In this paper, I will argue for a complex of three theses. First, that the problem of deep disagreement is an instance of the regress problem of justification. Second, that the problem of deep disagreement, as a regress problem, depends on a dialecticality requirement for arguments. Third, that the dialecticality requirement is plausible and defensible.

The design process in Kashmiri carpet weaving is distributed over a number of actors and artifacts and is mediated by a weaving notation called talim. The script encodes entire design in practice-specific symbols. This encoded script is decoded and interpreted via design-specific conventions by weavers to weave the design embedded in it. The cognitive properties of this notational system are described in the paper employing cognitive dimensions (CDs) framework of Green (People and computers, Cambridge University Press, Cambridge, 1989) and Blackwell (...) et al. (Cognitive technology: instruments of mind—CT 2001, LNAI 2117, Springer, Berlin, 2001). After introduction to the practice, the design process is described in ‘The design process’ section which includes coding and decoding of talim. In ‘Cognitive dimensions of talim’ section, after briefly discussing CDs framework, the specific cognitive dimensions possessed by talim are described in detail. (shrink)

Existing studies of the multi-group dynamics of prejudiced societies focus on the social- psychological knowledge behind the relevant processes. We instead create a multi-agent framework that simulates the propagation of prejudice and measures its tangible impact on prosperity. Levels of prosperity are tracked for individuals as well as larger social structures including groups and factions. We model social interactions using the Continuous Prisoner's Dilemma (CPD) and a new agent type called a prejudiced agent. Our simulations show that even modeling prejudice (...) as an exclusively out-group phenomenon nonetheless generates implicit in-group promotion, leading to higher relative prosperity of a prejudiced population. This skew in prosperity is seen to be correlated to factors such as size difference between groups, and the fraction of prejudiced agents in a group. Our model is a step towards a deeper understanding of the origins, propagation, and ramifications of prejudice through simulative studies grounded in apt theoretical backgrounds. (shrink)

If this can be seen as a long way from the beginning of the ancient history, where humans have envisioned different new things and then invented them to make their life’s working smoother and easier, then it can be found that they have attributed their discoveries to various aspects and names of Gods and tried to signify their belief in the form of portraying the God’s powers through the nature of their discovery. Rather, in much modern times, when humans have (...) developed the natural insights and prorated those in the form of a much more logically biased discovery, then, the atheists have started to dominate the scientific arena for their foreplay in the work of their discoveries. However, as time passes by, five special types of research communities have gathered to allocate their discovered data’s in the respective norms as such, i) Atheists to whom, there is in essence no God and nothing in this universe can be attributed to them. ii) Believer of only one God as a whole, where the principle of religious biasing is effluent and supreme in their regards of the physical laws associated with the life and stimuli, iii) Believer of multiple God’s as a whole which poses no such scientific evaluation but can be thought of as a conjugate mechanism for the creator of the universe, iv) A divine supreme, where there is exactly no God, but the whole universe is a manifestation of the nature, where nature indirectly focuses the presence of God’s or the supreme creator that maintains symmetry and working of the universe, v) The not-so-sure about mechanism of the God’s presence, where the researcher sometimes tends to belief in God when something magical happens and attribute all to their divine grace, or in times of failures where they accused them for not being philosophically intrinsic as to their own needs, and in times with the believe that, ‘we won’t believe what we can’t see!’, either in the middle of the good or bad moments or in general in a casual and carefree mode. But, this should be kept in mind, that, the Eastern mysticism has always signifies God’s action in terms of every scientific actions with a proper mythological essence which when accompanied by knowledge produces something so scientific in the ancient of the days, that modern day researchers also have had no options left than to attribute affirmation to the fantastic achievements in the ‘so’ ancient times discovery with a strict modern effluence. Therefore, to model this paper, I have gathered data’s and ideas from researchers of various fields mostly (PhDs) in their respective discipline, so as to emulate their minds in the norms of God and its associated beliefs. (shrink)

This article describes various ways actors in Kashmiri carpet weaving practice deploy a range of artifacts, from symbolic, to material, to hybrid, in order to achieve diverse cognitive accomplishments in their particular task domains: information representation, inter and intra-domain communication, distribution of cognitive labor across people and time, coordination of team activities, and carrying of cultural heritage. In this repertoire, some artifacts position themselves as naïve tools in the actors’ environment to the point of being ignored; however, their usage-in-context unfolds (...) their cognitive involvement in the tasks. These usages-in-context are shown through artifact analysis of their routine, improvised, and opportunistic uses, where cognitive artifacts like talim—the central artifact of this practice—are shown to play not only multifunctional roles beyond representation, but are also complemented by trade-specific skills bearing strong cognitive implications in a task. (shrink)

The design process in Kashmiri carpet weaving is a distributed process encompassing a number of actors and artifacts. These include a designer called naqash who creates the design on graphs, and a coder called talim-guru who encodes that design in a specific notation called talim which is deciphered and interpreted by the weavers to weave the design. The technological interventions over the years have influenced these artifacts considerably and triggered major changes in the practice, from heralding profound cognitive accomplishments in (...) manually driven design process causing major alterations in the overall structure of the practice. The recent intervention is by the digital technology: on the one hand, it has brought precision and speedy processing in the design process, and on the other, it has eliminated some of the crucial actors from the practice. This paper, which forms part of a larger study on the situated and distributed cognitive process in Kashmiri carpet-weaving practice, describes the technological makeover of the design artifacts involved in this practice over the years and their resultant cognitive impact on the design process as well as on the practice. (shrink)

Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...) Belt" due to its extensive corn production. Corn crops can be grown using a variety of methods, including conventional tillage, no-till farming, and the use of genetically modified crops. Due to its importance, there is a need for discovering the corn diseases and treating them. The aim of this study is to propose a deep learning model for the classification of corn leaf diseases based on Convolutional Neural Network. A model for classifying maize diseases was developed using a dataset for classifying Corn diseases that contains 4 classes of disease. The dataset was collected from Keggel website. The proposed model was trained, validated, and tested. The F1-score (99.83%), Recall (99.83%), precision (99.83%), Accuracy (99.83%). (shrink)

Deep brain stimulation has been of considerable interest to bioethicists, in large part because of the effects that the intervention can occasionally have on central features of the recipient’s personality. These effects raise questions regarding the philosophical concept of authenticity. In this article, we expand on our earlier work on the concept of authenticity in the context of deep brain stimulation by developing a diachronic, value-based account of authenticity. Our account draws on both existentialist and essentialist approaches to (...) authenticity, and Laura Waddell Ekstrom’s coherentist approach to personal autonomy. In developing our account, we respond to Sven Nyholm and Elizabeth O’Neill’s synchronic approach to authenticity, and explain how the diachronic approach we defend can have practical utility, contrary to Alexandre Erler and Tony Hope’s criticism of autonomy-based approaches to authenticity. Having drawn a distinction between the authenticity of an individual’s traits and the authenticity of that person’s values, we consider how our conception of authenticity applies to the context of anorexia nervosa in comparison to other prominent accounts of authenticity. We conclude with some reflections on the prudential value of authenticity, and by highlighting how the language of authenticity can be invoked to justify covert forms of paternalism that run contrary to the value of individuality that seems to be at the heart of authenticity. (shrink)

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons (...) based on their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

Deep Brain Stimulation (DBS) is a relatively new, experimental treatment for patients suffering from treatment-refractory Obsessive Compulsive Disorder (OCD). The effects of treatment are typically assessed with psychopathological scales that measure the amount of symptoms. However, clinical experience indicates that the effects of DBS are not limited to symptoms only: patients for instance report changes in perception, feeling stronger and more confident, and doing things unreflectively. Our aim is to get a better overview of the whole variety of changes (...) that OCD patients experience during DBS treatment. For that purpose we conducted in-depth, semi-structured interviews with 18 OCD patients. In this paper, we present the results from this qualitative study.We list the changes grouped in four domains: with regard to (a) person, (b) (social) world, (c)characteristics of person-world interactions, and (d) existential stance. We subsequently provide an interpretation of these results. In particular, we suggest that many of these changes can be seen as different expressions of the same process; namely that the experience of anxiety and tension gives way to an increased basic trust and increased reliance on one’s abilities. We then discuss the clinical implications of our findings, especially with regard to properly informing patients of what they can expect from treatment, the usefulness of including CBT in treatment, and the limitations of current measures of treatment success. We end by making several concrete suggestions for further research. (shrink)

We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful (...) models requires pragmatic understanding to apply modelling strategies that encourage the model to learn data patterns that will facilitate reliable generalisation. (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...) synthetic audiovisual media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

‘Shallow’ and ‘deep’ versions of scientific realism may be distinguished as follows: the shallow realist is satisfied with belief in the existence of the posits of our best scientific theories; by contrast, deep realists claim that realism can be legitimate only if such entities are described in metaphysical terms. We argue that this methodological discussion can be fruitfully applied in Everettian quantum mechanics, specifically on the debate concerning the existence of worlds and the recent dispute between Everettian actualism (...) and quantum modal realism. After presenting what is involved in such dispute, we point to a dilemma for realists: either we don’t have the available metaphysical tools to answer the deep realist’s demands, and realism is not justified in this case, or such demands of metaphysical dressing are not mandatory for scientific realism, and deep versions of realism are not really required. (shrink)

This paper constructs a model of metaphysical indeterminacy that can accommodate a kind of ‘deep’ worldly indeterminacy that arguably arises in quantum mechanics via the Kochen-Specker theorem, and that is incompatible with prominent theories of metaphysical indeterminacy such as that in Barnes and Williams (2011). We construct a variant of Barnes and Williams's theory that avoids this problem. Our version builds on situation semantics and uses incomplete, local situations rather than possible worlds to build a model. We evaluate the (...) resulting theory and contrast it with similar alternatives, concluding that our model successfully captures deep indeterminacy. (shrink)

Default logic has been a very active research topic in artificial intelligence since the early 1980s, but has not received as much attention in the philosophical literature thus far. This paper shows one way in which the technical tools of artificial intelligence can be applied in contemporary epistemology by modeling a paradigmatic case of deep disagreement using default logic. In §1 model-building viewed as a kind of philosophical progress is briefly motivated, while §2 introduces the case of deep (...) disagreement we aim to model. On the heels of this, §3 defines our formal framework, viz., a refined Horty-style default logic. §4 then uses the framework to model deep disagreement, and finally §5 provides a critical discussion of the result. (shrink)

Disagreements that resist rational resolution, often termed “deep disagreements”, have been the focus of much work in epistemology and informal logic. In this paper, I argue that they also deserve the attention of philosophers of mathematics. I link the question of whether there can be deep disagreements in mathematics to a more familiar debate over whether there can be revolutions in mathematics. I propose an affirmative answer to both questions, using the controversy over Shinichi Mochizuki’s work on the (...) abc conjecture as a potential example of both phenomena. I conclude by investigating the prospects for the resolution of mathematical deep disagreements in virtue-theoretic approaches to informal logic and mathematical practice. (shrink)

In this paper, we engage in dialogue with Jonathan Pugh, Hannah Maslen, and Julian Savulescu about how to best interpret the potential impacts of deep brain stimulation on the self. We consider whether ordinary people’s convictions about the true self should be interpreted in essentialist or existentialist ways. Like Pugh et al., we argue that it is useful to understand the notion of the true self as having both essentialist and existentialist components. We also consider two ideas from existentialist (...) philosophy – Jean-Paul Sartre and Simone de Beauvoir’s ideas about “bad faith” and “ambiguity” – to argue that there can be value to patients in regarding themselves as having a certain amount of freedom to choose what aspects of themselves should be considered representative of their true selves. Lastly, we consider the case of an anorexia nervosa-patient who shifts between conflicting mind-sets. We argue that mind-sets in which it is easier for the patient and his or her family to share values can plausibly be considered to be more representative of the patient’s true self, if this promotes a well-functioning relationship between the patient and the family. However, we also argue that families are well-advised to give patients room to figure out what such shared values mean to them, since it can be alienating for patients if they feel that others try to impose values on them from the outside. (shrink)

Under the current Mental Health Act of England and Wales, it is lawful to perform deep brain stimulation in the absence of consent and independent approval. We argue against the Care Quality Commission's preferred strategy of addressing this problematic issue, and offer recommendations for deep brain stimulation-specific provisions in a revised Mental Health Act.

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on (...) and take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (shrink)

People suffering from Obsessive-Compulsive Disorder (OCD) do things they do not want to do, and/or they think things they do not want to think. In about 10 percent of OCD patients, none of the available treatment options is effective. A small group of these patients is currently being treated with deep brain stimulation (DBS). Deep brain stimulation involves the implantation of electrodes in the brain. These electrodes give a continuous electrical pulse to the brain area in which they (...) are implanted. It turns out that patients may experience profound changes as a result of DBS treatment. It is not just the symptoms that change; patients rather seem to experience a different way of being in the world. These global effects are insufficiently captured by traditional psychiatric scales, which mainly consist of behavioural measures of the severity of the symptoms. In this article we aim to capture the changes in the patients’ phenomenology and make sense of the broad range of changes they report. For that we introduce an enactive, affordance-based model that fleshes out the dynamic interactions between person and world in four aspects. The first aspect is the patients’ experience of the world. We propose to specify the patients’ world in terms of a field of affordances, with the three dimensions of broadness of scope (‘width’ of the field), temporal horizon (‘depth’), and relevance of the perceived affordances (‘height’). The second aspect is the person-side of the interaction, that is, the patients’ self-experience, notably their moods and feelings. Thirdly, we point to the different characteristics of the way in which patients relate to the world. And lastly, the existential stance refers to the stance that patients take towards the changes they experience: the second-order evaluative relation to their interactions and themselves. With our model we intend to specify the notion of being in the world in order to do justice to the phenomenological effects of DBS treatment. (shrink)

This paper provides a reinterpretation of some of the most influential skeptical arguments, Agrippa’s trilemma, meta-regress arguments, and Cartesian external world skepticism. These skeptical arguments are reasonably regarded as unsound arguments about the extent of our knowledge. However, reinterpretations of these arguments tell us something significant about the preconditions and limits of persuasive argumentation. These results contribute to the ongoing debates about the nature and resolvability of deep disagreement. The variety of skeptical arguments shows that we must distinguish different (...) types of deep disagreement. Moreover, the reinterpretation of skeptical arguments elucidates that deep disagreement cannot be resolved via argumentation. (shrink)

Deep disagreements are characteristically resistant to rational resolution. This paper explores the contribution a virtue theoretic approach to argumentation can make towards settling the practical matter of what to do when confronted with apparent deep disagreement, with particular attention to the virtue of courage.

Why is it that some instances of disagreement appear to be so intractable? And what is the appropriate way to handle such disagreements, especially concerning matters about which there are important practical and political needs for us to come to a consensus? In this paper, I consider an explanation of the apparent intractability of deep disagreement offered by hinge epistemology. According to this explanation, at least some deep disagreements are rationally unresolvable because they concern ‘hinge’ commitments that are (...) unresponsive to rational considerations. This explanation, if correct, seems to have troubling implications for how we should respond to deep disagreement. If my position on a topic is not responsive to rational considerations, then what choice have I but to dogmatically hold to that position, and simply dismiss the views of those with whom I disagree? I address this problem by identifying an attitude of intellectual humility that is appropriate to have towards one's hinge commitments, and suggest that this attitude provides the basis for a non-rational, constructive way to resolve deep disagreement. (shrink)

The existence of deep moral disagreement is used in support of views ranging from moral relativism to the impossibility of moral expertise. This is done despite the fact that it is not at all clear whether deep moral disagreements actually occur, as the usually given examples are never of real life situations, but of some generalized debates on controversial issues. The paper will try to remedy this, as any strength of arguments appealing to deep moral disagreement is (...) partly depended on the fact the disagreement exists. This will be done by showing that some real life conflicts that are intractable, i.e. notoriously difficult to resolve, share some important features with deep moral disagreement. The article also deals with the objection that the mere conceptual possibility renders illustrations of actually happening deep moral disagreements unnecessary. The problem with such objection is that it depends on theoretical assumptions (i.e. denial of moral realism) that are not uncontroversial. Instead, the article claims we need not only suppose deep moral disagreements exist because they actually occur when some intractable conflicts occur. Thus, in so far as to the deep moral disagreement’s existence, the arguments appealing to it are safe. But as intractable conflicts can be resolved, by seeing deep moral disagreements as constitutive part of them, we might have to consider whether deep moral disagreements are resolvable too. A brief suggestion of how that might look like is given in the end of the paper. (shrink)

The ever-evolving ways attacker continues to improve their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack. Thus, current anti-phishing methods remain vulnerable to complex phishing because of the increasingly sophistication tactics adopted by attacker coupled with the rate at which new tactics are being developed to evade detection. In this research, we proposed an adaptable (...) framework that combines Deep learning and Randon Forest to read images, synthesize speech from deep-fake videos, and natural language processing at various predictions layered to significantly increase the performance of machine learning models for phishing attack detection. (shrink)

Although the discipline of vice epistemology is only a decade old, the broader project of studying epistemic vices and failings is much older. This paper argues that contemporary vice epistemologists ought to engage more closely with these earlier projects. After sketching some general arguments in section one, I then turn to deep epistemic vices: ones whose identity and intelligibility depends on some underlying conception of human nature or the nature of reality. The final section then offers a case study (...) from a vice epistemic tradition that emerged in early modern English natural philosophy. (shrink)

With the early success of the deep ecology movement in attracting adherents and with the increasing threat of a global ecological catastrophe, one would have expected this movement to have triumphed. We should be in the process of radically transforming society to create a harmonious relationship between humans and the rest of nature. Instead, deep ecology has been marginalized. What has triumphed instead is an alliance of managerialism, transnational corporations and neo-liberalism committed to replacing communities with markets and (...) transforming every facet of nature and society into means for increasing the profitability of corporations and expanding GDP. This outcome is here explained by the failure of deep ecologists to understand the ideological, political and economic forces driving ecological destruction, and thereby what is required to overcome these. To regain the initiative, it is argued, it will be necessary to recover the whole project of the Radical Enlightenment upholding the Renaissance quest for liberty that was subverted by the scientific materialism and possessive individualism of the Moderate Enlightenment. Not only will it be necessary to transform science to develop a comprehensive alternative conception of nature and humanity and its destiny, it will be necessary to revive and develop the institutions of the Radical Enlightenment to subordinate markets to democratically organized communities at multiple levels, as communities of communities committed to augmenting the life of these communities, including the life of ecological communities. Doing so will involve reformulating the grand narrative of emancipation as a dialogic, polyphonic grand narrative to orient individuals, organizations and nations to create a global ecological civilization. -/- . (shrink)

The precautionary principle is invoked in a number of important personal and policy decision contexts. Peterson shows that certain ways of making the principle precise are inconsistent with other criteria of decision-making. Some object that the results do not apply to cases of deep uncertainty or value incommensurability which are alleged to be in the principle’s wheelhouse. First, I show that Peterson’s impossibility results can be generalized considerably to cover cases of both deep uncertainty and incommensurability. Second, I (...) contrast an alternative way of giving voice to the precautionary impulse. (shrink)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (shrink)

In 2015, Fainos Mangena published an essay entitled “How Applicable is the Idea of Deep Ecology in the African Context?” where he presented a number of arguments to support his thesis that deep ecology as discussed in the West has no place in the African context. Mangena later presented a counter-version of deep ecology that he claims is based on African philosophy. In this paper, I interrogated Mangena’s arguments for rejecting deep ecology and found that they (...) were based on certain erroneous presuppositions. Further, I developed a critique of Mangena’s Shona version of deep ecology which shows it to be impractical, unappealing, and based on a misunderstanding of the true nature of the modern African environment. I employ the method of conversationalism in this work. Keywords: Deep Ecology, African Environmental Ethics, Fainos Mangena. (shrink)

This article starts off with a historical section showing that deep disagreements among notions of social and political justice are a characteristic feature of the history of political thought. Since no agreement or consensus on distributive justice is possible, the article argues that political philosophers should – instead of continuously proposing new normative theories of justice – focus on analyzing the reasons, significance, and consequences of such kinds of disagreements. The next two sections are analytical. The first sketches five (...) possible reasons for deep disagreements among notions of social and political justice. The second discusses the meta-ethical relevance of the lack of consensus on justice and rejects ethical realism and cognitivism based on the argument from deep disagreements. (shrink)

Seabed mining, the extraction of minerals from the deep-sea floor, is hotly contested. Policymakers have agreed on the need for a regulatory framework. However, traditional ethical theories and principles are not well equipped for the ethics of the alien deep sea. Engaging with the sea means engaging with something abstract that we can only access indirectly. We argue that this invisibility and alienness of the sea and its inhabitants can give new insights into how ethics are done. Rather (...) than getting even more grip on what is already directly known, considering what is outside our usual moral view may be just as valuable. To do so, art can help us think with these unknown and invisible parts of the ecosystem. For that, we describe three cases. The scientist and artist Eugen Ransonnet engaged with the underwater world in the late 19th century. The Victorian flower painter Marianne North's unruly approach greatly influenced the botanic discourse until today. And finally, Christina Stadlbauer's Institute for the Relocation of Biodiversity and her work with the mollusk Pinna Nobilis in Mar Menor, Spain. We describe the Pinna Nobilis video project and the ethical and political opportunities it opens. We propose that engaging with the arts can pave the way towards including the unknown in ethical reflection and, at the same time, how it can rephrase questions that can help us reconsider what is outside of our moral view. (shrink)

‘Deep adaptation’ refers to the personal and collective changes that might help us to prepare for – and live with – a climate-influenced breakdown or collapse of our societies. It is a framework for responding to the terrifying realization of increasing disruption by committing ourselves to reducing suffering while saving more of society and the natural world. This is the first book to show how professionals across different sectors are beginning to incorporate the acceptance of likely or unfolding societal (...) breakdown into their work and lives. They do not assume that our current economic, social and political systems can be made resilient in the face of climate change but, instead, they demonstrate the caring and creative ways that people are responding to the most difficult realization with which humanity may ever have to come to terms. Edited by the originator of the concept of deep adaptation, Jem Bendell, and a leading climate activist and strategist, Rupert Read, this book is the essential introduction to the concept, practice and emerging global movement of Deep Adaptation to climate chaos. (shrink)

La psychologie a toujours traité le comportement et l’expérience comme étant enchâssés dans un flux temporel unidimensionnel, « le courant du comportement » dans lequel les événements et les actions occupent des intervalles de temps qui ne se chevauchent pas. Pourtant, une analyse phénoménologique révèle que la structure de nos vies est bien plus riche et intéressante. En utilisant la notion de « quasidécomposabilité » de Herbert Simon, je décris cette structure comme un assemblage d’épisodes quasi-indépendants se réalisant de façon (...) concurrente, et de nature asynchrone. Il s’agit d’une « structure profonde» des vies contrairement à la conception courante qui conçoit les vies comme « plates » Psychology has always treated behavior and experience as embedded in a unidimensional flow in time, the "stream of behavior." This means that events and actions occupy non-overlapping time-intervals in this stream. Nevertheless a phenomenological analysis reveals that the structure of lives is richer and far more interesting. Using Herb Simon's notion of near-decomposability, I describe the structure of lives as a composite of nearly independent strands that run concurrently, and are asynchronous. This is a "deep structure"' of lives in contrast to the current conception, which conceives of lives as "flat." . (shrink)

Deep Self views of moral responsibility have been criticized for positing mysterious concepts, making nearly paradoxical claims about the ownership of one’s mental states, and promoting self-deceptive moral evasion. I defend Deep Self views from these pervasive forms of skepticism by arguing that some criticism is hasty and stems from epistemic injustice regarding testimonies of experiences of alienation, while other criticism targets contingent features of Deep Self views that ought to be abandoned. To aid in this project, (...) I provide original naturalistic analyses of “Self” and “internality” that replace the view’s metaphorical language with common-sensical concepts that make clear their usefulness. (shrink)

A paper of Roger Crisp’s four years ago contained arguments that seemed to imply that having deep personal relationships does not constitute an element of well‐being. The lesson to draw from that paper of Crisp’s, according to a recent journal article of mine, is that one’s having a deep personal relationship does constitute an element of one’s well‐being on condition that one’s affection for the other person is merited. Crisp’s paper earlier in this issue of Ratio responds to (...) my arguments. Here I reply to new questions that Crisp poses or provokes. (shrink)

This article addresses computational procedures that are no longer constrained by human modes of representation and considers how these procedures could be philosophically understood in terms of ‘algorithmic thought’. Research in deep learning is its case study. This artificial intelligence (AI) technique operates in computational ways that are often opaque. Such a black-box character demands rethinking the abstractive operations of deep learning. The article does so by entering debates about explainability in AI and assessing how technoscience and technoculture (...) tackle the possibility to ‘re-present’ the algorithmic procedures of feature extraction and feature learning to the human mind. The article thus mobilises the notion of incommensurability (originally developed in the philosophy of science) to address explainability as a communicational and representational issue, which challenges phenomenological and existential modes of comparison between human and algorithmic ‘thinking’ operations. (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)

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 images (...) belong to 3 species at a few developing phases. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results: found that CNN-driven lemon classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

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)

This article seeks to get clear on an important feature of a theistic way of life: namely, the appeal to ‘deep desires’ as part of an ethical and spiritual life-orientation. My main thesis is that such appeals should primarily be seen as pertaining to our acquired second nature and the space of meaning it makes possible, rather than first nature or innateness. To appeal to the ‘depth’ of a desire, on this account, is to say something about its normative (...) importance: it is something of profound significance for our human fulfilment about which we ought to be concerned, and it correlates with the normative ‘height’ of the object of desire. Thus, our deepest desire correlates with what is seen as the highest or most worthy object of our desire (or love), which the theist claims is God. This view is contrasted with subjectivist accounts where desires are seen as ‘deep’ in that they structure our identity. My account affirms that deep desires structure our identity, but they do so because of their perceived objective normative importance. I also seek to show how we should affirm Alasdair MacIntyre's claim that ‘the deepest desire of every [human] being, whether they acknowledge it or not, is to be at one with God’. (shrink)

Sripada has recently advanced a new account for asymmetries that have been uncovered in folk judgments of intentionality: the ?Deep Self model,? according to which an action is more likely to be judged as intentional if it matches the agent's central and stable attitudes and values (i.e., the agent's Deep Self). In this paper, we present new experiments that challenge this model in two ways: first, we show that the Deep Self model makes predictions that are falsified, (...) then we present cases that it cannot account for. Finally, we discuss how the Deep Self model could be modified to accommodate these new data. (shrink)

Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. (...) A dataset of 75,000 images was collected and annotated, consisting of 15,000 images for each of the five types of rice. The deep learning system uses convolutional neural networks (CNNs) to classify images of rice grains based on their physical characteristics. The performance of the deep learning system was evaluated using metrics such as accuracy, precision, recall, and F1-score. The results show that the proposed deep learning system was able to achieve high accuracy in classifying the different types of rice, outperforming traditional image processing techniques. This study provides valuable insights into the potential of deep learning for classifying different types of rice and can be useful for applications such as quality control in rice processing industries and research in crop science. The large size of the dataset, 15,000 images for each type of rice, helped the deep learning system to learn the features of each type of rice, and increase the performance of the classifier. The attained overall accuracy of the proposed model (99.96%), Precision (99.96%), Recall (99.96%) and F1-score (99.96%). Thus, the proposed model proved that it leaned the five categories of rice and it can generalize these categories and it is effective. (shrink)

Challenging the basic assumptions of a meat-eating society, Deep Vegetarianism is a spirited and compelling defense of a vegetarian lifestyle. Considering all of the major arguments both for and against vegetarianism and the habits of meat-eaters, vegetarians, and vegans alike, Michael Allen Fox addresses vegetarianism's cultural, historical, and philosophical background; details vegetarianism's impact on one's living and thinking; and relates vegetarianism to classical and recent defenses of the moral status of animals. Demonstrating how a vegetarian diet is related to (...) our awareness of the world and our ethical outlook on life, Fox looks at the different kinds of vegetarian commitments people make and their reasons for making them. In chapters that address such issues as the experiences, emotions, and grounds that are part of choosing vegetarianism, Fox discusses not only good health, animal suffering, and the environmental impacts of meat production, but such issues as the meaning of food, world hunger, religion and spirituality, and, significantly, the links share between vegetarianism and other human rights movements and ideologies, particularly feminism. In an extensive chapter that addresses arguments made by advocates of meat-eating, Fox speaks to claims of humans as natural carnivores, animals as replaceable, and vegetarians as anti-feminist. He also addresses arguments surrounding the eating habits of indigenous peoples, eating free-range animals, and carnivorous behavior among animals. The most complete examination of the vegetarian outlook to date, Deep Vegetarianism reveals the broad range of philosophical views that contribute to such a choice. It recognizes, and calls for, a conscious awareness of -- and an individual responsibility to -- the issues that exist in the moral, political, and social spheres of our existence. With its lively and controversial discussion, Deep Vegetarianism promises to appeal to anyone looking to explore the relationship between dietary choice, lifestyle, the treatment of animals and the environment, and personal ethical responsibility. It will also be particularly useful for students and teachers of moral philosophy, ethics, religion, comparative cultures, ecology, and feminism. (shrink)

The representations of deep convolutional neural networks (CNNs) are formed from generalizing similarities and abstracting from differences in the manner of the empiricist theory of abstraction (Buckner, Synthese 195:5339–5372, 2018). The empiricist theory of abstraction is well understood to entail infinite regress and circularity in content constitution (Husserl, Logical Investigations. Routledge, 2001). This paper argues these entailments hold a fortiori for deep CNNs. Two theses result: deep CNNs require supplementation by Quine’s “apparatus of identity and quantification” in (...) order to (1) achieve concepts, and (2) represent objects, as opposed to “half-entities” corresponding to similarity amalgams (Quine, Quintessence, Cambridge, 2004, p. 107). Similarity amalgams are also called “approximate meaning[s]” (Marcus & Davis, Rebooting AI, Pantheon, 2019, p. 132). Although Husserl inferred the “complete abandonment of the empiricist theory of abstraction” (a fortiori deep CNNs) due to the infinite regress and circularity arguments examined in this paper, I argue that the statistical learning of deep CNNs may be incorporated into a Fodorian hybrid account that supports Quine’s “sortal predicates, negation, plurals, identity, pronouns, and quantifiers” which are representationally necessary to overcome the regress/circularity in content constitution and achieve objective (as opposed to similarity-subjective) representation (Burge, Origins of Objectivity. Oxford, 2010, p. 238). I base myself initially on Yoshimi’s (New Frontiers in Psychology, 2011) attempt to explain Husserlian phenomenology with neural networks but depart from him due to the arguments and consequently propose a two-system view which converges with Weiskopf’s proposal (“Observational Concepts.” The Conceptual Mind. MIT, 2015. 223–248). (shrink)

This paper examines Susan Wolf's account of "the Reason View" of moral responsibility as articulated and defended in 'Freedom Within Reason' (OUP 1990). The discussion turns on two questions about the Reason View: -/- (1) Does the Reason View aim to satisfy what Bernard Williams describes as “morality” and its (“peculiar”) conception of responsibility and blame? -/- (2) If it does, how successful is the Reason View judged in these terms? -/- It is argued that if the Reason View aims (...) to satisfy “morality” in respect of its understanding of deserved blame -- as it seems to -- then it fails for reasons similar to those that apply to R. J. Wallace’s 'rational self-control' model. On the other hand, if Wolf’s Reason View does not aim to satisfy “morality” in this respect then it might well rest satisfied with the more limited conditions of Wallace’s Reflective Self-Control model, which in contrast with the Reason View, does not appeal to the (problematic) apparatus of asymmetry and PAP. The paper concludes by drawing a contrast between the Reason View and a more "realistic" conception of responsibility, as suggested by the critique of “the morality system” and the more radical "recasting" of our ethical concepts that it proposes. -/- . (shrink)

In their insightful article, Brent Kious and Margaret Battin (2019) correctly identify an inconsistency between an involuntary psychiatric commitment for suicide prevention and physician aid in dying (PAD). They declare that it may be possible to resolve the problem by articulating “objective standards for evaluating the severity of others’ suffering,” but ultimately they admit that this task is beyond the scope of their article since the solution depends on “a deep and difficult” question about comparing the worseness of two (...) possible scenarios: letting someone die (who could have been helped) with not letting someone die (whose suffering could only be alleviated by death). In our commentary, we argue that creating such standards is more difficult than the authors assume because of the many types of deep uncertainties we have to deal with: (1) diagnostic, (2) motivational, and (3) existential. (shrink)

According to manipulation arguments for incompatibilism, manipulation might undermine an agent’s responsibility even when the agent satisfies plausible compatibilist conditions on responsibility. According to Sripada, however, empirical data suggest that people take manipulation to undermine responsibility largely because they think that the manipulated act is in discord with the agent’s “deep self,” thus violating the plausible compatibilist condition of deep self concordance. This paper defends Sripada’s general methodological approach but presents data that strongly suggest that, contrary to Sripada’s (...) contention, most of the effect of manipulation on attributions of moral responsibility is unmediated by worries about inadequate information or deep self discordance. Instead, it depends largely on worries that the action is ultimately explained by factors outside the agent’s control, just as proponents of manipulation arguments have proposed. More generally, data suggest that judgments of... (shrink)

I intend to bring recent work applying virtue theory to the study of argument to bear on a much older problem, that of disagreements that resist rational resolution, sometimes termed "deep disagreements". Just as some virtue epistemologists have lately shifted focus onto epistemic vices, I shall argue that a renewed focus on the vices of argument can help to illuminate deep disagreements. In particular, I address the role of arrogance, both as a factor in the diagnosis of (...) class='Hi'>deep disagreements and as an obstacle to their mutually acceptable resolution. Arrogant arguers are likely to make any disagreements to which they are party seem deeper than they really are and arrogance impedes the strategies that we might adopt to resolve deep disagreements. As a case in point, since arrogant or otherwise vicious arguers cannot be trusted not to exploit such strategies for untoward ends, any policy for deep disagreement amelioration must require particularly close attention to the vices of argument, lest they be exploited by the unscrupulous. (shrink)