The conditions animals experience during the early developmental stages of their lives can have critical ongoing effects on their future health, welfare, and proper development. In this paper we draw on evolutionary theory to improve our understanding of the processes of developmental programming, particularly Predictive Adaptive Responses (PAR) that serve to match offspring phenotype with predicted future environmental conditions. When these predictions fail, a mismatch occurs between offspring phenotype and the environment, which can have long-lasting health and welfare (...) effects. Examples include metabolic diseases resulting from maternal nutrition and behavioral changes from maternal stress. An understanding of these processes and their evolutionary origins will help in identifying and providing appropriate developmental conditions to optimize offspring welfare. This serves as an example of the benefits of using evolutionary thinking within veterinary science and we suggest that in the same way that evolutionary medicine has helped our understanding of human health, the implementation of evolutionary veterinary science (EvoVetSci) could be a useful way forward for research in animal health and welfare. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

Mismatch is a prominent concept in evolutionary medicine, and a number of philosophers have published analyses of this concept. The word ‘mismatch’ has been used in a diversity of ways across a range of sciences, leading these authors to regard it as a vague concept in need of philosophical clarification. Here, in contrast, we concentrate on the use of mismatch in modelling and experimentation in evolutionary medicine. This reveals a rigorous theory of mismatch within which the term ‘mismatch’ is indeed (...) used in several ways, not because it is ill defined but because different forms of mismatch are distinguished within the theory. Contemporary evolutionary medicine has unified the idea of ‘evolutionary mismatch’, derived from the older idea of ‘adaptive lag’ in evolution, with ideas about mismatch in development and physiology derived from the developmental origins of health and disease (DOHaD) paradigm. A number of publications in evolutionary medicine have tried to make this theoretical framework explicit. We build on these to present the theory in as simple and general a form as possible. We introduce terminology, largely drawn from the existing literature, to distinguish the different forms of mismatch. This integrative theory of mismatch captures how organisms track environments across space and time on multiple scales in order to maintain an adaptive match to the environment, and how failures of adaptive tracking lead to disease. Mismatch is a productive organizing concept within this theory that helps researchers articulate how physiology, development, and evolution interact with one another and with environmental change to explain health outcomes. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics and historical (...) data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

Creativity and Intelligence: Emergent Properties of the Brain as a Balancing Mechanism for Overpopulation, Natural Disasters, and Diseases -/- The human brain is an extraordinary organ, capable of producing creativity and intelligence as emergent properties that allow humanity to address complex challenges. These traits are not merely tools for individual survival; they function as collective mechanisms to adapt to large-scale issues that threaten humanity’s balance with the environment. Overpopulation, natural disasters, and the prevalence of diseases and illnesses represent some of (...) the most significant pressures on human societies. Through the brain’s capacity for problem-solving and innovation, humanity has developed strategies to mitigate these challenges and maintain equilibrium within the universal law of balance. -/- The Brain as a Balancing Mechanism -/- At its essence, the brain operates as a dynamic system that processes external stimuli and generates adaptive responses. Creativity and intelligence arise from this system as tools to predict, analyze, and address challenges that disrupt balance. Overpopulation, natural disasters, and diseases disrupt human life on social, economic, and environmental levels, testing the brain’s ability to create solutions. -/- Creativity in Addressing Overpopulation -/- Overpopulation places immense strain on resources, ecosystems, and social structures, often leading to food shortages, environmental degradation, and urban overcrowding. The brain’s creative capacity has allowed humans to develop innovations to address these issues. Urban agriculture, such as vertical farming, is an example of how creativity has transformed food production in densely populated areas, reducing dependence on traditional farmland and conserving resources. Similarly, advancements in renewable energy technologies, such as solar and wind power, reduce the ecological footprint of growing populations, providing sustainable solutions to energy needs. -/- Creativity also plays a critical role in social policies and education. Family planning programs and reproductive health education have empowered individuals, particularly women, to make informed decisions, reducing population growth rates in many regions. These initiatives reflect the brain’s ability to create holistic solutions that align societal needs with the preservation of natural balance. -/- Intelligence in Managing Natural Disasters -/- Natural disasters, unpredictable and often catastrophic, require intelligent strategies to mitigate their impact. Intelligence enables humans to analyze data, predict disasters, and prepare for their consequences. Early warning systems for tsunamis, hurricanes, and earthquakes exemplify this, providing communities with critical time to evacuate and take protective measures. -/- Furthermore, intelligence drives the design of resilient infrastructure that can withstand disasters. For instance, earthquake-resistant buildings and flood mitigation systems demonstrate the brain’s capacity to transform scientific knowledge into practical solutions. These innovations save lives, reduce economic losses, and facilitate faster recovery after disasters, ensuring that human societies maintain their balance despite nature’s unpredictability. -/- Creativity and Intelligence in Combating Diseases and Illnesses -/- Diseases and illnesses have long been among humanity’s greatest challenges, especially in the context of overpopulation, which facilitates the rapid spread of infectious diseases. The brain’s emergent properties of creativity and intelligence have been critical in combating these threats through advancements in medicine, public health, and technology. -/- The development of vaccines, antibiotics, and antiviral drugs highlights humanity’s creative response to disease. For example, the eradication of smallpox and the near-elimination of polio are milestones achieved through creative and intelligent applications of medical science. During the COVID-19 pandemic, intelligence and creativity led to the rapid development of vaccines using mRNA technology, showcasing the brain’s ability to adapt to new challenges at an unprecedented pace. -/- Public health strategies, such as sanitation systems, clean water initiatives, and disease surveillance networks, also reflect the brain’s ability to create systemic solutions. These measures have significantly reduced the burden of communicable diseases, particularly in densely populated areas. Moreover, advancements in artificial intelligence and biotechnology continue to enhance humanity’s ability to detect, prevent, and treat illnesses. -/- The Interplay of Creativity, Intelligence, and Feedback Mechanisms -/- Creativity and intelligence act as feedback mechanisms that enable humans to respond to disruptions while maintaining balance within the universal law of nature. Overpopulation, natural disasters, and diseases disrupt this balance, prompting the brain to generate solutions that restore harmony. -/- For instance, urban planning that incorporates green spaces and sustainable infrastructure addresses the environmental strain caused by overpopulation. Similarly, the integration of traditional knowledge with modern technologies enhances disaster resilience. In the context of diseases, the collaboration of global institutions and local communities reflects the brain’s capacity to balance innovation with cultural and social considerations. -/- Challenges and Ethical Considerations -/- While creativity and intelligence empower humanity to address these challenges, they also carry significant ethical responsibilities. Technological advancements must align with principles of sustainability and equity. For example, while vaccines have saved millions of lives, unequal access to these innovations highlights the need for ethical distribution systems. Similarly, urban development projects must prioritize environmental conservation and community well-being to avoid exacerbating existing imbalances. -/- Additionally, the misuse of intelligence and creativity—such as the development of biological weapons or unsustainable industrial practices—can worsen the effects of overpopulation, natural disasters, and diseases. Ensuring that human ingenuity aligns with the principles of balance and harmony is essential to avoid unintended consequences. -/- Conclusion -/- Creativity and intelligence are emergent properties of the human brain that have enabled humanity to adapt to and mitigate the negative effects of overpopulation, natural disasters, and diseases. These traits function as balancing mechanisms, allowing humans to innovate and maintain harmony within the framework of natural laws. However, the application of these capabilities must be guided by ethical considerations and a commitment to sustainability. By aligning human creativity and intelligence with the universal law of balance, humanity can navigate its most pressing challenges and build a more resilient and equitable future. -/- . (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)

Emergency response times play a critical role in saving lives, especially in urban settings where traffic congestion and unpredictable events can delay ambulance arrivals. This paper explores a novel framework for smart route optimization for emergency vehicles, leveraging artificial intelligence (AI), Internet of Things (IoT) technologies, and dynamic traffic analytics. We propose a real-time adaptive routing system that integrates machine learning (ML) for predictive modeling and IoT-enabled communication with traffic infrastructure. The system is evaluated using simulated urban (...) environments, achieving a 35% reduction in response times compared to traditional methods. This work lays the foundation for future advancements in intelligent emergency systems and their integration into smart cities. (shrink)

Emergency response times play a critical role in saving lives, especially in urban settings where traffic congestion and unpredictable events can delay ambulance arrivals. This paper explores a novel framework for smart route optimization for emergency vehicles, leveraging artificial intelligence (AI), Internet of Things (IoT) technologies, and dynamic traffic analytics. We propose a real-time adaptive routing system that integrates machine learning (ML) for predictive modeling and IoT-enabled communication with traffic infrastructure. The system is evaluated using simulated urban (...) environments, achieving a 35% reduction in response times compared to traditional methods. This work lays the foundation for future advancements in intelligent emergency systems and their integration into smart cities. (shrink)

This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote (...) patient care. (shrink)

I distinguish two roles for a fitness concept in the context of explaining cumulative adaptive evolution: fitness as a predictor of gene frequency change, and fitness as a criterion for phenotypic improvement. Critics of inclusive fitness argue, correctly, that it is not an ideal fitness concept for the purpose of predicting gene-frequency change, since it relies on assumptions about the causal structure of social interaction that are unlikely to be exactly true in real populations, and that hold as approximations (...) only given a specific type of weak selection. However, Hamilton took this type of weak selection, on independent grounds, to be responsible for cumulative assembly of complex adaptations. In this special context, I argue that inclusive fitness is distinctively valuable as a criterion for improvement and a standard for optimality. Yet to call inclusive fitness a criterion for improvement and a standard for optimality is not to make any claim about the frequency with which inclusive fitness optimization actually occurs in nature. This is an empirical question that cannot be settled by theory alone. I close with some reflections on the place of inclusive fitness in the long running clash between ‘causalist’ and ‘statisticalist’ conceptions of fitness. (shrink)

Philosophers and scientists have across the ages been amazed about the fact that development and learning often lead to not just a merely incremental and gradual change in the learner but sometimes to a result that is strikingly different from the learner’s original situation: amazed, but at times also worried. Both philosophical and cognitive neuroscientific insights suggest that experts appear to perform ‘different’ tasks compared to beginners who behave in a similar way. These philosophical and empirical perspectives give some insight (...) into what happens when a novice is transitioning to a stage of expertise. Generally, this implies that increased skill and expertise support better results and a more flexible performance, in part because these allow an agent to withdraw part of her attention and other cognitive resources from the tasks involved, enabling her to devote those resources to supporting, or completely different, tasks. As positive as these developments appear, these changes have also raised concerns. The main concern is whether gaining expertise is like raising a ‘cognitive monster’ which escapes the individual’s conscious control and influences her actions with undesirable automatisms. If so, we should ask ourselves whether experts are capable of taming this monster. The answer appears initially not to be positive. Indeed, it has been noted that since it is difficult for experts to withhold automatic responses this can lead to inflexibility or performance that is only optimal under certain conditions, because it is limited to a specific domain, often context-dependent, biased and inflexible. In what follows, I will consider this challenge of protecting expertise and harnessing this brittleness from philosophical and cognitive neuroscientific perspectives. Taking into account that action is in general determined by a multitude of factors, with learning and development affecting how these factors exert their influence, a philosophical question is how this complex and dynamic process can be explained and subsequently, how controlling it might be understood. First, though, I will present the issue at hand more closely: should we appreciate expertise if it is similar to growing a ‘cognitive monster’? Second, I will introduce the framework of a “Sculpted Space of Actions” (Keestra, 2014), which I developed in order to explain how the challenge of selecting an adequate option for action is facilitated by expertise as it helps to constrain the space of potential action options. Subsequently, the question is raised of how such a Sculpted Space of Actions influences an expert’s engagement with specific situations, like teaching students in a classroom setting. It will be argued that a well prepared expert—teacher or otherwise— is not only able to rely upon her routines but will at the same time be more perceptive and attentive to unforeseen events and actions, according to the recent cognitive neuroscientific theory of Predictive Processing. Integrating the theory of Predictive Processing with the Sculpted Space of Actions framework, I conclude that expertise contributes to adaptive and flexible responses to specific contexts, yet only if it is associated with explicit planning and articulation of situation specific intentions—the latter effectively putting the cognitive monster at rest for a while. (shrink)

Betrayal trauma theory suggests that psychogenic amnesia is an adaptive response to childhood abuse. When a parent or other powerful figure violates a fundamental ethic of human relationships, victims may need to remain unaware of the trauma not to reduce suffering but rather to promote survival. Amnesia enables the child to maintain an attachment with a figure vital to survival, development, and thriving. Analysis of evolutionary pressures, mental modules, social cognitions, and developmental needs suggests that the degree to (...) which the most fundamental human ethics are violated can influence the nature, form, and processes of trauma and responses to trauma. (shrink)

The article presents a perspective on the scientific explanation of the subjectivity of conscious experience. It proposes plausible answers for two empirically valid questions: the ‘how’ question concerning the developmental mechanisms of subjectivity, and the ‘why’ question concerning its function. Biological individuation, which is acquired in several different stages, serves as a provisional description of how subjective perspectives may have evolved. To the extent that an individuated informational space seems the most efficient way for a given organism to select biologically (...) valuable information, subjectivity is deemed to constitute an adaptive response to informational overflow. One of the possible consequences of this view is that subjectivity might be (at least functionally) dissociated from consciousness, insofar as the former primarily facilitates selection, the latter action. (shrink)

The proposed system combines predictive analytics and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and (...) data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

This paper attempts to reconcile critics and defenders of inclusive fitness by constructing a synthesis that does justice to the insights of both. I argue that criticisms of the regression-based version of Hamilton’s rule, although they undermine its use for predictive purposes, do not undermine its use as an organizing framework for social evolution research. I argue that the assumptions underlying the concept of inclusive fitness, conceived as a causal property of an individual organism, are unlikely to be exactly (...) true in real populations, but they are approximately true given a specific type of weak selection that Hamilton took, on independent grounds, to be responsible for the cumulative assembly of complex adaptation. Finally, I reflect on the uses and limitations of “design thinking” in social evolution research. The debate about the foundations of inclusive fitness theory that has followed in the wake of Nowak, Tarnita and Wilson’s (1) critique has been remarkably polarizing. After several rounds of rebuttals and replies, there is still little evidence of any serious reconciliation between the theory’s critics (2-10) and its defenders (11-24). It doesn’t have to be this way. I believe that, on the main points of disagreement, it is possible to find a way forward that does justice to the insights of both camps. My aim in this paper is to find that way forward. (shrink)

We argue, contra Joshua Knobe in a companion chapter, that most people have an understanding of free will and responsible agency that is compatible with a naturalistic vision of the human mind. Our argument is supported by results from a new experimental philosophy study showing that most people think free will is consistent with complete and perfect prediction of decisions and actions based on prior activity in the brain (a scenario adapted from Sam Harris who predicts most people will find (...) it inconsistent with free will). We explain why most people are "theory-lite" about the nature of mind and free will--they are not committed to substantive theories of the underlying causal structure of mind, such as Knobe's "transcendence vision". Rather, we suggest a "causal competition principle"--that an agent's actions will be deemed unfree when they are perceived to be fully caused by factors that do not include her reasons. This principle explains why people, including some scientists, perceive neuroscientific explanations as threatening free will when they are described in terms of neural processes fully causing actions to the exclusion of agents' reasons or reasoning processes. (shrink)

Following the pioneering studies of the receptive field (RF), the concept gained further significance for visual perception by the discovery of input effects from beyond the classical RF. These studies demonstrated that neuronal responses could be modulated by stimuli outside their RFs, consistent with the perception of induced brightness, color, orientation, and motion. Lesion scotomata are similarly modulated perceptually from the surround by RFs that have migrated from the interior to the outer edge of the scotoma and in this way (...) provide filling-in of the void. Large RFs are advantageous to this task. In higher visual areas, such as the middle temporal and inferotemporal lobe, RFs increase in size and lose most of their retinotopic organization while encoding increasingly complex features. Whereas lowerlevel RFs mediate perceptual filling-in, contour integration, and figure–ground segregation, RFs at higher levels serve the perception of grouping by common fate, biological motion, and other biologically relevant stimuli, such as faces. Studies in alert monkeys while freely viewing natural scenes showed that classical and nonclassical RFs cooperate in forming representations of the visual world. Today, our understanding of the mechanisms underlying the RF is undergoing a quantum leap. What had started out as a hierarchical feedforward concept for simple stimuli, such as spots, lines, and bars, now refers to mechanisms involving ascending, descending, and lateral signal flow. By extension of the bottom-up paradigm, RFs are nowadays understood as adaptive processors, enabling the predictive coding of complex scenes. Top-down effects guiding attention and tuned to task-relevant information complement the bottom-up analysis. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Abstract: As the frequency and sophistication of cyberattacks continue to rise, organizations face increasing challenges in safeguarding their digital infrastructures. Traditional cybersecurity measures often struggle to keep pace with rapidly evolving threats, creating a pressing need for more adaptive and proactive solutions. Artificial Intelligence (AI) has emerged as a transformative force in this domain, offering enhanced capabilities for detecting, analyzing, and preventing cyberattacks in real- time. This paper explores the pivotal role of AI in strengthening cybersecurity defenses by leveraging (...) machine learning algorithms, predictive analytics, and automation to anticipate and mitigate potential threats before they manifest. Furthermore, it examines AI's ability to evolve with emerging attack vectors, providing a dynamic response to an ever-changing threat landscape. The paper also addresses the limitations and ethical considerations surrounding AI-driven cybersecurity, advocating for a balanced approach to its deployment. Through this exploration, the research underscores how AI is redefining the future of cyber defense by shifting the focus from reactive to proactive strategies. (shrink)

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder (...) but not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (shrink)

Abstract: As the integration of Artificial Intelligence (AI) continues to permeate various sectors, the legal domain stands on the cusp of a transformative era. This research paper delves into the multifaceted relationship between AI and the law, scrutinizing the profound implications and innovative applications that emerge at the intersection of these two realms. The study commences with an examination of the current landscape, assessing the challenges and opportunities that AI presents within legal frameworks. With an emphasis on efficiency, accuracy, and (...) accessibility, AI technologies are reshaping traditional legal processes, ranging from document analysis and contract review to predictive legal analytics. Furthermore, the paper scrutinizes the ethical considerations and potential biases inherent in AI algorithms, exploring the delicate balance between technological advancements and the preservation of legal principles such as fairness, accountability, and transparency. The research also delves into the evolving role of legal professionals in navigating and overseeing AI applications, emphasizing the importance of responsible AI deployment. Drawing on case studies and real-world examples, this paper showcases instances where AI has already demonstrated its efficacy in legal contexts, highlighting successful implementations and identifying areas for improvement. The discussion extends to the evolving regulatory landscape, as legal systems grapple with the need to adapt and establish frameworks that ensure the responsible and ethical use of AI technologies. In conclusion, this research contributes to the growing discourse on the dynamic interplay between AI and the legal domain. By illuminating the potential benefits, ethical considerations, and regulatory challenges, it provides a comprehensive overview for legal practitioners, policymakers, and technologists alike, fostering a nuanced understanding of the evolving landscape where artificial intelligence intersects with the law. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

-/- Intelligence, Balance, and the Laws of Nature: A Universal Connection -/- Introduction -/- The human mind has an extraordinary ability: it can understand the laws of nature, even though it is itself made of atoms and governed by these same laws. This raises a profound question: How can intelligence—whether human, artificial, or even extraterrestrial—grasp the very principles that shape the universe? The answer may lie in the fundamental nature of balance, a principle that underlies both intelligence and the structure (...) of reality. By examining the relationship between intelligence, balance, and the universal laws of nature, we can explore whether understanding is an inevitable outcome of how the universe operates. This perspective also aligns with the idea that human decision-making must follow natural laws, as suggested by Angelito Malicse’s universal formula for solving the problem of free will. -/- Intelligence as an Extension of Natural Laws -/- The first step in understanding intelligence is recognizing that it does not exist outside of nature but rather emerges from it. Just as the physical universe follows patterns—such as gravity, thermodynamics, and atomic interactions—so too does intelligence arise through a process of self-organization. -/- Self-Organization in Nature: Atoms form molecules, molecules form cells, and cells form complex organisms. This natural progression of increasing complexity leads to intelligence, much like galaxies, ecosystems, and weather patterns follow self-organizing principles. -/- The Brain as a Natural System: The human brain is composed of matter, but its function is not just a mechanical process—it is an adaptive system designed to recognize patterns, make predictions, and refine its understanding of reality. -/- Mathematics as a Universal Language: Many scientists have pointed out the “unreasonable effectiveness of mathematics” in describing reality. This suggests that mathematical principles are not human inventions but discoveries—patterns that exist independently in nature and are uncovered by intelligence. -/- If intelligence is simply an expression of natural laws, then the ability to recognize patterns and understand reality is an inevitable result of how the universe itself functions. -/- Balance as the Fundamental Principle of Intelligence -/- A key insight from Malicse’s universal formula is that decision-making must align with the natural law of balance. This idea applies not only to individual choices but also to the way intelligence operates at all levels. -/- Cognitive Balance: Human intelligence thrives when there is a balance between stability and change. Too much rigidity (dogma, closed-mindedness) leads to stagnation, while too much uncertainty (lack of foundational truths) leads to chaos. Intelligence must constantly balance existing knowledge with new discoveries in order to function effectively. -/- Societal Balance: Societies, like individual minds, must find a balance between order (structure, rules, and traditions) and progress (innovation, questioning, and adaptation). When societies fail to achieve this balance—whether through unregulated growth, misinformation, or rigid ideologies—they become unstable. -/- Scientific Progress as a Balance Mechanism: The scientific method itself is a process of maintaining balance between evidence and theory. As we gain more information, we refine our understanding of natural laws, continuously adjusting our models of reality. -/- If intelligence inherently follows balance, then the process of gaining knowledge is itself governed by a universal law of equilibrium. This connects directly to the idea that decisions must align with natural laws to prevent imbalance, which is central to Malicse’s universal formula. -/- The Laws of Nature as a Form of Universal Intelligence -/- If intelligence naturally emerges from balance, then it is possible that the laws of nature themselves represent a form of intelligence—not in a conscious, human-like sense, but as the underlying logic that structures reality. -/- The Universe as an Information System: Some physicists suggest that the universe functions like a vast information-processing system, where fundamental laws act as rules that govern how matter and energy behave. This aligns with the idea that knowledge is not “created” but rather “discovered” as intelligent beings uncover the rules that already exist. -/- Intelligence as the Universe Understanding Itself: If all intelligent beings (humans, AI, or extraterrestrials) follow the same fundamental laws of balance and logic, then intelligence might be a way for the universe to “self-reflect.” This means that understanding reality is not separate from nature but an essential part of its ongoing evolution. -/- The Connection to AI and Extraterrestrial Knowledge: If artificial intelligence or extraterrestrial civilizations exist, they too would likely discover the same fundamental truths, because these laws are universal. This suggests that intelligence is not an accident but a natural consequence of how the universe operates. -/- This perspective reinforces Malicse’s view that human decisions must align with natural laws to avoid imbalance—because intelligence itself is simply another expression of these laws. -/- Conclusion: Intelligence, Balance, and the Universal Formula -/- The ability to understand the universe is not a mystery if we recognize that intelligence is a product of nature itself. The same laws that govern the cosmos also govern the mind, and the process of discovering knowledge is a reflection of the natural balance found in all systems. -/- This idea strongly aligns with Angelito Malicse’s universal formula, which states that human decision-making must follow the natural law of balance to function properly. Just as an imbalanced mind leads to misunderstanding, and an imbalanced society leads to dysfunction, an imbalance in decision-making leads to human and societal problems. -/- If intelligence is a way for the universe to become aware of itself, then the responsibility of humanity is clear: we must align our knowledge, actions, and societies with the fundamental principles of balance that govern all things. By doing so, we not only advance scientifically and technologically but also ensure a sustainable and harmonious future. -/- Final Thought -/- If extraterrestrial intelligence exists, they may have already reached this understanding. Whether through direct knowledge transfer (as some speculate) or through independent discovery, any advanced intelligence—whether human, alien, or artificial—must ultimately align with the universal law of balance. This means that the search for truth is not just a scientific endeavor but a fundamental part of the structure of reality itself. -/- . 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Distribution of responsibility is one of the main focus areas in discussions about climate change ethics. Most of these discussions deal with the distribution of responsibility for climate change mitigation at the international level. The aim of this paper is to investigate if and how these principles can be used to inform the search for a fair distribution of responsibility for climate change adaptation on the local level. We found that the most influential distribution principles on the international level were (...) in turn built on one or more of seven basic principles: (P1) equal shares, (P2) desert, (P3) beneficiary pays, (P4) ability, (P5) self-help, (P6) limited responsibility for the worst off, and (P7) status quo preservation. It was found that all the basic principles, but P1, P3, and P7, are to some extent translatable to local climate adaptation. Two major problems hamper their usefulness on the local level: (1) several categories of agents need to take on responsibility; and (2) emissions do not work as a base for all principles. P4, P5, and P6 are applicable to local adaptation without changes. P4 is of particular importance as it seems to solve the first problem. P2 is applicable only if the second problem is solved, which can be achieved by using risk of harm instead of emissions as the basis for desert. (shrink)

Background: Subgenual cingulate cortex (SCC) responses to self-blaming emotion-evoking stimuli were previously found in individuals prone to self-blame with and without a history of major depressive disorder (MDD). This suggested SCC activation reflects self-blaming emotions such as guilt, which are central to models of MDD vulnerability. -/- Method: Here, we re-examined these hypotheses in an independent larger sample. A total of 109 medication-free participants (70 with remitted MDD and 39 healthy controls) underwent fMRI whilst judging self- and other-blaming emotion-evoking statements. (...) They also completed validated questionnaires of proneness to self-blaming emotions including those related to internal (autonomy) and external (sociotropy) evaluation, which were subjected to factor analysis. -/- Results: An interaction between group (remitted MDD v. Control) and condition (self- v. other-blame) was observed in the right SCC (BA24). This was due to higher SCC signal for self-blame in remitted MDD and higher other-blame-selective activation in Control participants. Across the whole sample, extracted SCC activation cluster averages for self- v. other-blame were predicted by a regression model which included the reliable components derived from our factor analysis of measures of proneness to self-blaming emotions. Interestingly, this prediction was solely driven by autonomy/self-criticism, and adaptive guilt factors, with no effect of sociotropy/dependency. -/- Conclusions: Despite confirming the prediction of SCC activation in self-blame-prone individuals and those vulnerable to MDD, our results suggest that SCC activation reflects blame irrespective of where it is directed rather than selective for self. We speculate that self-critical individuals have more extended SCC representations for blame in the context of self-agency. (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 visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual (...) patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

Solving Typhoon Turbulence Using the Universal Formula -/- By Angelito Malicse -/- Introduction -/- Typhoons are among the most destructive natural phenomena, bringing extreme winds, heavy rainfall, and turbulent ocean currents. The chaotic turbulence within a typhoon makes it difficult to predict and control, causing widespread devastation to coastal regions, infrastructure, and human lives. Despite advancements in meteorology and fluid dynamics, the turbulence inside typhoons remains a challenge for accurate forecasting and disaster mitigation. -/- By applying my universal formula, based (...) on three fundamental laws of nature, we can develop a structured and effective approach to understanding and controlling typhoon turbulence. This essay explores how the Law of Karma (causality and system integrity), the Law of Balance in Nature, and the Law of Feedback Regulation provide the ultimate solution to typhoon turbulence. -/- Understanding Typhoon Turbulence Using the Universal Formula -/- Typhoons form due to energy imbalances in the atmosphere and ocean, driven by heat, pressure differences, and moisture content. The chaotic turbulence inside a typhoon is the result of: -/- 1. Unstable air currents caused by pressure and temperature gradients. -/- 2. Vortex formation driven by Earth’s rotation and wind shear. -/- 3. Excess energy accumulation in warm ocean waters. -/- By examining typhoon turbulence through the three universal laws, we can develop a scientific strategy to predict, weaken, and potentially neutralize typhoons before they cause destruction. -/- 1. The Law of Karma: Cause, Effect, and Systemic Integrity -/- The Law of Karma states that every effect has a cause, and for a system to function properly, it must be free of defects. A typhoon is an effect caused by imbalances in atmospheric and oceanic conditions. If these imbalances are corrected, typhoon turbulence can be weakened or prevented. -/- Applying the Law of Karma to Typhoon Control -/- ✅ Eliminate the root cause: Typhoons are fueled by warm ocean waters. Artificial cooling methods, such as cloud seeding or deep-sea upwelling (bringing cold water to the surface), could reduce the heat energy supply and prevent typhoon formation. -/- ✅ Detect turbulence before it intensifies: AI-driven weather models can predict early-stage typhoon turbulence and allow preemptive interventions. AI can identify defective atmospheric conditions (such as extreme heat buildup in ocean currents) and trigger mitigation efforts. -/- ✅ Disrupt vortex formation: Since typhoons rely on rotational forces, deploying strategically placed atmospheric pressure disturbances (via drones or cloud-seeding techniques) could disrupt the vortex before it gains full strength. -/- By identifying and neutralizing the causes of typhoon turbulence, we ensure that the system remains balanced, preventing large-scale destruction. -/- 2. The Law of Balance in Nature -/- The Law of Balance states that all systems naturally seek equilibrium. When a typhoon forms, it represents an extreme imbalance in the Earth’s energy system—excess heat and moisture create an unstable feedback loop of wind and turbulence. -/- Restoring Balance to Weaken Typhoon Turbulence -/- ✅ Regulating ocean surface temperature: Large-scale ocean-based temperature regulation systems (such as reflective films or artificial cooling platforms) can prevent typhoon formation by reducing the excess heat energy that fuels storms. -/- ✅ Breaking the pressure imbalance: Typhoons depend on a low-pressure core that intensifies wind speeds. By artificially increasing local air pressure using ionization or controlled cloud seeding, the extreme wind turbulence can be diffused before it reaches destructive levels. -/- ✅ Balancing atmospheric moisture: AI-assisted weather control could help regulate humidity levels through strategic rainfall induction in high-risk areas, ensuring that water vapor does not accumulate excessively to fuel a typhoon. -/- Since all systems follow natural equilibrium, strategically rebalancing temperature, pressure, and humidity will neutralize extreme typhoon turbulence. -/- 3. The Law of Feedback Regulation -/- The Law of Feedback Regulation states that all systems operate through feedback loops, where continuous monitoring and adjustment are necessary for stability. Typhoon turbulence follows feedback patterns, which means it can be tracked, analyzed, and counteracted using real-time data. -/- Developing an AI-Driven Typhoon Suppression System -/- ✅ AI-powered real-time monitoring: Advanced satellites, ocean buoys, and drones can provide instant feedback on typhoon development, allowing for proactive interventions rather than reactive disaster response. -/- ✅ Adaptive wind and pressure control: Deploying AI-controlled drones or weather balloons to release cooling agents, modify air pressure, or disperse cloud formations could interrupt the storm's feedback loop, reducing its intensity. -/- ✅ AI-driven weather forecasting for early response: Using deep learning algorithms, AI can accurately predict turbulence patterns weeks in advance, allowing governments to take preventive action instead of just preparing for disaster relief. -/- By implementing real-time monitoring and intervention, we can use feedback regulation to weaken or redirect typhoons before they cause catastrophic damage. -/- The Future of Typhoon Control with the Universal Formula -/- By integrating my universal formula into meteorology and disaster prevention, we can develop a comprehensive AI-driven typhoon suppression system that follows the three fundamental laws of nature: -/- 1. Law of Karma (Causality and Systemic Integrity): Address the root causes of typhoon formation by eliminating atmospheric and oceanic imbalances. -/- 2. Law of Balance in Nature: Restore equilibrium by regulating ocean temperatures, air pressure, and humidity. -/- 3. Law of Feedback Regulation: Use AI-driven real-time monitoring and intervention to weaken or prevent typhoons. -/- Through advanced AI, environmental engineering, and a deep understanding of nature’s laws, we can move beyond simply predicting typhoons and start actively controlling their development. -/- Conclusion -/- Typhoon turbulence, long considered an unpredictable force of nature, is fundamentally a problem of imbalance, energy accumulation, and feedback-driven intensification. By applying my universal formula, we can shift from passive disaster response to active typhoon control, using AI, environmental intervention, and natural equilibrium principles to prevent devastation. -/- This solution is not just theoretical—it aligns with the fundamental laws governing all natural systems. Once implemented, it will mark the beginning of a new era where humanity can harness nature’s own principles to create balance, stability, and protection from extreme weather. -/- . (shrink)

To gain legitimacy for climate change adaptation decisions, the distribution of responsibility for these decisions and their implementation needs to be grounded in theories of just distribution and what those a ected by decisions see as just. The purpose of this project is to contribute to sustainable spatial planning and the ability of local and regional public authorities to make well-informed and sustainable adaptation decisions, based on knowledge about both climate change impacts and the perceptions of residents and civil servants (...) on what constitutes a sustainable distribution of responsibility. Our aims are: (1) a better understanding of the practical implications of theories about just distribution of responsibility for the choice of local and regional climate adaptation measures; (2) knowledge about what residents and civil servants consider a sustainable distribution of responsibility for climate adaptation measures; and (3) a better understanding of conflicts concerning the distribution of responsibilities and systematic knowledge about the possibilities to manage them. In this interdisciplinary project, we study six municipalities and their residents, and two county administrative boards, all in Sweden, using mixed methods: value theory, document studies, interviews, focus groups, and surveys. (shrink)

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

For successful climate change adaptation, the distribution of responsibility within society is an important question. While the literature highlights the need for involving both public and private actors, little is still known of how citizens perceive their own and others’ responsibility, let alone the moral groundings for such perceptions. In this paper, we report the results of a survey regarding people’s attitudes towards different ways of distributing responsibility for climate change adaptation. The survey was distributed to citizens in six Swedish (...) municipalities and completed by 510 respondents. A large number of respondents wanted to assign responsibility for making decisions about and implementing adaptation measures to local governments, but also to property owners, whereas the national government was raised as responsible for setting decision boundaries and for financial support. The most preferred principles for a fair distribution of responsibility among the respondents were desert, ability, efficiency and need, while the principle of equal shares found less support. All principles received some support, indicating that it is necessary to consider several principles when distributing responsibility for climate change adaptation. Compared to earlier studies, this study shows more nuanced perceptions on who should be responsible and on what moral grounds. (shrink)

The way that George Kelly treats moving from an act of love to an act of hate, via his formulation of the construct of hostility, may indicate how far apart Kelly’s model and embodied intersubjective approaches stand concerning the issue of the fundamental integrity of experiencing. All feeling and emotion for Kelly expresses an awareness of the relative ongoing success or failure in relating new events to one’s outlook. But his definition of hostility stands out from his account of guilt, (...) anxiety, fear and threat in that it consists of a two-stage process. -/- Kelly defines hostility as “the continued effort to extort validational evidence in favor of a type of social prediction which has already proved itself a failure.” -/- Notice that this definition combines awareness of a validational event(invalidation) with a response to that event(extortion of evidence). Furthermore, as we will see, the way in which the first step is understood determines the sense of the second step, and vice versa. The crucial importance of interpretation in fathoming what Kelly meant by hostility can be demonstrated in the following questions: -/- How far-reaching did he mean his definition to be? Is hostility the same thing as anger, and if so, is there such a thing as healthy, adaptive, anger, or do all forms of anger extort evidence? And what about subtle forms of affective perturbation like irritation and annoyance? Are these also forms of hostility? (shrink)

A strategy for investigating consciousness that has proven very productive has focused on comparing brain processes that are accompanied by consciousness with processes that are not. But comparatively little attention has been given to a related strategy that promises to be even more fertile. This strategy exploits the fact that as individuals develop, new classes of brain processes can transition from operating ‘in the dark’ to becoming conscious. It has been suggested that these transitions occur when a new class of (...) brain processes becomes object to a new, emergent, higher-level subject. Similar transitions are likely to have occurred during evolution. An evolutionary/developmental research strategy sets out to identify the nature of the transitions in brain processes that shift them from operating in the dark to ‘lighting up’. The paper begins the application of this strategy by extrapolating the sequence of transitions back towards its origin. The goal is to reconstruct a minimally-complex, subject-object subsystem that would be capable of giving rise to consciousness and providing adaptive benefits. By focusing on reconstructing a subsystem that is simple and understandable, this approach avoids the homunculus fallacy. The reconstruction suggests that the emergence of such a minimally-complex subsystem was driven by its capacity to coordinate body-environment interactions in real time e.g. hand-eye coordination. Conscious processing emerged initially because of its central role in organising real-time sensorimotor coordination. The paper goes on to identify and examine a number of subsequent major transitions in consciousness, including the emergence of capacities for conscious mental modelling. Each transition is driven by its potential to solve adaptive challenges that cannot be overcome at lower levels. The paper argues that mental modelling arose out of a pre-existing capacity to use simulations of motor actions to anticipate the consequences of the actions. As the capacity developed, elements of the simulations could be changed, and the consequences of these changes could be ‘thought through’ consciously. This enabled alternative motor responses to be evaluated. The paper goes on to predict significant new major transitions in consciousness. (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)

The most promising contemporary form of epistemic scientific realism is based on the following intuition: Belief should be directed, not toward theories as wholes, but toward particular theoretical constituents that are responsible for, or deployed in, key successes. While the debate on deployment realism is quite fresh, a significant degree of confusion has already entered into it. Here I identify five criteria that have sidetracked that debate. Setting these distractions aside, I endeavor to redirect the attention of both realists and (...) non-realists to the fundamental intuition above. In more detail: I show that Stathis Psillos (1999) has offered an explicit criterion for picking out particular constituents, which, contrary to Kyle Stanford’s (2006a) criticisms, neither assumes the truth of theories nor requires hindsight. I contend, however, that, in Psillos’s case studies, Psillos has not successfully applied his explicit criterion. After clarifying the various alternative criteria at work (in those case studies and in a second line of criticism offered by Stanford), I argue that, irrespective of Stanford’s criticisms, the explicit criterion Psillos does offer is not an acceptable one. Nonetheless, the deployment realist’s fundamental intuition withstands all of these challenges. In closing, I point in a direction toward which I’ve elsewhere focused, suggesting that, despite the legitimacy and applicability of the deployment realist’s intuition, the historical threat that prompted it remains. (shrink)

Companies committed to corporate social responsibility should ensure that their managers possess the appropriate competencies to effectively manage the CSR adaptation process. The literature provides insights into the individual competencies these managers need but fails to prioritize them and adequately contextualize them in a manner that makes them meaningful in practice. In this study, we contextualized the competencies within the different job roles CSR managers have in the CSR adaptation process. We interviewed 28 CSR managers, followed by a survey to (...) explore the relative importance of the competencies within each job role. Based on our analysis, we identified six distinct managerial roles, including strategic, coordinating, and stimulating roles. Next, we identified per role key individual CSR-related competencies as prioritized by the respondents. Our results show that the context, as indicated in this study by CSR managers’ job roles, indeed influenced the importance of particular CSR-related competencies, because each role seems to require a different combination and prioritization of these competencies. Moreover, the results suggest that the relative importance of these competencies within each role may be driven by business logic rather than an idealistic logic. The results are presented as a competence profile which can serve as a reflection tool and as a frame of reference to further develop the competence profile for CSR managers. (shrink)

An important question confronting feminist philosophers is why women are sometimes complicit in their own subordination. The dominant view holds that complicity is best understood in terms of adaptive preferences. This view assumes that agents will naturally gravitate away from subordination and towards flourishing as long as they do not have things imposed on them that disrupt this trajectory. However, there is reason to believe that ‘impositions’ do not explain all of the ways in which complicity can arise. This (...) paper defends a phenomenological account of complicity, which offers an alternative explanation. (shrink)

Adaptive preferences are preferences formed in response to circumstances and opportunities – paradigmatically, they occur when we scale back our desires so they accord with what is probable or at least possible. While few commentators are willing to wholly reject the normative significance of such preferences, adaptive preferences have nevertheless attracted substantial criticism in recent political theory. The groundbreaking analysis of Jon Elster charged that such preferences are not autonomous, and several other commentators have since followed Elster’s (...) lead. On a second front, Capacity Theorists Martha Nussbaum and Amartya Sen have objected that adaptive preferences lead people away from objective goods and constitute an impediment to progressive change in developing countries. In this paper I argue that the criticisms of Elster, Sen and Nussbaum fail on the one hand to take into account what may be positively said in favour of this type of preference formation, and fail on the other hand to distinguish between different types of psychological changes – with the result that many of the critiques offered have a narrower purview than is currently allowed. My analysis of adaptive preferences, even in their most ideal form, is however not entirely positive; I adduce reasons why we can be cautious about allowing adaptive preferences to play certain types of roles in political processes, even as we accept those very preferences as normative and autonomous for the agent holding them. [International scholars without access to the AJPAE are invited to email [email protected] for a pdf copy of this article.]. (shrink)

Philosophy of action in the context of Classical China is radically different from its counterpart in the contemporary Western philosophical narrative. Classical Chinese philosophers began from the assumption that relations are primary to the constitution of the person, hence acting in the early Chinese context necessarily is interacting and co-acting along with others –human and nonhuman actors. This book is the first monograph dedicated to the exploration and rigorous reconstruction of an extraordinary strategy for efficacious relational action devised by Classical (...) Chinese philosophers in order to account for the interdependent and embedded character of human agency –what the author has denominated “adapting” or “adaptive agency” (yin 因). As opposed to more unilateral approaches to action also conceptualized in the Classical Chinese corpus, such as forceful and prescriptive agency, adapting requires great capacity of self and other-awareness, equanimity, flexibility, creativity, and response, which allows the agent to co-raise courses of action ad-hoc: unique and temporary solutions to specific, non-permanent, and non-generalizable life problems. Adapting is one of the world’s oldest philosophies of action, and yet it is shockingly new for contemporary audiences, who will find in it an unlikely source of inspiration to deal with our current global problems. This book explores the core conception of adapting both on autochthonous terms and by cross-cultural comparison, drawing on the European and Analytic philosophical traditions as well as on scholarship from other disciplines, opening a brand-new topic in Chinese and comparative philosophy. (shrink)

The article presents the advantages and limitations of adaptive clinical trials for assessing the effectiveness of medical interventions and specifies the conditions that contributed to their development and implementation in clinical practice. I advance two arguments by discussing different cases of adaptive trials. The normative argument is that responsible adaptation should be taken seriously as a new way of doing clinical research insofar as a valid justification, sufficient understanding, and adequate operational conditions are provided. The second argument is (...) historical. The development of adaptive trials can be related to lessons learned from research in cases of urgency and to the decades-long efforts to end the productivity crisis of pharmaceutical research, which led to the emergence of translational, personalized, and, recently, precision medicine movements. (shrink)

Two decades ago, in 1994, in the context of the 4th EU Framework Programme, ELSA was introduced as a label for developing and funding research into the ethical, legal and social aspects of emerging sciences and technologies. Currently, particularly in the context of EU funding initiatives such as Horizon2020, a new label has been forged, namely Responsible Research and Innovation. What is implied in this metonymy, this semantic shift? What is so new about RRI in comparison to ELSA? First of (...) all, for both labels, the signifier was introduced in a top-down manner, well before the concept that was signified by it had acquired a clear and stable profile. In other words, the signifier preceded the research strategies actually covered by these labels. Moreover, the newness of RRI does not reside in its interactive and anticipatory orientation, as is suggested by authors who introduced the term, but rather in its emphases on social-economic impacts. (shrink)

Shared activity is often simply willed into existence by individuals. This poses a problem. Philosophical reflection suggests that shared activity involves a distinctive, interlocking structure of intentions. But it is not obvious how one can form the intention necessary for shared activity without settling what fellow participants will do and thereby compromising their agency and autonomy. One response to this problem suggests that an individual can have the requisite intention if she makes the appropriate predictions about fellow participants. I (...) argue that implementing this predictive strategy risks derailing practical reasoning and preventing one from forming the intention. My alternative proposal for reconciling shared activity with autonomy appeals to the idea of acting directly on another's intention. In particular, I appeal to the entitlement one sometimes has to another's practical judgment, and the corresponding authority the other sometimes has to settle what one is to do. (shrink)

The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of Universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable (...) approximations to Solomonoff prediction do not always converge. (shrink)

Employing BMF analytics to predict behaviors and intentions related to 3R initiatives, eco-friendly practices, and zero-waste lifestyles offers insights into adapting to environmental changes, an area that remains underexplored in the literature.

This paper investigates how environmental structure, given the innate properties of a population, affects the degree to which this population can adapt to the environment. The model we explore involves simple agents in a 2-d world which can sense a local food distribution and, as specified by their genomes, move to a new location and ingest the food there. Adaptation in this model consists of improving the genomic sensorimotor mapping so as to maximally exploit the environmental resources. We vary environmental (...) structure to see its specific effect on adaptive success. In our investigation, two properties of environmental structure, conditioned by the sensorimotor capacities of the agents, have emerged as significant factors in determining adaptive success: (1) the information content of the environment which quantifies the diversity of conditions sensed, and (2) the expected utility for optimal action. These correspond to the syntactic and pragmatic aspects of environmental information, respectively. We find that the ratio of expected utility to information content predicts adaptive success measured by population gain and information content alone predicts the fraction of ideal utility achieved. These quantitative methods and specific conclusions should aid in understanding the effects of environmental structure on evolutionary adaptation in a wide range of evolving systems, both artificial and natural. (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)

Predictive processing theorists have claimed PTSD and depression are maladaptive and epistemically distorting because they entail undesirably wide gaps between top-down models and bottom-up information inflows. Without denying this is sometimes so, the “maladaptive” label carries questionable normative assumptions. For instance, trauma survivors facing significant risk of subsequent attacks may overestimate threats to circumvent further trauma, “bringing forth” concretely safer personal spaces, to use enactive terminology, ensuring the desired gap between predicted worries and outcomes. The violation of predictive (...) processing can go in the opposite direction too, as when depression coincides with energy-depletion, and hence objectively strenuous situations in which things look farther away because they are (accurately anticipated to be) harder to reach. These examples partly encapsulate what predictive processing theorists call “active inference,” yet with differences. In the first case, actions fruitfully obviate predictions rather than fulfilling them. In the second, mental models do not dysregulate bodily processes, making coping harder. Instead, problems (e.g., personal obstacles, gastric illness) deplete energy, eliciting a depressive and adaptive slow-down. Some predictive proponents apply correspondence criteria when alleging mismatches between internal models and the world, while incongruously asserting that the brain did not evolve to see things veridically, but to execute actions. An alternative is to adopt pluralistic, pragmatic epistemologies suited to the complexity of mind. The upshot is that mental outlooks can depart from the norm without epistemically being distorted and that mismatches between anticipatory worries and outcomes, when they actually exist, can be a measure of adaptive and epistemic success. (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)

This research study employed the mixed-method approach. Quantitative data were tabulated and treated using the SPSS. Meanwhile, the qualitative data were subjected to Thematic Analysis. Results revealed that on the general dimensions of leadership practices, the novice school heads showed total adaptability. However, after dissecting the answers of the participants, it showed that under each sub-dimension of the leadership practices, most of the novice school heads found research and innovation very challenging that they could not really adopt at present. Another (...) sub-dimension includes updating of school files, policy reviews, managing resources and leading strategically. As to the experiences, some novice school heads gained understanding, became confident, and acknowledged the huge responsibilities of school leaders. Others also experienced the opposite such as the struggle to craft the School Improvement Plan, BED 1, 2, 3, Annual Improvement Plan, and liquidation of funds. It has been recommended by the researchers to conduct a division-wide leadership capacity training and provide re-calibration of technical assistance to the novice school heads so that they could adopt and function normally as responsible school leaders. (shrink)