Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...) dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (shrink)

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...) large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Diabetes is a major public health issue that affects the nations of our time to a large extent and is described as a non-communicable epidemic. Diabetes mellitus is a common disease where there is too much sugar (glucose) floating around in your blood. This occurs because either the pancreas can’t produce enough insulin or the cells in body have become resistant to insulin. The concentration in this paper is on diagnosis diabetes by designing a proposed expert system. The main goal (...) of this expert system is to get the appropriate diagnosing of the illness, dealing with it quickly, and tips for permanent treatment whenever possible is given out. SL5 object expert system language was used for designing and implementing the proposed expert system. (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

Malaria is a life-threatening disease spread to humans by some types of mosquitoes. It is mostly found in tropical countries. It is preventable and curable. The infection is caused by a parasite and does not spread from person to person. Symptoms can be mild or life-threatening. Mild symptoms are fever, chills and headache. Severe symptoms include fatigue, confusion, seizures, and difficulty breathing. Infants, children under 5 years, pregnant women, travelers and people with HIV or AIDS are at higher risk of (...) severe infection. Discovering this disease is a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid spreading this disease. The expert system diagnoses malaria disease correctly to facilitate doctors to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose malaria disease. (shrink)

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system software (...) to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam. (shrink)

Abstract: The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of (...) books. The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (shrink)

An Intelligent Tutoring System (ITS) is a computer system that offers an instant, adapted instruction and customized feedback to students without human teacher interference. Reciting "Tajweed" the Holy Quran in the appropriate way is very important for all Muslims and is obligatory in Islamic devotions such as prayers. In this paper, the researchers introduce an intelligent tutoring system for teaching Reciting "Tajweed". Our "Tajweed" tutoring system is limited to "Tafkhim and Tarqiq in TAJWEED" the Holy Quran, Rewaya: Hafs from ‘Aasem. (...) The system was evaluated by reciting teachers and students, and the results were auspicious. (shrink)

Life expectancy prediction, a pivotal facet of public health and policy formulation, has witnessed remarkable advancements owing to the integration of neural network models and comprehensive datasets. In this research, we present an innovative approach to forecasting life expectancy in diverse countries. Leveraging a neural network architecture, our model was trained on a dataset comprising 22 distinct features, acquired from Kaggle, and encompassing key health indicators, socioeconomic metrics, and cultural attributes. The model demonstrated exceptional predictive accuracy, attaining an impressive 99.27% (...) and an average error of 0.0034, underscoring the potency of deep learning in tackling complex, real-world challenges. Furthermore, our study delved into feature importance analysis, identifying critical determinants such as HIV/AIDS prevalence, income composition of resources, and socioeconomic status that significantly influence life expectancy. These findings provide actionable insights for healthcare policymakers and practitioners, emphasizing the importance of addressing health disparities, promoting economic development, and implementing targeted interventions. This research bridges the gap between data-driven methodologies and global health, offering a robust predictive tool and enriching our understanding of the multifaceted dynamics that shape life expectancy across nations. (shrink)

Undeniably, the greatest way for a Moslem to be closer to Allah, is recitation of Holy-Quran approves with the method conveyed from Messenger of Allah Mohammed from the feature of speech points of letters and the intrinsic and fleeting characteristics of the letters, So, there is a persistent need to teach all Moslems the science of Tajweed Al-Quran. ITS (Intelligent Tutoring System) is computer software that supplies direct and tailored training or response to students without human teacher interfering. The main (...) target of ITS is smoothing the learning process using the wide-ranging facilities of computer. The proposed system will be implemented using the ITSB Authoring tool. In this thesis, the researcher presents an intelligent tutoring system for teaching Reciting Al-Quran "Tajweed" with Rewaya: Hafs from ‘Aasem by the way of Shatebiyyah. It was a novel idea that the researcher combined the science of Tajweed Al-Quran and the science of artificial intelligence in his thesis. The researcher arranged the material into chapters, lessons, examples then, added all these to the proposed system. He also added questions, right answers and the level of difficulty for each lesson. He prepared an exam for each chapter and a final exam to test the knowledge of the learner in the whole material. The system was evaluated by teachers and students in reciting science and the outcome of the assessment was encouraging and promising. (shrink)

For the theorists of crisis, the revolutionary state comes into existence through violence, and due to its inability to provide an authoritative katechon (restrainer) against internal and external violence, it perpetuates violence until it self-destructs. Writing during extreme economic depression and growing social and political violence, the crisis theorists––Joseph de Maistre, Juan Donoso Cortés, and Carl Schmitt––each sought to blame the chaos of their time upon the Janus-faced postrevolutionary ideals of liberalism and socialism by urging a return to pre-revolutionary moral (...) and religious values. They are united by three counterrevolutionary principles, all of which are purported to remedy revolutionary violence: traditional constitutional fidelity, the philosophy of the decision, and opposition to bourgeois liberalism. This essay is followed by the first complete English translation and publication of Donoso’s letter of October 24, 1851, which contains Donoso’s only reference to the “discussing class,” a political entity later popularized by Schmitt in his 1922 work Political Theology. (shrink)

An Intelligent Tutoring System (ITS) is a computer system that offers an instant, adapted instruction and customized feedback to students without human teacher interference. Reciting "Tajweed" the Holy Quran in the appropriate way is very important for all Muslims and is obligatory in Islamic devotions such as prayers. In this paper, the researchers introduce an intelligent tutoring system for teaching Reciting "Tajweed". Our "Tajweed" tutoring system is limited to "Tafkhim and Tarqiq in TAJWEED" the Holy Quran, Rewaya: Hafs from ‘Aasem. (...) The system was evaluated by reciting teachers and students, and the results were auspicious. (shrink)

In much of the current academic and public discussion, conspiracy theories are portrayed as a negative phenomenon, linked to misinformation, mistrust in experts and institutions, and political propaganda. Rather surprisingly, however, philosophers working on this topic have been reluctant to incorporate a negatively evaluative aspect when either analyzing or engineering the concept conspiracy theory. In this paper, we present empirical data on the nature of the concept conspiracy theory from five studies designed to test the existence, prevalence and exact form (...) of an evaluative dimension to the ordinary concept conspiracy theory. These results reveal that, while there is a descriptive concept of conspiracy theory, the predominant use of conspiracy theory is deeply evaluative, encoding information about epistemic deficiency and often also derogatory and disparaging information. On the basis of these results, we present a new strategy for engineering conspiracy theory to promote theoretical investigations and institutional discussions of this phenomenon. We argue for engineering conspiracy theory to encode an epistemic evaluation, and to introduce a descriptive expression—such as ‘conspiratorial explanation’—to refer to the purely descriptive concept conspiracy theory. (shrink)

Though hair loss (alopecia) is not a debilitating or life threatening sickness, the very thought of becoming bald can lead to emotional stress and traumatic experience for those who suffer from premature or excessive hair loss. Many will try anything and everything to bring back their locks. Or at least, some of their once full head of hair. Hair loss sufferers spend billions of dollars annually on remedies ranging from drugs, vitamins to special tonics and shampoos. Conventional treatments of hair (...) thinning includes drugs therapy and hair transplant. Minoxidil and Propecia (Finasteride) are the only two drugs approved by the FDA for hair growth in men. Minoxidil is the only drug available for women with and rogenetic alopecia. These drugs have been proven to show positive results for balding conditions on the vertex region of the scalp. Though these drugs are effective, many are wary of their unknown long-term effect and potential side-effects. This has led to increase interest in alternative remedies such as herbal medicine. (shrink)

An interview with Dr. Alaa Algargoosh, a research fellow at MIT Media Lab.

In this paper I argue that both defence and criticism of the claim that humans act ‘under the guise of the good’ neglects the metaphysical roots of the theory. I begin with an overview of the theory and its modern commentators, with critics noting the apparent possibility of acting against the good, and supporters claiming that such actions are instances of error. These debates reduce the ‘guise of the good’ to a claim about intention and moral action, and in so (...) doing have become divorced from the theory's roots in classical and medieval philosophy. Aristotle and Aquinas’ ‘guise of the good’ is primarily a metaphysical claim resting on the equivalence between actuality and goodness, from which conclusions about moral action are derived. I show the reasoning behind their theory and how it forms the basis for the claims about intention and action at the centre of the modern debate. Finally, I argue that the absence of its original foundation is apparent in recent attacks on the ‘guise of the good’. It is unsurprising that modern action theory and ethics have not always been able to comfortably accommodate the ‘guise of the good’; they are only telling half of the story. (shrink)

Much discussion about experimental philosophy and philosophical methodology has been framed in terms of the reliability of intuitions, and even when it has not been about reliability per se, it has been focused on whether intuitions meet whatever conditions they need to meet to be trustworthy as evidence. But really that question cannot be answered independently from the questions, evidence for what theories arrived at by what sorts of inferences? I will contend here that not just philosophy's sources of evidence, (...) but also its inferential resources, are in great need of closer examination. (shrink)

Son dönemde yapılan araştırmalarda en mutlu şehir olarak seçilen Sinop’un yüzyıllar öncesinde bir sakini vardı ki insanlık için mutlu olmanın doğru yolunu bulmayı kendine dert edinmişti. Öğretileri Roma İmparatorluğu’nun resmi dini gibi benimsenecek, Marcus Aurelius gibi Roma Krallarının filozofu olmaktan gurur duyacağı Stoa Okulunun ve Dünya Hükümdarı Büyük İskender’in büyük övgüsüne mazhar olmuş, Sinoplu Diogenes.

Naturalist views of persons, such as those of the philosophers Annette Baier and Marjorie Grene, emphasize that human persons are cultural animals: We are living, embodied, organic beings, embedded in nature, the product of Darwinian evolution, but dependent on culture. Such naturalist views of persons typically eschew science fiction and look askance at the philosophical fantasies and thought experiments that often populate philosophical treatments of personal identity. Marge Piercy’s dystopian, cyberpunk, science fiction novel He, She and It weaves a complex (...) tale around the debate over the status of its central character Yod, a cyborg created in a lab but humanized through the efforts of two women, Malkah Shipman and her granddaughter Shira Shipman. Is Yod a person, despite having been engineered in a lab for a specific purpose? Piercy’s tale both challenges and ultimately supports a naturalist view of persons while simultaneously forewarning us of possible new styles of persons to come. (shrink)

Several variants of Lewis's Best System Account of Lawhood have been proposed that avoid its commitment to perfectly natural properties. There has been little discussion of the relative merits of these proposals, and little discussion of how one might extend this strategy to provide natural property-free variants of Lewis's other accounts, such as his accounts of duplication, intrinsicality, causation, counterfactuals, and reference. We undertake these projects in this paper. We begin by providing a framework for classifying and assessing the variants (...) of the Best System Account. We then evaluate these proposals, and identify the most promising candidates. We go on to develop a proposal for systematically modifying Lewis's other accounts so that they, too, avoid commitment to perfectly natural properties. We conclude by briefly considering a different route one might take to developing natural property-free versions of Lewis's other accounts, drawing on recent work by Williams. (shrink)

Since the publication of David Lewis's ''New Work for a Theory of Universals,'' the distinction between properties that are fundamental – or perfectly natural – and those that are not has become a staple of mainstream metaphysics. Plausible candidates for perfect naturalness include the quantitative properties posited by fundamental physics. This paper argues for two claims: (1) the most satisfying account of quantitative properties employs higher-order relations, and (2) these relations must be perfectly natural, for otherwise the perfectly natural properties (...) cannot play the roles in metaphysical theorizing as envisaged by Lewis. (shrink)

Two grams mass, three coulombs charge, five inches long – these are examples of quantitative properties. Quantitative properties have certain structural features that other sorts of properties lack. What are the metaphysical underpinnings of quantitative structure? This paper considers several accounts of quantity and assesses the merits of each.

Experimental philosophy of religion is the project of taking the tools and resources of the human sciences—especially psychology and cognitive science—and bringing them to bear on issues within philosophy of religion toward explicit philosophical ends. This paper introduces readers to experimental philosophy of religion. §1 explores the contours of experimental philosophy of religion by contrasting it with a few related fields: the psychology of religion and cognitive science of religion, on the one hand, and natural theology, on the other. §2 (...) offers a brief history of experimental philosophy of religion. The goal in this section is to highlight the ancient pedigree of this emerging area of research; as the contemporary experimental philosophy of religion literature expands and proliferates, it’s important to remember that this field has deep historical roots. Then, §3 focuses on the following questions: Why should we care about experimental philosophy of religion? And why is it needed? (shrink)

What are conspiracy theories? And what, if anything, is epistemically wrong with them? I offer an account on which conspiracy theories are a unique way of holding a belief in a conspiracy. Specifically, I take conspiracy theories to be self-insulating beliefs in conspiracies. On this view, conspiracy theorists have their conspiratorial beliefs in a way that is immune to revision by counter-evidence. I argue that conspiracy theories are always irrational. Although conspiracy theories involve an expectation to encounter some seemingly disconfirming (...) evidence (allegedly planted by the conspirators), resistance to all counter- evidence cannot be justified on these grounds. (shrink)

In recent literature, panpsychism has been defended by appeal to two main arguments: first, an argument from philosophy of mind, according to which panpsychism is the only view which successfully integrates consciousness into the physical world (Strawson 2006; Chalmers 2013); second, an argument from categorical properties, according to which panpsychism offers the only positive account of the categorical or intrinsic nature of physical reality (Seager 2006; Adams 2007; Alter and Nagasawa 2012). Historically, however, panpsychism has also been defended by appeal (...) to a third argument based on considerations about the nature and observability of causation. This argument has not been much discussed in recent times. Here is a concise version from William James: "… the concrete perceptual flux, taken just as it comes, offers in our own activity-situations perfectly comprehensible instances of causal agency … If we took these experiences as the type of what actual causation is, we should have to ascribe to cases of causation outside of our life, to physical cases also, an inwardly experiential nature. In other words, we should have to espouse a so-called “pan-psychic” philosophy" (James 1911: 218). James here suggests that we have direct experience of causation in our own agency. He thereby directly contradicts David Hume, who famously denied that we have any experience of causation. James goes on to claim that if this experience is representative of causation in general, it follows that all causation is mental, and that panpsychism is true. This kind of argument for panpsychism can be called the argument from (experience of) causation. This chapter offers, first, a history of this argument and arguments closely related to it, and second, an analysis of the argument – is it valid, are its premises in any way defensible, and how does it relate to the other, more popular arguments for panpsychism from philosophy of mind and categorical properties? (shrink)

Looking at the recent spate of claims about “fake news” which appear to be a new feature of political discourse, I argue that fake news presents an interesting problem in epistemology. Te phenomena of fake news trades upon tolerating a certain indiference towards truth, which is sometimes expressed insincerely by political actors. Tis indiference and insincerity, I argue, has been allowed to fourish due to the way in which we have set the terms of the “public” epistemology that maintains what (...) is considered “rational” public discourse. I argue one potential salve to the problem of fake news is to challenge this public epistemology by injecting a certain ethical consideration back into the discourse. (shrink)

This paper examines the role of reason in Shepherd's account of acquiring knowledge of the external world via first principles. Reason is important, but does not have a foundational role. Certain principles enable us to draw the required inferences for acquiring knowledge of the external world. These principles are basic, foundational and, more importantly, self‐evident and thus justified in other ways than by demonstration. Justificatory demonstrations of these principles are neither required, nor possible. By drawing on textual and contextual evidence, (...) I will show that Shepherd should have said that we know the first principles of any science, in general, and that “everything which begins to exist must have a cause”, in particular, via intuition, not via reason. Reasoning about such principles can help their self‐evidence shine through in certain cases; their justification, and our being justified in believing them, does not come from this reasoning, however. (shrink)

The Integrated Information Theory of consciousness (IIT) claims that consciousness is identical to maximal integrated information, or maximal Φ. One objection to IIT is based on what may be called the intrinsicality problem: consciousness is an intrinsic property, but maximal Φ is an extrinsic property; therefore, they cannot be identical. In this paper, I show that this problem is not unique to IIT, but rather derives from a trilemma that confronts almost any theory of consciousness. Given most theories of consciousness, (...) the following three claims are inconsistent. INTRINSICALITY: Consciousness is intrinsic. NON-OVERLAP: Conscious systems do not overlap with other conscious systems (a la Unger’s problem of the many). REDUCTIONISM: Consciousness is constituted by more fundamental properties (as per standard versions of physicalism and Russellian monism). In view of this, I will consider whether rejecting INTRINSICALITY is necessarily less plausible than rejecting NON-OVERLAP or REDUCTIONISM. I will also consider whether IIT is necessarily committed to rejecting INTRINSICALITY or whether it could also accept solutions that reject NON-OVERLAP or REDUCTIONISM instead. I will suggest that the best option for IIT may be a solution that rejects REDUCTIONISM rather than INTRINSICALITY or NON-OVERLAP. (shrink)

Two problems are considered here. One relates to who has moral status, and the other relates to who has moral responsibility. The criteria for mattering morally have long been disputed, and many humans and nonhuman animals have been considered “marginal cases,” on the contested edges of moral considerability and concern. The marginalization of humans and other species is frequently the pretext for denying their rights, including the rights to health care, to reproductive freedom, and to bodily autonomy. There is broad (...) agreement across cultural and philosophical traditions about the capacities and responsibilities of moral agents. I propose an inclusive and expansive way of thinking about moral status, situating it not in the characteristics or capacities of individuals, but in the responsibilities and obligations of moral agents. Moral agents, under this view, are not privileged or entitled to special treatment but rather have responsibilities. I approach this by considering some African communitarian conceptions of moral status and moral agency. I propose that moral agency can also be more expansive and include not just individual moral agents but collective entities that have some of the traits of moral agents: power, freedom, and the capacity to recognize and act on the demands of morality and acknowledge and respect the rights of others. Expanding who and what is a moral agent correspondingly extends moral responsibility for respecting rights and fostering the conditions for the health and well-being of humans and animals onto the collective entities who uniquely have the capacity to attend to global-scale health threats such as pandemics and human-caused climate change. (shrink)

Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...) change; they are not discrete, apportionable causes. Our objective here is to provide a definitive statement of the statistical position, so as to allay some confusions in the current literature. We outline four commitments that are central to statisticalism. They are: 1. Natural Selection is a higher order effect; 2. Trait fitness is primitive; 3. Modern Synthesis (MS)-models are substrate neutral; 4. MS-selection and drift are model-relative. (shrink)

The Argument from Temporary Intrinsics is one of the canonical arguments against endurantism. I show that the two standard ways of presenting the argument have limited force. I then present a new version of the argument, which provides a more promising articulation of the underlying objection to endurantism. However, the premises of this argument conflict with the gauge theories of particle physics, and so this version of the argument is no more successful than its predecessors. I conclude that no version (...) of the Argument from Temporary Intrinsics gives us a compelling reason to favor one theory of persistence over another. (shrink)

Qualitative fieldwork research on sensitive topics sometimes requires that interviewees be granted confidentiality and anonymity. When qualitative researchers later publish their findings, they must ensure that any statements obtained during fieldwork interviews cannot be traced back to the interviewees. Given these protections to interviewees, the integrity of the published findings cannot usually be verified or replicated by third parties, and the scholarly community must trust the word of qualitative researchers when they publish their results. This trust is fundamentally abused, however, (...) when researchers publish articles reporting qualitative fieldwork data that they never collected. Using only publicly available information, I argue that a 2017 article in an Elsevier foreign policy and international relations journal presents anonymised fieldwork interviews that could not have occurred as described. As an exercise in post-publication peer review (PPPR), this paper examines the evidence that calls into question the reliability of the putative fieldwork quotations. I show further that the 2017 article is not a unique case. The anonymity and confidentiality protections common in some areas of research create an ethical problem: the protections necessary for obtaining research data can be used as a cover to hide substandard research practices as well as research misconduct. (shrink)

Is part of a perfectly natural, or fundamental, relation? Philosophers have been hesitant to take a stand on this issue. One reason for this hesitancy is the worry that, if parthood is perfectly natural, then the perfectly natural properties and relations are not suitably “independent” of one another. In this paper, I argue that parthood is a perfectly natural relation. In so doing, I argue that this “independence” worry is unfounded. I conclude by noting some consequences of the naturalness of (...) parthood. (shrink)

It has recently been argued that hope is polysemous in that it sometimes refers to hoping and other times to being hopeful. That it has these two distinct senses is reflected in the observation that a person can hope for an outcome without being hopeful that it will occur. Below, I offer a new argument for this distinction. My strategy is to show that accepting this distinction yields a rich account of two distinct ways in which hope can be lost, (...) ways that map onto the two senses of hope: A person can lose hope either by ceasing to hope for an outcome (hopelessness) or by ceasing to be hopeful that it will obtain (despair). Thinking about these negative attitudes in these two ways, I contend, is explanatorily rich and fruitfully reveals how they differ in phenomenology, behavioral differences, and the ways in which a person can escape them. (shrink)

The aim of this paper is to provide a conceptual framework that will help in understanding and evaluating, along social and ethical lines, the issue of killing day-old male chicks and two alternative directions of responsible innovations to solve this issue. The following research questions are addressed: Why is the killing of day-old chicks morally problematic? Are the proposed alternatives morally sound? To what extent do the alternatives lead to responsible innovation? The conceptual framework demonstrates clearly that there is a (...) moral “lock-in”, and why the killing of day-old chicks is indeed an issue. Furthermore, it is shown that both alternative directions address some important objections with regard to the killing of day-old chicks, but that they also raise new dilemmas. It also becomes clear that the framework enables and secures anticipation, reflection, deliberation with and responsiveness to stakeholders, the four dimensions of responsible innovation, in a structured way. (shrink)

The meta-problem of consciousness is the problem of explaining why we have the intuition that there is a hard problem of consciousness. David Chalmers briefly notes that my phenomenal powers view may be able to answer to this challenge in a way that avoids problems (having to do with avoiding coincidence) facing other realist views. In this response, I will briefly outline the phenomenal powers view and my main arguments for it and—drawing in part on a similar view developed by (...) Harold Langsam—discuss how more precisely its answer to the challenge would go. (shrink)

Panpsychism is the view that consciousness is everywhere. Panpsychism has significant theoretical implications with respect to the mind–body problem, as well as the question of the intrinsic nature of the physical world. This paper considers one of its potential practical or ethical implications; specifically, whether, if panpsychism is true, it follows that “we are all one”, in a sense that implies that egoism (understood as bias towards what we normally, but falsely, take to constitute the self or ego) is not (...) only immoral but fundamentally irrational (or imprudent). (shrink)

Panpsychism is the view that every concrete and unified thing has some form of phenomenal consciousness or experience. It is an age-old doctrine, which, to the surprise of many, has recently taken on new life. In philosophy of mind, it has been put forth as a simple and radical solution to the mind–body problem (Chalmers 1996, 2003;Strawson 2006; Nagel 1979, 2012). In metaphysics and philosophy of science, it has been put forth as a solution to the problem of accounting for (...) the intrinsic nature of the physical itself (Strawson 2006, Seager 2006). In this thesis, I show that panpsychism can also be defended on the basis of an argument from our (arguable) acquaintance with the nature of causation in agency. This argument has made frequent appearances throughout the history of philosophy, with philosophers such as Leibniz, Schopenhauer and James, and I construct and defend an updated version of it. Furthermore, I offer a solution to the combination problem: how can complex (human and animal-type) consciousness result from simple (fundamental particle-type) consciousness? This is generally regarded as the most serious problem facing contemporary panpsychism. I propose that mental combination can be construed as kind causal process culminating in a fusion, and show how this avoids the main difficulties with accounting for mental combination. (shrink)

Phenomenal knowledge is knowledge of what it is like to be in conscious states, such as seeing red or being in pain. According to the knowledge argument (Jackson 1982, 1986), phenomenal knowledge is knowledge that, i.e., knowledge of phenomenal facts. According to the ability hypothesis (Nemirow 1979; Lewis 1983), phenomenal knowledge is mere practical knowledge how, i.e., the mere possession of abilities. However, some phenomenal knowledge also seems to be knowledge why, i.e., knowledge of explanatory facts. For example, someone who (...) has just experienced pain for the first time learns not only that this is what pain is like, but also why people tend to avoid it. Some philosophers have claimed that experiencing pain gives knowledge why in a normative sense: it tells us why pain is bad and why inflicting it is wrong (Kahane 2010). But phenomenal knowledge seems to explain not (only) why people should avoid pain, but why they in fact tend to do so. In this paper, I will explicate and defend a precise version of this claim and use it as a basis for a new version of the knowledge argument, which I call the explanatory knowledge argument. According to the argument, some phenomenal knowledge (1) explains regularities in a distinctive, ultimate or regress-ending way, and (2) predict them without induction. No physical knowledge explains and predicts regularities in the same way. This implies the existence of distinctive, phenomenal explanatory facts, which cannot be identified with physical facts. I will show that this argument can be defended against the main objections to the original knowledge argument, the ability hypothesis and the phenomenal concept strategy, even if it turns out that the original cannot. In this way, the explanatory knowledge argument further strengthens the case against physicalism. (shrink)

Each thing is fundamental. Not only is no thing any more or less real than any other, but no thing is prior to another in any robust ontological sense. Thus, no thing can explain the very existence of another, nor account for how another is what it is. I reach this surprising conclusion by undermining two important positions in contemporary metaphysics: hylomorphism and hierarchical views employing so-called building relations, such as grounding. The paper has three main parts. First, I observe (...) hylomorphism is alleged by its proponents to solve various philosophical problems. However, I demonstrate, in light of a compelling account of explanation, that these problems are actually demands to explain what cannot be but inexplicable. Second, I show how my argument against hylomorphism illuminates an account of the essence of a thing, thereby providing insight into what it is to exist. This indicates what a thing, in the most general sense, must be and a correlative account of the structure in reality. Third, I argue that this account of structure is incompatible not only with hylomorphism, but also with any hierarchical view of reality. Although hylomorphism and the latter views are quite different, representing distinct philosophical traditions, I maintain they share untenable accounts of structure and fundamentality and so should be rejected on the same grounds. (shrink)

In Science Without Numbers (1980), Hartry Field defends a theory of quantity that, he claims, is able to provide both i) an intrinsic explanation of the structure of space, spacetime, and other quantitative properties, and ii) an intrinsic explanation of why certain numerical representations of quantities (distances, lengths, mass, temperature, etc.) are appropriate or acceptable while others are not. But several philosophers have argued otherwise. In this paper I focus on arguments from Ellis and Milne to the effect that one (...) cannot provide an account of quantity in ''purely intrinsic'' terms. I show, first, that these arguments are confused. Second, I show that Field's treatment of quantity can provide an intrinsic explanation of the structure of quantitative properties; what it cannot do is provide an intrinsic explanation of why certain numerical representations are more appropriate than others. Third, I show that one could provide an intrinsic explanation of this sort if one modified Field's account in certain ways. (shrink)

In this paper we focus on some new normativist positions and compare them with traditional ones. In so doing, we claim that if normative judgments are involved in determining whether a condition is a disease only in the sense identified by new normativisms, then disease is normative only in a weak sense, which must be distinguished from the strong sense advocated by traditional normativisms. Specifically, we argue that weak and strong normativity are different to the point that one ‘normativist’ label (...) ceases to be appropriate for the whole range of positions. If values and norms are not explicit components of the concept of disease, but only intervene in other explanatory roles, then the concept of disease is no more value-laden than many other scientific concepts, or even any other scientific concept. We call the newly identified position “value-conscious naturalism” about disease, and point to some of its theoretical and practical advantages. (shrink)

A remarkable feature of the philosophical work on conspiracy theory theory has been that most philosophers agree there is nothing inherently problematic about conspiracy theories (AKA the thesis of particularism). Recent work, however, has challenged this consensus view, arguing that there really is something epistemically wrong with conspiracy theorising (AKA generalism). Are particularism and generalism incompatible? By looking at just how much particularists and generalists might have to give away to make their theoretical viewpoints compatible, I will argue that particularists (...) can accept many of the concerns that motivate generalism because generalism can never be about ‘all’ conspiracy theories without being either ahistorical or apolitical. In the end generalist critiques are best seen as useful guidelines or considerations for the appraising of particular conspiracy theories. (shrink)