The relative efficiency of an action is a central criterion in action control and can be used to predict others’ behavior. Yet, it is unclear when the ability to predict on and reason about the efficiency of others’ actions develops. In three main and two follow-up studies, 3- to 6-year-old children (n = 242) were confronted with vignettes in which protagonists could take a short (efficient) path or a long path. Children predicted which path the protagonist would take (...) and why the protagonist would take a specific path. The 3-year-olds did not take efficiency into account when making decisions even when there was an explicit goal, the task was simplified and made more salient, and children were questioned after exposure to the agent’s action. Four years is a transition age for rational action prediction, and the 5-year-olds reasoned on the efficiency of actions before relying on them to predict others’ behavior. Results are discussed within a representational redescription account. (shrink)

The folk Psychology frames propositional attitudes as fundamental theoretical entities for the construction of a model designed to predict the behavior of a subject. A trivial, such as grasping a pen and writing reveals - something complex - about the behavior. When I take a pen and start writing I do, trivially, because I believe that a certain object in front of me is a pen and who performs a specific function that is, in fact, that of writing. When I (...) believe that the object that stands before me is a pen, I am in relation to "believe" with the propositional content: that in front of me is a pen. Philosophers of the proposition, from Frege onwards, have dedicated their studies to the analysis of what kinds of entities are the propositional attitudes. Jerry Fodor says that now, the proper prediction of the psychology of common sense, can not be questioned and that the propositional attitudes represent the most effective way to describe our behavior. What Fodor says, however, is that propositional attitudes function, but not how they work. Most philosophers interested in the issue, we are dedicated to the search for a theory that can account consistently both a semantics for propositional attitudes, both of these entities that seem to cause the behavior of a rational subject. There are two main paradigms in the theory of the proposition that contributed to the discussion of the propositional attitudes. One is the one that begins with Gottlob Frege, the other with Bertrand Russell. Defenders of Frege argue that the paradigm scrub objects and properties can not be constituents of the propositional content which have a purely conceptual. In other words, the philosophers belonging to the paradigm of Frege, but not all, mean that you can test in a rigorous way the truth conditions of propositional attitudes. Who defends the russellian’s paradigm argues that the propositional content are made by the objects and properties on which propositional attitudes relate. The purpose of this article is not to rebuild - in detail - both paradigms, nor to reconstruct one but, in a sense, my work will be a completely partial objective is to demonstrate how the paradigm is more profitable russell not only to make a coherent semantic theory for propositional attitudes2 but also to predict the behavior of a rational subject thing, completely innovative, given the repeated objections in contemporary literature3. At the end of this paper will be drafted a proposal to build a consistent model to predict the behavior,of a rational agent, based on a referential theory of propositional attitudes. (shrink)

This article is a comparative study between predictive processing (PP, or predictive coding) and cognitive dissonance (CD) theory. The theory of CD, one of the most influential and extensively studied theories in social psychology, is shown to be highly compatible with recent developments in PP. This is particularly evident in the notion that both theories deal with strategies to reduce perceived error signals. However, reasons exist to update the theory of CD to one of “predictive dissonance.” First, the hierarchical PP (...) framework can be helpful in understanding varying nested levels of CD. If dissonance arises from a cascade of downstream and lateral predictions and consequent prediction errors, dissonance can exist at a multitude of scales, all the way up from sensory perception to higher order cognitions. This helps understand the previously problematic dichotomy between “dissonant cognitive relations” and “dissonant psychological states,” which are part of the same perception-action process while still hierarchically distinct. Second, since PP is action-oriented, it can be read to support recent action-based models of CD. Third, PP can potentially help us understand the recently speculated evolutionary origins of CD. Here, the argument is that responses to CD can instill meta-learning which serves to prevent the overfitting of generative models to ephemeral local conditions. This can increase action-oriented ecological rationality and enhanced capabilities to interact with a rich landscape of affordances. The downside is that in today’s world where social institutions such as science a priori separate noise from signal, some reactions to predictive dissonance might propagate ecologically unsound (underfitted, confirmation-biased) mental models such as climate denialism. (shrink)

Abstract: The standard picture of rationality requires that the agent acts so as to realize her most preferred alternative in the light of her own desires and beliefs. However, there are circumstances where such an agent can predict that she will act against her preferences. The story of Ulysses and the Sirens is the paradigmatic example of such cases. In those circumstances the orthodoxy requires the agent to be ‘sophisticated’. That is to say, she should take into account her expected (...) future choices and prevent her future self to act in certain ways. She should ‘bind’ herself to a certain course of action. This is a form of causal commitment. It is generally recognized that this form of self-commitment is the only one that is available to a rational agent. Rational commitment, where the agent gives herself a reason to act in a certain way rather than making herself act in that way, is considered not feasible. In this paper, I question this verdict. I sketch the broad outlines of a model of rational commitment, which takes as its starting point Michael Bratman’s ‘planning theory’ of intention. There are two important objections against this theory (one by John Broome and one by the Dutch philosopher Govert den Hartogh.) Both criticisms claim that such a theory is a form of ‘bootstrapping’ reasons for action into existence. In the remainder of the paper, I will defend the theory against these objections. This way, I hope to establish that defending the feasibility of rational commitment is not an obvious mistake. (shrink)

Some arguments include imperative clauses. For example: ‘Buy me a drink; you can’t buy me that drink unless you go to the bar; so, go to the bar!’ How should we build a logic that predicts which of these arguments are good? Because imperatives aren’t truth apt and so don’t stand in relations of truth preservation, this technical question gives rise to a foundational one: What would be the subject matter of this logic? I argue that declaratives are used to (...) produce beliefs, imperatives are used to produce intentions, and beliefs and intentions are subject to rational requirements. An argument will strike us as valid when anyone whose mental state satisfies the premises is rationally required to satisfy the conclusion. For example, the above argument reflects the principle that it is irrational not to intend what one takes to be the necessary means to one’s intended ends. I argue that all intuitively good patterns of imperative inference can be explained using off-the-shelf formulations of our rational requirements. I then develop a formal-semantic theory embodying this view that predicts a range of data, including free-choice effects and Ross’s paradox. The resulting theory shows one way that our aspirations to rational agency can be discerned in the patterns of our speech, and is a case study in how the philosophy of language and the philosophy of action can be mutually illuminating. (shrink)

Alan Hájek launches a formidable attack on the idea that deliberation crowds out prediction – that when we are deliberating about what to do, we cannot rationally accommodate evidence about what we are likely to do. Although Hájek rightly diagnoses the problems with some of the arguments for the view, his treatment falls short in crucial ways. In particular, he fails to consider the most plausible version of the view, the best argument for it, and why anyone would ever (...) believe it in the first place. In doing so, he misses a deep puzzle about deliberation and prediction – a puzzle which all of us, as agents, face, and which we may be able to resolve by recognizing the complicated relationship between deliberation and prediction. (shrink)

Mental actions are things we do with our minds. Consider inferring, deliberating, imagining, remembering, calculating, and so on. I introduce a non-reductive alternative to standard causalist accounts of mental action that understands such action in terms of dispositions for performing mental actions. I call this alternative the powers framework. On the powers framework, habitual and skillful mental actions are themselves infused with practical intelligence by being expressions of the agent’s rational tendencies and capacities, respectively. The intelligence exemplified (...) in the performance of habitual and skillful mental actions stems from the agent’s having shaped the corresponding tendencies and capacities through training and practice. In this way, mental habits and skills are ‘second nature’ to us. I substantiate the powers framework by giving an account of imagining as a type of skillful mental action. In particular, I argue that imagination is a power to construct representations and select their contents as a means to performing learned behaviors like pretending, engaging with fiction, predicting others’ behavior, reasoning about possibility and necessity, reasoning hypothetically or counterfactually about contingent matters of fact, and even imagining for its own sake. I extend the account of imagining to episodic remembering. I argue that such remembering, considered as a mental action, is a kind of imagining by virtue of the agent’s constructing a representation and selecting its content as a means of performing the learned behavior of navigating her personal past. (shrink)

Deliberation is often seen as the site of human freedom, but the binding power of rationality seems to imply that deliberation is, in its own way, a deterministic process. If one knows the starting preferences and circumstances of an agent, then, assuming that the agent is rational and that those preferences and circumstances don’t change, one should be in a position to predict what the agent will decide. However, given that an agent could conceivably confront equally attractive alternatives, it (...) is an open question whether rational choice theory can ever eliminate indeterminacy. The clearest support for such a limitation comes from the “Buridan’s ass” scenario, where an agent is confronted with two (or more) equally attractive/unattractive options. Does rationality by itself have the resources needed to prevent such paralysis of action? Those who cannot accept the idea of decisional impotence devise various ways to avoid it: postulating a neutral valence, tipping the utilities, positing sub-personal influences, and bunching the options. I argue that each of these responses is either unwarranted or flawed. All parties to the debate agree that, factually, paralysis of action is not a pervasive phenomenon. This is either because (i) the utilities one assigns to two or more options can never be balanced or because (ii) thanks to some non-rational faculty (say, the will), we would not be stuck even if those utilities were perfectly counterpoised. By looking critically at four untenable responses, I aim to show that (i) is often just a dogma and (ii) is by no means a silly position. (shrink)

Within the social sciences, much controversy exists about which status should be ascribed to the rationality assumption that forms the core of rational choice theories. Whilst realists argue that the rationality assumption is an empirical claim which describes real processes that cause individual action, instrumentalists maintain that it amounts to nothing more than an analytically set axiom or ‘as if’ hypothesis which helps in the generation of accurate predictions. In this paper, I argue that this realist-instrumentalist debate about (...) rational choice theory can be overcome once it is realised that the rationality assumption is neither an empirical description nor an ‘as if’ hypothesis, but a normative claim. (shrink)

This paper analyses the phenomenon of strange, rigid beliefs through the lens of predictive processing (PP). By “strange, rigid beliefs” I refer to abstract beliefs about the world for which, according to a rational and scientific worldview, there is no evidence available, yet which people struggle to abandon even when challenged with strong counterarguments or counterevidence. Following recent PP accounts of delusion formation, I show that one explanation for such strangely persistent beliefs can be a breakdown of the predictive (...) machinery itself. However, given how common strange, rigid beliefs are, I argue that there must be another kind of explanation too – one that does not presuppose a malfunction of the prediction engine. This will lead me to develop an alternative account that I will call “hijacking beliefs”. Using the example of supernatural beliefs, I will argue that certain abstract beliefs, when adopted under the right circumstances, are especially hard to dislodge for a predictive mind, as they are evidentially self-protective. Such beliefs may be consistent with a wide range of experiences and therefore hard to falsify, and might also bias future perception, action, and model-updating in ways that make them immune to rational revision. (shrink)

In the opening lines of this article it is claimed that history is a discipline taking role as part of unique body of science. The concept of scientific rationality is presented as the criterion of demarcation between science and pseudoscience. From this statement as a starting point, it follows that the methodological grounds for scientific predictions are common for all scientific disciplines. Different aspects of scientific predicting are critically examined: thesis of symmetry, determinism and predictability, indeterminism and predictability, reflexivity of (...) predictions, prediction of novelty and progress, predictions in relation to the time of their uttering, the prediction sketch, truthfulness and regularity in implying prediction, and predictability of human actions. In the concluding section, the author admits of the possibility of constructing the theory of history, opposed to eschatological philosophy of history, as a predictive theory with a scientific basis and a theory whose specifications limit its misuse in practice. (shrink)

LLMs have dramatically improved in capabilities in recent years. This raises the question of whether LLMs could become genuine agents with beliefs and desires. This paper demonstrates an in principle limit to LLM agency, based on their architecture. LLMs are next word predictors: given a string of text, they calculate the probability that various words can come next. LLMs produce outputs that reflect these probabilities. I show that next word predictors are exploitable. If LLMs are prompted to make probabilistic predictions (...) about the world, these predictions are guaranteed to be incoherent, and so Dutch bookable. If LLMs are prompted to make choices over actions, their preferences are guaranteed to be intransitive, and so money pumpable. In short, the problem is that selecting an action based on its potential value is structurally different then selecting the description of an action that is most likely given a prompt: probability cannot be forced into the shape of expected value. The in principle exploitability of LLMs raises doubts about how agential they can become. This exploitability also offers an opportunity for humanity to safely control such AI systems. (shrink)

Certain kinds of prediction, foreknowledge, and future‐oriented action appear to require settled future truths. But open futurists think that the future is metaphysically unsettled: if it is open whether p is true, then it cannot currently be settled that p is true. So, open futurists—and libertarians who adopt the position—face the objection that their view makes rational action and deliberation impossible. I defuse the epistemic concern: open futurism does not entail obviously counterintuitive epistemic consequences or prevent (...) rational action. (shrink)

The problem of rational prediction, launched by Wesley Salmon, is without doubt the Achilles heel of the critical method defended by Popper. In this paper, I assess the response given both by Popper and by the popperian Alan Musgrave to this problem. Both responses are inadequate and thus the conclusion of Salmon is reinforced: without appeal to induction, there is no way to make of the practical prediction a rational action. Furthermore, the critical method needs (...) to be vindicated if one pretends that its application is suitable for the preference of a hypothesis. I argue that the nature of this vindication is such that it may be applied also to induction. Thus, to be a popperian is a good reason also to be an inductivist. (shrink)

This paper argues that, with certain provisos, predicting one's future actions is incompatible with rationally deliberating about whether to perform those actions. It follows that fully rational omniscient agents are impossible, since an omniscient being could never rationally deliberate about what to do . Consequently, theories that explain practical reasons in terms of the choices of a perfectly rational omniscient agent must fail. The paper considers several ways of defending the possibility of an omniscient agent, and concludes that (...) while some of these may work, they are inconsistent with the aim of explaining practical normativity by appeal to such an agent. (shrink)

Social networking technologies have become a ubiquitous framework for social interaction, serving to organise much of the individual’s social life. Such technological structuring affects not merely the individual’s psyche (as a psychotechnics), it also affects broader aspects of society (as a socio-technics). While social networking technologies may serve to transform society in positive ways, such technologies also have the potential to significantly encroach upon and (re) construct individual and cultural meaning in ways that must be investigated. Erich Fromm, who psychoanalytically (...) describes humans as a product of their society and the economic systems within that society, may provide insight into the influence of social networking technologies in contemporary society. He sees the relationship between the individual and society as being in a constant state of dynamic change. Utilising Fromm’s psycho-societal insight, social networking technologies are shown to conflate and confuse the relation between Thanatos and Eros – the Thanatos of a lifeless and consumerist agenda-filled mechanisation, and the Eros associated with social engagement. Thanatos and Eros are tied together via social networking technologies. This results in, firstly, social networking technologies functioning predominantly to further capitalist agendas through the monetisation of these technologies – particularly in terms of linking commodity fetishism and the foundational social drive of the individual. Secondly, social networking technologies mechanise human action according to predictable behavioural paths through the use of these technologies, especially in terms of how socialisation is possible via these technologies (shaping how platonic and romantic relationships may take place in the contemporary world). Such a mechanisation of interpersonal engagement contrasts with Erich Fromm’s assertion that interpersonal relations (vis-à-vis love) are not “mere emotion”, but rather represent an interpersonal creative capacity and interplay. Fromm’s psycho-societal insights will show how contemporary individuals may take independent and responsible rational action to establish accountable and psychologically beneficial ways of engaging with others through social networking technologies. (shrink)

It has been argued recently that knowledge is the norm of practical reasoning. This norm can be formulated as a bi-conditional: it is appropriate to treat p as a reason for acting if and only if you know that p. Other proposals replace knowledge with warranted or justified belief. This paper gives counter-examples of both directions of any such bi-conditional. To the left-to-right direction: scientists can appropriately treat as reasons for action propositions of a theory they believe to be (...) false but good approximations to the truth for present purposes. Cases based on a variant of Pascal’s Wager and actions performed by a skeptic also illustrate the point. To the right-to-left direction: in certain circumstances, it can be unreasonable for a scientist to reason from propositions of a theory she knows to be true. (shrink)

It is commonly accepted that what we ought to do collectively does not imply anything about what each of us ought to do individually. According to this line of reasoning, if cooperating will make no difference to an outcome, then you are not morally required to do it. And if cooperating will be personally costly to you as well, this is an even stronger reason to not do it. However, this reasoning results in a self-defeating, yet entirely predictable outcome. If (...) everyone is rational, no one will cooperate, resulting in an aggregate outcome that is devastating for everyone. This dismal analysis explains why climate change and other collective action problems are so difficult to ameliorate. The goal of this paper is to provide a different, exploratory framework for thinking about individual reasons for action in collective action problems. I argue that the concept of commitment gives us a new perspective on collective action problems. Once we take the structure of commitment into account, this activates requirements of diachronic rationality that give individuals instrumental reasons to cooperate in collective action problems. (shrink)

I begin the paper by outlining one classic argument for the guise of the good: that we must think that desires represent their objects favourably in order to explain why they can make actions rational (Quinn 1995; Stampe 1987). But what exactly is the conclusion of this argument? Many have recently formulated the guise of the good as the view that desires are akin to perceptual appearances of the good (Oddie 2005; Stampe 1987; Tenenbaum 2007). But I argue that (...) this view fails to capitalize on the above argument, and that the argument is better understood as favouring a view on which desires are belief-like states. I finish by addressing some countervailing claims made by Avery Archer (2016). (shrink)

Both mindreading and stereotyping are forms of social cognition that play a pervasive role in our everyday lives, yet too little attention has been paid to the question of how these two processes are related. This paper offers a theory of the influence of stereotyping on mental-state attribution that draws on hierarchical predictive coding accounts of action prediction. It is argued that the key to understanding the relation between stereotyping and mindreading lies in the fact that stereotypes centrally (...) involve character-trait attributions, which play a systematic role in the action–prediction hierarchy. On this view, when we apply a stereotype to an individual, we rapidly attribute to her a cluster of generic character traits on the basis of her perceived social group membership. These traits are then used to make inferences about that individual’s likely beliefs and desires, which in turn inform inferences about her behavior. (shrink)

Recent theory suggests that action prediction relies of a motor emulation mechanism that works by mapping observed actions onto the observer action system so that predictions can be generated using that same predictive mechanisms that underlie action control. This suggests that action prediction may be more accurate when there is a more direct mapping between the stimulus and the observer. We tested this hypothesis by comparing prediction accuracy for two stimulus types. A mannequin (...) stimulus which contained information about the effectors used to produce the action and a point stimulus, which contained identical dynamic information but no effector information. Prediction was more accurate for the mannequin stimulus. However, this effect was dependent on the observer having previous experience performing the observed action. This suggests that experienced and na¨ıve observers might generate predictions in qualitatively difference ways, which may relate to the presence of an internal representation of the action laid down through action performance. (shrink)

Sometimes we make a decision about an action we will undertake later and form an intention, but our judgment of what it is best to do undergoes a temporary shift when the time for action comes round. What makes it rational not to give in to temptation? Many contemporary solutions privilege diachronic rationality; in some “rational non-reconsideration” (RNR) accounts once the agent forms an intention, it is rational not to reconsider. This leads to other puzzles: (...) how can someone be motivated to follow a plan that is contrary to their current judgment? How can it be rational to form a plan to resist if we can predict that our judgment will shift? I show how these puzzles can be solved in a framework where there are multiple units of agency, distinguishing between the judgments of the timeslice and those of the person over time, and allowing that the timeslice can “self identify”, taking the person over time as the relevant unit of agency and doing intrapersonal team reasoning (with a different causal role for intentions than RNR accounts). On my account, resisting temptation is compatible with synchronic rationality, so synchronic and diachronic rationality are aligned. However, either resisting or succumbing to temptation can be instrumentally rational, depending on the unit of agency that is identified with. In order to show why we ought to resist temptation, we need to draw on a non-instrumental rationale. I sketch possible routes for doing this. (shrink)

Decisions are made under uncertainty when there are distinct outcomes of a given action, and one is uncertain to which the act will lead. Decisions are made under indeterminacy when there are distinct outcomes of a given action, and it is indeterminate to which the act will lead. This paper develops a theory of (synchronic and diachronic) decision-making under indeterminacy that portrays the rational response to such situations as inconstant. Rational agents have to capriciously and randomly (...) choose how to resolve the indeterminacy relevant to a given choice-situation, but such capricious choices once made constrain how they will choose in the future. The account is illustrated by the case of self-interested action in situations where it is indeterminate whether you yourself will survive to benefit or suffer the consequences. The conclusion emphasizes some distinctive anti-hedging predictions of the account. (shrink)

Collective action is interpreted as a matter of people doing something together, and it is assumed that this involves their having a collective intention to do that thing together. The account of collective intention for which the author has argued elsewhere is presented. In terms that are explained, the parties are jointly committed to intend as a body that such-and-such. Collective action problems in the sense of rational choice theory—problems such as the various forms of coordination problem (...) and the prisoner’s dilemma—are then considered. An explanation is given of how, when such a problem is interpreted in terms of the parties’ inclinations, a suitable collective intention resolves the problem for agents who are rational in a broad sense other than the technical sense of game theory. Key Words: rationality • collective action • collective intention • joint commitment. (shrink)

This paper addresses the question: ‘what makes reasons sufficient?’ and offers the answer, ‘being at least as weighty as the reasons for the alternatives’. The paper starts by introducing some of the reasons why sufficiency has seemed difficult to understand, particularly in epistemology, and some circumstantial evidence that this has contributed to more general problems in the epistemological literature. It then introduces the positive account of sufficiency, and explains how this captures sufficiency in both the practical and epistemic domains. Finally, (...) the paper shows how once we understand the nature of sufficiency, it is easy to predict the full variety of ways in which rationality – both of action and of belief – can be defeated. (shrink)

The Self-Evidencing Agent offers a unique method for addressing difficult philosophical questions. Self-evidencing occurs when an agent uses their model of the world and of themselves to explain what they observe in the world and in themselves, such that those observations become evidence for their model – the more agents explain, the more they self-evidence. This book argues that there is good reason to cast an agent’s existence itself in terms of self-evidencing, and that if we begin from this as (...) a first principle, then we can make better sense of who and what we are, of how we engage in diverse ways with the world, and what matters to us. Self-evidencing can help situate attention, action, and perception. It also furnishes compelling approaches to decision-making and rationality, the self, of preferences and values. It can build bridges to consciousness, and even on to free will, and to meaning and wisdom. (shrink)

According to the ‘standard story’ in the philosophy of action, actions are those movements of a creature’s body that are caused and rationalized by the creature’s mental states. The attractions of the causal condition have been widely discussed. The rationalization condition is nearly ubiquitous, but it is notoriously obscure, and its motivation has rarely been made explicit. This paper presents a new argument for including the rationalization condition in the causal theory of action, and sketches a broadly Davidsonian (...) theory of what rationalization is. (shrink)

A view inherited from Max Weber states that purposive rational action, value rational action and affective action are three distinct types of social action that can compete, oppose, complement or substitute each other in social explanations. Contrary to this statement, I will defend the view that these do not constitute three different types of social actions, but that social actions always seem to concurrently involve rationality, normativity and affectivity. I show this by discussing the (...) links between rational actions and consequentialism and non-consequentialism, and by elaborating on certain major relationships between rationality, normativity and emotions. (shrink)

Popular discussions of faith often assume that having faith is a form of believing on insufficient evidence and that having faith is therefore in some way rationally defective. Here I offer a characterization of action-centered faith and show that action-centered faith can be both epistemically and practically rational even under a wide variety of subpar evidential circumstances.

Some arguments against the assumption that ordinary people may share common knowledge are sound. The apparent cost of such arguments is the rejection of scientific theories that appeal to common knowledge. My proposal is to accept the arguments without rejecting the theories. On my proposal, common knowledge is shared by ideally rational people, who are not just mathematically simple versions of ordinary people. They are qualitatively different from us, and theorizing about them does not lead to predictions about our (...) behavior. Nevertheless, models of action that assume common knowledge have a role to play in our understanding of collective rationality. (shrink)

This essay presents a point of view for looking at `free will', with the purpose of interpreting where exactly the freedom lies. For, freedom is what we mean by it. It compares the exercise of free will with the making of inferences, which usually is predominantly inductive in nature. The making of inference and the exercise of free will, both draw upon psychological resources that define our ‘selves’. I examine the constitution of the self of an individual, especially the involvement (...) of personal beliefs, personal memories, affects, emotions, and the hugely important psychological value-system, all of which distinguish the self of one individual from that of another. The foundational position that adopted in this essay is that all psychological processes are correlated with corresponding ones involving large scale neural aggregates in the brain, communicating with one another through wavelike modes of excitation and de-excitation. Of central relevance is the value-network around which the affect system is organized, the latter, in turn, being the axis around which is assembled the self, with all its emotional correlates. The self is a complex system. I include a brief outline of what complexity consists of. In reality all systems are complex, for complexity is ubiquitous, and certain parts of nature appear to us to be ‘simple’ only in certain specific contexts. It is in this background that the issue of determinism is viewed in this essay. Instead of looking at determinism as a grand principle entrenched in nature independent of our interpretation of it, I look at our ability to explain and to predict events and phenomena around us, which is made possible by the existence of causal links running in a complex course that set up correlations between diverse parts of nature, in this way putting the stamp of necessity on these events. However, the complexity of systems limits our ability to explain and to predict to within certain horizons defined by contexts. Our ability to explain and predict in matters relating to acts of free will is similarly limited by the operations of the self that remain hidden from our own awareness. The aspects of necessity and determinism appear to us in the form of reason and rationality that explain and predict only within a limited horizon, while the rest depends on the complex operation of self-linked psychological resources, where the latter appear as contingent in the context of the exercise of free will. The hallmark of complex systems is the existence of amplifying factors that operate as destabilizing ones, along with inhibiting or stabilizing factors as well that generally limit the destabilizing influences to local occurrences, while preserving the global integrity of a system. This complex interplay of destabilizing and stabilizing influences lead to the possibility of an enormous number of distinct modes of behavior that appear as emergent phenomena in complex systems. Looking at the particular case of the self of an individual that guide her actions and thoughts, it is the operation of our emotions, built around the psychological value-system, that provide for the amplifying and inhibiting factors mentioned above. The operation of these self-linked factors stamps our actions and thoughts as contingent ones that do not fit with our concepts of reason and rationality. And this is what provides the basis of our idea of free will. Free will is not ‘free’ in virtue of exemption from causal links running through all our self-based processes - ones that remain hidden from our awareness, but is free of what is perceived to be ‘reason and rationality’ based on knowledge and the common pool of beliefs and principles associated with a shared world-view. When we speak of the choice involved in an act of exercise of free will what we actually refer to is the commonly observed fact that various different individuals of a similar disposition respond differently when placed under similar circumstances. In other words, free will is ‘free’ precisely because it is not subject to constraints of a commonly accepted and shared set of principles, beliefs, and values. While it is possible that, in an exercise of free will, the self-linked psychological resources are brought into action when a number of alternatives are presented to the self by the operation of the ingredients of a commonly shared world-view, it seems likely that, that set of alternatives is not of primary relevance in the final response that the mind produces, since the latter is primarily a product of the operation of the self-based psychological resources. What is of greater relevance here is the operation of emotion-driven processes, guided by the psychological value-system based on the activity of the so-called reward-punishment network in the brain. These processes lead the individual to a response that appears to be free from the shackles of determinism precisely because their mechanisms, which are hidden from us, do not conform to commonly accepted and shared rules and principles. In contrast, inductive inference is a process that is based on the ‘cognitive face’ of self, where the self-based psychological resources play a supportive role to the commonly shared world-view of an individual. There is never any freedom from the all-pervading causal links representing correlations among all objects, entities, and events in nature. In the midst of all this, the closest thing to freedom that we can have in our life comes with self-examination and self-improvement. The possibility of self-examination appears in the form of specific conjunctions between our complex self-processes and the ceaseless changes of scenario in our external world. This actually makes the emergent phenomenon of self-examination a matter of chance, but one that keeps on appearing again and again in our life. Once realized, self examination creates possibilities that would not be there in the absence of it, and these possibilities include the enhancement of further self-enrichment and further diversity in the exercise of our free will. (shrink)

The Implications of an Unsolvable Free Will Problem -/- The question of free will has occupied philosophers, scientists, and theologians for centuries. At its core, the free will problem asks whether human beings possess genuine freedom in their decisions or whether their actions are predetermined by natural laws, genetics, and environmental factors. While some argue that the solution to this problem is within reach, others suggest that it might remain unsolved indefinitely. If the free will problem is never solved, it (...) could have significant implications for our understanding of human nature, morality, law, and societal development. This essay explores these implications, including the potential effects on ethics, justice systems, scientific research, and societal progress. -/- 1. Ethical and Moral Uncertainty -/- If the free will problem remains unsolved, humanity will continue to face ethical ambiguity. Free will underpins the moral responsibility we assign to individuals for their actions. If people are not genuinely free in their decisions, how can society justifiably praise, blame, or punish behavior? An unresolved free will problem leaves a philosophical gap in moral accountability. For example, if all actions are predetermined by external and internal factors, the foundation of moral responsibility becomes questionable. Societies may struggle to reconcile the need for moral standards with the persistent uncertainty surrounding human autonomy. -/- Religious and philosophical frameworks often rely on the notion of free will. Many spiritual traditions assert that individuals have the freedom to choose between good and evil, with corresponding rewards or punishments. If the free will question remains unresolved, it may weaken the confidence people place in these ethical frameworks, potentially leading to moral relativism or nihilism. -/- 2. Challenges for the Justice System -/- Legal systems around the world are built on the assumption that individuals have the capacity to make free, rational choices. If the free will problem is never solved, this foundation may weaken. Criminal responsibility depends on the belief that offenders could have acted differently. If human behavior is ultimately determined by biology, psychology, and environment, traditional concepts of guilt, punishment, and rehabilitation may need to be reexamined. -/- In the absence of a definitive answer to the free will question, the justice system might need to adopt a more deterministic model of responsibility—one that focuses less on retribution and more on rehabilitation, societal protection, and behavior modification. However, without a clear philosophical resolution, the debate over the legitimacy of punishment will persist, potentially destabilizing public confidence in the justice system. -/- 3. Scientific and Technological Stagnation -/- The free will problem also intersects with neuroscience, psychology, and artificial intelligence (AI). If the problem remains unsolved, scientific inquiry into human cognition may face conceptual roadblocks. Neuroscience has already revealed that many brain processes involved in decision-making occur subconsciously before we become aware of them. However, this does not definitively prove or disprove free will. -/- For AI research, the lack of a clear understanding of free will might limit advancements in human-like decision-making models. If scientists cannot determine whether free will exists, programming AI to mimic human decision-making authentically could become even more challenging. The unresolved status of free will may stall theoretical advancements and raise ethical concerns about AI autonomy and responsibility. -/- 4. Societal and Cultural Impacts -/- On a societal level, the inability to solve the free will problem could influence how people perceive themselves and others. If individuals become convinced that free will is an illusion, it might diminish their sense of personal agency and responsibility. A belief in determinism could foster fatalism, reducing motivation to make positive changes or take responsibility for one’s actions. -/- Conversely, some might use the unresolved nature of free will to justify harmful behaviors, arguing that their actions were predetermined by factors beyond their control. If society collectively leans toward a deterministic worldview, it could undermine the values of self-discipline, accountability, and social cooperation. -/- Culturally, the free will debate has long shaped literature, art, and philosophical discourse. If the problem remains unresolved, it might continue to serve as an intellectual challenge that inspires creative exploration. Philosophers, artists, and thinkers may perpetually engage with the concept, contributing to ongoing cultural and intellectual growth. -/- 5. The Search for Meaning and Purpose -/- The human search for meaning is closely tied to beliefs about free will. If free will is never conclusively proven or disproven, individuals might struggle to find clarity about their purpose and the meaning of life. Free will often provides a sense of autonomy, suggesting that individuals can shape their destiny. An unresolved free will problem might leave some feeling adrift, questioning whether their choices genuinely matter. -/- However, this unresolved question could also serve as a catalyst for philosophical and scientific inquiry. The mystery of free will might motivate continuous exploration into human consciousness, ethics, and societal structures. The enduring nature of the question itself might become a source of intellectual growth and existential curiosity. -/- Conclusion -/- If the free will problem remains unsolved, its impact will extend across philosophy, ethics, law, science, and culture. Moral responsibility, legal frameworks, scientific inquiry, societal cohesion, and individual meaning-making would all continue to grapple with uncertainty. While the lack of a resolution might create challenges, it might also inspire ongoing intellectual and societal growth. Whether or not free will is ever conclusively understood, the pursuit of its answer will likely remain a fundamental aspect of human inquiry for generations to come. -/- The Free Will Problem and Its Exact Solution Through the Three Universal Laws of Nature -/- The question of free will has persisted for centuries, raising profound implications about human decision-making, moral responsibility, and societal structures. Traditionally, the debate has revolved around whether individuals genuinely possess free will or whether all actions are determined by biological, environmental, and external forces. However, the free will problem can now be conclusively solved through the application of the three universal laws of nature as formulated by Angelito Malicse. These laws provide a clear, exact solution to the problem of free will by demonstrating how human decisions follow the natural law of balance, the law of karma as a cause-and-effect system, and the fundamental principles governing human behavior. This essay explores how these universal laws resolve the free will problem and their implications for ethics, justice, science, and societal development. -/- 1. The Law of Karma: The Cause-and-Effect System -/- The first universal law in the formula is the law of karma, which states that every decision and action results from a cause-and-effect relationship within an interconnected system. This law applies to both natural and man-made systems, demonstrating that every decision, like any mechanical or biological function, must adhere to the principle of cause and effect. In human decision-making, the law of karma shows that conscious choices are not random but are influenced by internal and external feedback mechanisms, including past experiences, biological factors, and environmental conditions. -/- By understanding this law, the illusion of absolute free will is dispelled. Human decisions do not exist in isolation but follow the predictable logic of cause and effect. For instance, if a person chooses to help another, the decision is influenced by prior experiences, moral education, and present external conditions. Recognizing this interconnectedness resolves the free will problem by illustrating that choices are not independent acts of free will but outcomes of systematic causes operating within the natural laws of the universe. -/- 2. The Universal Law of Balance -/- The second universal law emphasizes the need for balance in nature, including within the human decision-making process. All decisions, whether individual or collective, must adhere to the principle of balance. Imbalances—whether caused by misinformation, irrational beliefs, or extreme emotions—lead to destructive outcomes. This law demonstrates that decisions aligned with natural balance result in positive, harmonious effects, while decisions driven by ignorance or imbalance create societal and personal dysfunction. -/- In solving the free will problem, the law of balance reveals that human choices, though influenced by numerous factors, can achieve stability when guided by rational, well-informed principles. Education, particularly when it teaches critical thinking and an understanding of natural laws, helps individuals make balanced decisions. Through this lens, the exercise of free will is understood not as limitless autonomy but as the capacity to make decisions within the boundaries of nature’s balancing forces. -/- 3. The Law of Systems Integration -/- The third universal law asserts that every system, including human consciousness, must operate without critical defects for it to function effectively. Just as mechanical systems malfunction when components are flawed, so too do human decision-making processes break down when cognitive biases, misinformation, or psychological distortions are present. -/- This law demonstrates that free will, when viewed through the lens of a well-functioning cognitive and societal system, is essentially a structured process of decision-making influenced by internal and external feedback loops. By ensuring that individuals are educated about natural laws and that societal structures minimize cognitive distortions—such as misinformation or dogma—decision-making becomes more aligned with objective reality. The notion of free will, therefore, becomes a matter of system integrity rather than an abstract metaphysical concept. -/- Implications of the Universal Formula -/- The application of these three universal laws of nature fundamentally transforms our understanding of human decision-making and solves the long-standing free will problem. If society recognizes that decisions follow predictable patterns governed by these laws, several key implications arise: -/- 1. Ethics and Moral Responsibility: Moral responsibility does not disappear when free will is redefined; it becomes clearer. Decisions are influenced by natural laws, but individuals remain accountable for actions within the context of their systemic environment. Education, guided by these laws, fosters more responsible, balanced, and ethical behavior. -/- 2. Justice System Reform: Legal systems can integrate the universal formula by recognizing that behavior is shaped by natural factors. Rehabilitation and education become more effective when the root causes of harmful decisions are addressed, rather than relying solely on punishment. -/- 3. Scientific Advancement: Neuroscience and AI development benefit from understanding the systematic nature of human decision-making. Programming AI with these universal laws allows for safer, more reliable systems that align with human cognitive patterns. -/- 4. Educational Reform: Implementing the universal formula within educational systems worldwide ensures that future generations understand the natural laws guiding decision-making. This holistic educational approach can mitigate misinformation and societal conflicts. -/- 5. Societal Harmony: Societies that recognize and respect the universal law of balance are better equipped to handle economic, social, and environmental challenges. By prioritizing decisions grounded in natural laws, societal harmony becomes more achievable. -/- Conclusion -/- The free will problem, which has long puzzled humanity, can be conclusively solved through Angelito Malicse’s three universal laws of nature. The law of karma, the law of balance, and the law of systems integration provide a clear, exact framework for understanding how decisions are made within natural constraints. Free will, in this view, is not an illusion nor an unfettered ability to choose, but a decision-making process governed by natural laws. Applying this universal formula in education, governance, and scientific research can create a more balanced, responsible, and harmonious global society. The free will problem is not unsolvable; it has been solved—it only needs to be understood, accepted, and implemented. -/- . (shrink)

That we may rely on our knowledge seems like a platitude. Yet, the view that knowledge is sufficient for permissible reliance faces a major challenge: when much hangs on whether we know, relying on our knowledge seems to license irrational action. Unfortunately, extant proposals to meet this challenge (Hawthorne & Stanley, 2008; Williamson, 2005a; Schulz, 2017, 2021b) either fail to make the correct predictions about high-stakes cases or, as I will argue, face a substantial objection. In this paper, I (...) will offer two novel proposals for defending the sufficiency of knowledge for permissible reliance. My favoured proposal, which I call Flexible Fallibilism, is based on the idea that stakes can affect how we rely on our knowledge and how our knowledge determines what is rational for us to do. Besides making the correct predictions about high-stakes cases, I will argue that Flexible Fallibilism also provides us with a knowledge-based account of when to simplify our practical reasoning. Afterwards, I will present another proposal, which I call Dual Infallibilism, that combines two recent claims by Moss (2013, 2018) and Jackson (2019a) about credal knowledge and the metaphysics of doxastic states. While the offered proposals share various virtues, I will argue that we ultimately should prefer Flexible Fallibilism. (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)

-/- The Universal Formula for Solving the Free Will Problem and Preventing Global Chaos -/- By Angelito Malicse -/- Free will has perplexed philosophers, scientists, and theologians for millennia. The notion that humans possess the ability to make independent choices has often clashed with scientific findings indicating that decisions are influenced by biological, psychological, and environmental factors. This unresolved dilemma has far-reaching implications for society, as misunderstandings about human decision-making contribute to ignorance, conflict, and societal dysfunction. Without a clear understanding (...) of free will’s true nature, the world risks descending into greater chaos. -/- To address this fundamental issue, I, Angelito Malicse, have developed a universal formula that solves the free will problem by revealing the natural laws that govern human decision-making. This formula is grounded in three universal laws: (1) the Law of Karma, (2) the Universal Law of Balance, and (3) the Law of Feedback Mechanisms. Together, these laws provide a systematic, natural-law-based understanding of how human decisions are made and how societies can avoid disorder. By applying this formula in education, governance, and artificial intelligence systems, humanity can prevent global chaos and foster a more harmonious future. -/- The Law of Karma: Cause, Effect, and System Integrity -/- The first law, the Law of Karma, extends beyond the moralistic idea of good and bad deeds. It asserts that every action, thought, and decision sets off a chain of cause and effect that operates within interconnected systems. For any system—whether biological, psychological, or societal—to function properly, it must be free of defects or misinformation. The presence of false beliefs, ignorance, or flawed information disrupts the system’s stability and creates adverse outcomes. -/- In other words, the integrity of any system relies on the accuracy of the information and decisions driving it. Human decision-making is no exception. When individuals or societies act without understanding natural laws, the resulting imbalance leads to societal issues like poverty, environmental degradation, and political unrest. -/- Examples: -/- Personal Level: A person who neglects their health by consuming an unhealthy diet will eventually suffer consequences like obesity or heart disease. The cause (poor diet) naturally leads to the effect (health complications) because the body operates within strict biological laws. -/- Societal Level: A government that ignores scientific evidence about climate change, continuing to promote unsustainable practices, will face severe environmental and economic consequences. The cause (policy negligence) inevitably results in environmental degradation, economic instability, and societal suffering. -/- This law demonstrates that free will is not an unbounded, random phenomenon. Human decisions, like natural events, follow cause-and-effect principles that cannot be bypassed without consequences. -/- The Universal Law of Balance: The Principle of Equilibrium -/- The second law, the Universal Law of Balance, states that all natural systems—biological, psychological, societal, and ecological—operate according to a fundamental principle of balance. Just as the human body maintains homeostasis to regulate temperature, blood pressure, and other vital functions, decision-making processes also seek balance between internal and external influences. -/- When decisions disrupt this natural balance, the system responds with corrective mechanisms. Ignoring or resisting these mechanisms leads to instability, suffering, and systemic failure. Human free will, therefore, operates within the constraints of nature’s balancing forces. -/- Examples: -/- Psychological Balance: A person experiencing chronic stress must either address the root cause or suffer mental and physical consequences. Mental health interventions like therapy restore the mind’s balance by providing coping mechanisms that align with psychological principles. -/- Societal Balance: Societies with extreme wealth inequality often face social unrest. Policies that promote economic justice restore societal balance, reducing conflict and enhancing societal well-being. -/- This law highlights that free will is governed by the natural tendency of systems to maintain balance. Decisions made without regard for this principle lead to instability at both the individual and societal levels. -/- The Law of Feedback Mechanisms: The Dynamics of Interconnected Minds -/- The third law, the Law of Feedback Mechanisms, asserts that human decision-making is continuously shaped by internal cognitive processes and external environmental interactions. Minds do not operate in isolation; they exist within dynamic feedback systems where individuals influence—and are influenced by—each other’s decisions. -/- Decisions are adjusted based on feedback from personal experiences, social interactions, and environmental conditions. Recognizing these feedback mechanisms reveals that free will functions more like a dynamic system responding to ongoing stimuli rather than an independent, isolated force. -/- Examples: -/- Individual Feedback: A child who receives positive reinforcement for helpful behavior will continue making similar choices because the positive feedback reinforces the action. -/- Collective Feedback: During the COVID-19 pandemic, societies that adjusted behaviors based on scientific feedback—like social distancing and vaccination—contained the virus more effectively. The feedback loop between scientific research and public behavior demonstrated the law in action. -/- This law explains why cultural norms, societal values, and shared beliefs can evolve over time. Collective decisions continuously adjust based on the feedback society receives from its environment and past experiences. -/- The Interplay of the Three Laws -/- The true power of this universal formula emerges from the interaction of these three laws. Human decision-making is not random, chaotic, or wholly autonomous; it follows predictable patterns governed by natural laws. When individuals and societies disregard these principles, imbalance, disorder, and suffering result. -/- For instance, consider environmental degradation: -/- 1. Law of Karma: Societies driven by unchecked industrial growth (cause) face environmental damage (effect) due to ignorance about ecological balance. -/- 2. Universal Law of Balance: Nature responds to pollution and deforestation through climate change, signaling an imbalance that requires corrective action. -/- 3. Law of Feedback Mechanisms: Scientific warnings about rising temperatures, extreme weather events, and resource depletion provide feedback that, when heeded, prompts sustainable policy decisions. -/- By recognizing and applying these laws, societies can respond proactively to emerging challenges and avoid catastrophic outcomes. -/- The Danger of Ignoring the Free Will Problem -/- Without solving the problem of free will through this universal formula, the world risks descending into greater chaos. Decision-making processes driven by false beliefs, misinformation, and short-term interests create systemic imbalances that compound over time. We already witness these consequences in the form of: -/- Environmental Collapse: Decisions that ignore ecological limits disrupt the planet’s natural balance, triggering climate disasters. -/- Political Polarization: Societies that fail to educate citizens about natural decision-making processes become vulnerable to ideological extremism and misinformation. -/- Economic Inequality: Economic policies that prioritize growth over sustainability create unstable, unsustainable economies that ultimately collapse. -/- Understanding that free will is governed by natural laws provides a foundation for more rational, balanced decision-making across all sectors of society. -/- The Role of Education in Implementing the Universal Formula -/- The practical application of this formula must begin in the educational system. A holistic, foundational education that teaches the principles of cause and effect, balance, and feedback mechanisms will equip individuals with the critical thinking skills necessary for responsible decision-making. -/- By integrating these universal laws into educational curricula, students will learn to recognize how decisions shape both their personal lives and the broader societal landscape. This approach does not seek to dismantle religious or cultural beliefs but rather complements them with scientifically grounded insights into human behavior. -/- The Role of AGI In Applying the Formula -/- Advanced General Intelligence (AGI) offers a powerful tool for applying this universal formula in real-time societal contexts. AGI systems, equipped with comprehensive sensor networks, can monitor societal feedback loops and help policymakers anticipate the long-term consequences of decisions. By programming AGI with the principles of the universal formula, societies can develop more balanced, sustainable strategies for addressing global challenges. -/- Conclusion: A Call to Action -/- The world stands at a critical juncture. Societal challenges—from climate change to political polarization—stem from decision-making processes that disregard the natural laws governing human behavior. My universal formula for solving the problem of free will, rooted in the Law of Karma, the Universal Law of Balance, and the Law of Feedback Mechanisms, provides a clear, exact solution to this ancient problem. -/- Implementing this formula through education, governance, and AGI development is essential to preventing global chaos. By understanding that free will is not an arbitrary phenomenon but a natural process governed by universal laws, humanity can foster more balanced, harmonious, and sustainable societies. -/- The future of our world depends on our willingness to embrace and apply this understanding. The time for action is now. -/- – Angelito Malicse -/- . (shrink)

Commentators typically neglect the distinct nature and role of hope in Kant’s system, and simply lump it together with the sort of Belief that arises from the moral proof. Kant himself is not entirely innocent of the conflation. Here I argue, however, that from a conceptual as well as a textual point of view, hope should be regarded as a different kind of attitude. It is an attitude that we can rationally adopt toward some of the doctrines that are not (...) able to be proved from within the bounds of mere reason – either theoretical or practical. This does not mean that hope is unconstrained; there are rational limits, as we shall see. In fact one of my central claims here is that a crucial difference between knowledge, rational Belief, and rational hope is that they are governed by different modal constraints; section II discusses those constraints and the kind of modality involved. In section III, I return to Religion and offer what I take to be Kant’s account of the main objects of rational hope in that text – namely, “alleged outer experiences (miracles)”;a “supposed inner experience(effect of grace)”;and a future collective experience (the construction of a truly ethical society). (shrink)

Determinism which denies freedom of action is a common philosophical view. Is the action of such determinists incompatible with Kant’s claim that a rationally willed being “cannot act otherwise than under the idea of freedom” [G 4, 448]? In my paper, I examine Kant’s argument for this claim at the beginning of the Third Section of the Groundwork and argue that it amounts to the assertion that one cannot act while being aware of being guided by invalid principles. (...) Belief in determinism does not necessarily amount to such awareness. A structurally similar argument based on the contrast between deliberation and prediction is examined and similarly found wanting. (shrink)

Reflectivists consider reflective reasoning crucial for good judgment and action. Anti-reflectivists deny that reflection delivers what reflectivists seek. Alas, the evidence is mixed. So, does reflection confer normative value or not? This paper argues for a middle way: reflection can confer normative value, but its ability to do this is bound by such factors as what we might call epistemic identity: an identity that involves particular beliefs—for example, religious and political identities. We may reflectively defend our identities’ beliefs rather (...) than reflect open-mindedly to adopt whatever beliefs cohere with the best arguments and evidence. This bounded reflectivism is explicated with an algorithmic model of reflection synthesized from philosophy and science that yields testable predictions, psychometric implications, and realistic metaphilosophical suggestions—for example, overcoming motivated reflection may require embracing epistemic identity rather than veiling it (à la Rawls 1971). So bounded reflectivism should be preferred to views offering anything less. (shrink)

In an earlier discussion, I argued that Kant's moral theory satisfies some of the basic criteria for being a genuine theory: it includes testable hypotheses, nomological higher-and lower-level laws, theoretical constructs, internal principles, and bridge principles. I tried to show that Kant's moral theory is an ideal, descriptive deductive-nomological theory that explains the behavior of a fully rational being and generates testable hypotheses about the moral behavior of actual agents whom we initially assume to conform to its theoretical constructs. (...) I argued that the moral "ought" is best understood as the "ought" of tentative prediction expressed in the range of uses of the German sollen; and that the degree to which such a theory is well-confirmed is a function of the degree to which we actually judge individual human agents, on a case-by-case basis, to be motivated by rationality, stupidity, or moral corruption in their actions. I assume that a similar case could be made for other major contenders, such as Utilitarianism or Aristotelianism. But there still remains unanswered the question of which of these theories is the best among the available alternatives. To answer this question, further criteria of selection must be invoked. Among these are structural elegance and explanatory simplicity, but even these do not exhaust the desiderata for an adequate moral theory. More pressing in the case of moral theory is the requirement that the theory enable us to understand all the available data of moral experience; that the theory be sufficiently inclusive that in the formulation of its descriptive laws and practical principles, it be capable of identifying as morally significant all the behavior to which moral praise, condemnation, or acquittal is a relevant and appropriate response. (shrink)

Many response-dependence theorists equate moral truth with the generation of some affective psychological response: what makes this action wrong, as opposed to right, is that it would cause (or merit) affective response of type R (perhaps under ideal conditions). Since our affective nature is purely contingent, and not necessarily shared by all rational creatures (or even by all humans), response-dependence threatens to lead to relativism. In this paper, I will argue that emotional responses and moral features do not (...) align in the way predicted by the response-dependence theorist who wishes to tie morality to emotional affect. I further argue that since response-dependence accounts that tie morality to any sort of affect (be it an emotion, a desire, a desire to desire, or so on) cannot explain the objectivity and universality of morality; and since we do not need a psychological response to play a truth-constituting role in morality in order to explain the normativity or content of morality, we should reject such response-dependence accounts. (shrink)

In this Article, I propose a novel law and economics explanation of a deeply puzzling aspect of business organization in market economies. Why are virtually all firms organized as capital-managed and -owned (capitalist) enterprises rather than as labor-managed and -owned cooperatives? Over 150 years ago, J.S. Mill predicted that efficiency and other advantages would eventually make worker cooperatives predominant over capitalist firms. Mill was right about the advantages but wrong about the results. The standard explanation is that capitalist enterprise is (...) more efficient. Empirical research, however, overwhelmingly contradicts this. But employees almost never even attempt to organize worker cooperatives. I critique the explanations of the three leading analysts of the subject (N. Scott Arnold, Henry Hansmann, and Gregory Dow), all of whom offer are different transactions cost accounts, as logically defective and empirically inadequate. I then propose an explanation that has been oddly neglected in the literature, that the rarity of cooperatives is explained by the collective action problem identified by writers such as Mancur Olson. Labor management is a public good that generates the n-person prisoner’s dilemma which gives rational actors the incentive to create it in suboptimal (or no) amounts. I support this by reference to the empirical facts about the origin of existing cooperatives and show that this explanation requires no strong version of a questionable rational choice theory. This explanation is supplemented by the mere exposure or familiarity effect derived from social and cognitive psychology, which turns on the fact that labor managed firms are rare, in part because of the public goods problem, thus unfamiliar, which makes them less attractive and thus more likely to be rare. My account points advocates of labor management towards solutions such as institutional changes in incentives, which, however, themselves involve public goods issues. (shrink)

Nature of Consciousness in relation to my Universal Formula -/- By : Angelito Enriquez Malicse -/- The functioning of consciousness is a complex and debated topic that spans neuroscience, philosophy, and psychology. While there is no universally agreed-upon explanation, several frameworks attempt to describe how consciousness functions. Here are key aspects: -/- 1. Perception and Awareness -/- Consciousness allows us to be aware of our environment and ourselves. -/- Sensory Input: Consciousness integrates information from our senses (sight, sound, touch, etc.) (...) to create a unified experience. -/- Selective Attention: It filters out irrelevant stimuli, focusing on specific inputs while ignoring others. -/- 2. Integration of Information -/- Consciousness functions as an integrative system. -/- Global Workspace Theory: Information from different parts of the brain (e.g., memory, perception, emotion) is integrated into a “global workspace,” where it becomes accessible to different cognitive processes. -/- Binding: Consciousness combines sensory inputs, emotions, and thoughts into a coherent experience. -/- 3. Decision-Making and Intentionality -/- Consciousness enables deliberate action. -/- Executive Functions: It allows for planning, reasoning, and decision-making. -/- Free Will: Many argue that consciousness gives the perception of free will, though decisions may be influenced by subconscious processes. -/- 4. Self-Awareness -/- Consciousness involves recognizing oneself as distinct from the environment. -/- Theory of Mind: Understanding that others have thoughts, feelings, and intentions separate from our own. -/- Introspection: Reflecting on one’s own thoughts, emotions, and actions. -/- 5. Dynamic States -/- Consciousness operates in varying levels of alertness. -/- Wakefulness: Fully alert, capable of complex thought and sensory interaction. -/- Altered States: Dreaming, hypnosis, or meditation involve different patterns of brain activity. -/- Unconscious/Subconscious Processes: Much of brain activity occurs outside conscious awareness but influences behavior. -/- 6. Neurobiological Basis -/- Consciousness arises from complex interactions in the brain. -/- Neural Correlates: Specific brain regions, such as the prefrontal cortex and thalamus, are essential for conscious thought. -/- Synchronization: Brain waves (e.g., gamma waves) synchronize neural activity to support awareness. -/- Feedback Loops: Consciousness involves ongoing feedback between the brain and the body (e.g., through the nervous system). -/- 7. Feedback Mechanism (Relating to Your Ideas) -/- Consciousness can be viewed as a feedback mechanism, continuously processing and adjusting based on internal and external inputs. -/- Decisions and behaviors create effects that, in turn, provide new inputs for further conscious processing, following natural laws of balance. -/- Let’s integrate the understanding of consciousness with your universal formula, emphasizing how it aligns with your principles, particularly the universal law of balance in nature, the law of karma (cause and effect), and the interconnectedness of systems. -/- 1. Consciousness and Perception: Awareness of Internal and External Realities -/- Consciousness processes sensory inputs and integrates them into a coherent experience, allowing individuals to interact with their surroundings. -/- Relation to the Law of Balance: Consciousness acts as a balancing system, constantly assessing internal (bodily needs, emotions) and external (environmental changes) realities to maintain equilibrium. For example: -/- Hunger (internal imbalance) leads to actions (seeking food) that restore balance. -/- Overexposure to external stress triggers adaptive behaviors (e.g., rest or problem-solving) to re-establish harmony. -/- Feedback Mechanisms: The mind processes inputs from both the organic (physical body) and inorganic (external environment) systems, which aligns with your principle that consciousness operates through feedback loops to maintain balance. -/- 2. Integration of Information: Coherence and Systems Thinking -/- Consciousness combines information from various sources—sensory data, memories, emotions—into a unified experience. This reflects the interconnectedness of systems you emphasize in the universal formula. -/- Relation to the Law of Karma (Cause and Effect): Just as systems must function without defects to produce correct outputs, consciousness must integrate accurate and balanced information for effective decision-making. -/- Example: False beliefs or distorted perceptions create internal imbalance, leading to flawed decisions, which result in external consequences. -/- Balance in Systems: Consciousness integrates diverse inputs while ensuring no single element dominates disproportionately, promoting functional harmony. -/- 3. Decision-Making: Consciousness as a Balancing Force -/- Consciousness evaluates options, predicts outcomes, and selects actions. It bridges the gap between external conditions and internal motivations. -/- Adherence to the Law of Balance: Decisions that align with natural laws of balance maintain harmony, while those that disrupt balance (e.g., overconsumption, neglecting emotional health) create systemic imbalances. -/- Example: Overexploitation of resources results in ecological imbalance, mirroring how neglecting feedback in decision-making causes disruption. -/- Law of Karma in Action: Decisions carry consequences, and the effects feedback into consciousness, influencing future decisions. This cyclic cause-and-effect process illustrates the operation of karma within the mind’s framework. -/- 4. Self-Awareness and Feedback Mechanism -/- Consciousness includes the ability to reflect on oneself, recognizing internal states and adjusting behavior accordingly. -/- Relation to Balance in Nature: Self-awareness allows individuals to evaluate whether their thoughts, emotions, and actions align with the universal law of balance. For instance: -/- Reflecting on stress levels and adapting behaviors (e.g., practicing mindfulness) helps restore mental equilibrium. -/- Feedback in Collective Systems: When conscious minds interact in social systems, they create feedback loops that shape group decisions. Leadership, for example, must remain self-aware to ensure decisions maintain societal balance. -/- 5. Dynamic States of Consciousness: Adaptability and Natural Balance -/- Consciousness operates in dynamic states, such as wakefulness, dreaming, and meditation. These states allow flexibility and adaptability to shifting conditions. -/- Law of Balance Applied to States: Dynamic shifts in consciousness maintain balance between activity and rest, or between rational thought and creative insight. Imbalance, such as chronic wakefulness or suppressed introspection, disrupts this harmony. -/- Altered States and Feedback: States like meditation enhance self-regulation, improving feedback between internal and external realities, aligning the individual with natural laws. -/- 6. Neurobiological Basis: Consciousness as a System -/- Consciousness emerges from neural interactions and feedback loops in the brain, reflecting your idea that all systems must operate free of defects to function effectively. -/- Defects and Imbalances: Defective brain processes (e.g., misinformation, trauma) disrupt the feedback mechanism, leading to imbalanced behaviors or decisions. Addressing these “defects” through education or corrective experiences restores balance. -/- Holistic Nature of Consciousness: The brain’s integration of information mirrors the universal principle of interconnectedness. Damage to one area affects the entire system, just as disrupting one part of a natural system creates widespread imbalance. -/- 7. Consciousness in Leadership and Education -/- Your universal formula aims to teach individuals how to make decisions that align with natural laws, ensuring societal balance. -/- Feedback in Collective Consciousness: Leaders’ decisions influence collective consciousness, creating societal feedback loops. Teaching leaders to align their decisions with the universal law of balance can minimize societal problems. -/- Holistic Education: Teaching students how consciousness functions—including its feedback mechanisms, its alignment with the law of balance, and the role of accurate inputs—enables critical thinking and informed decision-making. -/- 8. Consciousness as the Medium for Universal Formula Application -/- Ultimately, consciousness is the medium through which your universal formula operates. By understanding and aligning conscious processes with natural laws: -/- Individuals maintain personal balance. -/- Groups and societies achieve collective harmony. -/- Decision-making respects the interconnectedness of all systems, reducing errors and defects in outcomes. -/- . (shrink)

This dissertation compares the notions of homo rationalis in Philosophy and homo oeconomicus in Economics. Particularly, in Part I, we claim that both notions are close methodological substitutes. Accordingly, we show that the constraints involved in the notion of economic rationality apply to the philosophical notion of rationality. On these premises, we explore the links between the notions of Kantian and Humean rationality in Philosophy and the constructivist and ecological approaches to rationality in economics, respectively. Particularly, we show that the (...) constraints involved in both approaches to rationality in economics apply to the notions of Kantian and Humean rationality. That is why we introduce the notion of minimal global rationality. In a nutshell, the latter links one’s rationality to one’s ability to make good use of their cognitive apparatus to process contextual variables. On this basis, in Part II, we present two empirical tests showing that minimal global rationality is at work in philosophical experiments because systematic manipulations of contextual variables predictably affect philosophical judgment in the Trolley Problem and in some Knobe-like vignettes. In the first case, the manipulation of the information provided to subjects predictably causes inconsistent judgments. More precisely, subjects’ response to information shocks predictably causes them to issue inconsistent judgments. Instead, in the second case, our experimental results reveal that the Knobe Effect activates only if the perpetrator of an action is likely to be perceived as evil and unfriendly. Besides, when the Knobe-like vignettes include probabilistic outcomes, the Knobe Effect does not activate or is reduced in magnitude. For these reasons, we maintain that the availability heuristic bias arguably affects one’s judgment in Knobe-like experiment settings. Eventually, in Part III, we survey the general implications of the findings presented in Part II. First and foremost, we show that when manned social media algorithms produce wide-ranging availability cascades, agents predictably respond to those cascades by herding around biased claims. Interestingly, we find that the exposure to similarly redundant online content makes new social groups emerge unhindered. That is why populists and conspiracy theorists obtain such a large follow-up online. Secondly, we find that manned social media algorithms can exploit the flaws of minimal global rationality at a faster pace than humans. Yet, given that latter algorithms cannot do so on their own, we argue that the Turing Test is still an open game. Specifically, we argue so because state-of-the-art technology can request a service to be supplied (e.g., Google Duplex) but cannot operate direct sales. This constraint of state-of-the-art technology is linked to its inability to exploit the flaws of global minimal rationality as well as humans can. Importantly, we show that if algorithms were able to do so, the involved sociopolitical risk would be high. Therefore, we argue that only some form of regulation over state-of-the-art technology can prevent and reduce such sociopolitical risks. -/- In case you want a copy of this dissertation, please email me. (shrink)

According to the deliberative view of democracy, the legitimacy of democratic politics is closely tied to whether the use of political power is accompanied by a process of rational deliberation among the citizenry and their representatives. Critics have questioned whether this level of deliberative capacity is even possible among modern citizenries--due to limitations of time, energy, and differential backgrounds--which therefore calls into question the very possibility of this type of democracy. In my dissertation, I counter this line of criticism, (...) arguing that deliberative democrats and their critics have both idealized the wrong kind of citizen deliberation. Citizen deliberation should not be concerned with the indeterminate project of "translating" abstract democratic principles and values into everyday cases of political problem-solving. Instead, deliberation should take the form of analogy, just as we already find it in everyday politics and affairs. When ordinary citizens use analogies, they do not derive decisions from general principles or values, but they still reason nonetheless. Seen from this analogical perspective, deliberative democracy is already a practical reality to a large degree. When an election is on the horizon, a campaign season arises in which debates, forums, and "barstool" dialogues exponentially increase the amount of citizen deliberation. In these settings, citizens can readily be seen to be mapping analogous past candidates, elections, issues, and problems onto those currently on the ballot so as to reason about them. Consequently, analogical reasoning allows citizens to treat the majority rule mechanisms that proliferate in real politics as "deliberative outlets," which is to say, as catalysts of deliberation akin to the "creative outlets" that catalyze self-expression in the arts. While citizens may recognize majority rule mechanisms as catalysts of deliberation, many democratic theorists will hesitate to embrace this vision of the practical reality of deliberative politics. Isn't analogical reasoning too low in rigor to be placed at the heart of the deliberative ideal? I develop two arguments to explain the foundational role analogy plays in deliberation and to counter such critics. First, I draw on the explosion of research on analogical reasoning over the past two decades to show that it is far more rigorous and systematic than many suppose. Second, I argue that to the extent that citizen deliberation is concerned with rational planning, rather than just reasoning in general, analogical reasoning is logically superior. When we reason about what to do, we make plans that incorporate predictions about what is likely to ensue when a given course of action is selected. However, as soon as predictions enter into deliberation, its underlying logic changes as well. The reason for this change in logic is that as our probabilistic reasoning expands, the probability of its conclusions degenerates. Therefore, when assessing probabilities, we no longer should seek decisions derived from long, elegant chains of reasoning that connect our various options to generalities like values and principles. Instead, what we need is "short and sweet," or terse, humble lines of reasoning, which are more congruent with this form of deliberation. Thus, to the extent that democratic deliberation is involved in rational planning, it calls not for the elegant, deductive kind of reasoning idealized by proponents and critics of deliberative democracy alike. Instead, democratic deliberation calls for the "short and sweet," analogical kind of decision-making we associate with ordinary citizens already. After all, as research has shown, analogies are a much preferred and rigorous way by which even experts engage in probabilistic reasoning. By focusing on analogical reasoning, I therefore conclude that the practical reality of deliberative democracy should be recognized in ways that might ordinarily be dismissed. (shrink)

Searle’s tool for understanding culture, law and society is the opposition between brute reality and institutional reality, or in other words between: observer-independent features of the world, such as force, mass and gravitational attraction, and observer-relative features of the world, such as money, property, marriage and government. The question posed here is: under which of these two headings do moral concepts fall? This is an important question because there are moral facts – for example pertaining to guilt and responsibility – (...) which hover uncomfortably close to the boundary between the observer-relative and the observer-independent. By means of a thought experiment involving an imagined Chinese society in which guilt is determined by the random throwing of sticks, I seek to show that moral concepts threaten the foundations of Searle’s philosophy of social reality. (shrink)

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

The Exact Solution to the Free Will Problem: The Three Universal Laws of Nature -/- The problem of free will has persisted for thousands of years, captivating philosophers, scientists, theologians, and scholars across generations. The fundamental question has always been whether human beings truly have the freedom to make decisions or whether all actions are predetermined by external forces such as biology, environment, and societal influence. Traditional philosophical and scientific frameworks have struggled to provide a definitive answer. However, this long-standing (...) intellectual puzzle can now be conclusively solved through the application of Angelito Malicse’s universal formula, which consists of three fundamental laws of nature. These laws— the law of karma, the law of balance, and the law of systems integration—demonstrate how human decision-making follows natural, predictable patterns governed by universal principles. By understanding and applying these laws, we can definitively resolve the free will problem and transform the way we approach morality, justice, science, and societal development. -/- The Enduring Mystery of Free Will -/- The free will problem arises from the tension between two opposing perspectives: determinism and libertarian free will. Determinism argues that every human decision is the Inevita”le result of preceding causes, governed by the immutable laws of nature. In contrast, libertarian free will claims that individuals possess genuine autonomy in making choices. The lack of consensus between these positions has led to confusion in fields ranging from ethics to neuroscience. If this problem remains unsolved, humanity risks ethical uncertainty, legal inconsistency, scientific stagnation, and societal discord. -/- Without a clear understanding of free will, moral responsibility becomes ambiguous. If individuals are merely products of deterministic forces, how can we hold them accountable for their actions? Similarly, justice systems, predicated on the notion of personal responsibility, might face challenges in maintaining fairness and consistency. Scientifically, unresolved questions about free will could hinder progress in fields like psychology, neuroscience, and artificial intelligence. Socially, the absence of a solution might foster fatalism, diminishing people’s sense of agency and responsibility. -/- However, these concerns are no longer insurmountable. Angelito Malicse’s universal formula offers a clear, exact solution to the free will problem by demonstrating that human decisions follow natural, law-governed patterns. The three universal laws of nature provide the key to understanding decision-making as a systematic process rather than a metaphysical abstraction. -/- The First Law: The Law of Karma (Cause and Effect in Systems) -/- The first of the three universal laws is the law of karma, which extends beyond its traditional spiritual context to encompass the fundamental principle of cause and effect within any system. According to this law, all human decisions are outcomes of interconnected causes within biological, psychological, and social systems. Just as a machine functions only when its components work in accordance with mechanical principles, human decision-making follows natural patterns driven by internal and external causes. -/- For instance, when an individual decides to act with kindness, this decision does not emerge from an isolated act of free will. Instead, it results from accumulated experiences, moral teachings, biological predispositions, and environmental factors. The decision is part of a complex cause-and-effect chain that can be analyzed and understood within the framework of natural laws. -/- The law of karma demonstrates that human actions are neither random nor wholly autonomous. They are systematic responses to the internal and external stimuli interacting with the mind. Therefore, free will is not a supernatural or metaphysical phenomenon but a natural process governed by the principle of cause and effect. -/- The Second Law: The Universal Law of Balance -/- The second law in the universal formula is the law of balance, which states that all natural systems, including human consciousness, strive for equilibrium. This principle is observable in physical phenomena such as thermodynamics and ecological systems, but it also applies to human decision-making. Every decision seeks to restore or maintain a certain internal and external balance. -/- When individuals are exposed to misinformation, cognitive dissonance, or emotional disturbances, this balance is disrupted, leading to irrational or harmful decisions. For example, societal problems such as overpopulation, economic inequality, and environmental degradation often stem from decisions that violate the law of balance. Ignorance of this law results in societal imbalances that manifest as conflict, suffering, and systemic dysfunction. -/- In the context of free will, the law of balance reveals that decisions are influenced by the mind’s constant effort to restore equilibrium. When individuals are educated to understand this principle, they become more capable of making rational, well-informed decisions aligned with natural balance. The apparent freedom in decision-making is, therefore, a reflection of the mind’s adaptive response to external and internal conditions, not a mysterious, ungoverned phenomenon. -/- The Third Law: The Law of Systems Integration -/- The third universal law, the law of systems integration, explains that for any decision-making process to function correctly, the underlying system must be free of critical errors or distortions. Just as a computer cannot operate properly if its software is corrupted, human decisions become flawed when misinformation, irrational beliefs, or cognitive biases infiltrate the mental system. -/- Human decision-making does not occur in isolation; it is part of an integrated system involving sensory input, memory, reasoning, and external environmental feedback. If any component of this system is compromised, decisions will deviate from rational, balanced outcomes. For example, societies that rely heavily on dogma or misinformation struggle to make sound collective decisions, resulting in persistent social and economic problems. -/- By understanding the law of systems integration, we recognize that the integrity of decisions depends on the quality and accuracy of the information being processed. Free will, therefore, is not a matter of pure autonomy but a system-dependent phenomenon that requires reliable, unbiased inputs and well-functioning cognitive processes. -/- The Resolution of the Free Will Problem -/- The application of these three universal laws of nature provides the exact solution to the free will problem. Human decisions are neither random nor unbounded acts of personal freedom; they are outcomes of natural processes governed by cause and effect, the drive for balance, and the need for system integrity. Free will, as traditionally conceived, is an illusion rooted in a misunderstanding of these underlying natural laws. -/- By accepting the universal formula, society can move beyond the philosophical deadlock that has hindered intellectual and practical progress for centuries. This formula does not negate human responsibility; instead, it clarifies it by illustrating how decisions follow natural patterns that can be understood, predicted, and influenced through education, societal reforms, and scientific advancements. -/- Implications for Ethics, Justice, Science, and Society -/- The exact resolution of the free will problem through the universal formula has profound implications across multiple domains: -/- 1. Ethics and Moral Responsibility: Ethical frameworks must shift from abstract notions of free will to a system-based understanding of decision-making. Moral responsibility remains intact but is grounded in the recognition that actions result from natural causes. Education should focus on teaching individuals how to align their decisions with the law of balance, promoting rational, ethical behavior. -/- 2. Justice System Reform: Legal systems traditionally assume that individuals act with free will. The universal formula shows that actions stem from natural causes and systemic factors. Justice systems must, therefore, prioritize rehabilitation, education, and preventive measures rather than retribution. Understanding the natural laws of decision-making helps create more effective and fair legal practices. -/- 3. Scientific Advancement and AI Development: The universal formula offers a solid foundation for research in neuroscience, psychology, and artificial intelligence. By programming AGI (Artificial General Intelligence) to adhere to these natural laws, future AI systems can make more reliable, human-like decisions while avoiding cognitive distortions and biases. -/- 4. Educational Reforms: Education systems worldwide must integrate the universal formula to teach students about the natural laws governing human behavior. A holistic, science-based curriculum that emphasizes cause and effect, balance, and systems integration can combat misinformation, dogmatic thinking, and societal discord. -/- 5. Societal Progress and Global Harmony: Societies that understand and apply these universal laws can address complex challenges like overpopulation, environmental degradation, and social inequality. Decisions based on natural balance, rather than short-term economic or ideological gains, lead to sustainable, harmonious development. -/- Conclusion -/- The free will problem, once deemed an unsolvable philosophical puzzle, can be definitively resolved through Angelito Malicse’s three universal laws of nature. The law of karma reveals that decisions follow cause-and-effect relationships; the law of balance shows that choices aim to restore or maintain equilibrium; and the law of systems integration demonstrates the importance of accurate, unbiased information in decision-making. Together, these laws provide an exact, scientific explanation of human behavior, eliminating the need for metaphysical assumptions about free will. -/- By understanding and applying these natural laws, humanity can foster a more rational, ethical, and balanced society. This formula is not a theory—it is a complete, exact solution grounded in observable natural principles. The challenge now lies in implementing these insights within educational, legal, and societal frameworks to address the root causes of human suffering and societal dysfunction. The free will problem is solved; the task ahead is to ensure that this understanding becomes part of our collective knowledge and practice. -/- . (shrink)

-/- Solving the Problem of Free Will: A Universal Formula for Societal Balance -/- Introduction -/- For thousands of years, philosophers, scientists, and scholars have debated the concept of free will without arriving at a definitive solution. The persistent societal problems we witness today—wars, poverty, crime, overpopulation—are deeply rooted in ignorance, particularly about how natural laws govern human decision-making. This essay presents a universal formula that solves the problem of free will by aligning decision-making processes with the universal law of (...) balance found in nature. This solution, if implemented through a holistic educational system, can fundamentally transform societies by eliminating the ignorance that leads to human suffering. -/- The Root of Societal Problems: Ignorance -/- Ignorance is the foundation of nearly all societal problems. Misunderstanding natural laws and disregarding the principles of balance result in poor decision-making, whether on an individual, societal, or global level. Decisions based on misinformation, false beliefs, unproven theories, or emotional biases create imbalances that manifest as societal issues. -/- Examples of Ignorance-Driven Problems: -/- 1. Wars: Wars often arise from misunderstandings, territorial greed, ideological conflicts, and the inability to find peaceful solutions. The ignorance of the law of balance—where equilibrium between differing interests is possible—leads to destruction, suffering, and loss of life. -/- 2. Poverty and Crime: Poverty is frequently the result of systemic imbalances in wealth distribution. Ignorance about how societal resources should be distributed equitably to maintain stability leads to widespread deprivation. Crime similarly stems from a lack of understanding regarding personal responsibility and societal interdependence. -/- 3. Overpopulation: In many countries, overpopulation results from the misconception that growth is inherently good. However, natural systems always maintain balance. Unregulated population growth places immense pressure on resources, leading to poverty, environmental degradation, and societal instability. -/- The Universal Formula: Three Fundamental Laws of Nature -/- This universal formula, derived from observable natural phenomena, consists of three interconnected laws: -/- 1. The Law of Karma (Cause and Effect) Every decision and action produces corresponding consequences. In nature, defective systems—whether mechanical, biological, or societal—inevitably fail. Human societies must recognize that decisions based on ignorance create systemic problems. -/- 2. The Law of Balance Nature operates through balance. From ecosystems to societal structures, stability requires equilibrium. Societal issues like poverty and crime reflect imbalances caused by ignorance of this law. -/- 3. The Law of Homeostasis Homeostasis maintains internal stability despite external changes. Societies must develop adaptive yet balanced policies to ensure long-term well-being. -/- These laws reveal that human free will is not arbitrary but governed by predictable patterns. Conscious decisions, whether individual or collective, operate like feedback loops responding to external and internal stimuli while adhering to natural laws. -/- The Role of the Educational System -/- To address ignorance effectively, societies must adopt a holistic educational system that integrates these universal laws into foundational curricula. Current education often overlooks the principles that govern human behavior and societal balance. The new system should prioritize critical thinking, scientific literacy, and moral responsibility. -/- Key Objectives of a Holistic Educational System: -/- 1. Eliminate Ignorance: Equip students with a deep understanding of natural laws and their role in decision-making. -/- 2. Promote Critical Thinking: Teach students to question information, identify biases, and recognize the long-term impacts of decisions. -/- 3. Prepare Responsible Future Generations: Produce a high-quality generation of future parents who understand the importance of balance in raising children, managing resources, and contributing to societal stability. -/- Example: Incorporating environmental science with lessons on population dynamics can help students grasp why unchecked population growth leads to resource scarcity and societal challenges. Lessons in psychology, combined with discussions about collective decision-making, can illustrate the importance of balanced, informed leadership. -/- The Misconception of Unlimited Growth -/- One of the most damaging misconceptions societies face today is the belief in continuous economic and population growth. In nature, growth is always regulated by available resources. Societies that ignore this principle face environmental destruction, social unrest, and economic instability. -/- Example: Countries experiencing rapid population growth often encounter overcrowded cities, unemployment, and resource depletion. By understanding the law of balance, policymakers can implement sustainable growth strategies, ensuring resources meet population needs without compromising long-term stability. -/- The Feedback Mechanism of Conscious Minds -/- Human decision-making, both individually and collectively, operates as a feedback mechanism. Minds continuously exchange information, influencing one another’s decisions. This interaction follows natural laws, ensuring that any deviation from balance triggers societal disruptions. -/- Example: When misinformation spreads through social media, collective decisions become skewed. Understanding the feedback mechanism can help societies implement educational strategies that foster discernment and rational decision-making. -/- The Need for’Global Collaboration -/- The successful implementation of this universal formula requires global collaboration. International organizations like the United Nations and the World Economic Forum, along with educational institutions worldwide, must prioritize the integration of these natural laws into educational frameworks. -/- Example: The Philippines, facing governance challenges and population pressures, could significantly benefit from such an educational overhaul. Similarly, China’s “whole-process people’s democracy” could incorporate these principles to enhance holistic governance strategies. -/- The Role of Artificial General Intelligence (AGI) -/- AGI, when developed with a complete sensor system, can apply the universal formula to predict and address societal problems. Programming AGI to follow these natural laws will ensure its decisions align with human well-being and societal stability. -/- Conclusion -/- Solving the problem of free will is not an abstract philosophical pursuit but a practical necessity for societal stability. Ignorance of the natural laws governing decision-making has perpetuated human suffering for centuries. The universal formula, grounded in the principles of karma, balance, and homeostasis, offers a concrete, actionable solution. By implementing this understanding through a holistic educational system, we can eliminate the root causes of wars, poverty, crime, and overpopulation. The time to act is now—before ignorance further destabilizes the delicate balance upon which our future depends. -/- . (shrink)

Since Donald Davidson issued his challenge to anticausalism in 1963, most philosophers have espoused the view that our actions are causally explained by the reasons why we do them. This Davidsonian consensus, however, rests on a faulty argument. Davidson’s challenge has been met, in more than one way, by anticausalists such as C. Ginet, G. Wilson, and S. Sehon. Hence I endeavor to support causalism with a stronger argument. Our actions are correlated with our motivating reasons; to wit, we often (...) do what we have reason to do. In yet other words, we are often rational. Our frequent rationality is easily explained if causalism is correct, but looks like a staggering coincidence otherwise. Anticausalism thus appears to be ill-equipped to account for the very existence of rational behavior, and so far no attempts in this direction have succeeded. (shrink)

This work develops a philosophically credible and psychologically realisable account of control that is necessary for moral responsibility. We live, think, and act in an environment of subjective uncertainty and limited information. As a result, our decisions and actions are influenced by factors beyond our control. Our ability to act freely is restricted by uncertainty, ignorance, and luck. Through three articles, I develop a naturalistic theory of control for action as a process of error minimisation that extends over time. (...) Thus conceived, control can serve to minimise the influence of luck on action and enable freedom in uncertainty. -/- In Article 1, Thor Grünbaum and I argue for a psychologically plausible account of the kind of control that is necessary for moral responsibility. We begin by establishing the relationship between agentive contribution and responsibility-level control. One way to determine whether one the right kind and degree of control to be morally responsible is to track one’s degree of contribution to an action. However, a psychologically plausible account of control in terms of agentive contribution may seem to contradict the types of functional-mechanistic explanations used in cognitive science. In cognitive psychology and cognitive neuroscience, personal-level capacities are explained by a set of sub-personal mechanisms. Often, such explanations leave no room for a contribution by the agent. By integrating insights from theories of cognitive control and incorporating them into a philosophical account of intentions, we propose a way of thinking about the distribution of cognitive control resources as something the agent does. -/- Article 2 argues that a classic argument concerning luck, originally aimed at libertarianism, generalises beyond any specific theory of free will, and regardless of whether determinism or indeterminism is true. I call this mental luck. Because we all make decisions under conditions of relative uncertainty and limited information, it is possible for an agent to make decisions that are contrary to their own motivation. In such situations, it may be a matter of luck whether the agent makes the right decision. Mentally lucky decisions are not rationally governed by attitudes within the agent's perspective, and thus, may be indistinguishable from unlucky ones. From the perspective of the agent, such decisions may resemble the outcome of a lottery. Therefore, mental luck poses a challenge to most prominent theories of free action and moral responsibility. -/- Finally, article 3 engages with the issue of resultant luck, namely luck in how things turn out. Resultant luck raises a challenge for theories of moral responsibility because its existence suggests that one may be responsible for factors beyond one’s control. Prominent responses to resultant luck led to a choice between internalism and scepticism. I argue that familiar cases of resultant luck are based on the assumption that actions are events. Instead, I propose an alternative ontology of action as an ongoing goal-directed process with a many-shots structure. Described this way, cases of resultant luck are not representative of ordinary action. The proposal of action as a many-shots process is consistent with predictive coding, a cognitive architecture which centres around error minimisation. Under this framework, cases of resultant more luck are no longer failures of action, but rather anticipated errors to be settled within the ordinary process of action. (shrink)