Embodied cognitive theories predict that linguistic conceptual representations are grounded and continually represented in real world, sensorimotor experiences. However, there is an on-going debate on whether this also holds for abstract concepts. Grammar is the archetype of abstract knowledge, and therefore constitutes a test case against embodied theories of language representation. Former studies have largely focussed on lexical-level embodied representations. In the present study we take the grounding-by-modality idea a step further by using reaction time (RT) data from the linguistic (...) processing of nominal classifiers in Chinese. We take advantage of an independent body of research, which shows that attention in hand space is biased. Specifically, objects near the hand consistently yield shorter RTs as a function of readiness for action on graspable objects within reaching space, and the same biased attention inhibits attentional disengagement. We predicted that this attention bias would equally apply to the graspable object classifier but not to the big object classifier. Chinese speakers (N = 22) judged grammatical congruency of classifier-noun combinations in two conditions: graspable object classifier and big object classifier. We found that RTs for the graspable object classifier were significantly faster in congruent combinations, and significantly slower in incongruent combinations, than the big object classifier. There was no main effect on grammatical violations, but rather an interaction effect of classifier type. Thus, we demonstrate here grammatical category- specific effects pertaining to the semantic content and by extension the visual and tactile modality of acquisition underlying the acquisition of these categories. We conclude that abstract grammatical categories are subjected to the same mechanisms as general cognitive and neurophysiological processes and may therefore be grounded. (shrink)

Realists about aesthetic judgment believe something like the following: for an aesthetic judgment of be correct, it must respond to the intrinsic aesthetic properties possessed by the object in question (e.g., Meskin et al., 2013; Kieran 2010). However, Cutting’s (2003) empirical research on aesthetic judgment puts pressure on that position. His work indicates that unconscious considerations extrinsic to an artwork can underpin said judgements. This paper takes Cutting’s conclusion a step further: If philosophers grant that it’s possible (...) to appreciate artwork on the basis of unconscious biases, then we never can be fully confident that our aesthetic judgment is undergirded by the intrinsic aesthetic properties of an artwork. Furthermore, if judgment on the basis of unconscious, external reasons cannot be ruled out, we cannot be confident that our aesthetic judgments are ‘correct’. I argue that Cutting’s research is just the tip of the iceberg regarding the extrinsic, unconscious factors that influence aesthetic judgment. Expectation bias formed via social influence and context greatly influence aesthetic judgments and are unavoidable: we inevitably form expectations based on all kinds of contextual cues independently of any actual exposure to the item in question. Such factors make it terribly difficult to be confident in our aesthetic judgments. Even if there are objective properties that mark out some items as aesthetically superior to others, we cannot be sure that our judgments are responding to those properties. (shrink)

Philosophers who have written about implicit bias have claimed or implied that individuals are not responsible, and therefore not blameworthy, for their implicit biases, and that this is a function of the nature of implicit bias as implicit: below the radar of conscious reflection, out of the control of the deliberating agent, and not rationally revisable in the way many of our reflective beliefs are. I argue that close attention to the findings of empirical psychology, and to the (...) conditions for blameworthiness, does not support these claims. I suggest that the arguments for the claim that individuals are not liable for blame are invalid, and that there is some reason to suppose that individuals are, at least sometimes, liable to blame for the extent to which they are influenced in behaviour and judgment by implicit biases. I also argue against the claim that it is counter-productive to see bias as something for which individuals are blameworthy; rather, understanding implicit bias as something for which we are liable to blame could be constructive. (shrink)

Many philosophers think that we should use a lottery to decide who gets a good to which two persons have an equal claim but which only one person can get. Some philosophers think that we should save identified persons from harm even at the expense of saving a somewhat greater number of statistical persons from the same harm. I defend a principled way of justifying both judgements, namely, by appealing to the decreasing marginal moral value of survival chances. I identify (...) four desiderata that, I contend, any such justification should satisfy, and explain how my account meets these desiderata, unlike some previous accounts. (shrink)

Extant research has shown that ordinary causal judgments are sensitive to normative factors. For instance, agents who violate a norm are standardly deemed more causal than norm-conforming agents in identical situations. In this paper, we explore two competing explanations for the Norm Effect: the Responsibility View and the Bias View. According to the former, the Norm Effect arises because ordinary causal judgment is intimately intertwined with moral responsibility. According to the alternative view, the Norm Effect is the result (...) of a blame-driven bias. In a series of five preregistered experiments (N = 2688), we present evidence that predominantly favours the Bias View. In particular, and against predictions made by the Responsibility View, we show that participants deem agents who violate nonpertinent or silly norms – norms that do not relate to the outcome at hand – as more causal, and that this effect cannot be explained in terms of plausible mediators such as the agent’s foreknowledge and desire, or the foreseeability of harm. We close with a discussion regarding the implications of these findings, in as regards the just assessment of proximate cause in the law. (shrink)

This paper is a warning that objections based on thought experiments can be misleading because they may elicit judgments that, unbeknownst to the judger, have been seriously skewed by psychological biases. The fact that most people choose not to plug in to the Experience Machine in Nozick’s (1974) famous thought experiment has long been used as a knock-down objection to hedonism because it is widely thought to show that real experiences are more important to us than pleasurable experiences. This paper (...) argues that the commonplace choice to remain in reality when offered a life in the Experience Machine is best explained by status quo bias – the irrational preference for things to remain the same. An alternative thought experiment, empirical evidence, and discussion of how psychological biases can affect our judgments are provided to support this argument. (shrink)

Consider the case wherein a person refuses to listen to a woman’s testimony of leadership, due to the belief that women are incompetent. This is testimonial injustice. It involves the hearer’s prejudicial belief over the speaker’s socially imagined identity. This injustice creates lasting kinds of harms to one’s epistemic self-respect and freedom, as the hearer gives a decreased credibility level to the speaker. In Epistemic Injustice: Power and the Ethics of Knowing, Miranda Fricker proposes the virtue of testimonial justice, which (...) aims to restrain identity prejudice from harming speakers. With this, the hearer reflexively identifies her prejudice and corrects or suspends it. In this essay, I argue that employing the cognitive attitude of suspension is counter-effective to the purpose of the virtue. I explain my argument through the following: 1) the relationship of inquiring attitudes (IAs) with the attitude of suspension; and 2) the argumentative function of reason. Through the suspension of prejudice an IA over the prejudice is acquired by the hearer. Consider, “Is my belief that all women are weak, true?” From this, the argumentative function of reason, and confirmation bias, a metacognitive desire to reaffirm and reestablish the prejudice arises. Thus, defeating the purpose of the virtue. As such, I suggest the attitude of acceptance instead, which serves as settled judgement over the prejudice’s truth and need not involve belief. Through it, the hearer does not inquire over the status of the prejudice’s truth, removing the problems presented by suspension of judgement. (shrink)

We often find ourselves thinking of others as boring, nauseating, dim, dodgy, clumsy, or otherwise irritating or unpleasant. What’s the right thing to do when we have such thoughts? Some philosophers argue we ought to be civil and conceal them, lest others pick up on them and feel disrespected. Drawing on experimental psychology and classical Confucianism, I argue otherwise, suggesting that we ought to (literally) doubt such appraisals and be wary of their veracity.

Garrett Cullity contends that fairness is appropriate impartiality (See Cullity (2004) Chapters 8 and 10 and Cullity (2008)). Cullity deploys his account of fairness as a means of limiting the extreme moral demand to make sacrifices in order to aid others that was posed by Peter Singer in his seminal article ‘Famine, Affluence and Morality’. My paper is founded upon the combination of (1) the observation that the idea that fairness consists in appropriate impartiality is very vague and (2) the (...) fact that psychological studies show the self-serving bias is especially likely to infect one’s judgements when the ideas involved are vague. I argue that Cullity’s solution to extreme moral demandingness is threatened by these findings. I then comment on whether some other theories of fairness are vulnerable to the same objection. (shrink)

Purpose – The purpose of this paper is to examine the popular “information transmitted” interpretation of absolute judgments, and to provide an alternative interpretation if one is needed. Design/methodology/approach – The psychologists Garner and Hake and their successors used Shannon’s Information Theory to quantify information transmitted in absolute judgments of sensory stimuli. Here, information theory is briefly reviewed, followed by a description of the absolute judgment experiment, and its information theory analysis. Empirical channel capacities are scrutinized. A remarkable coincidence, (...) the similarity of maximum information transmitted to human memory capacity, is described. Over 60 representative psychology papers on “information transmitted” are inspected for evidence of memory involvement in absolute judgment. Finally, memory is conceptually integrated into absolute judgment through a novel qualitative model that correctly predicts how judgments change with increase in the number of judged stimuli. Findings – Garner and Hake gave conflicting accounts of how absolute judgments represent information transmission. Further, “channel capacity” is an illusion caused by sampling bias and wishful thinking; information transmitted actually peaks and then declines, the peak coinciding with memory capacity. Absolute judgments themselves have numerous idiosyncracies that are incompatible with a Shannon general communication system but which clearly imply memory dependence. Research limitations/implications – Memory capacity limits the correctness of absolute judgments. Memory capacity is already well measured by other means, making redundant the informational analysis of absolute judgments. Originality/value – This paper presents a long-overdue comprehensive critical review of the established interpretation of absolute judgments in terms of “information transmitted”. An inevitable conclusion is reached: that published measurements of information transmitted actually measure memory capacity. A new, qualitative model is offered for the role of memory in absolute judgments. The model is well supported by recently revealed empirical properties of absolute judgments. (shrink)

This paper means to demonstrate the theoretical-and- methodological potential of a particular pattern of thought about culture. Employing an end-means and absolute value plus concept of reality approach, the continuous model of culture aims to embrace from one holistic standpoint various concepts and debates of the modern human, social, and political sciences. The paper revisits the debates of fact versus value, nature versus culture, culture versus structure, agency versus structure, and economics versus politics and offers the concepts of the rule (...) of law, state capitalism, a dialectical model of progress, and interpretative qualitative research, as well as of cultural diffusion, autonomy, alienation, and individuality. This model distinguishes between the ideal-symbolical and the instrumental functions of culture, sees culture as being sewn from universal binaries, and provides a certain understanding of the cognitive function of a value judgment, with positivism so far vague about the topic. It, too, suggests an extra method for investigating culture : the comparative literature study of culture enables social science to view literature as its potential in-depth interviewee— a case for arguing for a certain conception of interdisciplinarity as well. In addition, it predicts that cultural particularism or individuality remains an essential factor of human existence. Analyzing the issue of Eurocentrism in social science, the model finds modernity ’s concept of reality to be involved in ” methodological ” intellectualistic reductionism, characterizing it since the empiricism/ rationalism origination. Systematically confusing the universal oppositions in a Eurocentric manner, intellectualism becomes a contributing factor in unfolding post- modernity. (shrink)

The discussion in Perspectives on Psychological Science about criteria for scholarly merit shows a potential bias of quantitative measurements compared with informed judgments of scholarly merits. This comment argues for a selection procedure that is open for qualitative arguments.

This paper critically examines the philosophical underpinnings of current experimental investigation into animal affect-related decision-making. Animals’ affective states are standardly operationalised by linking positively valenced states with “approach” behaviours and negatively valenced states with “avoidance” behaviours. While this operationalisation has provided a helpful starting point to investigate the ecological role of animals’ internal states, there is extensive evidence that valenced and motivational states do not always neatly align, namely, instances where “liking” does not entail “wanting” (and vice versa). To address (...) this limitation, this paper proposes the (re-)integration of dominance as a dimension of affect. In particular, I argue that dominance, construed as a measure of organisms’ self-assessed behavioural control, can provide the necessary nuance to understand animal affect-related decision-making. Thus, after addressing the theoretical and methodological challenges related to incorporating dominance into a definition of “core affect”, this paper introduces the “Valence-Arousal-Dominance” model of animal affect. This model is explored for its potential applications in two domains. Firstly, in the study of animal affect-related decision-making under predation risk, and secondly, in the study of animal wellbeing. Through these applications, this model aims to bring experimental paradigms of animal affect-related behaviour closer to ecologically relevant scenarios. (shrink)

This paper explores some ways in which artificial intelligence (AI) could be used to improve human moral judgments in bioethics by avoiding some of the most common sources of error in moral judgment, including ignorance, confusion, and bias. It surveys three existing proposals for building human morality into AI: Top-down, bottom-up, and hybrid approaches. Then it proposes a multi-step, hybrid method, using the example of kidney allocations for transplants as a test case. The paper concludes with brief remarks (...) about how to handle several complications, respond to some objections, and extend this novel method to other important moral issues in bioethics and beyond. (shrink)

In many spheres, the law takes the legal concept of causation to correspond to the folk concept (the correspondence assumption). Courts, including the US Supreme Court, tend to insist on the "common understanding" and that which is "natural to say" (Burrage v. United States) when it comes to expressions relating to causation, and frequently refuse to clarify the expression to juries. As recent work in psychology and experimental philosophy has uncovered, lay attributions of causation are susceptible to a great number (...) of unexpected factors, some of which seem rather peripheral to causation. One of those is the norm effect (Knobe & Fraser, 2008): Agents who, in acting as they do, break a salient norm, are more likely to be considered as having caused a certain consequence than when they do not violate a norm. According to some (e.g., Alicke, 1992) this constitutes a bias. According to others (e.g., Sytsma, 2020), the folk concept of causation is sensitive to normative factors, and there’s nothing wrong with that. In this paper, we explore the question whether the norm effect should be considered a bias from the legal perspective on the one hand, and from the psychological perspective on the other. To do this, we test whether norms which are nonpertinent to the consequences or outright silly also impact causation judgements. The data from two preregistered experiments (total N=593) clearly show they do. This, we argue, makes the bias interpretation plausible from the psychological perspective, and both plausible and problematic from the legal perspective. It also shows that the law should abstain from unreflectively assuming conceptual correspondence between legal and ordinary language concepts. (shrink)

Much has been made about the ways that implicit biases and other apparently unreflective attitudes can affect our actions and judgments in ways that negatively affect our ability to do right. What has been discussed less is that these attitudes negatively affect our freedom. In this paper, I argue that implicit biases pose a problem for free will. My analysis focuses on the compatibilist notion of free will according to which acting freely consists in acting in accordance with our reflectively (...) endorsed beliefs and desires. Though bias presents a problem for free action, I argue that there are steps agents can take to regain their freedom. One such strategy is for agents to cultivate better self-knowledge of the ways that their freedom depends on the relationship between their conscious and unconscious attitudes, and the way these work together to inform action and judgment. This knowledge can act as an important catalyst for agents to seek out and implement short- and long-term strategies for reducing the influence of bias, and I offer four proposals along these lines. The upshot is that though bias is a powerful influence on our actions, we need not resign ourselves to its negative effects for freedom. (shrink)

This chapter provides an account of what dogmatism is, why the term matters, and how it applies to withholding judgment. Roughly, a person is dogmatic about P when a certain problematic personal investment—a superiority complex, broadly construed—biases their judgment concerning whether P. The term dogmatism and its cognates matter because of their social function. To accuse you of dogmatism is to signal how you are to be treated: your judgment or behavior needs to be “brought down to (...) earth,” so that you have a more accurate view of yourself or so you stop treating others as less important or less than. Withholding judgment can be dogmatic in the same way that belief is dogmatic. Belief (withholding) is dogmatic just when the relevant problematic personal investment results in biases that keep a person stuck in that belief (withholding). (shrink)

Moral philosophers and psychologists often assume that people judge morally lucky and morally unlucky agents differently, an assumption that stands at the heart of the Puzzle of Moral Luck. We examine whether the asymmetry is found for reflective intuitions regarding wrongness, blame, permissibility, and punishment judg- ments, whether people’s concrete, case-based judgments align with their explicit, abstract principles regarding moral luck, and what psychological mechanisms might drive the effect. Our experiments produce three findings: First, in within-subjects experiments favorable to reflective (...) deliberation, the vast majority of people judge a lucky and an unlucky agent as equally blameworthy, and their actions as equally wrong and permissible. The philosophical Puzzle of Moral Luck, and the challenge to the very possibility of systematic ethics it is frequently taken to engender, thus simply do not arise. Second, punishment judgments are significantly more outcome- dependent than wrongness, blame, and permissibility judgments. While this constitutes evidence in favor of current Dual Process Theories of moral judgment, the latter need to be qualified: punishment and blame judgments do not seem to be driven by the same process, as is commonly argued in the literature. Third, in between-subjects experiments, outcome has an effect on all four types of moral judgments. This effect is mediated by negligence ascriptions and can ultimately be explained as due to differing probability ascriptions across cases. (shrink)

A growing body of literature has revealed ordinary causal judgement to be sensitive to normative factors, such that a norm-violating agent is regarded more causal than their non-norm-violating counterpart. In this paper, we explore two competing explanations for this phenomenon: the Responsibility View and the Bias View. The Bias View, but not the Responsibility View, predicts features peripheral to the agent’s responsibility to impact causal attributions. In a series of three preregistered experiments (N = 1162), we present new (...) evidence that the Norm Effect arises from such peripheral features, namely from nonpertinent or entirely silly norm violations. Furthermore, we show that this effect cannot be explained by recourse to the agent’s foreknowledge or desire of the outcome, nor by its foreseeability: the Norm Effect arises even when participants judge the norm-violating agent’s doing as equally foreseeable. This, we argue, provides evidence in favour of the Bias View. (shrink)

A model of face representation, inspired by the biology of the visual system, is compared to experimental data on the perception of facial similarity. The face representation model uses aggregate primary visual cortex (V1) cell responses topographically linked to a grid covering the face, allowing comparison of shape and texture at corresponding points in two facial images. When a set of relatively similar faces was used as stimuli, this Linked Aggregate Code (LAC) predicted human performance in similarity judgment experiments. (...) When faces of perceivable categories were used, dimensions such as apparent sex and race emerged from the LAC model without training. The dimensional structure of the LAC similarity measure for the mixed category task displayed some psychologically plausible features but also highlighted differences between the model and the human similarity judgements. The human judgements exhibited a racial perceptual bias that was not shared by the LAC model. The results suggest that the LAC based similarity measure may offer a fertile starting point for further modelling studies of face representation in higher visual areas, including studies of the development of biases in face perception. (shrink)

Knowledge is good, ignorance is bad. So it seems, anyway. But in this dissertation, I argue that some ignorance is epistemically valuable. Sometimes, we should suspend judgment even though by believing we would achieve knowledge. In this apology for ignorance (ignorance, that is, of a certain kind), I defend the following four theses: 1) Sometimes, we should continue inquiry in ignorance, even though we are in a position to know the answer, in order to achieve more than mere knowledge (...) (e.g. understanding) while minimizing the effects of confirmation bias. 2) It’s false that we should believe every proposition such that we are guaranteed to be right about it (and even such that we are guaranteed to know it) if we believe it. 3) Being in a position to know is the norm of assertion: importantly, this does not require belief or (thereby) knowledge, and so proper assertion can survive speaker-ignorance. 4) It can be permissible and conversationally useful to tell audiences things that it is logically impossible for them to come to know: Proper assertion can survive (necessary) audience-side ignorance. Cumulatively, this project suggests that, properly understood, ignorance has an important role to play in the good epistemic life. (shrink)

According to a common view, prejudice always involves some form of epistemic culpability, i.e., a failure to respond to evidence in the appropriate way. I argue that the common view wrongfully assumes that prejudices always involve universal generalizations. After motivating the more plausible thesis that prejudices typically involve a species of generic judgment, I show that standard examples provide no grounds for positing a strong connection between prejudice and epistemic culpability. More generally, the common view fails to recognize the (...) extent to which prejudices are epistemically insidious: once they are internalized as background beliefs, they quite reasonably come to control the assessment and interpretation of new evidence. This property of insidiousness helps explain why prejudices are so recalcitrant to empirical counterevidence and also why they are frequently invisible to introspective reflection. (shrink)

Policing in many parts of the world—the United States in particular—has embraced an archetypal model: a conception of the police based on the tenets of individuated archetypes, such as the heroic police “warrior” or “guardian.” Such policing has in part motivated moves to (1) a reallocative model: reallocating societal resources such that the police are no longer needed in society (defunding and abolishing) because reform strategies cannot fix the way societal problems become manifest in (archetypal) policing; and (2) an algorithmic (...) model: subsuming policing into technocratic judgements encoded in algorithms through strategies such as predictive policing (mitigating archetypal bias). This paper begins by considering the normative basis of the relationship between political community and policing. It then examines the justification of reallocative and algorithmic models in light of the relationship between political community and police. Given commitments to the depth and distribution of security—and proscriptions against dehumanizing strategies—the paper concludes that a nonideal-theory priority rule promoting respect for personhood (manifest in community and dignity-promoting policing strategies) is a necessary condition for the justification of the above models. (shrink)

Experimental philosophy involves subjecting philosophical methods and judgments to empirical scrutiny. I begin by exploring conceptual, confirmational, and empirical factors that limit the significance of experiment-based and survey-based approaches to the evaluation of philosophical epistemic activities. I then consider specific criticisms of experimental philosophy: its experimental conditions lack ecological validity; it wrongly assumes that philosophers rely on psychologized data; it overlooks the reflective and social elements of philosophical case analysis; it misconstrues the importance of both procedural and evaluative forms of (...) philosophical expertise; it incorrectly views psychological bias as incompatible with reliability; and it generalizes to a global, self-defeating skepticism about case judgment. I explain why these criticisms should be understood as converging and interdependent. I also set out a three-level model of philosophical case judgment that frames the criticisms. (shrink)

What makes fast, cumulative cultural evolution work? Where did it come from? Why is it the sole preserve of humans? We set out a self-assembly hypothesis: cultural evolution evolved culturally. We present an evolutionary account that shows this hypothesis to be coherent, plausible, and worthy of further investigation. It has the following steps: (0) in common with other animals, early hominins had significant capacity for social learning; (1) knowledge and skills learned by offspring from their parents began to spread because (...) bearers had more offspring, a process we call CS1 (or Cultural Selection 1); (2) CS1 shaped attentional learning biases; (3) these attentional biases were augmented by explicit learning biases (judgements about what should be copied from whom). Explicit learning biases enabled (4) the high-fidelity, exclusive copying required for fast cultural accumulation of knowledge and skills by a process we call CS2 (or Cultural Selection 2), and (5) the emergence of cognitive processes such as imitation, mindreading and metacognition – ‘cognitive gadgets’ specialised for cultural learning. This self-assembly hypothesis is consistent with archaeological evidence that the stone tools used by early hominins were not dependent on fast, cumulative cultural evolution, and suggests new priorities for research on ‘animal culture’. (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)

Sentencing outcomes turn on moral and evaluative determinations. For example, a finding of “irreparable corruption” is generally a precondition for juvenile life without parole. A finding that the “aggravating factors outweigh the mitigating factors” determines whether a defendant receives the death penalty. Should such moral determinations that expose defendants to extraordinary penalties be subject to a standard of proof? A broad range of federal and state courts have purported to decide this issue “in the abstract and without reference to our (...) sentencing case law,” as the Supreme Court recently put it. Kansas v. Carr, 577 U.S. 108, 119 (2016). According to these courts, “it would mean nothing” to ask whether the defendant “deserves mercy beyond a reasonable doubt” or “more-likely-than-not deserves it” because moral questions are not “factual.” Instead, moral determinations are highly subjective “value calls” to which concepts of doubt and certainty do not intelligibly apply. -/- Implicit in these rulings is a controversial view of the nature of moral judgment. This Article traces the contours of the view and argues that it is out of step with the way the broader public thinks about morality and fails to address the issues defendants have raised. Courts should avoid wading into such controversial waters for two reasons. First, the judiciary has historically maintained neutrality on issues of significant public concern. Second, even if moral determinations are not factual, applying a standard of proof to at least some moral decisions at sentencing would change the outcome of the sentencer’s deliberations, and improve the legitimacy of the legal system. For the reasonableness of doubt depends on context; and moral questions—"are you certain the defendant deserves death?”—make salient the stakes relative to which a person should decide what to believe about ordinary empirical matters. On the resulting view, reasonable doubt in the final moral analysis is not just intelligible, but essential for correcting a bias in the structure of the bifurcated criminal trial that systematically disadvantages defendants: the tendency for de-contextualized "factual findings” in the guilt phase to control outcomes at sentencing. (shrink)

Steve Clarke, Nathan Emmerich, Francesca Minerva and Toni Saad have offered nuanced and insightful commentaries on my paper ‘The truth behind conscientious objection in medicine’.1 I cannot, in this brief response, do justice to all of the objections and suggestions that they have raised. I have tried to focus my response on what I take to be my interlocutors’ main concerns with my Smithian account, with the hope that we can continue the conversation elsewhere. Clarke argues that both Smith and (...) I ‘underestimate the difficulties involved in overcoming the distorting influence of “self-love” on moral judgement’ and ‘fail to recognise how easy it is for us to mistake a self-interested view for an impartial one’.2 His thought is that cognitive bias and ideological commitments will prevent many of us from identifying the standpoint of the impartial spectator and from realising that we are not impartial.1 I agree that successfully adopting the standpoint of the impartial spectator is not an easy task. However, moral reasoning more generally is difficult and susceptible to bias. This does not mean that we should cease such reasoning; rather, we ought to do our best, and we are, at times, successful. Clarke discusses the entrenched attitudes of Antebellum white racists. However, attitudes about slavery have changed, and cognitive biases can change too. In other words, moral progress is possible. Moreover, as I argue in the paper, one of the advantages of the impartial-spectator approach is that it ‘provides a standpoint from which shared deliberation is possible and public reasons are available’.1 Thus, we can appreciate, with relative ease, whether an objector is reasoning from this standpoint. Clarke further argues that we should entertain the idea of employing ‘experts who are trained to overcome cognitive bias and to set aside ideological commitments’ and …. (shrink)

-/- The Inefficiency of the Biological Brain and Its Impact on Personal, Social, and Societal Problems: A Perspective Based on the Universal Formula -/- The human brain, though remarkably complex and capable of extraordinary feats, is inherently limited by its biological structure and inefficiencies. These limitations often lead to errors in perception, cognition, and decision-making, which in turn contribute to a wide range of personal, social, and societal problems. Using the framework of the universal formula, which incorporates the law of (...) karma (cause and effect) and the necessity for systems to be free of defects, we can analyze how the inefficiency of the brain manifests as imbalances that disrupt the natural order. -/- The Biological Brain as an Inefficient System -/- The human brain operates as a biological system, governed by physical and chemical processes. Like any system, it is susceptible to defects, such as cognitive biases, emotional dysregulation, and limitations in memory and reasoning. These inefficiencies stem from evolutionary constraints, where survival and reproduction were prioritized over optimal functioning. -/- For instance, the brain’s tendency toward confirmation bias—favoring information that aligns with existing beliefs—illustrates a defect that disrupts rational decision-making. This defect violates the universal law of balance in nature by creating distorted perceptions of reality, leading to decisions that are not aligned with objective truth. As a result, personal problems such as poor judgment, anxiety, and conflict arise. -/- Impact on Social Interactions and Collective Decisions -/- The inefficiencies of individual brains are amplified in social contexts, where interactions between flawed minds create feedback loops of misunderstanding, miscommunication, and conflict. For example, tribalism—a byproduct of evolutionary social bonding—leads to in-group favoritism and out-group hostility. These behaviors create social imbalances, fueling discrimination, prejudice, and division. -/- According to the universal formula, collective decision-making systems must also adhere to the law of balance. However, when individuals operating under cognitive and emotional inefficiencies participate in governance, education, or economic systems, these defects propagate, resulting in flawed policies and societal structures. For example, leaders influenced by personal biases or misinformation can implement policies that favor short-term gains over long-term sustainability, creating systemic imbalances in society. -/- Societal Problems Rooted in Brain Inefficiency -/- The accumulation of individual and social imbalances inevitably manifests as societal problems, such as poverty, inequality, and environmental degradation. These issues can be traced back to the inefficiency of the biological brain in processing complex, interconnected systems. The human brain struggles to comprehend long-term consequences, leading to overconsumption, unchecked population growth, and unsustainable economic models. -/- The law of karma in the universal formula emphasizes that defective systems produce flawed outcomes. Societies governed by human brains that fail to account for natural balance are bound to experience the consequences of imbalance, such as resource depletion, social unrest, and climate change. These problems are not merely incidental; they are the inevitable result of a system that violates the principles of natural harmony. -/- Addressing Brain Inefficiency Through the Universal Formula -/- The universal formula provides a roadmap for addressing the inefficiencies of the biological brain by emphasizing the importance of balance, feedback mechanisms, and defect-free systems. Education plays a crucial role in this process. By teaching the universal law of balance in nature and fostering critical thinking, individuals can learn to recognize and correct cognitive biases, emotional distortions, and flawed reasoning. -/- Furthermore, the integration of artificial intelligence programmed with the universal formula offers a promising solution to mitigate human brain inefficiencies. AI systems, equipped with complete sensor systems and free from cognitive biases, can serve as objective feedback mechanisms to guide human decision-making. These systems can help individuals and societies adhere to the principles of natural balance, preventing and solving problems that arise from brain inefficiencies. -/- Conclusion -/- The inefficiency of the biological brain is a fundamental cause of many personal, social, and societal problems. By understanding these inefficiencies through the lens of the universal formula, we can identify the root causes of imbalance and implement solutions that align with the natural laws of balance and karma. Through education, technological innovation, and adherence to universal principles, humanity can transcend the limitations of its biological brain and move toward a more harmonious and sustainable future. -/- . (shrink)

Cognitive tests show that identity and symmetry reflect intellect. 'Guess of other guess' creates various symmetries, while only one is right: 'absolute symmetry', which can be outvoted by the majority. Prejudices result from differences between ME (my identity) and others. Unbiased judgement is symmetrical, always in the middle: neither in favor, nor against ME. Intelligence reduces prejudices, but the lack of opportunities can counterbalance it. That's why type of bias differs in various groups: people from war zones, people in (...) therapy, artists, etc.. "The law of values' equity" is a symmetrical principle redefining utility in economics, when people equate all their values. E.g. 2 children averagely rich, is better than one child rich and another poor. If 'a' is an average richness, and 'x' is a difference in richness, and Utility multiplies all values, then: a * a > (a - x) * (a + x), which is: a² > a² - x². It does not however imply egalitarianism, as it is still better to have both children rich than both average or poor. (shrink)

Prof. Miščević has long been an ardent defender of the use of thought experiments in philosophy, foremost metaphysics, epistemology and philosophy of mind. Recently he has, in his typically sophisticated manner, extended his general account of philosophical thought-experimenting to the domain of normative politics. Not only can the history of political philosophy be better understood and appreciated, according to Miščević, when seen as a more or less continuous, yet covert, practice of thought-experimenting, the very progress of the discipline may crucially (...) depend on finding the right balance between the constraints of (biological, psychological, economic, political, and so on) reality and political-moral ideals when we set to design our basic political notions and institutions. I have much less confidence in this project than prof. Miščević does. As a subspecies of moral TE, political TE share all their problems plus exhibit some of their own. In the paper, I present and discuss two types of evidence that threaten to undermine political philosophers’ trust in thought-experiments and the ethical/political intuitions elicited by them: (i) the dismal past record of thought-experimentation in moral and political philosophy; and (ii) the variety, prevalence, and stubbornness, of bias in ordinary social/political judgment. (shrink)

Several studies have shown that people are more likely to attribute intentionality and blame to agents who perform actions that have harmful consequences. This kind of bias has problematic implications for jury decisions because it predicts that judgment in juries will malfunction if an action has a blameworthy effect. Most of these studies include in their design a vignette in which it is clear that agents have foreknowledge of the effects of their actions. This kind of design fails (...) to replicate trial situations where, in most cases, it is impossible to know with certainty whether agents have foreknowledge of the effects of their actions. In the present study, we adopt an alternative design that includes vignettes in which there is no direct evidence of foreknowledge to investigate the relationship between intentionality and blame in actions that have harmful and helpful effects. We find that people are still more likely to attribute intentionality to actions that produce harmful effects than actions that produce good effects. However, we find that people tend to attribute more blame when they have direct evidence of foreknowledge than when presented with an alternative design that does not include foreknowledge. Results indicate the relevant role that evidence of foreknowledge plays in experimental designs that study blame attribution. (shrink)

Many philosophers have become sceptical of the use of thought experiments in theorising about personal identity. In large part this is due to work in experimental philosophy that appears to confirm long held philosophical suspicions that thought experiments elicit inconsistent judgements about personal identity, and hence judgements that are thought to be the product of cognitive biases. If so, these judgements appear to be useless at informing our theories of personal identity. Using the methods of experimental philosophy, we investigate whether (...) people exhibit inconsistent judgements and, if they do, whether these judgements are likely to be the source of cognitive bias or, instead, sensitivity to some relevant factor. We do not find that people’s judgements are sensitive to any of the factors we investigate (relevant or irrelevant), nor that people have inconsistent judgements across cases. Rather, people’s judgements are best explained by them having a very minimal account of what it takes for a person to survive. Since this pattern of judgements is no reason to think that we are subject to cognitive bias, we see no reason, as things stand, to be sceptical of our judgements. (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)

Prof. Miščević has long been an ardent defender of the use of thought experiments in philosophy, foremost metaphysics, epistemology and philosophy of mind. Recently he has, in his typically sophisticated manner, extended his general account of philosophical thought-experimenting to the domain of normative politics. Not only can the history of political philosophy be better understood and appreciated, according to Miščević, when seen as a more or less continuous, yet covert, practice of thought-experimenting, the very progress of the discipline may crucially (...) depend on finding the right balance between the constraints of (biological, psychological, economic, political, and so on) reality and political-moral ideals when we set to design our basic political notions and institutions. I have much less confidence in this project than prof. Miščević does. As a subspecies of moral TEs, political TEs share all their problems plus exhibit some of their own. In the paper, I present and discuss two types of evidence that threaten to undermine political philosophers’ trust in thought experiments and the ethical/political intuitions elicited by them: (i) the dismal past record of thought-experimentation in moral and political philosophy; and (ii) the variety, prevalence, and stubbornness, of bias in social/political judgment. (shrink)

The Inefficiency of the Biological Brain and the Importance of AI for the Next Generation -/- The human brain, often considered the pinnacle of evolutionary design, is an extraordinary organ capable of creativity, critical thinking, and adaptation. However, despite its remarkable abilities, it is inherently inefficient when compared to artificial intelligence (AI) systems in certain domains. The inefficiencies of the biological brain, coupled with the rapid development of AI technology, underline why artificial general intelligence (AGI) holds immense promise for shaping (...) the future of the next generation. By complementing and extending human cognition, AI can address many of the limitations of the biological brain and equip young people with tools to solve the world’s most pressing challenges. -/- The Inefficiencies of the Biological Brain -/- The biological brain operates under significant constraints that limit its potential. Some of these inefficiencies include: -/- 1. Cognitive Biases and Emotional Interference The human brain is subject to cognitive biases, such as confirmation bias, which can hinder rational decision-making. Emotional states, while vital for human experience, can cloud judgment and lead to impulsive or irrational behavior. These limitations often result in flawed decisions, particularly in complex or high-stakes situations. -/- 2. Limited Processing Power and Memory While the brain is capable of parallel processing, it has finite processing power and memory storage. Tasks requiring large-scale computations, vast data analysis, or instantaneous recall of details often exceed its capabilities. For instance, analyzing terabytes of data to identify patterns or trends is beyond the capacity of any single individual. -/- 3. Slow Learning and Knowledge Retention Learning is a time-intensive process for humans. Acquiring expertise in a single domain can take years, and even then, the retention of knowledge often deteriorates over time. The brain also struggles to adapt quickly to entirely new fields or technologies without substantial effort. -/- 4. Physical Vulnerabilities The brain is biologically constrained by aging, disease, and trauma. These vulnerabilities can result in cognitive decline, memory loss, or even the complete inability to function. These natural limitations cannot yet be fully mitigated through biological means. -/- 5. Bias from Evolutionary Pressures The human brain evolved for survival in environments vastly different from the modern world. Traits like fear, aggression, or tribalism, which were once advantageous, can now lead to social conflicts, inefficiency, and short-term thinking. -/- Why AI and AGI Are Crucial for the Next Generation -/- Artificial intelligence has the potential to address the inefficiencies of the biological brain and create a brighter, more equitable future for the next generation. Its capabilities go far beyond traditional human cognition in several key areas: -/- 1. Enhanced Problem-Solving Abilities AI systems are capable of processing massive datasets, analyzing patterns, and generating solutions far more efficiently than the human brain. For example, AI is already transforming industries such as healthcare by diagnosing diseases with greater accuracy and speed. Future AGI could enable young people to tackle global challenges such as climate change, resource distribution, and poverty with unprecedented precision. -/- 2. Overcoming Human Biases Unlike the biological brain, which is prone to emotional and cognitive biases, well-designed AI systems can function based on objective logic and evidence. This could lead to more equitable policy-making, unbiased education systems, and transparent governance. -/- 3. Accelerated Learning and Knowledge Access AI-powered tools can revolutionize education by providing personalized learning experiences tailored to individual needs. With access to AI tutors and resources, young people can acquire skills and knowledge faster and more effectively than ever before, bridging educational gaps and fostering innovation. -/- 4. Augmentation of Human Potential By integrating AI with human cognition, individuals can expand their capabilities beyond natural limits. For example, brain-computer interfaces (BCIs) could allow people to directly interact with AI systems, enhancing memory, decision-making, and creativity. This symbiosis between humans and machines could redefine what it means to be human. -/- 5. Future-Proofing Against Global Challenges The next generation will face challenges that require solutions at a scale and complexity beyond human capacity. AI and AGI are indispensable for managing these challenges, from predicting pandemics and optimizing energy usage to navigating ethical dilemmas in an interconnected world. -/- Building a New Paradigm for the Next Generation -/- To ensure that AI benefits society as a whole, it is essential to integrate it into the foundational education and development of young people. Teaching students about AI, its capabilities, and ethical implications will empower them to use these tools responsibly. Furthermore, fostering collaboration between humans and AI, rather than fearing technological displacement, will cultivate a new paradigm where human creativity and machine efficiency coexist harmoniously. -/- Governments, educational institutions, and industries must work together to democratize access to AI technologies, ensuring that the benefits are shared equitably. Ethical frameworks should be developed to guide the use of AI, ensuring that it remains a tool for human progress rather than a source of inequality or harm. -/- Conclusion -/- The inefficiencies of the biological brain highlight the need for complementary technologies that can amplify human potential. AI and AGI represent the next frontier in human evolution, offering solutions to our cognitive and societal limitations. For the next generation, these technologies are not merely tools but essential companions in shaping a better, more sustainable world. By embracing AI and equipping young people with the skills to harness its power, humanity can transcend its limitations and unlock a future of unparalleled possibilities. -/- . (shrink)

-/- The Science Behind Excessive Irrational Behavior: A Cognitive, Social, and Natural Law Perspective -/- Irrational behavior is a fundamental aspect of human interaction, serving as a response to perceived threats, misunderstandings, or emotional distress. However, when irrational behavior becomes excessive, unbalanced, or emotionally driven, it can indicate inefficiencies in cognitive processing, mental health issues, and misunderstandings arising from proximity of individual perception and the no-input perception of others. This essay explores the scientific basis of excessive irrational behavior through neuroscience, (...) psychology, evolutionary biology, and the principles of dynamic social interaction, while also examining its relation to the universal law of balance in nature. -/- The Cognitive Science of Irrational Behavior -/- From a neurological perspective, excessive irrational behavior can result from cognitive biases, emotional dysregulation, and inefficient brain processing. The prefrontal cortex, responsible for rational thinking and impulse control, plays a crucial role in judgment. If it functions inefficiently, a person may engage in rash or erratic behavior without fully analyzing the situation. Similarly, an overactive amygdala, which processes emotions like fear and anger, can make individuals more reactive and prone to negative responses. -/- Cognitive biases also shape how people engage in irrational behavior. Negativity bias makes the brain focus more on flaws and mistakes, while the fundamental attribution error leads people to blame others’ failures on personality traits rather than external circumstances. The Dunning-Kruger effect further explains how individuals with limited knowledge may overestimate their understanding, making them more prone to irrational responses while unaware of their own shortcomings. -/- Dynamic Social Interaction, Irrational Behavior, and Mental Health -/- Human interactions are governed by dynamic social interaction principles, which emphasize that all social behavior involves continuous feedback loops, adaptation, and reciprocal influence. However, irrational behavior, mental health disorders, and distortions in perception can disrupt these processes, leading to dysfunctional social interactions and social imbalance in the following ways: -/- 1. Feedback Mechanisms and Cognitive Distortions – In a healthy social system, irrational behavior can be corrected through feedback loops. However, mental health disorders such as anxiety, depression, and personality disorders can distort perception, leading individuals to engage in excessive or unbalanced irrational behavior. -/- 2. Reciprocity and Social Imbalance – Rational social interactions require a balance between rational responses and emotional regulation. However, conditions like narcissistic personality disorder (NPD) or borderline personality disorder (BPD) can create patterns of excessive emotional reactivity, hypersensitivity to perceived slights, and instability, disrupting healthy reciprocity. -/- 3. Homeostasis in Social Groups and Emotional Dysregulation – Just as biological systems maintain balance, social groups function best when there is emotional regulation and rational decision-making. Individuals suffering from bipolar disorder, schizophrenia, or severe mood disorders may engage in irrational behavior, causing instability in group dynamics. -/- 4. Emergent Behavior and Influence of Mental Health Issues – Social groups evolve based on collective interactions. If individuals with irrational thought patterns dominate discussions, they can influence others through groupthink, paranoia, or mob behavior, leading to misguided responses and social dysfunction. -/- 5. Emotional Contagion and the Spread of Irrational Behavior – Irrational behavior, like other emotions, spreads through social contagion. If negativity becomes dominant in a group due to irrational behaviors or mental health struggles, it can lower morale, increase hostility, and reduce cooperation, leading to chronic stress and conflict in relationships. -/- The Effect of Proximity of Individual Perception and No-Input Perception -/- Proximity of individual perception refers to how close or far an individual is to an issue, shaping the way they perceive reality. People who experience a problem firsthand tend to see more details, nuances, and complexity, while those who are distant from the issue may form oversimplified, biased, or incorrect judgments. -/- On the other hand, no-input perception occurs when individuals lack direct experience, knowledge, or sensory input about a situation, yet they still form strong opinions and engage in irrational behavior based on assumptions, external influences, or personal biases. This phenomenon is particularly dangerous in social decision-making because: -/- 1. False Confidence in Judgment – When individuals rely on second-hand information rather than direct experience, they may feel certain about their views despite lacking critical knowledge. This leads to misguided behavior and the spread of false narratives. -/- 2. Oversimplification and Cognitive Errors – People distant from an issue tend to reduce complex realities into black-and-white thinking. This prevents them from seeing the underlying causes of human behavior, leading to unfair or exaggerated judgments. -/- 3. Social Fragmentation and Conflict – When different individuals or groups have varying levels of proximity to an issue, their perceptions may clash, causing misunderstandings, polarization, and difficulty in reaching consensus. -/- 4. Echo Chambers and Groupthink – No-input perception can thrive in echo chambers, where individuals hear only information that reinforces their existing beliefs. This leads to blind behavior, where people react impulsively based on false or incomplete information. -/- 5. Distorted Leadership and Decision-Making – Leaders who make decisions without firsthand experience or diverse input may rely on no-input perception, leading to ineffective policies and misplaced blame on individuals rather than systemic problems. -/- The Interplay between proximity of perception and no-input perception further amplifies irrational behavior, creating cycles of misguided responses and resistance to correction. -/- The Universal Law of Balance in Nature and Rational Social Behavior -/- According to the universal law of balance in nature, all decision-making—whether individual or collective—should maintain equilibrium. Irrational behavior, when properly understood, should function as a natural feedback mechanism that corrects errors and enhances overall balance. However, if behavior is driven by ignorance, false beliefs, emotional bias, mental health issues, or distorted perceptions, it disrupts balance and creates unnecessary conflict. -/- To align behavior with natural balance, individuals must develop self-awareness, emotional intelligence, and holistic thinking. Instead of reacting impulsively, they should analyze situations objectively and ensure their responses contribute to constructive improvement rather than unnecessary negativity. -/- Conclusion -/- Excessive irrational behavior can often be traced to cognitive inefficiencies, evolutionary conditioning, ignorance of natural laws, mental health issues, and distortions caused by perception proximity and no-input perception. While the ability to respond to situations is essential for growth and problem-solving, it must be applied with rationality, fairness, and a holistic understanding of human nature. -/- By recognizing the interconnected nature of decision-making, mental health influences, dynamic social interaction principles, and the effects of perception distortions, individuals can transform destructive irrational behavior into a tool for progress, harmony, and collective well-being. -/- Integrating mental health awareness, perception analysis, and rational feedback mechanisms into education and social systems will help societies maintain balance, cooperation, and sustainable decision-making, preventing the harmful effects of misguided behavior and irrational social conflict. -/- . (shrink)

In this dissertation, I construct scientifically and practically adequate moral analogs of cognitive heuristics and biases. Cognitive heuristics are reasoning “shortcuts” that are efficient but flawed. Such flaws yield systematic judgment errors—i.e., cognitive biases. For example, the availability heuristic infers an event’s probability by seeing how easy it is to recall similar events. Since dramatic events, such as airplane crashes, are disproportionately easy to recall, this heuristic explains systematic overestimations of their probability (availability bias). The research program on (...) cognitive heuristics and biases (e.g., Daniel Kahneman’s work) has been scientifically successful and has yielded useful error-prevention techniques—i.e., cognitive debiasing. I attempt to apply this framework to moral reasoning to yield moral heuristics and biases. For instance, a moral bias of unjustified differences in the treatment of particular animal species might be partially explained by a moral heuristic that dubiously infers animals’ moral status from their aesthetic features. While the basis for identifying judgments as cognitive errors is often unassailable (e.g., per violating laws of logic), identifying moral errors seemingly requires appealing to moral truth, which, I argue, is problematic within science. Such appeals can be avoided by repackaging moral theories as mere “standards-of-interest” (a la non-normative metrics of purportedly right-making features/properties). However, standards-of-interest do not provide authority, which is needed for effective debiasing. Nevertheless, since each person deems their own subjective morality authoritative, subjective morality (qua standard-of-interest and not moral subjectivism) satisfies both scientific and practical concerns. As such, (idealized) subjective morality grounds a moral analog of cognitive biases—namely, subjective moral biases (e.g., committed anti-racists unconsciously discriminating). I also argue that "cognitive heuristic" is defined by its contrast with rationality. Consequently, heuristics explain biases, which are also so defined. However, such contrasting with rationality is causally irrelevant to cognition. This frustrates the presumed usefulness of the kind, heuristic, in causal explanation. As such, in the moral case, I jettison the role of causal explanation and tailor categories solely for contrastive explanation. As such, “moral heuristic” is replaced with "subjective moral fallacy," which is defined by its contrast with subjective morality and explains subjective moral biases. The resultant subjective moral biases and fallacies framework can undergird future empirical research. (shrink)

The evidence based medicine movement has championed the need for objective and transparent methods of clinical guideline development. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) framework was developed for that purpose. Central to this framework is criteria for assessing the quality of evidence from clinical studies and the impact that body of evidence should have on our confidence in the clinical effectiveness of a therapy under examination. Grades of Recommendation, Assessment, Development, and Evaluation has been adopted by a (...) number of professional medical societies and organizations as a means for orienting the development of clinical guidelines. As a result, the method of GRADE has implications on how health care is delivered and patient outcomes. In this paper, we reveal several issues with the underlying logic of GRADE that warrant further discussion. First, the definitions of the “grades of evidence” provided by GRADE, while explicit, are functionally vague. Second, the “criteria for assigning grade of evidence” is seemingly arbitrary and arguably logically incoherent. Finally, the GRADE method is unclear on how to integrate evidence grades with other important factors, such as patient preferences, and trade‐offs between costs, benefits, and harms when proposing a clinical practice recommendation. Much of the GRADE method requires judgement on the part of the user, making it unclear as to how the framework reduces bias in recommendations or makes them more transparent—both goals of the programme. It is our view that the issues presented in this paper undermine GRADE's justificatory scheme, thereby limiting the usefulness of GRADE as a tool for developing clinical recommendations. (shrink)

Impairment of self-control is often said to be a defining feature of addiction. Yet many addicts display what appears to be a considerable amount of control over their drug-oriented actions. Not only are their actions clearly intentional and frequently carried out in a conscious and deliberate manner, there is evidence that many addicts are responsive to a wide range of ordinary incentives and counter-incentives. Moreover, addicts have a wide variety of reasons for using drugs, reasons which often seem to go (...) a long way towards explaining their drug-oriented behavior. Many use drugs, for example, to cope with stressful or traumatic experiences. In this article I argue that some standard philosophical explanations of addicts’ impairment of self-control are inadequate, and propose an alternative. (shrink)

Eyal Shahar’s essay review [1] of James Penston’s remarkable book [2] seems more inspired playful academic provocation than review or essay, expressing dramatic views of impossible validity. The account given of modern biostatistical causation reveals the slide from science into the intellectual confusion and non-science RCTs have created: “…. the purpose of medical research is to estimate the magnitude of the effect of a causal contrast, for example the probability ratio of a binary outcome …” But Shahar’s world is simultaneously (...) not probabilistic, but of absolute uncertainty: “We should have no confidence in any type of evidence ….. We should have no confidence at all”. Shahar’s "Causal contrast" is attractive. It seems to make sense, but bypasses in two words the means of establishing causation by the scientific method. This phrase assumes a numeric statistically significant “contrast” is causal rather than a potential correlation requiring further investigation. The concept of “causal contrast” is a slippery slope from sense into biostatistical non-science. This can be illustrated with an hypothetical RCT where 100% of interventions exhibit a posited treatment effect and 0% of placebo controls. Internal validity is seemingly quite reasonably assumed satisfied (common-sense dictating the likelihood of an awesome magnificent fraud, bias or plain error of the magnitude required is infinitesimal). Scientific method appears satisfied. The RCT demonstrates: (1) strict regularity of outcome in the presence of posited cause; (2) the absence of outcome in its absence and (3) an intervention (experiment) showing the direction of causation is from posited cause to posited effect. Now travel further down the slope from science. Assume 50% of interventions and 0% of controls are positive. We compromise scientific method, but justify this by assuming a large subgroup which we say surely must on these figures be exhibiting the posited treatment effect. But what of 10% of interventions and 9% of placebo controls exhibiting the posited treatment effect? Our biostatistician says the 1% “causal contrast” is statistically significant. But we have: (1) minimal evidence of regularity; (2) the posited outcome irrespective of presence of posited cause and (3) our intervention is at the highest equivocal in demonstrating any form of causation. This is not science. It is, however, where biostatistics has unthinkingly taken us, as Penston has shown comprehensively [2]. We, the audience of published medical research, are now for the 10% / 9% example well down the slope from science. An unattractive hypothesis results requiring numerous assumptions similar to these:- "There is a 'contrast' which is ‘causal’, albeit the method employed is not scientific. An effect of the intervention has been observed in a very small subgroup. This subgroup is susceptible to treatment. The similar number of placebo controls exhibiting the outcome sought is irrelevant, because the 1% difference between intervention and controls is statistically significant. The statistical analysis is valid and reliable. The RCT’s internal validity is sufficiently satisfied. No funding or bias or fraud has affected the results or their analysis.” As Penston notes: “Confirming and refuting the results of research is crucial to science …. But … there’s no way of testing the results of any particular large-scale RCT or epidemiological study. Each study … is left hanging in the air, unsupported.” It gets worse. To identify a rare serious adverse reaction of a frequency of 1:10,000 can require a trial of 200,000 or larger split between controls and interventions. This is not done. But for every 100 who prospectively benefit from the intervention, 9,900 also receive it. And for every 100 benefiting one person (who likely gains no benefit) will suffer a serious unidentified adverse reaction. This is also without taking account of more common adverse reactions whether serious or otherwise. References [1] Shahar, E. (2011) Research and medicine: human conjectures at every turn. International Journal of Person Centered Medicine 1 (2), 250-253. [2] Penston, J. (2010). stats.con: How we’ve been fooled by statistics-based research in medicine. London: The London Press, UK. (shrink)

Mental accounting is a concept associated with the work of Richard Thaler. According to Thaler, people think of value in relative rather than absolute terms. They derive pleasure not just from an object’s value, but also the quality of the deal – its transaction utility (Thaler, 1985). In addition, humans often fail to fully consider opportunity costs (tradeoffs) and are susceptible to the sunk cost fallacy. Why are people willing to spend more when they pay with a credit card than (...) cash (Prelec & Simester, 2001)? Why would more individuals spend $10 on a theater ticket if they had just lost a $10 bill than if they had to replace a lost ticket worth $10 (Kahneman & Tversky, 1984)? Why are people more likely to spend a small inheritance and invest a large one (Thaler, 1985)? According to the theory of mental accounting, people treat money differently, depending on factors such as the money’s origin and intended use, rather than thinking of it in terms of the “bottom line” as in formal accounting (Thaler, 1999). An important term underlying the theory is fungibility, the fact that all money is interchangable and has no labels. In mental accounting, people treat assets as less fungible than they really are. Even seasoned investors are susceptible to this bias when they view recent gains as disposable “house money” (Thaler & Johnson, 1990) that can be used in high-risk investments. In doing so, they make decisions on each mental account separately, losing out the big picture of the portfolio. (See also partitioning and pain of paying for ideas related to mental accounting.) . (shrink)

chapter on perception and bias including implicit bias.

The rationality of future bias figures crucially in various metaphysical and ethical arguments (Prior 1959; Parfit 1984; Fischer 2019). Recently, however, philosophers have raised several arguments to the effect that future bias is irrational (Dougherty 2011; Suhler and Callender 2012; Greene and Sullivan 2015). Particularly, Greene and Sullivan (2015) claim that future bias is irrational because future bias leads to two kinds of irrational planning behaviors in agents who also seek to avoid regret. In this paper, (...) I join others who have objected to Greene and Sullivan’s argument (Dorsey 2016; Tarsney 2017), but for significantly different reasons that put into question an unchallenged premise in the debate. These reasons are based on the relationship between the alleged irrational planning behaviors and certain features of regret that regret shares with future bias. First, regret is dynamic, involving preferences that change over time and in inconsistent ways. Second, regret comes in degrees, meaning that we can rank our potential regrets. Because regret has these features, I show that the future-biased agents in Greene and Sullivan’s cases do not need to act in irrational ways to rationally avoid regret. (shrink)

What is the mental representation that is responsible for implicit bias? What is this representation that mediates between the trigger and the biased behavior? My claim is that this representation is neither a propositional attitude nor a mere association. Rather, it is mental imagery: perceptual processing that is not directly triggered by sensory input. I argue that this view captures the advantages of the two standard accounts without inheriting their disadvantages. Further, this view also explains why manipulating mental imagery (...) is among the most efficient ways of counteracting implicit bias. (shrink)

Philosophers have long noted, and empirical psychology has lately confirmed, that most people are “biased toward the future”: we prefer to have positive experiences in the future, and negative experiences in the past. At least two explanations have been offered for this bias: belief in temporal passage and the practical irrelevance of the past resulting from our inability to influence past events. We set out to test the latter explanation. In a large survey, we find that participants exhibit significantly (...) less future bias when asked to consider scenarios where they can affect their own past experiences. This supports the “practical irrelevance” explanation of future bias. It also suggests that future bias is not an inflexible preference hardwired by evolution, but results from a more general disposition to “accept the things we cannot change”. However, participants still exhibited substantial future bias in scenarios in which they could affect the past, leaving room for complementary explanations. Beyond the main finding, our results also indicate that future bias is stake-sensitive and that participants endorse the normative correctness of their future-biased preferences and choices. In combination, these results shed light on philosophical debates over the rationality of future bias, suggesting that it may be a rational response to empirical realities rather than a brute, arational disposition. (shrink)

All else being equal, most of us typically prefer to have positive experiences in the future rather than the past and negative experiences in the past rather than the future. Recent empirical evidence tends not only to support the idea that people have these preferences, but further, that people tend to prefer more painful experiences in their past rather than fewer in their future (and mutatis mutandis for pleasant experiences). Are such preferences rationally permissible, or are they, as time-neutralists contend, (...) rationally impermissible? And what is it that grounds their having the normative status that they do have? We consider two sorts of arguments regarding the normative status of future-biased preferences. The first appeals to the supposed arbitrariness of these preferences, and the second appeals to their upshot. We evaluate these arguments in light of the recent empirical research on future-bias. (shrink)

This paper examines the role of prestige bias in shaping academic philosophy, with a focus on its demographics. I argue that prestige bias exacerbates the structural underrepresentation of minorities in philosophy. It works as a filter against (among others) philosophers of color, women philosophers, and philosophers of low socio-economic status. As a consequence of prestige bias our judgments of philosophical quality become distorted. I outline ways in which prestige bias in philosophy can be mitigated.

Our focus here is on whether, when influenced by implicit biases, those behavioural dispositions should be understood as being a part of that person’s character: whether they are part of the agent that can be morally evaluated.[4] We frame this issue in terms of control. If a state, process, or behaviour is not something that the agent can, in the relevant sense, control, then it is not something that counts as part of her character. A number of theorists have argued (...) that individuals do not have control, in the relevant sense, over the operation of implicit bias. We will argue that this claim is mistaken. We articulate and develop a notion of control that individuals have with respect to implicit bias, and argue that this kind of control can ground character-based evaluation of such behavioural dispositions. (shrink)

Are individuals morally responsible for their implicit biases? One reason to think not is that implicit biases are often advertised as unconscious, ‘introspectively inaccessible’ attitudes. However, recent empirical evidence consistently suggests that individuals are aware of their implicit biases, although often in partial and inarticulate ways. Here I explore the implications of this evidence of partial awareness for individuals’ moral responsibility. First, I argue that responsibility comes in degrees. Second, I argue that individuals’ partial awareness of their implicit biases makes (...) them (partially) morally responsible for them. I argue by analogy to a close relative of implicit bias: moods. (shrink)