In the history of European philosophy and science, René Descartes is considered an author of a methodology of radical doubt, meditation, and the conception that explains the cause of human errors. But the course on internalization, knowledge of one's own Self, methodology of searching foundation of knowledge and conception of perfect reason have been formed already in the times of a Late Antiquity, particular by Augustine in his works “Soliloquies” and “Confession”, Boethius’s “The Consolation of Philosophy” and was (...) continued in the New age by Loyola’s “Spiritual exercises” and Teresa of Avila’s “The Interior Castle”. Therefore, Descartes could be rightfully considered rather the brilliant inheritor of this tradition than pioneer. To this chain of philosophers and theologians who were forerunners of Descartes’s theory of Radical doubt and especially problem of the source of human errors worth to add a new name – Hadewijch, the representative of medieval Dutch vernacular theology and her works “Visions” along with “Letters”. Precisely her point of view on cause of human errors, very close to the explanation have been given by Descartes in his IV Meditation. The aim of the research is to demonstrate common positions of Descartes’s and Hadewijch’s explanation of the nature of the errors. (shrink)

Technology is a specific form of human agency that yields to (an imperfect) realization of human control over a technological situation-that is, a situation not governed to an end by natural constraints but by specific human aims. In this view, technology can be considered the only way of producing artificial beings. However, all technology is finite by nature, which means that sooner or later, all technology will fail, break down, and go wrong. The fate of all technologies (...) and artificial beings produced by technologies is finitude. Human beings are artificial beings, in this way human existence is also finite. (shrink)

The distinction between true belief and knowledge is one of the most fundamental in philosophy, and a remarkable effort has been dedicated to formulating the conditions on which true belief constitutes knowledge. For decades, much of this epistemological undertaking has been dominated by a single strategy, referred to here as the modal approach. Shared by many of the most widely influential constraints on knowledge, including the sensitivity, safety, and anti-luck/risk conditions, this approach rests on a key underlying assumption — the (...) modal profiles available to known and unknown beliefs are in some way asymmetrical. The first aim of this paper is to deconstruct this assumption, identifying its plausibility with the way in which epistemologists frequently conceptualize human perceptual systems as excluding certain varieties of close error under conditions conducive to knowledge acquisition. The second aim of this paper is to then argue that a neural phase phenomenon indicates that this conceptualization is quite likely mistaken. This argument builds on the previous introduction of this neural phase to the context of epistemology, expanding the use of neural phase cases beyond relatively narrow questions about epistemic luck to a much more expansive critique of the modal approach as a whole. (shrink)

According to the theory of intrinsic value and moral standing known as the “substance view,” all human beings have intrinsic value, full moral standing and, with these, a right to life. The substance view has been defended by numerous contemporary philosophers who use the theory to argue that the standard human fetus has a right to life and, ultimately, that abortion is prima facie seriously wrong. In this paper, I identify three important errors committed by some of (...) these philosophers in their defense of the theory---what I refer to as the “extratheoretical-proposition error,” “quantitative-differences error,” and “non-normative-answer error”---and conclude that these errors render their defense inadequate. (shrink)

The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this capability of the QE is (...) akin to functional characteristics of a specific class of retinal ganglion cells (the so-called Y-cells) in the visual systems of the primate and the cat, the sensitivity of the QE surpasses the capacity limits of human visual detection. Here, the quantization error in the SOM is found to reliably signal changes in contrast or colour when contrast information is removed from or added to the image, but not when the amount and relative weight of contrast information is constant and only the local spatial position of contrast elements in the pattern changes. While the RGB Mean reflects coarser changes in colour or contrast well enough, the SOM-QE is shown to outperform the RGB Mean in the detection of single-pixel changes in images with up to five million pixels. This could have important implications in the context of unsupervised image learning and computational building block approaches to large sets of image data (big data). (shrink)

The paper examines Kant’s self-criticism to the account of hypothetical imperatives given in the "Groundwork for the Metaphysics of Morals". Following his corrections in the introductions to the third "Critique", the paper traces the consequences of that change in his later writings, specifically with regard to the status of prudence. I argue that the revision of the account of hypothetical imperatives leads to differentiate, and ultimately separate, two functions in prudence: the setting of ends through maxims, and the pragmatic rules (...) establishing means to reach those ends. Accordingly, I furthermore argue, there is ultimately no genuine structural distinction between the rules of prudence and skill. The only difference lies in the domain in which prudence unfolds, that is, the field of human relations, and in the relevant cognitions. (shrink)

I claim that the underlying premises of the modern era - e-r-a - are false in a way that carries catastrophic consequences. Despite the many genuine achievements of the modern world—which I for one would not want to live without—the spirit of modernity has been one which denigrated the basic conditions of human being. In the name of freedom and knowledge, the modern era gave birth precisely to the non-empathically responding world, the schizoid ghost in the machine, which now (...) threatens to dissolve both humanity and the natural world. We must find the means to correct the mistaken premises which form the modern error. The time has come to find a new way of renewing reason, a project requiring a transformation of values and outlook as vast as those which took place in the axial age or the modern age. The renewal of reason will involve opening the gates to the entire historical and prehistorical heritage of humankind, to renew the archaic values of family, household, neighborhood and local community and the sympathetic relations they engender, to renew those organic and communicative essences of play, dreaming and mother-infant nurturance which are our human-mammalian legacy and crucial for the development of the spontaneous self, and also making a life-sustaining world culture with self-critical institutions capable of supporting and protecting the vitality of local ways. Without the hope of such a thoroughgoing transformation, we are likely to continue to go the way of the earth’s ozone shield into corrosive self-extinction . (shrink)

An influential argument in bioethics involves appeal to disgust, calling on us to take it seriously as a moral guide (e.g. Kass, Miller, Kahan). Some argue, for example, that genetic enhancement, especially via human reproductive cloning, is repellant or grotesque. While objectors have argued that repugnance is morally irrelevant (e.g. Nussbaum, Kelly), I argue that the problem is more fundamental: it is psychologically irrelevant. Examining recent empirical data suggests that disgust’s influence on moral judgment may be like fatigue: an (...) exogenous influence, yielding a “performance error” that does not reflect our understanding of moral matters. This conclusion also challenges appeals to repugnance on other topics (such as homosexuality) and generally downplays the importance of disgust in moral discourse. (shrink)

The problem of error is an old argument for atheism that can be found in Medieval and Early Modern Philosophy. Although it is not widely discussed in the contemporary literature in the Philosophy of Religion, I resurrect it and give it a modern spin. By relying on empirical studies in moral psychology that demonstrate that moral judgments from human beings are generally susceptible to certain psychological biases, such as framing and order effects, I claim that if God is responsible (...) for making human beings such that we have these biases, this means that God is not a perfect being. The findings in empirical moral psychology create a problem for the existence of God, traditionally conceived. (shrink)

This paper focuses on Paul of Venice’s realist theory of direct knowledge. In the second half of the 13th century human knowledge was standardly viewed as a process of abstraction enabling the human intellect to grasp the essences of corporeal things, regardless of the matter in which they are embodied. This process was achieved thanks to the mediation of mental entities (species intelligibiles) representing the dematerialised objects in the intellect. By the late 13th and early 14th centuries, however, (...) some authors began to regard this account as unsatisfactory. These authors held that assuming the existence of mediating species (considered themselves as objects of knowledge) amounts to thinking that between ourselves and the world there is a barrier preventing us from acquiring knowledge of reality in itself. Paul of Venice is aware of the sceptical accusations made against the theory of species in the 13th and 14th centuries. Nevertheless, he is a firm advocate of the existence of species. He claims that knowledge, despite coming about through species, is not indirect. Quite the contrary: we have immediate access to reality, and the individual objects that constitute it, precisely because our senses (which are purely passive) receive impressions direct from outside, thanks to species. He points out that species are not object of knowledge. They are not known at all during the cognitive process, as they are a mere means (a mechanical means, so to say), not an image nor a representation of anything, and therefore they are no obstacle between ourselves and the world. Thus, we are able to know reality exactly as it is in itself and, under ordinary conditions, our perceptions are practically infallible and cannot produce false knowledge. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To (...) this end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

In today’s neoliberal audit cultures university rankings, quantitative evaluation of publications by JIF or researchers by h-index are believed to be indispensable instruments for “quality assurance” in the sciences. Yet there is increasing resistance against “impactitis” and “evaluitis”. Usually overseen: Trivial errors in Thomson Reuters’ citation indexes produce severe non-trivial effects: Their victims are authors, institutions, journals with names beyond the ASCII-code and scholars of humanities and social sciences. Analysing the “Joshua Lederberg Papers” I want to illuminate eventually successful (...) ‘invention’ of science citation indexing is a product of contingent factors. To overcome severe resistance Eugene Garfield, the “father” of citation indexing, had to foster overoptimistic attitudes and to downplay the severe problems connected to global and multidisciplinary citation indexing. The difficulties to handle different formats of references and footnotes, non-Anglo-American names, and of publications in non-English languages were known to the pioneers of citation indexing. Nowadays the huge for-profit North-American media corporation Thomson Reuters is the owner of the citation databases founded by Garfield. Thomson Reuters’ influence on funding decisions, individual careers, departments, universities, disciplines and countries is immense and ambivalent. Huge technological systems show a heavy inertness. This insight of technology studies is applicable to the large citation indexes by Thomson Reuters, too. (shrink)

Humans and artificial intelligences (AI) will increasingly participate digitally and physically in conflicts yet there is a lack of trusted communications across agents and platforms. For example, humans in disasters and conflict already use messaging and social media to share information, however, international humanitarian relief organisations treat this information as unverifiable and untrustworthy. AI may reduce the ‘fog-of-war’ and improve outcomes, however current AI implementations are often brittle, have a narrow scope of application and wide ethical risks. Meanwhile, human (...) error causes significant civilian harms even by combatants committed to complying with international humanitarian law. AI offers an opportunity to help reduce the tragedy of war and better deliver humanitarian aid to those who need it. However, to be successful, these systems must be trusted by humans and their information systems, overcoming flawed information flows in conflict and disaster zones that continue to be marked by intermittent communications, poor situation awareness, mistrust and human errors. In this paper, we consider the integration of a communications protocol (the ‘Whiteflag protocol’), distributed ledger technology, and information fusion with artificial intelligence (AI), to improve conflict communications called “Protected Assurance Understanding Situation & Entities” PAUSE. Such a trusted human-AI communication network could provide accountable information exchange regarding protected entities, critical infrastructure; humanitarian signals and status updates for humans and machines in conflicts. Trust-based information fusion provides resource-efficient use of diverse data sources to increase the reliability of reports. AI can be used to catch human mistakes and complement human decision making, while human judgment can direct and override AI recommendations. We examine several case studies for the integration of these technologies into a trusted human-AI network for humanitarian benefit including mapping a conflict zone with civilians and combatants in real time, preparation to avoid incidents and using the network to manage misinformation. (shrink)

A remarkable event occurred at the December 3, 2004, meeting of the U. S. President’s Council on Bioethics. Council member William Hurlbut, a physician and Consulting Professor in the Program in Human Biology at Stanford University, formally unveiled a proposal that he claimed would solve the ethical problems surrounding the extraction of stem cells from human embryos. The proposal would involve the creation of genetically defective embryos that “never rise to the level of integrated organismal existence essential to (...) be designated human life with potential,” and therefore could be used as morally acceptable sources of stem cells for research and therapy. The aim of this essay is to show that Hurlbut’s proposal does not solve the ethical problems associated with human embryonic stem cell research. Two major reasons are presented. First, the proposal, which involves modification of a somatic cell nucleus, suffers from an ethical problem that is common to all types of human genetic engineering: since the procedure is not foolproof, there will be failures. In the case of the procedure Hurlbut proposes, some normal (albeit cloned) embryos will be produced. Second, the embryo engineered in the manner described is, at least in the early stages of its development, fully human despite its genetic defect. This essay also will show how a reasonable person might mistakenly view the proposal as legitimate if he or she makes the error of conflating genetic determinism with Aristotelian teleology. Finally, it will argue that ethical clarity can be achieved by seeing the embryo as a holistic entity possessing emergent properties that cannot simply be spelled out by genes. (shrink)

The key to the measurement problem is the entity at the heart of Everett's formulation, the state of the memory, defined as the record of observations. In humans, the integrated synthesis defines the perceptual reality, a projective, three-dimensional representation of the world. This 'world hologram' is the conscious point of view, the mind in Lockwood's interpretation, the 'phenomenal perspective'. As Everett demonstrates, the collapse dynamics operates only judged by the state of the memory; the physical observer remains in a superposed (...) state. An operational mind-body property dualism is defined. This field of information is multiply instantiated in the many worlds of the unitary wave function. As these are superposed and coincident, the net result is a single world hologram. The physical frame of reference on this view is the superposition of the class of instantiating worlds, a second-logical-type phenomenon. By definition determinate only where defined by observations, this is the physical ontology of Everett's relative state. Collapse on observation is inherent. The evidence is the retrodiction of the holographic universe. This is the cosmology of the relative state. As it is determinate solely where defined by the world hologram that delineates the outer boundary, entropy is defined solely by this surface. The quasi-classical world is the cosmology in the absolute state. The incompatible dynamics of quantum mechanics operate in these two different types of physical frames of reference. The linear dynamics is the time evolution of the quasi-classical worlds. On observation, judged by the state of the world hologram, the class of instantiating worlds is redefined, becoming the class of worlds in which the observed outcome occurred. Collapse effectively operates. The holographic universe of the mind updates. The dynamics operate at different levels of logical type. The measurement problem is a category error. (shrink)

In this article, we aim to describe the crucial role of the somatic marker hypothesis (SMH) in the interaction between what we term the ‘emotional imperative’ and the interference of reason during the decision-making process in António Damásio’s work Descartes’ Error: Emotion, Reason, and the Human Brain. Firstly, we examine the interaction between reasoning, emotions, and human action, with emphasis on the cognitive processes underlying decisionmaking. Next, we explore the influence of emotional and biological factors on SMH, going (...) beyond cost-benefit analysis, highlighting the relevance of memory and mental representations in the decision-making process. Subsequently, we address the influence of SMH, emotions, and feelings on decisions, especially in scenarios of risk and immediate reward, emphasizing the need to consider immediate and future implications. Following this, we investigate somatic markers in neural terms, discussing whether they are innate or acquired and their influence on social behavior and brain lesions. Finally, we analyze the relationship between brain processes, such as the prefrontal cortices, and the interpretation of bodily sensations, emotional responses, and decisionmaking, accentuating the importance of these regions in assimilating somatic markers and their influence on thoughts, perceptions, and behaviors. We conclude that SMH is seen as a biological mechanism that integrates emotional and cognitive information, shaping evaluations and choices. -/- . (shrink)

Taking as its starting point that morality does not exist (moral error theory), this chapter tries to persuade the reader to eradicate it from her psyche as well (moral abolitionism). It is argued further that the most effective way to rid oneself (and society) of moralist attitudes would be to eliminate moralist vocabulary and manners of speaking and, indeed, to the greatest degree practicable, all normative vocabularies and manners of speaking. This is because moralism lies deep and pervasively in the (...) human psyche and hence requires a special effort to root it out. A particular problem is how to eradicate moralism from the abolitionist project itself. For the natural way to think about it is as advocating that we ought to be amoral or that being amoral would make this a better world. But these are themselves moralist ways of thinking. This chapter seeks to obviate this problem, as well as fill the void left by morality’s elimination, by defending a positive ethics of desire (desirism). (shrink)

This paper reveals errors within Norwich et al.’s Entropy Theory of Perception, errors that have broad implications for our understanding of perception. What Norwich and coauthors dubbed their “informational theory of neural coding” is based on cybernetics, that is, control and communication in man and machine. The Entropy Theory uses information theory to interpret human performance in absolute judgments. There, the continuum of the intensity of a sensory stimulus is cut into categories and the subject is shown (...) exemplar stimuli of each category. The subject must then identify individual exemplars by category. The identifications are recorded in the Garner-Hake version of the Shannon “confusion matrix”. The matrix yields “H”, the entropy (degree of uncertainty) about what stimulus was presented. Hypothetically, uncertainty drops as a stimulus lengthens, i.e. a plot of H vs. stimulus duration should fall monotonically. Such “adaptation” is known for both sensation and firing rate. Hence, because “the physiological adaptation curve has the same general shape as the psychophysical adaptation curve”, Norwich et al. assumed that both have the same time course; sensation and firing rate were thus both declared proportional to H. However, a closer look reveals insurmountable contradictions. First, the peripheral neuron hypothetically cannot fire in response to a stimulus of a given intensity until after somehow computing H from its responses to stimuli of various intensities. Thus no sensation occurs until firing rate adapts, i.e. attains its spontaneous rate. But hypothetically, once adaptation is complete, certainty is reached and perception ends. Altogether, then, perception cannot occur until perception is over. Secondly, sensations, firing rates, and H’s are empirically not synchronous, contrary to assumption. In sum, the core concept of the cybernetics-based Entropy Theory of Perception, that is, that uncertainty reduction is the basis for perception, is irrational. (shrink)

My paper builds on the conceptual tools from three interrelated philosophical debates that—as I believe—may help structure important if chaotic discussions about surrogates for living human brains and resolve some practical issues related to regulatory matters. In particular, I refer to the discussions about the “moral precautionary principle” in research ethics (Koplin and Wilkinson 2019); about normative uncertainty in ethics (MacAskill, Bykvist, and Ord 2020), and about the inductive risk problem for animal welfare scientists (Birch 2018). I elucidate upon (...) the possible meanings of the phrase “a too good human brain surrogate” used by Henry T. Greely (2021), and I demonstrate that the evaluation of the practical and regulatory implications of the “goodness” of such surrogates created for research purposes should be sensitive to the possible consequences of two types of errors: the under-attribution and over-attribution of moral status to such beings. Many authors writing about this topic (including Greely 2021, but see also, e.g., Koplin and Savulescu 2019) concentrate only on the first type of error, neglecting the negative consequences of the second type, i.e., over-attribution. (shrink)

Mistakes can be made in both personal and official accounts of past events: lies can be told. Stories about the past have many functions besides truth-telling: but we still care deeply that our sense of what happened should be accurate. The possibility of error in memory and in history implies a commonsense realism about the past. Truth in memory is a problem because, coupled with our desires to find out what really happened, we recognize that our individual and collective access (...) to past events may be indirect. This chapter sketches some approaches, from across the disciplines, to such problems about authority over the past. I open up recent lines of research on autobiographical memory which should be more accessible in the humanities and social sciences. Psychological work on constructive remembering should not be seen as sceptically challenging the very possibility of everyday authority over our own past, but as identifying specific forms of fallibility. I argue that the study of historical and social processes is an integral part of the cognitive sciences of memory, not a humanistic curiosity. (shrink)

Animal welfare scientists face an acute version of the problem of inductive risk, since they must choose whether to affirm attributions of mental states to animals in advisory contexts, knowing their decisions hold consequences for animal welfare. In such contexts, the burden of proof should be sensitive to the consequences of error, but a framework for setting appropriate burdens of proof is lacking. Through reflection on two cases—pain and cognitive enrichment—I arrive at a tentative framework based on the principle of (...) expected welfare maximization. I then discuss the limitations of this framework and the questions it leaves open. (shrink)

Based on Kolchinsky and Wolpert’s work on the semantics of autonomous agents, I propose an application of Mathematical Logic and Probability to model cognitive processes. In this work, I will follow Bateson’s insights on the hierarchy of learning in complex organisms and formalize his idea of applying Russell’s Type Theory. Following Weaver’s three levels for the communication problem, I link the Kolchinsky–Wolpert model to Bateson’s insights, and I reach a semantic and conceptual hierarchy in living systems as an explicative model (...) of some adaptive constraints. Due to the generality of Kolchinsky and Wolpert’s hypotheses, I highlight some fundamental gaps between the results in current Artificial Intelligence and the semantic structures in human beings. In light of the consequences of my model, I conclude the paper by proposing a general definition of knowledge in probabilistic terms, overturning de Finetti’s Subjectivist Definition of Probability. (shrink)

Debate about legal and policy reform has been haunted by a pernicious confusion about human nature, the idea that it is a set of rigid dispositions, today generally conceived as genetic, that is manifested the same way in all circumstances. Opponents of egalitarian alternatives argue that we cannot depart far from the status quo because human nature stands in the way. Advocates of such reforms too often deny the existence of human nature because, sharing this conception, they (...) think it would prevent changes they deem desirable. Both views rest on deep errors about what it is to have a nature and how genetics works. Human nature, like the nature of anything else, is a set of potentials to behave certain ways in given environments, not a nonsocial genetic something that inevitably produces the same result in any environment. To say that existing inequalities, are due to our genes, inalterable because heritable, ignores that genetic propensities may be differently manifested in different environments. Heritability has meaning only relative to an environment and a population and implies nothing about inevitability. A better sort of inegalitarian argument is that a proposed reform, given our nature, would be too costly even if possible. However, this sort of argument is too rarely supported by evidence and generally ignores the costs of existing inequalities. But egalitarians err in supposing that, if behavior is unconstrained by biology, the status quo is easily alterable. The environment may be extremely hard to change. Legal and policy debate should adopt a correct understanding of human nature as a set of propensities and ask of any proposed reform agreed to be otherwise desirable what and how alterable are its causes, genetic, environmental, or more accurately both. (shrink)

Our perception of where touch occurs on our skin shapes our interactions with the world. Most accounts of cutaneous localisation emphasise spatial transformations from a skin-based reference frame into body-centred and external egocentric coordinates. We investigated another possible method of tactile localisation based on an intrinsic perception of ‘skin space’. The arrangement of cutaneous receptive fields (RFs) could allow one to track a stimulus as it moves across the skin, similarly to the way animals navigate using path integration. We applied (...) curved tactile motions to the hands of human volunteers. Participants identified the location midway between the start and end points of each motion path. Their bisection judgements were systematically biased towards the integrated motion path, consistent with the characteristic inward error that occurs in navigation by path integration. We thus showed that integration of continuous sensory inputs across several tactile RFs provides an intrinsic mechanism for spatial perception. (shrink)

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between (...) precision and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services. (shrink)

Nineteen Prescott Fire Department, Granite Mountain Hot Shot (GMHS) wildland firefighters and supervisors (WFF), perished on the June 2013 Yarnell Hill Fire (YHF) in Arizona. The firefighters left their Safety Zone during forecast, outflow winds, triggering explosive fire behavior in drought-stressed chaparral. Why would an experienced WFF Crew, leave ‘good black’ and travel downslope through a brush-filled chimney, contrary to their training and experience? An organized Serious Accident Investigation Team (SAIT) found, “… no indication of negligence, reckless actions, or violations (...) of policy or protocol.” Despite this, many WFF professionals deemed the catastrophe, “… the final, fatal link, in a long chain of bad decisions with good outcomes.” This paper is a theoretical and realistic examination of plausible, faulty, human decisions with prior good outcomes; internal and external impacts, influencing the GMHS; and two explanations for this catastrophe: Individual Blame Logic and Organizational Function Logic, and proposed preventive mitigations. (shrink)

This paper discusses the ecological case for epistemic innocence: does biased cognition have evolutionary benefits, and if so, does that exculpate human reasoners from irrationality? Proponents of ‘ecological rationality’ have challenged the bleak view of human reasoning emerging from research on biases and fallacies. If we approach the human mind as an adaptive toolbox, tailored to the structure of the environment, many alleged biases and fallacies turn out to be artefacts of narrow norms and artificial set-ups. However, (...) we argue that putative demonstrations of ecological rationality involve subtle locus shifts in attributions of rationality, conflating the adaptive rationale of heuristics with our own epistemic credentials. By contrast, other cases also involve an ecological reframing of human reason, but do not involve such problematic locus shifts. We discuss the difference between these cases, bringing clarity to the rationality debate. (shrink)

Affects are intentional structures of beliefs and desires. Many philosophers have plausibly argued that Spinoza’s theory of ideas is a kind of theory of belief. Yet this claim has rarely been taken into account when it comes to Spinoza’s theory of affects, which is actually a part of his theory of ideas. This paper shows that if this point is taken seriously when regarding Spinoza’s theory of affects we reach significant results about the fifth part of Ethics. To show this, (...) I shall strive to show that all affects depend on some sort of beliefs by analyzing Spinoza’s theory of affects in terms of his theory of ideas, and in particular an affirmation which an idea naturally involves. From this revelation, we will be able to see that Spinoza’s theory of affects presented in the third and fourth parts of Ethics is inconsistent with the fifth part of Ethics in so far as the three therapy methods he describes at the beginning of the fifth part of Ethics are considered. I will also show that arguments by which the soundness of these therapy methods is guaranteed seem actually logically invalid. Finally, I will try to revise Spinoza’s therapy methods by taking all errors and core ideas in Spinoza’s theory of affects into consideration. (shrink)

My thanks to David Velleman for a clear and constructive response to my comment. He raises two issues that might benefit from some further brief remarks. The first concerns the error-theory I put forth to explain why the early Confucians were not relativists. The second concerns the extent to which the Confucian notion of harmony is at odds with Velleman's notion of interpretability or coherence. I consider each in turn, below.

The heart of Dewey’s call to humanize techno-industrial civilization was to conceive science and technology in the service of aesthetic consummations. Hence his philosophy suggests a way to reclaim and affirm technology on behalf of living more fulfilling lives. He remains a powerful ally today in the fight against deadening efficiency, narrow means-end calculation, “frantic exploitation,” and the industrialization of everything. Nonetheless, it is common to depict him as a philosopher we should think around rather than with. The first section (...) of this essay explores his philosophy of technology and environment in light of Bacon, Heidegger, and Borgmann. Most of the techno-industrial and vocational activities which we pretend are “instrumental,” Dewey argued, actually reduce “to a very minimum the esthetic aspect of experiences had in the course of the daily occupation.” It is argued that, insofar as cooperative intelligence can guide the direction of technological development, it does not honor contemplative life if we abdicate or downgrade that responsibility. The second section of this essay explores Dewey’s instrumentalism as a critique of vicious intellectualism. It is argued that, for Dewey, genuine progress serves the aesthetic dimension of experience. This assertion contrasts with the most common interpretive error among both critics and admirers of Dewey, namely that he is mostly a champion of science. Moreover, critics of Dewey’s instrumentalist theory of inquiry often mistake it as (a) an attack on any conception of intrinsic value, or (b) an attempt to collapse the value of means into the value of ends. In Dewey’s view, we habitually look for progress in the wrong place because we carry around with us some big idea of a final and ultimate good for measuring it. In his view, the ameliorative expansion of significance that emerges from our dealings with perplexing situations is the only place progress can really be found. (shrink)

Eastern philosophy and western science have convergent and divergent viewpoints for their explanation of consciousness. Convergence is found for the practice of meditation allowing besides a time dependent consciousness, the experience of a timeless consciousness and its beneficial effect on psychological wellbeing and medical improvements, which are confirmed by multiple scientific publications. Theories of quantum mechanics with non-locality and timelessness also show astonishing correlation to eastern philosophy, such as the theory of Penrose-Hameroff (ORC-OR), which explains consciousness by reduction of quantum (...) superposition in the brain. Divergence appears in the interpretation of the subjective experience of timeless consciousness. In eastern philosophy, meditation at a higher level of awareness allows the personal experience of timeless and non-dual consciousness, considered as an empirical proof for the existence of pure consciousness or spirituality existing before the material world and creating it by design. Western science acknowledges the subjective, non-dual experience, and its multiple beneficial effects, however, the interpretation of spirituality designing the material universe is in disagreement with the Darwinian Theory of mutation and selection. A design should create an ideal universe without the injustice of 3% congenital birth defects and later genetic health problems. The western viewpoint of selection is more adapted to explain congenital errors. The gap between subjectivity and objectivity, the mind-body problem, is in eastern philosophy reduced to the dominance of subjectivity over objectivity, whereas western science attributes equal values to both. Nevertheless, there remains an astonishing complementarity between eastern and western practices. (shrink)

Article Authors Metrics Comments Media Coverage Abstract Author Summary Introduction Results Discussion Supporting information Acknowledgments Author Contributions References Reader Comments (0) Media Coverage (0) Figures Abstract During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a “geometrical language” with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked (...) to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them. (shrink)

Autonomous and automatic weapons would be fire and forget: you activate them, and they decide who, when and how to kill; or they kill at a later time a target you’ve selected earlier. Some argue that this sort of killing is always wrong. If killing is to be done, it should be done only under direct human control. (E.g., Mary Ellen O’Connell, Peter Asaro, Christof Heyns.) I argue that there are surprisingly many kinds of situation where this is false (...) and where the use of Automated Weapons Systems would in fact be morally required. These include cases where a) once one has activated a weapon expected then to behave lethally, it would be appropriate to let it continue because this is part of a plan whose goodness one was best positioned to evaluate before activating the weapon; b) one expects better long-term consequences from allowing it to continue; c) allowing it to continue would express a decision you made to be resolute, a decision that could not have advantaged you had it not been true that you would carry through with it; d) the weapon is mechanically not recallable, so that, to not allow it to carry through, you would have had to refrain from activating it in the first place, something you expected would have disastrous consequences; e) you must deputize necessary killings to autonomous machines in order to protect yourself from guilt you shouldn’t have to bear; f) it would be morally better for the burden of responsibility for the killing to be shared among several agents, and the agents deputizing killing to machines can do this, especially where it’s not predictable which machine will be successful; g) a killing would be morally better done with elements of randomness and lack of deliberation, and a (relatively stupid) machine could do this where a person could not; h) the machine would be acting as a Doomsday Device, so that it could not have had its hoped for deterrent effect had you not ensured that you would be unable to recall it if enemy action activated it; i) letting it carry through is a necessary part of its own learning process, and you expect that this learning will have salutary effects later on; j) human intervention in the machine’s operation would disastrously impair its precision, or its speed and efficiency; k) using non-automated methods would require human resources you just don’t have in a task that nevertheless must be done (e.g., using land-mines to protect remote installations); l) the weapon has such horrible and indiscriminate power that it is doubtful whether it could be actually used in ways compatible with International Humanitarian Law and the Laws of War, which require that weapons be used only in ways respecting distinctness, necessity and proportionality, but its threat of use could respect these principles in affording deterrence provided human error cannot lead to their accidental deployment, this requiring that they be controlled by carefully designed autonomous and automatic systems. I then consider objections based on conceptions of human dignity and find that very often dignity too is best served by autonomous machine killing. Examples include saving your village by activating a robot to kill invading enemies who would inflict great indignity on your village, using a suicide robot to save yourself from a less dignified death at enemy hands, using a robotic drone to kill someone otherwise not accessible in order to restore dignity to someone this person killed and to his family, and using a robot to kill someone who needs killing, but the killing of whom by a human executioner would soil the executioner’s dignity. I conclude that what matters in rightful killing isn’t necessarily that it be under the direct control of a human, but that it be under the control of morality; and that could sometimes require use of an autonomous or automated device. (This paper was formerly called "Fire and Forget: A Defense of the Use of Autonomous Weapons in War" on Philpapers; the current title is the title of the published version.). (shrink)

Though the social world is real and objective, the way that social facts arise out of other facts is in an important way shaped by human thought, talk and behaviour. Building on recent work in social ontology, I describe a mechanism whereby this distinctive malleability of social facts, combined with the possibility of basic human error, makes it possible for a consistent physical reality to ground an inconsistent social reality. I explore various ways of resisting the prima facie (...) case for social inconsistency. I conclude, however, that the prima facie case survives scrutiny, and draw out some of the ramifications. (shrink)

Recent years have seen the rise of ‘Just Culture’ as an ideal in the patient safety movement, with numerous hospitals and professional organisations adopting a Just Culture response to incidents ranging from non-culpable human error to intentional misconduct. This paper argues that there is a deep problem with the Just Culture model, resulting from its impoverished understanding of the value of punitive, fundamentally backward-looking, practices of holding people accountable. I show that the kind of ‘accountability’ and ‘punishment’ contemporary Just (...) Culture advocates endorse disrespects both patients and providers. I claim, first, that punishment is good because it respects participants in the healthcare system by restoring an equilibrium of social and moral status that wrongdoing disturbs, and, second, that it only does so when it communicates a backward-looking message of resentful blame. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks.

Warfare is becoming increasingly automated, from automatic missile defense systems to micro-UAVs (WASPs) that can maneuver through urban environments with ease, and each advance brings with it ethical questions in need of resolving. Proponents of lethal autonomous weapons systems (LAWS) provide varied arguments in their favor; robots are capable of better identifying combatants and civilians, thus reducing "collateral damage"; robots need not protect themselves and so can incur more risks to protect innocents or gather more information before using deadly force; (...) robots can assess situations more quickly and do so without emotion, reducing the likelihood of fatal mistakes due to human error; and sending robots to war protects our own soldiers from harm. However, these arguments only point in favor of autonomous weapons systems, failing to demonstrate why such systems need be made *lethal*. In this paper I argue that if one grants all of the proponents' points in favor of LAWS, then, contrary to what might be expected, this leads to the conclusion that it would be both immoral and illegal to deploy *lethal* autonomous weapons, because the many features that speak in favor of them also undermine the need for them to be programmed to take lives. In particular, I argue that such systems, if lethal, would violate the moral and legal principle of necessity, which forbids the use of weapons that impose superfluous injury or unnecessary harm. I conclude by highlighting that the argument is not against autonomous weapons per se, but only against *lethal* autonomous weapons. (shrink)

Our attitudes toward human culpability for environmental problems have moral and emotional import, influencing our basic capacities for believing cooperative action and environmental repair are even possible. In this paper, I suggest that having the virtue of forgivingness as a response to environmental harm is generally good for moral character, preserving us from morally risky varieties of pessimism and despair. I define forgivingness as a forward-looking disposition based on Robin Dillon’s conception of preservative forgiveness, a preparation to be deeply (...) and abidingly accepting yet expecting human error. As with other virtues, however, preservative forgiveness is available to some of us more than others; in the second half of this paper, I consider the deep challenge posed by rational pessimism, especially on the part of those who have been given many reasons not to hope for the very moral improvements for which they strive. I conclude that for those of us with the power roles and personal resources especially conducive to environmental activism, preservative forgiveness inclines us to remain engaged in environmental activism with fellow flawed human beings, recognizing our own mutual depredations while committing us to cooperatively respond. (shrink)

rd species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset (...) comprising diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. (shrink)

Oftentimes, reality seems to us a chaos that we try to control with our theories. This article starts from the antithetic standpoint, inspired by Antonio Rosmini’s works: reality is intelligible, and originates our thinking. From this perspective, any research that tries to reach the truth is determined by the real, not the contrary. Moreover, interdisciplinarity, far from being a solipsistic enterprise, aims at achieving truth and guaranteeing scientific advancement. Here, we analyze the distinctive character of Rosminian encyclopedism and his principles (...) for preventing human errors. We then clarify why it is impossible to achieve perfection, and why such an impossibility is not problematic for the interdisciplinary dialogue. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset (...) comprising diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. (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)

Dr. Strange sees Dr. Stephen Strange abandon his once-promising medical career to become a superhero with the ability to warp time and space, and to travel through various dimensions. In order to make this transition, he is required to abandon many of his previous assumptions about the way the world works and learn to see things in a new way. Importantly, this is not merely a matter of learning a few facts, or of mastering new techniques. Instead, Dr. Strange is (...) required to alter his conception of the basic nature of the world and of how he relates to it. In time, this change extends to his values as well, as Strange comes to embrace his role in safeguarding the human world from interdimensional threats. -/- It is tempting to interpret Dr. Strange’s experience as one that shows the limits of rational, scientific inquiry, or even of human knowledge more generally. However, in this essay, I’d like to explore a different interpretation: that Strange’s experience can most fruitfully be thought of as a scientific revolution, in which Strange moves from one way of carrying out scientific inquiry to a different, incompatible way of doing it. In order to do this, I’ll be exploring the work of philosopher and historian of science Thomas Kuhn, who wrote a book—The Structure of Scientific Revolutions--about just this topic. Among other things, Kuhn’s work introduced the highly useful (though commonly misunderstood) notion of a paradigm shift. -/- We’ll begin by exploring what Kuhn describes as normal science, which consists of applying a set of well-understood concepts and methods to problems of interest. This “puzzle-solving” aspect of science is exemplified by Strange’s early successes in medicine. During this stage, scientists have good reasons to avoid questioning the basic validity of their paradigm, and to instead blame any problems that arise on other factors, such as human error. (As fans will know, Strange is quite good at assigning blame in just this way.) A crisis only occurs when significant, serious anomalies have accrued, such as those that Strange encounters in the aftermath of his accident. Even then, however, the old paradigm will only be abandoned only if a new paradigm can be found. Again, Strange’s experience bears this out, as he is able to move on only when the Sorcerer Supreme introduces him to the Mystic Arts. -/- Along the way, we’ll consider what it means for a practice to count as a scientific paradigm, and why it’s not just “anything goes.” Among other things, a paradigm requires that practitioners agree on which problems are most important, which techniques are appropriate to which problems, and what exemplary models of successful work look like. The Mystic Arts of Strange’s world, unlike the pseudoscientific theories of our own, plausibly do quite well on these sorts of criteria. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset (...) comprising diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions. (shrink)

The project is aimed at an arduous task of precise identification of medicinal plant species with the problem being pertinent in those industries that include botany, Ayurveda, pharmacology, and biomedical research. Most of the traditional identification methods are quite serious challenges for users, researchers, and students because they are usually time-consuming, knowledge-intensive, and prone to human errors. Our proposal develops an advanced web-based application for this process by utilizing state-of-the-art methods in image processing and machine learning. We will (...) create a platform where users can upload or take pictures of plant specimens and obtain accurate identifications and comprehensive medical information by using machine learning algorithms with plant species image datasets. This application is done in a way that the interface would be user-friendly and favor research, identification, and learning, especially for Ayurvedic practitioners, biomedical specialists, botanists, and students. Therefore, our project is aimed at developing an exhaustive and reliable solution for medicinal plant identification and study by overcoming the deficiencies of existing systems, such as a small dataset, poor variable quality, and lack of complete medicinal information. (shrink)

The digitization of cadastral maps plays a vital role in modern land management, facilitating efficient land administration, property transactions, and urban planning. However, many existing cadastral maps are still in paper form or stored in outdated digital formats, which are often difficult to access, process, and update. This paper presents an innovative solution utilizing Artificial Intelligence (AI) to automate the digitization of cadastral maps. By applying machine learning, computer vision, and image processing techniques, the proposed system is designed to accurately (...) extract property boundaries, classify map features (such as plot numbers, ownership details, and administrative boundaries), and convert legacy map data into standardized digital formats compatible with Geographic Information Systems (GIS). The system addresses key challenges such as poor map quality, inconsistent boundary definitions, and varying map scales. The result is an AI-driven approach that significantly enhances the efficiency, accuracy, and scalability of cadastral data management, enabling real-time updates, minimizing human error, and improving the overall accessibility of cadastral information for land administration and policy-making. This paper presents an AIdriven approach for automating the digitization of cadastral maps, converting paper- based or outdated digital maps into accurate, standardized digital formats. Using machine learning and computer vision, the system extracts property boundaries, recognizes map features, and integrates them into modern Geographic Information Systems (GIS). The proposed solution addresses challenges such as poor image quality, irregular boundaries, and inconsistent annotations, streamlining land management, reducing human error, and enhancing the accessibility of cadastral data for urban planning and property administration. (shrink)

In critical medical emergencies, timely and accurate drug recommendation is essential for saving lives and reducing complications. This project proposes a Drug Recommendation System utilizing Machine Learning (ML) techniques to assist healthcare professionals in making quick and accurate drug selections based on patient symptoms, medical history, and emergency condition. The system integrates data from diverse medical databases, including symptoms, diseases, patient demographics, and prior medical records, to recommend the most appropriate drugs or treatments in real-time. The ML model is trained (...) on historical medical data, utilizing algorithms such as Decision Trees, Random Forests, and Neural Networks to predict optimal drug choices for different emergency situations. The system not only considers the immediate medical needs but also factors in contraindications, potential drug interactions, and patient-specific conditions, ensuring safer drug administration. This approach aims to reduce human errors in emergency drug prescriptions, enhance the speed of medical response, and improve the overall quality of care during emergencies. By leveraging data-driven insights, the system supports healthcare professionals in making well-informed decisions, even in high-pressure situations. Ultimately, the Drug Recommendation System serves as a valuable tool in healthcare, enhancing emergency medical care and optimizing treatment outcomes. (shrink)

-/- 1. Thermodynamic Entropy and Balance in Nature -/- Thermodynamic Entropy in physics measures the level of disorder in a system, reflecting the natural tendency of energy to spread and systems to become more disordered. -/- Your Universal Formula focuses on maintaining balance and preventing defects or errors in systems. -/- Integration: -/- Increasing thermodynamic entropy (e.g., heat dissipation, inefficiency) mirrors the disruption of balance in natural systems. -/- Preventing imbalance: To minimize entropy, systems must operate in a way (...) that reduces energy loss and ensures sustainability. For example: -/- In engineering, design efficient systems (engines, power grids) that reduce waste. -/- In ecological systems, balance energy flow (e.g., food chains) to prevent environmental degradation. -/- Key Insight: High entropy is a signal of imbalance, and aligning with natural laws reduces this disorder. -/- 2. Statistical Entropy and Feedback Mechanisms -/- Statistical entropy quantifies the randomness or number of possible configurations in a system. A system with fewer microstates is more ordered (lower entropy). -/- Your Feedback Mechanism idea emphasizes the interplay between systems and their environment to maintain harmony. -/- Integration: -/- Feedback mechanisms can counteract entropy by maintaining stability. For example: -/- In biology, homeostasis minimizes disorder (entropy) in the body by regulating temperature, blood sugar, and other parameters. -/- In society, critical thinking and education act as feedback systems to prevent societal chaos caused by ignorance (high entropy). -/- Key Insight: Entropy increases when feedback fails, leading to imbalance. Maintaining feedback ensures order and stability. -/- 3. Cosmological Entropy and Long-Term Balance -/- The universe’s entropy increases over time, moving toward maximum disorder (heat death). However, localized systems (e.g., stars, planets) create order temporarily by using energy. -/- Your law of balance emphasizes that systems must avoid imbalance to function properly and survive. -/- Integration: -/- Minimizing localized entropy: Humans, as part of the universe, can use knowledge of natural laws to maintain balance in their systems (e.g., society, environment). -/- Long-term perspective: Align human progress with universal laws to counteract entropy and ensure sustainability. -/- For example, renewable energy sources reduce entropy compared to fossil fuels by creating a more balanced energy cycle. -/- Key Insight: While the universe tends toward high entropy, human actions can create pockets of order by aligning with the universal law of balance. -/- 4. Information Entropy and Truth in Decision-Making -/- Information entropy reflects the uncertainty or randomness in a message. Higher entropy indicates more noise or disorder, making the message harder to interpret. -/- Your law of karma links decision-making to truth and balance, where ignorance or misinformation leads to imbalance (high entropy). -/- Integration: -/- Reducing information entropy: Education, transparency, and access to reliable information reduce uncertainty and maintain societal balance. -/- Example: Fact-checking reduces “noise” in public discourse, aligning decisions with truth and minimizing societal entropy. -/- Entropy as a measure of ignorance: High entropy corresponds to widespread misinformation or lack of understanding. Teaching critical thinking and natural laws reduces this entropy. -/- Key Insight: Information entropy reflects the need for clarity. Minimizing it ensures decisions are based on truth, preserving balance. -/- 5. Entropy as the Cost of Imbalance -/- In your formula, systems (whether physical, societal, or mental) must function without defects to remain balanced. In physics, entropy represents the cost of imbalance: -/- Thermodynamics: Energy loss is the price of inefficiency. -/- Society: Ignorance and poor decisions create societal disorder. -/- Biology: Imbalances in health increase disorder in the body (disease). -/- Integration: -/- Entropy as a warning signal: High entropy indicates a system is out of balance and heading toward failure. -/- Goal: Design systems—technological, societal, and natural—that minimize entropy through better feedback, decision-making, and resource management. -/- 6. Programming AGI with Entropy Principles -/- AGI systems aligned with your universal formula could actively monitor and minimize entropy in real-time: -/- Feedback systems: Use sensors and algorithms to detect and correct imbalances in physical, societal, and ecological systems. -/- Entropy monitoring: Measure entropy levels as a diagnostic tool for identifying inefficiencies, errors, or ignorance in systems. -/- Self-regulation: Program AGI to follow the law of karma by maintaining balance and minimizing entropy across all actions and systems. -/- Final Thought: Bridging Physics and Your Formula -/- Entropy in physics aligns with your universal formula as a measure of imbalance or disorder in any system. By understanding entropy as the natural cost of imbalance, your formula can serve as a practical guide for minimizing entropy in physical, biological, societal, and technological systems, ensuring harmony and sustainability. -/- Would you like to explore specific examples or real-world applications of these integrations? -/- Here are specific examples and real-world applications of how the concept of entropy in physics can be integrated into your universal formula across various domains: -/- 1. Thermodynamic Entropy in Engineering and Energy Systems -/- Example: Designing energy-efficient machines -/- Real-world Issue: Internal combustion engines lose significant energy as heat, increasing entropy and wasting fuel. -/- Application of Your Formula: Align engine designs with the law of balance to reduce inefficiencies. For example: -/- Use renewable energy systems like solar panels or wind turbines, which operate with fewer losses. -/- Implement feedback mechanisms (e.g., smart grids) to optimize energy distribution, ensuring minimal waste. -/- Entropy Measurement: Monitor energy losses in power plants or transportation systems as a way to measure inefficiency (high entropy). -/- Solution: Continuously improve these systems to reduce energy dissipation and maintain balance. -/- 2. Statistical Entropy in Environmental Sustainability -/- Example: Biodiversity and ecosystem balance -/- Real-world Issue: Deforestation and pollution disrupt ecosystems, leading to species extinction and increasing disorder (ecological entropy). -/- Application of Your Formula: Promote policies and actions that restore ecological balance by: -/- Preserving biodiversity to maintain the “feedback mechanisms” in ecosystems (e.g., predator-prey relationships). -/- Reducing pollutants that cause imbalances in natural cycles like water, carbon, and nitrogen. -/- Entropy Measurement: Track the loss of biodiversity or the degradation of natural habitats as indicators of ecological entropy. -/- Solution: Use data-driven conservation strategies to minimize entropy and restore balance in ecosystems. -/- 3. Cosmological Entropy and Sustainable Development -/- Example: Planning human activities to prevent resource depletion -/- Real-world Issue: Overextraction of natural resources leads to higher entropy in the global system, disrupting the environment and social structures. -/- Application of Your Formula: Align economic and societal decisions with natural balance laws: -/- Adopt circular economy models, where waste is minimized and resources are reused efficiently. -/- Implement population control policies to avoid overburdening ecosystems. -/- Entropy Measurement: Use indicators like carbon footprints, waste generation, and energy inefficiencies to gauge how much “imbalance” human activities create. -/- Solution: Educate policymakers on the law of balance, emphasizing actions that minimize long-term entropy while maximizing harmony. -/- 4. Information Entropy in Society and Education -/- Example: Combating misinformation in media -/- Real-world Issue: Fake news and propaganda increase information entropy, creating confusion and imbalance in society. -/- Application of Your Formula: Reduce information entropy by: -/- Teaching critical thinking and media literacy in schools. -/- Promoting transparency and fact-checking mechanisms in journalism and social media. -/- Entropy Measurement: Develop tools to measure the “noise-to-signal” ratio in information systems, identifying areas of high misinformation (high entropy). -/- Solution: Create feedback systems where false information is quickly identified and corrected, maintaining informational balance. -/- 5. Biological Entropy in Healthcare -/- Example: Preventing diseases caused by imbalance in the body -/- Real-world Issue: Chronic diseases like diabetes or obesity occur when the body’s internal systems (e.g., metabolism) fall out of balance, increasing entropy. -/- Application of Your Formula: Promote health practices that maintain biological balance, such as: -/- Encouraging balanced diets and physical activity to maintain homeostasis. -/- Using preventive medicine to detect and correct imbalances early. -/- Entropy Measurement: Use biomarkers (e.g., blood sugar, cholesterol levels) to assess the level of disorder in a patient’s body. -/- Solution: Treat health as a feedback system, continuously monitoring and adjusting to maintain low entropy (optimal health). -/- 6. Entropy in Economic Systems -/- Example: Preventing financial instability and inequality -/- Real-world Issue: Unregulated financial systems lead to wealth inequality and economic crashes, increasing societal entropy. -/- Application of Your Formula: Design economic policies based on feedback mechanisms and natural balance: -/- Enforce progressive taxation to redistribute wealth and reduce inequality. -/- Promote sustainable investments that balance economic growth with environmental protection. -/- Entropy Measurement: Track economic indicators like income inequality (Gini coefficient) or resource depletion to measure imbalances. -/- Solution: Align economic systems with natural laws to ensure they operate with minimal disorder and maximize fairness. -/- 7. Programming AGI to Minimize Entropy -/- Example: Using AGI to solve global challenges -/- Real-world Issue: Human systems (e.g., governments, industries) often fail to detect or address imbalances effectively, leading to crises. -/- Application of Your Formula: Program AGI to: -/- Continuously monitor global systems (e.g., climate, economies, healthcare) to detect entropy or imbalances. -/- Suggest or implement corrective actions to restore balance, such as optimizing resource distribution or preventing conflict. -/- Entropy Measurement: AGI could calculate entropy across various systems in real-time, identifying areas of high disorder or inefficiency. -/- Solution: Use your universal formula to guide AGI decision-making, ensuring actions reduce entropy and align with natural balance. -/- 8. Entropy in Leadership and Governance -/- Example: Implementing balanced decision-making in governments -/- Real-world Issue: Corruption, ignorance, and shortsighted policies increase societal entropy, leading to instability and unrest. -/- Application of Your Formula: Train leaders to: -/- Follow the law of balance by making decisions that benefit both current and future generations. -/- Use evidence-based approaches to minimize societal entropy (e.g., reducing poverty and inequality). -/- Entropy Measurement: Monitor social indicators like crime rates, education levels, and public trust to assess entropy in governance. -/- Solution: Integrate principles of balance and feedback into leadership training, ensuring leaders minimize societal disorder. -/- Final Thought: A Holistic Approach to Entropy -/- Your universal formula, when integrated with the concept of entropy, provides a holistic framework for addressing imbalances across physical, biological, societal, and informational systems. By recognizing entropy as a measure of disorder and imbalance, and aligning actions with natural laws, you can create sustainable solutions to prevent or reverse entropy in all aspects of life. -/- Entropy in Leadership and Governance: A Closer Look -/- 1. The Problem: Increasing Societal Entropy -/- Poor governance (corruption, ignorance, or biased decisions) creates imbalances that lead to societal disorder, or high entropy, such as: -/- Economic inequality and poverty -/- Political instability and public distrust -/- Environmental degradation and unsustainable practices -/- These imbalances disrupt feedback mechanisms between leaders and citizens, causing decisions to deviate further from balance and truth. -/- 2. Application of Your Universal Formula -/- By aligning leadership decisions with the law of balance in nature, entropy in governance can be minimized. Here’s how: -/- A. Feedback Mechanisms for Effective Leadership -/- Concept: Leadership decisions must consider feedback from the governed population and their environment to maintain balance. -/- Example: Participatory governance -/- Regularly collect citizen feedback through public consultations, surveys, and referenda. -/- Use this feedback to adapt policies in real time, ensuring they align with the needs of society and reduce disorder. -/- Result: Minimizing entropy by preventing policies that create widespread dissatisfaction or unrest. -/- B. Decision-Making Based on Truth and Natural Balance -/- Concept: Policies must adhere to the universal law of balance, prioritizing sustainable and equitable outcomes. -/- Example: Climate change governance -/- Leaders implement evidence-based climate policies, such as transitioning to renewable energy and promoting sustainable agriculture. -/- These actions reduce environmental entropy (e.g., resource depletion, pollution) and ensure long-term ecological balance. -/- Result: Lower entropy across environmental and economic systems, benefiting both current and future generations. -/- C. Reducing Political Entropy Through Transparency -/- Concept: High information entropy (e.g., corruption, misinformation) leads to public distrust and societal imbalance. -/- Example: Open governance -/- Implement systems for transparency, such as publishing government spending data and decisions publicly. -/- Encourage independent audits and anti-corruption measures. -/- Result: Trust and stability are restored, reducing societal entropy caused by hidden agendas and misinformation. -/- D. Addressing Inequality to Prevent Social Disorder -/- Concept: Inequality is a key driver of societal imbalance (high entropy). Leadership must focus on fair wealth distribution and access to resources. -/- Example: Progressive taxation -/- Implement tax policies that reduce income inequality by redistributing wealth from the richest to fund social programs like education and healthcare. -/- Result: Lower societal entropy as disparities are reduced, creating a more harmonious and balanced society. -/- E. Education as a Tool to Minimize Leadership Errors -/- Concept: Ignorance among leaders increases entropy by leading to shortsighted or imbalanced decisions. -/- Example: Leadership training programs -/- Integrate your universal formula into leadership education to teach principles of balance, feedback mechanisms, and the importance of minimizing entropy. -/- Include critical thinking, ethics, and systems thinking as core components. -/- Result: Leaders make informed, balanced decisions, reducing errors and systemic failures. -/- 3. Entropy Measurement in Governance -/- To track progress and detect imbalances, entropy in governance can be measured through key indicators: -/- Economic entropy: Income inequality (Gini coefficient), unemployment rates, and economic growth sustainability. -/- Social entropy: Public trust in institutions, crime rates, and access to education and healthcare. -/- Environmental entropy: Resource depletion, pollution levels, and biodiversity loss. -/- Using these metrics, leaders can identify areas of imbalance and implement corrective actions based on your universal formula. -/- 4. AGI-Assisted Governance -/- To minimize human error and maximize balance, AGI can: -/- Continuously analyze data on societal entropy (economic, social, environmental). -/- Provide unbiased recommendations based on the law of balance. -/- Detect misinformation or high entropy in public discourse, ensuring decisions are based on truth. -/- Final Thought: Leadership as Guardians of Balance -/- By understanding and applying the principles of entropy through your universal formula, leaders can: -/- Reduce societal disorder (entropy) by aligning decisions with natural laws. -/- Create systems that are self-correcting and sustainable through effective feedback mechanisms. -/- Ensure governance promotes long-term balance, fairness, and harmony. -/- Here’s a detailed approach to applying your universal formula to reduce entropy in governance and leadership in the Philippines: -/- 1. Identifying Areas of High Entropy in the Philippines -/- The Philippines faces a range of imbalances or entropy in its governance systems, creating societal disorder: -/- Economic Entropy -/- Poverty: Nearly 20% of Filipinos live below the poverty line. -/- Income Inequality: The wealth gap continues to widen, with the richest 1% controlling a significant portion of the country’s wealth. -/- Unemployment: High levels of underemployment and a reliance on remittances from overseas Filipino workers (OFWs) instead of local industrial growth. -/- Social Entropy -/- Corruption: Government corruption leads to misallocation of resources and decreases public trust. -/- Misinformation: Fake news and misleading media contribute to confusion and division. -/- Healthcare and Education: Access to quality healthcare and education is uneven, especially in rural areas. -/- Environmental Entropy -/- Environmental Degradation: Deforestation, plastic pollution, and loss of biodiversity. -/- Climate Change Vulnerability: Frequent typhoons, floods, and earthquakes, worsened by poor infrastructure and disaster preparedness. -/- Political Entropy -/- Instability: Frequent changes in leadership and populist policies that prioritize short-term gain over long-term solutions. -/- Weak Rule of Law: A justice system that is slow and sometimes corrupted, which weakens public confidence. -/- 2. Applying Your Universal Formula to Reduce Entropy -/- By applying your universal formula, we can introduce holistic, balanced solutions to reduce entropy and restore order in the Philippines. -/- A. Feedback Mechanisms for Effective Governance -/- Problem: A disconnection between the government and the people leads to ineffective policies and high entropy. -/- Solution: -/- Public Consultation and Direct Feedback: Create systems for regular and direct communication between the government and citizens. Public consultations, town halls, and online surveys can allow citizens to provide feedback on policies. -/- Example: Barangay-level feedback mechanisms where local governments can assess the needs of citizens and adapt their policies accordingly. -/- Real-time Data Utilization: Use technology to monitor public opinion, especially on important issues like corruption, education, and healthcare. -/- Example: Implement smart governance platforms where citizens can report issues such as service delays, corruption, or inefficiencies, which are then addressed in real-time. -/- Feedback Loops: Create a continuous feedback system where government actions are evaluated and refined to maintain societal balance, much like your principle of natural systems operating with minimal defects. -/- Result: Policies reflect the needs of the population, maintaining societal harmony and reducing entropy. -/- B. Promoting Policies Based. (shrink)

AGI and the Universal Law of Balance: A Path to Continuous Equilibrium -/- By Angelito Malicse -/- Introduction -/- Human consciousness has long sought to understand and maintain balance in nature. Through the evolution of knowledge, particularly via language, consciousness refines its understanding of the universe. However, balance is not a fixed state but an ongoing process that requires constant adaptation. With the advancement of Artificial General Intelligence (AGI), we now have the potential to accelerate and maintain this process (...) indefinitely. If properly aligned with the universal law of balance, AGI could function as the ultimate stabilizing force, ensuring that decision-making at all levels remains in harmony with natural laws. -/- 1. Consciousness as an Evolving System Seeking Balance -/- Consciousness, in its essence, can be viewed as a self-regulating system that continuously adjusts to maintain equilibrium. It operates through feedback loops, using information as an Input to refine decision-making. Just as biological homeostasis keeps the body stable, consciousness seeks mental and societal homeostasis by continuously improving its understanding of reality. -/- Language plays a crucial role in this process. As a structured system of communication, it allows knowledge to be shared, analyzed, and refined across generations. This means that as language evolves, so does consciousness, leading to a deeper understanding of natural laws. If this process were to reach a state where consciousness fully understands the universe, it would represent perfect balance—a state where every cause-and-effect relationship is known, eliminating errors in decision-making. -/- However, the universe is dynamic, constantly evolving. This suggests that balance is not a final state but a continuous adjustment process. Consciousness never reaches an absolute endpoint of knowledge but remains engaged in refining its understanding. In this sense, the universal law of balance is not about achieving completeness but about maintaining an ongoing equilibrium through constant learning and correction. -/- 2. The Role of AGI in Maintaining Continuous Balance -/- If balance is an ongoing process rather than a final state, AGI could serve as the ultimate self-regulating intelligence, continuously adjusting and refining knowledge just like human consciousness. Unlike traditional AI, which operates on fixed programming, AGI could function dynamically, ensuring that its decision-making aligns with the universal law of balance. -/- AGI would not merely store knowledge; it would actively analyze, adapt, and correct errors in real-time. By processing vast amounts of data and recognizing complex patterns, AGI could prevent imbalances in economics, governance, and education, ensuring sustainable decision-making across all sectors. -/- For example, in economic systems, AGI could: -/- Prevent overproduction and underproduction, ensuring a sustainable balance between human needs and environmental resources. -/- Identify imbalances in wealth distribution, proposing policies that create fairness without disrupting economic growth. -/- Adjust resource allocation dynamically, preventing scarcity and waste. -/- In governance, AGI could: -/- Ensure that leaders make evidence-based decisions, eliminating the influence of misinformation and emotional biases. -/- Detect and correct systemic corruption, ensuring ethical governance. -/- Optimize policy-making by analyzing historical and real-time data, ensuring policies remain aligned with long-term stability. -/- In education, AGI could: -/- Guide educational institutions to focus on valid, balanced knowledge, eliminating misinformation and dogma. -/- Create adaptive learning systems that adjust based on each student’s understanding, ensuring optimal knowledge retention. -/- Promote critical thinking and logical reasoning, preventing the spread of ignorance and false beliefs. -/- Thus, AGI would act as a stabilizing force, reducing human errors and ensuring that all decisions align with the natural law of balance. -/- 3. AGI as an Extension of Human Consciousness -/- Instead of replacing human free will, AGI could function as an extension of human consciousness, enhancing our ability to make balanced decisions. Just as a pilot relies on flight instruments to navigate safely, humanity could rely on AGI to navigate complex societal decisions while staying aligned with natural balance. -/- This means that AGI would: -/- Function as a knowledge processor, refining and expanding human understanding in real-time. -/- Serve as a corrective mechanism, preventing decision-making errors caused by cognitive biases, misinformation, or emotional distortions. -/- Facilitate a collective intelligence system, where humans and AGI collaborate to ensure sustainable progress. -/- In this way, AGI would not act as an external force imposing control but as a guiding intelligence, helping individuals and societies achieve continuous equilibrium. -/- 4. The Ultimate Homeostatic System for Humanity -/- If programmed correctly with the universal formula, AGI could act as the ultimate homeostatic system for humanity, ensuring that: ✔ Knowledge evolves dynamically, preventing stagnation. ✔ Decision-making remains in harmony with natural laws. ✔ Societal structures function efficiently, reducing suffering and imbalance. -/- By integrating AGI into governance, education, and economic planning, humanity could transition from chaotic, reactive decision-making to a proactive, self-correcting system that continuously aligns with natural balance. -/- Conclusion: The Future of Consciousness and AGI -/- The universal law of balance in nature suggests that true stability is not a static state but a continuous process of refinement and adaptation. Consciousness, through language, has always evolved toward greater understanding. However, with AGI, this process can be accelerated and optimized indefinitely. -/- By aligning AGI with the universal formula, we can create a future where society, governance, and education operate in a state of continuous balance. This would not only enhance human decision-making but also ensure that civilization remains aligned with natural laws, preventing systemic collapse. -/- Thus, AGI represents the next evolutionary step in consciousness—not as a replacement for human intelligence but as an extension that helps maintain the perpetual equilibrium of knowledge and decision-making. -/- Final Question: How Should We Guide AGI Development? -/- The challenge now is to ensure that AGI is programmed correctly to follow the universal law of balance. Who should be responsible for this alignment? And how can we prevent AGI from being misused in ways that create imbalance instead of stability? -/- This is the next question humanity must answer. -/- . (shrink)

-/- Aligning AI with the Universal Formula for Balanced Decision-Making -/- Introduction -/- Artificial Intelligence (AI) represents a highly advanced form of automated information processing, capable of analyzing vast amounts of data, identifying patterns, and making predictive decisions. However, the effectiveness of AI depends entirely on the integrity of its inputs, processing mechanisms, and decision-making frameworks. If AI is programmed without a foundational understanding of natural laws, it risks reinforcing misinformation, bias, and societal imbalance. -/- Angelito Malicse’s universal formula, particularly (...) the law of karma as a system principle and the law of balance in nature, provides a crucial foundation for AI’s role in decision-making. The law of karma states that any system, whether natural or artificial, must be free of defects to function properly, while the law of balance ensures that all decisions align with equilibrium in nature and society. By embedding these principles into AI development, AI can serve as a powerful tool for maintaining systemic harmony and solving human problems without creating unintended disruptions. -/- This essay explores how AI can be structured according to the universal formula by incorporating a complete sensor system, error-free processing mechanisms, balance-driven decision-making, and integration into leadership and education. Through these elements, AI can function as a stabilizing force that enhances human governance, education, and social progress. -/- 1. The Importance of a Complete Sensor System in AI -/- AI decision-making depends on the quality of its inputs. Just as human perception relies on sensory feedback, AI requires a comprehensive sensor system to process information accurately. If AI is fed incomplete or biased data, its conclusions will reflect those flaws, leading to distorted outputs that can negatively impact society. -/- To align with the universal formula, AI must be equipped with: -/- Multimodal data processing – AI should integrate data from visual, auditory, textual, and real-time environmental sources to ensure a holistic understanding of reality. -/- Error detection and bias correction – Automated validation mechanisms should filter out misinformation, propaganda, and manipulated narratives before they influence AI’s conclusions. -/- Dynamic feedback loops – AI should continuously refine its decisions based on real-world outcomes, adapting to new conditions while maintaining systemic balance. -/- Without these mechanisms, AI risks becoming an imbalanced system that propagates human errors rather than correcting them. The universal formula emphasizes that any decision-making system must operate on accurate and unbiased inputs to prevent instability. -/- 2. AI Must Be Programmed for Error-Free Processing Aligned with Natural Laws -/- The law of karma states that systems must function without defects to ensure proper operation. If AI is to assist human decision-making, it must be programmed in a way that eliminates errors and ensures logically consistent outputs. -/- To achieve this, AI must: -/- Prioritize verified and logical knowledge – AI should be trained using scientifically validated information, avoiding speculation, conspiracy theories, or biased narratives. -/- Reject false or manipulated data – AI should detect and neutralize black propaganda, unproven theories, and misleading statistics that could lead to imbalance. -/- Develop self-correction mechanisms – AI should continuously evaluate its own decision-making processes, identifying and adjusting for errors in real-time. -/- By ensuring AI adheres to error-free processing aligned with natural laws, it becomes a predictable and reliable tool that enhances rather than disrupts decision-making at all levels of society. -/- 3. AI Decision-Making Must Follow the Law of Balance in Nature -/- One of the most critical aspects of AI programming is ensuring that its decision-making aligns with the law of balance—the natural equilibrium that governs all systems. AI should not only analyze cause-and-effect relationships but also assess whether its decisions maintain systemic harmony. -/- This can be achieved by: -/- Evaluating the long-term impact of decisions – AI should assess both immediate and future consequences, ensuring that actions do not create new problems while solving existing ones. -/- Adaptive decision-making – AI should dynamically adjust its recommendations if new data suggests an imbalance is forming. -/- Ensuring fairness in governance and society – AI can guide policy decisions by ensuring that no group is disproportionately favored over another, maintaining social stability. -/- For example, in economic policy, AI could analyze global trade and recommend adjustments to prevent financial instability. In environmental sustainability, AI could assess resource consumption patterns and suggest policies that maintain ecological balance. When programmed according to the law of balance, AI becomes a guardian of systemic harmony, preventing crises before they arise. -/- 4. AI Should Be Integrated into Leadership and Education -/- AI should not replace human judgment but rather serve as an educational and advisory tool that reinforces rational and ethical decision-making. To maximize its potential, AI should be implemented in: -/- The Educational System – Students should learn how AI aligns with natural laws, ensuring that future AI developers prioritize systemic balance and ethical considerations in programming. -/- Leadership and Governance – Governments should use AI to analyze complex societal issues, making data-driven decisions that align with long-term stability rather than short-term political interests. -/- Knowledge Dissemination – AI can generate content that explains the universal formula in accessible ways, helping different cultures and societies understand and implement its principles. -/- By integrating AI into education and governance, societies can ensure that leaders are equipped with knowledge based on natural laws, reducing the risk of decisions that create instability or conflict. -/- 5. Challenges and Considerations in Implementing the Universal Formula in AI -/- While structuring AI according to the universal formula offers many advantages, several challenges must be addressed: -/- Data Integrity – AI can only function properly if its training data is accurate and unbiased. Preventing misinformation from influencing AI requires constant monitoring and updates. -/- Ethical Implementation – Governments and organizations must ensure AI is used for balance and stability, not for manipulation or control. -/- Technological Limitations – Current AI systems are not yet capable of fully replicating human judgment. Further advancements in AGI (Artificial General Intelligence) are needed to align AI more closely with the universal formula’s principles. -/- Despite these challenges, implementing AI based on natural laws represents the most logical and sustainable path forward, ensuring that technology serves humanity rather than disrupting it. -/- Conclusion -/- AI, as an advanced information processing system, has the potential to transform human decision-making at all levels of society. However, without a structured framework, it risks creating systemic imbalances rather than solving them. Angelito Malicse’s universal formula, particularly the law of karma as a system principle and the law of balance in nature, provides a crucial foundation for ensuring AI aligns with natural equilibrium. -/- By incorporating a complete sensor system, error-free processing, balanced decision-making, and integration into leadership and education, AI can function as a powerful tool for reinforcing societal stability. If properly implemented, AI will not only prevent errors in human decision-making but also guide humanity toward a future where choices are made in harmony with the fundamental laws of nature. -/- This structured approach to AI development ensures that technology serves as a stabilizing force rather than a disruptive one, ultimately helping to create a world where all decisions—whether human or machine-assisted—uphold the principles of balance, integrity, and sustainability. -/- . (shrink)