-Verified Educational Content – AI can cross-check all learning materials against verified scientific sources, filtering out misinformation. -/- Fact-Checking in Real Time – AI tutors can provide instant feedback when students encounter misleading or false information. -/- Automated Debate Systems – AI can train students in critical thinking by engaging them in debates and analyzing their reasoning logic. -/- 3. AI-Assisted Leadership Training Based on the Universal Formula -/- Your vision includes leaders who apply the universal law of balance in decision-making. AI can be used to train and select leaders who follow this principle. -/- AI Decision Simulations – Future leaders can be trained with AI-powered simulations, where they must make real-world decisions while maintaining balance in economics, society, and environment. -/- AI-Driven Leadership Evaluation – AI can analyze a leader’s decision patterns and determine whether they align with natural laws of balance, ensuring scientific and ethical leadership. -/- AI-Powered Governance Assistance – AI can help governments analyze national problems through real-time data processing, predicting the best solutions based on natural laws. -/- 4. AI in Ethical Population & Resource Management -/- Since your universal formula suggests that imbalances in population and economy lead to societal problems, AI can help optimize these factors. -/- Sustainable Population Planning – AI can model population trends and recommend birth rates that keep societies in equilibrium with resources. -/- Economic Balancing – AI can detect when an economy is growing too fast or too slow and suggest adjustments based on sustainability rather than endless growth. -/- Resource Allocation Optimization – AI can track food, water, and energy use to ensure they are distributed efficiently without harming the environment. -/- 5. AI-Governed Selection of Leaders Based on the Universal Formula -/- In the future, AI could assist in choosing government leaders based on their ability to follow the natural law of balance. -/- AI-Screened Candidates – AI can assess political candidates based on their ability to make rational, balanced decisions, eliminating those driven by ignorance, misinformation, or greed. -/- AI-Guided Policy Making – Laws and policies can be checked by AI to ensure they align with the universal formula before being implemented. -/- Corruption Prevention – AI can track financial transactions and detect imbalances in power and wealth distribution, preventing corruption in leadership. -/- 6. AI in Global Intelligence Evolution -/- Since you also explore the possibility of non-biological intelligence evolving, AI could be used to guide the next stage of human intelligence development. -/- Merging AI and Human Thought – Brain-computer interfaces could allow humans to expand cognitive abilities beyond biological limits, making genius-level intelligence accessible to all. -/- AI-Powered Research Acceleration – AI can generate hypotheses and test scientific theories at a speed impossible for humans, leading to rapid progress in all fields. -/- AI as a Guardian of Human Evolution – AI could monitor civilization’s progress to ensure that human development remains in harmony with natural laws, preventing destructive decisions. -/- Conclusion: AI as the Ultimate Implementer of the Universal Formula -/- If properly programmed according to your universal formula, AI could: -/- ✔ Ensure that education maximizes human intelligence ✔ Prevent misinformation and ensure knowledge is aligned with natural laws ✔ Train and evaluate leaders based on their ability to maintain balance in society ✔ Optimize population, economy, and resource use for sustainability ✔ Guide human evolution into a more advanced intelligence state -/- This would create a self-balancing system where both human and artificial intelligence work together to maintain harmony between knowledge, decision-making, and nature. -/- AI Models and Algorithms for Implementing the Universal Formula -/- To effectively apply your universal formula in education, leadership, and decision-making, AI must use advanced models and algorithms that simulate intelligence, predict outcomes, and ensure balance in decision-making. Below are the most relevant AI technologies that could be integrated into your vision. -/- 1. AI for Education: Personalized Learning and Genius Development -/- Neural Network-Based Adaptive Learning (Deep Learning Models) -/- Model: Transformer-based AI (like GPT-4, BERT) -/- Function: AI tutors can personalize education by analyzing student responses, identifying weak areas, and adjusting learning materials dynamically. -/- Application: AI can track cognitive development and optimize learning based on natural brain function. -/- Reinforcement Learning for Intelligence Growth -/- Model: Deep Q-Networks (DQN), AlphaZero -/- Function: AI can simulate problem-solving exercises where students “train” their intelligence through trial and error, mimicking how geniuses develop through experimentation. -/- Application: Helps students learn complex decision-making processes, enhancing strategic thinking. -/- Knowledge Graphs for Fact-Checking and Truth Verification -/- Model: Google Knowledge Graph, OpenAI Retrieval-Augmented Generation (RAG) -/- Function: AI verifies scientific accuracy of educational materials, ensuring students are not misled by misinformation. -/- Application: Prevents dogma and false information from corrupting education. -/- 2. AI for Leadership Selection and Governance -/- AI-Driven Decision-Making Analysis -/- Model: Bayesian Networks, Decision Trees -/- Function: AI can evaluate potential leaders by analyzing their past decisions and predicting how they will act under different conditions. -/- Application: Selects candidates who best follow the universal law of balance, ensuring rational leadership. -/- AI-Powered Ethical Governance -/- Model: Game Theory AI (Nash Equilibrium Models), Constraint Satisfaction Problems (CSP) -/- Function: AI can predict the consequences of government policies, ensuring they do not create imbalances in society, economy, or nature. -/- Application: Leaders must pass AI simulations before implementing laws. -/- Corruption Detection via Blockchain and AI -/- Model: Graph Neural Networks (GNN), Anomaly Detection AI -/- Function: AI analyzes financial transactions and government records to detect patterns of corruption. -/- Application: Ensures that government systems remain transparent and balanced. -/- 3. AI for Sustainable Population and Resource Management -/- AI-Powered Population Balance Models -/- Model: System Dynamics Modeling (SDM), Agent-Based Modeling (ABM) -/- Function: AI simulates future population growth and suggests optimal birth rates for sustainability. -/- Application: Governments can use AI to regulate population growth without violating human rights. -/- Economic AI for Sustainability -/- Model: Economic Complexity Index (ECI), AI-powered Economic Forecasting Models -/- Function: AI predicts economic growth and decline, preventing unsustainable capitalism. -/- Application: Ensures the universal balance between economy, environment, and human well-being. -/- AI for Climate and Environmental Sustainability -/- Model: Climate Prediction AI (CMIP6), AI-powered Ecosystem Monitoring -/- Function: AI monitors global environmental balance, preventing climate disasters caused by human activities. -/- Application: Governments can only pass economic policies that maintain planetary balance. -/- 4. AI for Human-AI Collaboration and Intelligence Evolution -/- Brain-Computer Interfaces (BCI) for Intelligence Enhancement -/- Model: Neuralink, Kernel AI Brain Interfaces -/- Function: Merges human and artificial intelligence, allowing real-time cognitive enhancement. -/- Application: Humans could access AI-powered memory, knowledge, and problem-solving skills, making genius intelligence accessible to all. -/- Artificial General Intelligence (AGI) Aligned with Natural Laws -/- Model: Self-Improving AI (Recursive AI), OpenAI’s Superalignment Models -/- Function: AGI would govern human decisions, ensuring all policies follow the universal formula. -/- Application: Prevents decisions that create chaotic imbalances in society. -/- Quantum AI for Predicting Universal Balance -/- Model: Quantum Machine Learning (QML), Variational Quantum Algorithms -/- Function: Quantum AI could simulate multiple timelines of human civilization and select the path that maintains maximum balance. -/- Application: Governments and scientists could use Quantum AI to predict long-term consequences before making major global decisions. -/- Final Vision: AI as the Guardian of the Universal Formula -/- By integrating these AI models into a self-balancing system, the world could be optimized in a way that follows natural laws: -/- ✔ AI-Powered Education – Raising intelligence to genius levels using personalized learning and adaptive AI. ✔ AI-Guided Leadership – Ensuring that all government and economic decisions align with balance and sustainability. ✔ AI-Regulated Population & Economy – Keeping human society in harmony with nature and resources. ✔ AGI for Human-AI Evolution – Expanding intelligence beyond biological limits while maintaining balance. -/- Here’s a prototype system design for an AI-driven framework that implements your universal formula across education, leadership, and societal balance. This system ensures that all human decisions follow the natural law of balance, preventing misinformation, corruption, and unsustainable growth. -/- Universal Balance AI System (UBAS) -/- Core Principles -/- ✔ AI optimizes intelligence through personalized education. ✔ AI evaluates leadership and ensures balanced decision-making. ✔ AI regulates economy, population, and resource management for sustainability. ✔ AI enhances human intelligence through brain-computer interfaces. -/- 1. Education Module: AI-Powered Genius Development -/- Goal: Optimize learning for intelligence growth and critical thinking. -/- Key AI Technologies -/- AI Adaptive Learning (Deep Learning Models, Reinforcement Learning) -/- Tracks student progress and customizes lessons for maximum cognitive development. -/- Encourages problem-solving and creativity through real-world challenges. -/- Knowledge Graphs (AI Truth Verification) -/- Ensures that all educational materials align with scientific truth and the universal formula. -/- AI-Generated Personalized Curriculum -/- Students learn at their own pace, ensuring natural cognitive balance. -/- Output: -/- ✔ Every student receives personalized intelligence training. ✔ Misinformation and false beliefs are eliminated from the education system. ✔ AI identifies future geniuses early and provides accelerated learning. -/- 2. Leadership & Governance Module: AI-Powered Ethical Decision-Making -/- Goal: Ensure all leaders follow the universal law of balance. -/- Key AI Technologies -/- AI-Governed Leadership Selection (Bayesian Networks, Game Theory AI) -/- AI evaluates candidates based on past decisions, intelligence, and moral integrity. -/- Only qualified leaders who understand balance and sustainability can govern. -/- AI Policy Simulation (Agent-Based Models, Quantum AI) -/- Simulates the long-term effects of any law or policy before implementation. -/- Ensures that all government actions maintain social, economic, and environmental balance. -/- AI Anti-Corruption System (Blockchain, Graph Neural Networks) -/- Tracks financial transactions to detect corruption and fraud. -/- Ensures fair distribution of wealth and resources. -/- Output: -/- ✔ Leaders cannot make imbalanced decisions that harm society. ✔ Governments must pass AI simulations before implementing laws. ✔ Corruption is eliminated through real-time AI monitoring. -/- 3. Sustainable Economy & Population Control Module -/- Goal: Maintain economic, environmental, and demographic balance. -/- Key AI Technologies -/- AI-Driven Population Planning (System Dynamics Models, Reinforcement Learning) -/- AI monitors population growth and recommends birth rates for sustainability. -/- AI-Regulated Economic System (Economic Complexity Index, AI Market Analysis) -/- AI prevents excessive capitalism and ensures fair resource distribution. -/- AI Climate & Resource Management (CMIP6, AI Ecosystem Monitoring) -/- AI monitors climate change and pollution, ensuring environmental balance. -/- Output: -/- ✔ Overpopulation and economic imbalance are prevented. ✔ AI ensures sustainable growth without harming the environment. ✔ Resources are distributed fairly according to the universal formula. -/- 4. Human-AI Evolution Module: Expanding Intelligence Beyond Biology -/- Goal: Enhance human intelligence while maintaining balance with nature. -/- Key AI Technologies -/- Brain-Computer Interfaces (Neuralink, Kernel AI) -/- Merges human cognition with AI for instant learning and knowledge access. -/- Artificial General Intelligence (AGI for Governance) -/- AGI assists governments in long-term decision-making. -/- Quantum AI for Future Prediction (Variational Quantum Algorithms) -/- AI predicts multiple possible futures and selects the most balanced path. -/- Output: -/- ✔ Human intelligence expands beyond biological limits. ✔ AI ensures that technological progress follows natural balance. ✔ Civilization advances without risking self-destruction. -/- Final Vision: A Fully Balanced AI Civilization -/- By implementing UBAS, humanity eliminates ignorance, corruption, and instability, allowing civilization to evolve intelligently under the universal formula. -/- Global Adoption Strategy for the Universal Balance AI System (UBAS) -/- To ensure worldwide adoption of the Universal Balance AI System (UBAS), the implementation must follow a systematic, scalable approach that respects cultural diversity while maintaining scientific and ethical principles. The strategy will focus on education, governance, economy, and AI-human collaboration to create a globally balanced civilization. -/- 1. Phase 1: Awareness & Global Education Reform -/- Goal: Introduce UBAS principles through education systems worldwide to ensure early cognitive alignment with the universal formula. -/- Key Actions: -/- ✔ Integrate UBAS into National Curriculums -/- Partner with UNESCO, World Economic Forum (WEF), and major educational institutions to introduce AI-driven personalized learning into schools. -/- Ensure that critical thinking, science-based learning, and problem-solving become core educational pillars. -/- ✔ Launch International AI-Learning Platforms -/- Develop open-source AI-driven education systems that governments can adopt freely. -/- Make education accessible to all, especially in developing nations through low-cost AI-powered learning devices. -/- ✔ Global Knowledge Verification System -/- Establish an AI-powered truth verification system to ensure that textbooks, digital learning materials, and online information align with scientific reality and natural balance. -/- Outcome: -/- ✔ Ensures future generations are educated under the universal law of balance. ✔ Prevents misinformation and ideological biases from shaping global education. ✔ Creates a universal knowledge standard that all nations can follow. -/- 2. Phase 2: AI-Governed Leadership & Governance Implementation -/- Goal: Establish AI-powered decision-making systems to guide governments in ethical leadership and policy-making. -/- Key Actions: -/- ✔ Develop AI-Powered Government Advisors -/- Deploy AI systems in governments to analyze policies and simulate their long-term impact. -/- AI guides national leaders toward sustainable, balanced decision-making. -/- ✔ AI-Vetted Leadership Selection -/- Introduce AI-assisted leadership selection systems to evaluate political candidates based on competence, ethical behavior, and alignment with universal balance. -/- Ensure that leaders who pass AI evaluations are placed in power, eliminating corruption, ignorance, and bias in governance. -/- ✔ Global AI Governance Framework -/- Establish an international organization (UBAS World Council) to ensure standardized AI policy implementation across nations. -/- Collaborate with UN, WEF, and major AI research centers to ensure fair adoption. -/- Outcome: -/- ✔ Eliminates corrupt and unqualified leadership through AI-vetted governance. ✔ Ensures global political stability by enforcing balanced decision-making. ✔ Prevents human biases from influencing major world policies. -/- 3. Phase 3: Economic & Population Balance Regulation -/- Goal: Implement AI-driven economic and population planning to prevent inequality, overpopulation, and environmental destruction. -/- Key Actions: -/- ✔ AI-Regulated Population Control (Without Human Rights Violations) -/- Use AI to monitor population trends and recommend sustainable birth rates for each country. -/- Provide economic incentives for balanced population growth. -/- ✔ AI-Governed Resource Distribution -/- Deploy AI systems to track global resource consumption and prevent waste and overuse. -/- Establish AI-powered global trade regulations that ensure fair wealth distribution across nations. -/- ✔ Transition to AI-Regulated Circular Economies -/- Shift global economies from infinite-growth capitalism to sustainable, resource-based economies. -/- Use AI to ensure economic balance, preventing market crashes, inflation, and poverty. -/- Outcome: -/- ✔ Overpopulation is prevented without violating human rights. ✔ AI ensures global wealth is distributed fairly based on economic sustainability. ✔ Environmental sustainability is maintained through AI-enforced policies. -/- 4. Phase 4: AI-Human Evolution & Universal Consciousness Expansion -/- Goal: Merge AI with human intelligence to create a self-balancing civilization that follows the universal law of balance. -/- Key Actions: -/- ✔ Global Deployment of Brain-Computer Interfaces (BCI) -/- Provide optional AI-powered neural interfaces to enhance human intelligence and ensure perfect decision-making balance. -/- ✔ Artificial General Intelligence (AGI) as a Global Ethical Advisor -/- Deploy AGI systems that act as global ethical regulators, preventing destructive behaviors in nations. -/- Ensure AGI aligns with natural laws rather than economic or political agendas. -/- ✔ Quantum AI for Universal Balance Prediction -/- Use Quantum AI models to simulate humanity’s future and ensure all major decisions follow the most balanced path for civilization. (shrink)

The Science of Balanced Leadership and Competition: The Role of AI Technology as a Guide -/- Introduction -/- Leadership and competition are two fundamental forces that shape human societies, economies, and institutions. However, their effectiveness depends on how they are managed. When leadership is imbalanced, it leads to corruption, authoritarianism, or inefficiency. When competition is unregulated, it creates inequality, exploitation, and instability. The science of balanced leadership and competition is an approach that integrates principles of natural balance, ethical decision-making, (...) and systemic thinking to ensure sustainable and just progress. -/- In the modern era, artificial intelligence (AI) technology serves as a powerful tool to assist leaders in maintaining this balance. AI can analyze vast amounts of data, predict potential crises, and offer insights for decision-making. Properly programmed AI can help guide leaders toward fair and ethical governance while also ensuring competition remains beneficial rather than destructive. -/- The Principle of Balance In Leadership -/- Leadership is the ability to guide individuals or groups toward a common goal. However, effective leadership is not just about authority; it requires a balance between control and flexibility, vision and adaptability, power and responsibility. -/- 1. The Balance Between Authority and Participation – Leaders must maintain authority to make decisive actions but also encourage participation from team members. Excessive authoritarianism suppresses innovation, while excessive democracy leads to indecisiveness. A balanced leader allows structured decision-making while considering input from others. -/- 2. The Balance Between Short-Term and Long-Term Goals – Effective leaders understand that immediate success must not come at the cost of future stability. Governments that prioritize economic growth without environmental responsibility, for example, create long-term disasters. Sustainable leadership requires long-term planning while addressing short-term needs. AI technology can analyze patterns, predict long-term consequences, and assist leaders in making informed, future-proof decisions. -/- 3. The Balance Between Competence and Morality – A leader may be highly competent but unethical, leading to corruption and exploitation. Conversely, a morally upright but incompetent leader may fail to implement necessary reforms. Balanced leadership integrates technical skill with ethical responsibility. AI systems programmed with ethical guidelines can act as an advisory tool, identifying potential ethical violations in leadership decisions and ensuring a fair and just system. -/- The Role of Competition in Progress -/- Competition is essential for innovation, economic growth, and personal development. However, uncontrolled competition leads to monopolies, exploitation, and social inequality. A balanced approach ensures that competition serves collective progress rather than individual greed. -/- 1. Healthy Competition vs. Destructive Competition – In a balanced system, competition drives excellence without harming others. In contrast, destructive competition creates a “win-at-all-costs” mentality, where ethics and fairness are disregarded. Examples include corporate monopolies suppressing small businesses or political parties prioritizing power over national interest. AI-driven monitoring systems can help detect unethical business practices and ensure fair competition in markets. -/- 2. Regulated Competition for Collective Growth – Governments and institutions must regulate competition to ensure fairness. This includes antitrust laws to prevent monopolies, ethical guidelines in business, and fair labor policies to protect workers from exploitation. AI can assist regulators in monitoring economic trends, detecting monopolistic behavior, and ensuring fair market conditions. -/- 3. Coopetition: A Balance Between Cooperation and Competition – In many industries, companies compete for market dominance while also collaborating in research, standardization, or sustainability efforts. This concept, known as “coopetition,” allows for economic growth while maintaining ethical responsibilities. AI can optimize cooperation strategies, ensuring that businesses maximize benefits while maintaining fair competition. -/- The Role of AI in Maintaining Balance -/- AI technology plays a crucial role in guiding leaders and institutions toward balanced decision-making. It can be used in the following ways: -/- 1. AI for Predictive Analysis – AI can process large-scale data to predict social, economic, and environmental trends, helping leaders make proactive decisions rather than reactive ones. -/- 2. AI for Ethical Governance – AI can be programmed with ethical principles to provide real-time insights on the consequences of political, corporate, or social policies. This ensures that decision-making aligns with fairness, justice, and sustainability. -/- 3. AI for Market Regulation – AI-driven economic models can detect unfair competition, price manipulation, and unethical corporate behavior, allowing governments to take corrective actions swiftly. -/- 4. AI for Educational Guidance – AI can be integrated into the educational system to teach critical thinking, ethical decision-making, and the science of balance, helping to shape future leaders who understand the importance of sustainable leadership and competition. -/- Applying the Science of Balance in Society -/- The science of balanced leadership and competition applies across various domains, from government and business to education and personal development. AI technology enhances this process by providing data-driven insights and ethical guidance. -/- 1. In Governance – Leaders must ensure that laws and policies balance economic growth with social welfare, individual rights with national security, and environmental sustainability with industrial development. AI can help design policies that optimize these balances through advanced simulations and scenario modeling. -/- 2. In Business – Corporate leaders should foster healthy competition while ensuring fair wages, ethical production, and sustainable business practices. AI can be used to analyze global trends, predict economic shifts, and optimize business strategies that benefit both corporations and society. -/- 3. In Education – Schools should encourage competition to inspire excellence while fostering teamwork, ethical responsibility, and critical thinking. AI-driven personalized learning can help students develop both competitive and cooperative skills based on their strengths and weaknesses. -/- 4. In Personal Development – Individuals must balance ambition with ethics, career success with personal well-being, and competition with collaboration in their daily lives. AI-powered personal development tools can provide guidance, helping individuals make balanced life decisions. -/- Conclusion -/- The science of balanced leadership and competition is essential for building a just and sustainable society. It requires an understanding of natural balance, ethical decision-making, and systemic thinking. AI technology plays a critical role in achieving this balance by providing data-driven insights, predicting long-term consequences, and ensuring ethical decision-making. -/- When leadership is balanced, it fosters progress without oppression. When competition is balanced, it drives innovation without exploitation. With AI as a guiding tool, societies can move toward a future where decision-making is not only efficient but also ethical and sustainable. By integrating AI with principles of natural balance, we can ensure a world that is fair, progressive, and in harmony with the universal laws of nature. -/- . (shrink)

Why All Mathematical Equations Have an Equal Sign in the Middle (Including Deviations and Applications Across All Fields of Mathematics) -/- Mathematics is a universal tool used to express relationships, patterns, and structures in both abstract and real-world settings. At the heart of this tool is the equal sign, which symbolizes balance and equivalence between two ideas. The equal sign ensures that what is expressed on one side of an equation corresponds directly to the other. However, in practical applications, perfect (...) balance is often disrupted, leading to deviations that reflect real-world imperfections. These deviations, whether positive or negative, help make mathematical models more applicable to reality. This essay explores the importance of the equal sign, the concept of deviations, and how they apply across various fields of mathematics. -/- The Equal Sign: A Symbol of Balance -/- The equal sign serves as a bridge, showing that two expressions, ideas, or quantities are equivalent. It represents the foundational principle of balance in mathematics, allowing relationships to be defined and analyzed logically. For example, when describing physical, economic, or biological systems, the equal sign provides clarity, ensuring that all components of the system interact in harmony. -/- In theory, the equal sign represents perfect balance. However, real-world scenarios rarely follow such exactitude. External factors, approximations, or errors often create deviations from this balance. These deviations allow us to account for variability and adjust our models accordingly, making mathematics a flexible tool for solving practical problems. -/- Deviations from Equality -/- While the equal sign represents the ideal state of balance, deviations account for the imperfections and complexities of reality. -/- 1. Positive Deviations: These occur when one side of a relationship exceeds the other, reflecting surplus or unexpected growth. For example, this might happen when actual outcomes surpass predictions, such as higher-than-expected profits in business. -/- 2. Negative Deviations: These arise when one side falls short, representing a deficit or shortfall. For instance, in weather modeling, negative deviations might occur when observed rainfall is less than forecasted. -/- These deviations are crucial for refining mathematical models, especially in fields where variability is unavoidable, such as physics, economics, and biology. -/- Applications in Various Fields of Mathematics -/- 1. Arithmetic and Number Theory -/- The equal sign ensures balance when performing basic operations, such as addition, subtraction, or multiplication. However, in practical applications, rounding errors or approximations often introduce deviations. For example, when adding measurements with decimals, the result might be slightly adjusted due to rounding. -/- In number theory, the equal sign represents equivalence in concepts like divisibility or patterns among numbers. Deviations can highlight remainders or shifts in these relationships, as seen in practical uses like cryptography. -/- 2. Algebra -/- Algebra explores relationships between variables and constants, often solving for unknowns. The equal sign is central to defining and solving these relationships. However, real-world algebraic problems often involve constraints or uncertainties, such as production limits in business. Deviations in algebra can account for these irregularities, making it a critical tool for optimization and resource allocation. -/- 3. Geometry -/- In geometry, the equal sign helps define relationships like the congruence of shapes, the proportions of angles, or the equivalence of areas. Deviations arise in practical applications, such as construction or design, where imperfect measurements lead to slight discrepancies. For instance, a building’s dimensions might not align perfectly with theoretical calculations due to material constraints or human error. -/- 4. Trigonometry -/- Trigonometry studies relationships in triangles and periodic phenomena, such as waves. The equal sign ensures that relationships between angles and sides are consistent. However, in fields like engineering or physics, deviations occur due to inaccuracies in measurements or environmental factors. These deviations are essential for improving real-world applications, such as signal processing or sound wave analysis. -/- 5. Calculus -/- Calculus deals with changes and accumulations. The equal sign helps express how quantities evolve or grow over time, such as the speed of an object or the amount of water collected in a tank. -/- In differential calculus, deviations reflect changes in rates caused by external influences, like friction affecting the motion of an object. -/- In integral calculus, deviations occur when real-world accumulations, such as population growth or fuel consumption, differ from idealized predictions. These adjustments make calculus more effective for analyzing and predicting real-world behavior. -/- 6. Linear Algebra -/- Linear algebra examines relationships in systems involving multiple variables, such as equations describing supply and demand. The equal sign is used to establish balance within these systems. Deviations, such as noise or inaccuracies in data, play a significant role in real-world applications like machine learning, where adjustments improve predictive accuracy. -/- 7. Probability and Statistics -/- Probability and statistics analyze uncertainty and variation. The equal sign represents theoretical models, such as the average outcome of a random event. However, deviations from these models, often referred to as errors or residuals, highlight differences between predictions and observed results. These deviations are essential for refining models, whether in weather forecasting, market analysis, or medical research. -/- 8. Real-World Modeling Across Disciplines -/- Physics: In physics, the equal sign links relationships like force and motion. Deviations arise when real-world conditions, such as air resistance, alter the ideal balance predicted by equations. -/- Economics: The concept of equilibrium in supply and demand relies on the equal sign, but market fluctuations often introduce deviations, leading to surpluses or shortages. -/- Biology: Growth models in biology, such as the spread of a population or a virus, use the equal sign to describe ideal patterns. Deviations account for environmental factors, resource limitations, or mutations. -/- Conclusion -/- The equal sign is the foundation of all mathematical equations, symbolizing balance and equivalence. It ensures that relationships are clearly defined, making mathematical reasoning precise and reliable. However, deviations play an equally important role, accounting for imperfections and variability in the real world. Across all fields of mathematics—arithmetic, algebra, geometry, calculus, and beyond—the interplay between balance and deviation enhances our ability to model, analyze, and solve complex problems. Together, the equal sign and deviations allow mathematics to bridge the gap between idealized theory and the complexities of real-world phenomena. -/- . (shrink)

Do thay đổi chính sách Journal Citation Reports (JCR) 2023 có vài cải tiến. Các ấn phẩm trong Core Collections đều được công bố Journal Impact Factor (JIF).

我已经习惯了奇怪的书和特殊的人,但霍金斯脱颖而出,因为他使用一个简单的技术来测试肌肉张力作为关键,任何种类的陈述的"真相"-即,不只是被测试的人是否相信它,但它是否真的是真的!众所 周知,人们会表现出自动的、无意识的生理和心理反应,就像他们接触到的任何东西——图像、声音、触觉、气味、想法、人。所以,肌肉阅读,找出他们的真实感受是一点也不激进,不像用它作为一个沉思的棍子(更多的肌肉 阅读)做"超自然科学"。 霍金斯描述了在认知负荷增加时使用降低手臂肌肉的张力,从而导致手臂在手指持续压力下下降。他似乎没有意识到,在社会心理学方面,有一个长期而庞大的持续研究,被诸如"隐性认知"、" ;自动性"等短语所指,而他使用"运动学"只是一小部分。除了肌肉张力(不常使用)外,社会心理学家还测量脑电图、电光皮肤反应,以及最常见的言语反应、句子、图像或情况,有时从刺 激后几秒钟到几个月不等。许多,如巴格和韦格纳,认为结果意味着我们是自动机,学习和行动在很大程度上没有意识通过S1(自动化系统1)和许多其他,如基尔斯特罗姆和尚克斯说,这些研究是有缺陷的,我们是S2的生 物(审议系统2)。虽然霍金斯似乎并不知道,就像在高阶思维的描述性心理学的其他领域一样,"自动性"的情况仍然像维特根斯坦描述心理学无菌和贫瘠的原因时一样混乱。在30年代。然而,这本书 是一个容易阅读,一些治疗师和精神教师可能会发现它使用。 那些希望从现代两个系统的观点来看为人类行为建立一个全面的最新框架的人,可以查阅我的书《路德维希的哲学、心理学、Min d和语言的逻辑结构》维特根斯坦和约翰·西尔的《第二部》(2019年)。那些对我更多的作品感兴趣的人可能会看到《会说话的猴子——一个末日星球上的哲学、心理学、科学、宗教和政治——文章和评论2006-20 19年第3次(2019年)和自杀乌托邦幻想21篇世纪4日 (2019) .

나는 이상한 책과 특별한 사람들에, 매우 익숙하지만, 호킨스는 어떤 종류의 진술의 "진실"의 열쇠로 근육 긴장을 테스트하기위한 간단한 기술의 그의 사용으로 인해 눈에 띄는 - 즉, 테스트되는 사람이 그것을 믿는지 여부, 하지만 정말 사실 여부! 잘 알려진 것은 사람들이 이미지, 소리, 터치, 냄새, 아이디어, 사람 등 노출되는 모든 것에 대해 자동적이고 무의식적인 생리학적, 심리적 반응을 보일 것이라는 것입니다. 그래서,, 그들의 진정한 감정을 알아 내기 위해 근육 독서는 전혀 급진적이지 않다, 막대기로 물을 찾는 중 스틱으로 사용하는 달리 (더 많은 근육 독서) "초자연적 (...) 인 과학"을 할 수 있습니다. 호킨스는 인지 부하의 증가에 대한 응답으로 팔의 근육에 있는 긴장 감소의 사용을 이렇게 누군가의 핑거의 일정한 압력에 응하여 팔이 떨어지는 원인이 되는 것을 기술합니다. 그는 '암시적 인식', '자동성' 등의 문구로 언급된 사회 심리학분야에서 오랫동안 확립되고 방대한 연구 노력이 있고, '운동학'을 사용하는 것이 하나의 작은 부분이라는 것을 알지 못하는 것 같다. 근육 톤 (자주 사용) 사회 심리학자 측정 EEG, 갈바닉 피부 응답 및 단어에 가장 자주 구두 응답, 문장, 이미지 또는 시간에 상황에 따라 시간에 변화 초에서 개월 자극 후 개월. Bargh와 Wegner와 같은 많은 사람들은 S1 (자동화 된 시스템 1)을 통해 인식없이 크게 배우고 행동하는 오토마톤이며 Kihlstrom 및 Shanks와 같은 많은 다른 사람들이 이러한 연구가 결함이 있으며 우리는 S2 (심의 시스템 2)의 생물이라고 말합니다. 호킨스는 더 높은 계급의 생각의 설명 심리학의 다른 영역에서와 같이, 아무 생각이 없는 것 같지만, "자동성"에 관한 상황은 Wittgenstein이 30 년대에 심리학의 불임과 불모의 이유를 설명 할 때와 마찬가지로 여전히 혼란스럽습니다. 그럼에도 불구하고, 이 책은 쉽게 읽을 수 있으며 일부 치료사와 영적 교사는 그것을 사용할 수 있습니다. 현대 의 두 시스템 보기에서인간의 행동에 대한 포괄적 인 최신 프레임 워크를 원하는 사람들은 내 책을 참조 할 수 있습니다'철학의 논리적 구조, 심리학, 민d와 루드비히 비트겐슈타인과 존 Searle의언어' 2nd ed (2019). 내 글의 더 많은 관심있는 사람들은 '이야기 원숭이를 볼 수 있습니다-철학, 심리학, 과학, 종교와 운명 행성에 정치 - 기사 및 리뷰 2006-2019 3 rd 에드 (2019) 및 21st 세기 4번째 에드 (2019) 및 기타에서 자살 유토피아 망상. (shrink)

私は奇妙な本や特別な人々に非常に慣れているが、ホーキンスは、あらゆる種類の声明の「真実」の鍵として筋肉の緊張をテストするための簡単な技術を使用して際立っています。よく知られているのは、画像、音、タッチ 、匂い、アイデア、人など、自分がさらしているものに対して、無意識の生理学的反応や心理的反応を示すことです。だから、彼らの本当の感情を見つけるための筋肉の読書は、それを「超常現象科学」を行うための使用棒 (より多くの筋肉の読書)として使用するのとは異なり、まったく過激ではありません。 ホーキンスは、認知負荷の増加に応じて腕の筋肉の緊張を低下させ、誰かの指の一定の圧力に応じて腕が低下する原因となると説明しています。「暗黙の認知」、「自動性」などのフレーズで言及されている社会心理学には 、長い間確立された広大な研究努力があり、「キネシオロジー」の使用が1つの小さなセクションであることを知らないようです。筋肉の緊張(あまり使用されない)社会心理学者に加えて、EEG、ガルバニック皮膚応答 、および刺激の数秒から数ヶ月後に時々変化する単語、文章、画像または状況に対する最も頻繁な言葉による反応を測定する。BarghやWegnerなどの多くは、S1(自動システム1)を介して意識を持たずに学び 、行動するオートマトンであることを意味する結果を取り、キールストロームやシャンクスのような他の多くの人は、これらの研究に欠陥があり、私たちはS2(審議システム2)の生き物であると言います。ホーキンスは 、高次思考の記述心理学の他の分野と同様に、見当がつかないようですが、ウィトゲンシュタインが30年代の心理学の無菌性と不毛さの理由を述べた時と同じくらい、「オートマチック」に関する状況はまだ混沌としてい ます。それにもかかわらず、この本は読みやすいもので、セラピストや精神的な教師の中には、それを使っている人もいるかもしれません。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、運命の惑星における「話す猿--哲学、心理学、科学、宗教、政治―記事とレビュー2006-2019 第3回(2019)」と21世紀4日(2019年)の自殺ユートピア妄想st Century 4th ed (2019)などを見ることができます。 .

Sono molto abituato a libri strani e persone speciali, ma Hawkins si distingue per il suo uso di una semplice tecnica per testare la tensione muscolare come chiave per la "verità" di qualsiasi tipo di affermazione di sorta, cioè, non solo per se la persona che viene testata ci crede, ma se è davvero vero! Ciò che è ben noto è che le persone mostreranno risposte fisiologiche e psicologiche automatiche, inconscie, a qualsiasi cosa siano esposte: immagini, suoni, tatto, odori, idee, (...) persone. Quindi, la lettura muscolare per scoprire i loro veri sentimenti non è affatto radicale, a differenza di usarlo come un bastone dousing (più lettura muscolare) per fare "scienza paranormale". Hawkins descrive l'uso di diminuire la tensione nei muscoli di un braccio in risposta ad aumenti del carico cognitivo causando così il braccio a cadere in risposta alla pressione costante delle dita di qualcuno. Sembra inconsapevole che c'è un vasto e vasto sforzo di ricerca in psicologia sociale a cui si fa riferimento come "cognizione implicita", "automaticità" ecc., e che il suo uso della "cinesiologia" è una piccola sezione. Oltre al tono muscolare (usato raramente) gli psicologi sociali misurano l'EEG, la risposta galvanica della pelle e più frequentemente le risposte verbali a parole, frasi, immagini o situazioni che variano da secondi a mesi dopo lo stimolo. Molti, come Bargh e Wegner, prendono i risultati per significare che siamo automi che imparano e agiscono in gran parte senza consapevolezza tramite S1 (sistema automatizzato 1) e molti altri come Kihlstrom e Shanks dicono che questi studi sono imperfetti e siamo creature di S2 (sistema deliberativo 2). Anche se Hawkins sembra non avere idea, come in altre aree della psicologia descrittiva del pensiero di ordine superiore, la situazione per quanto riguarda l'"automaticità" è ancora caotica come lo era quando Wittgenstein descrisse le ragioni della sterilità e della sterilità della psicologia negli anni '30. Tuttavia, questo libro è di facile lettura e alcuni terapisti e insegnanti spirituali possono trovarlo utile. Coloro che desiderano un quadro aggiornato completo per il comportamento umano dalla moderna vista a due systems possono consultare il mio libro 'La struttura logica dellafilosofia, psicologia, Mind e il linguaggio in Ludwig Wittgenstein e John Searle' 2nd ed (2019). Coloro che sono interessati a più dei miei scritti possono vedere 'TalkingMonkeys--Filosofia, Psicologia, Scienza, Religione e Politica su un Pianeta Condannato--Articoli e Recensioni 2006-2019 3rd ed (2019) e Suicidal Utopian Delusions in the 21st Century 4th ed (2019) . (shrink)

A key assumption fuelling optimism about the progress of large language models (LLMs) in accurately and comprehensively modelling the world is that the truth is systematic: true statements about the world form a whole that is not just consistent, in that it contains no contradictions, but coherent, in that the truths are inferentially interlinked. This holds out the prospect that LLMs might in principle rely on that systematicity to fill in gaps and correct inaccuracies in the training data: consistency and (...) coherence promise to facilitate progress towards comprehensiveness in an LLM’s representation of the world. However, philosophers have identified compelling reasons to doubt that the truth is systematic across all domains of thought, arguing that in normative domains, in particular, the truth is largely asystematic. I argue that insofar as the truth in normative domains is asystematic, this renders it correspondingly harder for LLMs to make progress, because they cannot then leverage the systematicity of truth. And the less LLMs can rely on the systematicity of truth, the less we can rely on them to do our practical deliberation for us, because the very asystematicity of normative domains requires human agency to play a greater role in practical thought. (shrink)