Results for ' good learning'

948 found
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  1. Good Learning and Epistemic Transformation.Kunimasa Sato - 2023 - Episteme 20 (1):181-194.
    This study explores a liberatory epistemic virtue that is suitable for good learning as a form of liberating socially situated epistemic agents toward ideal virtuousness. First, I demonstrate that the weak neutralization of epistemically bad stereotypes is an end of good learning. Second, I argue that weak neutralization represents a liberatory epistemic virtue, the value of which derives from liberating us as socially situated learners from epistemic blindness to epistemic freedom. Third, I explicate two distinct forms (...)
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  2. Socially Good AI Contributions for the Implementation of Sustainable Development in Mountain Communities Through an Inclusive Student-Engaged Learning Model.Tyler Lance Jaynes, Baktybek Abdrisaev & Linda MacDonald Glenn - 2023 - In Francesca Mazzi & Luciano Floridi (eds.), The Ethics of Artificial Intelligence for the Sustainable Development Goals. Springer Verlag. pp. 269-289.
    AI is increasingly becoming based upon Internet-dependent systems to handle the massive amounts of data it requires to function effectively regardless of the availability of stable Internet connectivity in every affected community. As such, sustainable development (SD) for rural and mountain communities will require more than just equitable access to broadband Internet connection. It must also include a thorough means whereby to ensure that affected communities gain the education and tools necessary to engage inclusively with new technological advances, whether they (...)
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  3. Aristotle on Shame and Learning to Be Good, Marta Jimenez. [REVIEW]Rachel Singpurwalla - 2022 - Ethics 132 (4):894-898.
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  4.  85
    (2 other versions)Learning from Learning from our Mistakes.Clayton Littlejohn - 2016 - In Martin Grajner & Pedro Schmechtig (eds.), Epistemic Reasons, Epistemic Norms, Epistemic Goals. De Gruyter. pp. 51-70.
    What can we learn from cases of knowledge from falsehood? Critics of knowledge-first epistemology have argued that these cases provide us with good reason for rejecting the knowledge accounts of evidence, justification, and the norm of belief. I shall offer a limited defense of the knowledge-first approach to these matters. Knowledge from falsehood cases should undermine our confidence in like-from-like reasoning in epistemology. Just as we should be open to the idea that knowledge can come from non-knowledge, we should (...)
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  5. Using Deep Learning to Detect the Quality of Lemons.Mohammed B. Karaja & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):97-104.
    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 (...)
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  6. Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide (...)
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  7. Teaching & Learning Guide for: The Epistemic Aims of Democracy.Robert Weston Siscoe - 2023 - Philosophy Compass 18 (11):e12954.
    In order to serve their citizens well, democracies must secure a number of epistemic goods. Take the truth, for example. If a democratic government wants to help its impoverished citizens improve their financial position, then elected officials will need to know what policies truly help those living in poverty. Because truth has such an important role in political decision-making, many defenders of democracy have highlighted the ways in which democratic procedures can lead to the truth. But there are also a (...)
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  8. Good Looking.Jennifer Matey - 2016 - Philosophical Issues 26 (1):297-313.
    Studies show that people we judge to have good character we also evaluate to be more attractive. I argue that in these cases, evaluative perceptual experiences represent morally admirable people as having positive (often intrinsic) value. Learning about a person's positive moral attributes often leads us to feel positive esteem for them. These feelings of positive esteem can come to partly constitute perceptual experiences. Such perceptual experiences evaluate the subject in an aesthetic way and seem to attribute aesthetic (...)
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  9. Machine learning in bail decisions and judges’ trustworthiness.Alexis Morin-Martel - 2023 - AI and Society:1-12.
    The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong (...)
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  10. Learning Implicit Biases from Fiction.Kris Goffin & Stacie Friend - 2022 - Journal of Aesthetics and Art Criticism 80 (2):129-139.
    Philosophers and psychologists have argued that fiction can ethically educate us: fiction supposedly can make us better people. This view has been contested. It is, however, rarely argued that fiction can morally “corrupt” us. In this article, we focus on the alleged power of fiction to decrease one's prejudices and biases. We argue that if fiction has the power to change prejudices and biases for the better, then it can also have the opposite effect. We further argue that fictions are (...)
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  11. A aquisição da virtude em Aristóteles a partir da obra "Learning to be good" de M. F. Burnyeat -uma discussão sobre a ressocialização e a pena de morte.Rubin Souza - 2014 - CONPEDI - Conselho Nacional de Pesquisa Em Pós-Graduação Em Direito 1 (1):1-17.
    Pretendeu-se estudar a aquisição da virtude em Aristóteles a partir da interpretação de M. F. Burnyeat. Para esse, a virtude aristotélica exige dimensões cognitivas e emocionais, sendo que ao aprendiz não basta conhecer os princípios e as regras gerais da ação, mas deve ter internalizado, através do hábito, uma vontade de praticar ações nobres e justas. Compete ao sujeito virtuoso, portanto, ter o conhecimento do que é correto (the that), assim como, subsidiariamente, a justificativa do porquê é apropriada determinada ação (...)
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  12. LEARNING ENVIRONMENT RELATED FACTORS AFFECTING AFGHAN EFL UNDERGRADUATES’ SPEAKING SKILL.Hazrat Usman Mashwani & Siti Maftuhah Damio - 2022 - Journal of Foreign Language Teaching and Learning (JFLTL) 7 (2):225-244.
    Of the four language skills, speaking is usually considered an indicator of proficiency in a language. As an EFL student, one should master speaking skill (Nazara, 2012). Unfortunately, most Afghan EFL undergraduates are not as good at speaking as they are in the other three English language skills (reading, writing and listening). Most Afghan undergraduate EFL learners are good at reading and writing, but in part of oral communication, they are not accurate and fluent (Zia & Sulan, 2015). (...)
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  13. Facebook Social Learning Group (FBSLG) as a Classroom Learning Management Tool.Jomar M. Urbano - 2022 - Universal Journal of Educational Research 1 (2):1-9.
    This study focuses on the step-to-step procedure in creating Facebook Social Learning Group (FBSLG) and the perception of students on using FBSLG as learning management tool. Descriptive method was employed in this study participated by two hundred eighty (280) teacher education students in Nueva Ecija University of Science and Technology – College of Education during the academic year 2020-2021 who were purposively selected based on the criteria set by the researcher. Five simple steps on creating FBSLG were discussed (...)
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  14. Good Thinking.Tim Kearl - 2022 - Dissertation, University of Arizona
    Good Thinking is a collection of papers about abilities, skills, and know-how and the distinctive but often overlooked—or explained away—role that these phenomena play in various foundational issues in epistemology and action theory. Each chapter, taken on its own, represents a fairly specific intervention into debates in (i) epistemic responsibility, (ii) the nature of inferential justification, and (iii) connections between inference and action. But taken collectively, these chapters constitute fragments of a larger mosaic of commitments about the explanatory priority (...)
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  15. Fish Classification Using Deep Learning.M. N. Ayyad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):51-58.
    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 (...)
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  16. Learning to be Reliable: Confucius' Analects.Karyn L. Lai - 2018 - In Karyn L. Lai, Rick Benitez & Hyun Jin Kim (eds.), Cultivating a Good Life in Early Chinese and Ancient Greek Philosophy: Perspectives and Reverberations. Bloomsbury. pp. 193-207.
    In the Lunyu, Confucius remarks on the implausibility—or impossibility—of a life lacking in xin 信, reliability (2.22). In existing discussions of Confucian philosophy, this aspect of life is often eclipsed by greater emphasis on Confucian values such as ren 仁 (benevolence), li 禮 (propriety) and yi 義 (rightness). My discussion addresses this imbalance by focusing on reliability, extending current debates in two ways. First, it proposes that the common translation of xin as denoting coherence between a person’s words and deeds (...)
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  17. Tomato Leaf Diseases Classification using Deep Learning.Mohammed F. El-Habibi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):73-80.
    Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has (...)
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  18. Diagnosis of Pneumonia Using Deep Learning.Alaa M. A. Barhoom & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):48-68.
    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 (...)
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  19. What good is love?Lauren Ware - 2014 - Analytic Teaching and Philosophical Praxis 34 (2).
    The role of emotions in mental life is the subject of longstanding controversy, spanning the history of ethics, moral psychology, and educational theory. This paper defends an account of love’s cognitive power. My starting point is Plato’s dialogue, the Symposium, in which we find the surprising claim that love aims at engendering moral virtue. I argue that this understanding affords love a crucial place in educational curricula, as engaging the emotions can motivate both cognitive achievement and moral development. I first (...)
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  20. Using Deep Learning to Classify Eight Tea Leaf Diseases.Mai R. Ibaid & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):89-96.
    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 (...)
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  21. An Unconventional Look at AI: Why Today’s Machine Learning Systems are not Intelligent.Nancy Salay - 2020 - In LINKs: The Art of Linking, an Annual Transdisciplinary Review, Special Edition 1, Unconventional Computing. pp. 62-67.
    Machine learning systems (MLS) that model low-level processes are the cornerstones of current AI systems. These ‘indirect’ learners are good at classifying kinds that are distinguished solely by their manifest physical properties. But the more a kind is a function of spatio-temporally extended properties — words, situation-types, social norms — the less likely an MLS will be able to track it. Systems that can interact with objects at the individual level, on the other hand, and that can sustain (...)
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  22. (1 other version)Good Governance - A Perspective from Sri Guru Granth Sahib.Devinder Pal Singh - 2020 - In Proc. International Conference on Contemporary Issues & Challenges to Polity & Governance in India: Emerging Paradigm Shifts & Future Agenda, Govt. Mohindra College, Patiala, Punjab, India. 17-18 February,. Patiala, Punjab, India: pp. 26-30.
    Governance encompasses the processes by which organizations are directed, controlled and held to account. It includes the authority, accountability, leadership, direction, and control exercised in an organization. Greatness can be achieved when good governance principles and practices are applied throughout the whole organization. Ethical Governance requires that public officials adhere to high moral standards while serving others. Authentic Governance entails the systematic process of continuous, gradual, and routine personal/corporate improvement, steering, and learning that lead to sustainable high personal/corporate (...)
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  23. A statistical learning approach to a problem of induction.Kino Zhao - manuscript
    At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we (...)
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  24. Intuitive Learning in Moral Awareness. Cognitive-Affective Processes in Mencius’ Innatist Theory.İlknur Sertdemir - 2022 - Academicus International Scientific Journal 13 (25):235-254.
    Mencius, referred to as second sage in Chinese philosophy history, grounds his theory about original goodness of human nature on psychological components by bringing in something new down ancient ages. Including the principles of virtuous action associated with Confucius to his doctrine, but by composing them along psychosocial development, he theorizes utterly out of the ordinary that makes all the difference to the school. In his argument stated a positive opinion, he explains the method of forming individuals' moral awareness by (...)
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  25. A Confucian Perspective on Tertiary Education for the Common Good.Edmond Eh - 2018 - Journal of the Macau Ricci Institute 3:26-34.
    Confucian education is best captured by the programme described in the Great Learning. Education is presented first as the process of self-cultivation for the sake of developing virtuous character. Self-cultivation then allows for virtue to be cultivated in the familial, social and international dimensions. My central thesis is that Confucianism can serve as a universal framework of educating people for the common good in its promotion of personal cultivation for the sake of human progress. On this account the (...)
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  26. Can reinforcement learning learn itself? A reply to 'Reward is enough'.Samuel Allen Alexander - 2021 - Cifma.
    In their paper 'Reward is enough', Silver et al conjecture that the creation of sufficiently good reinforcement learning (RL) agents is a path to artificial general intelligence (AGI). We consider one aspect of intelligence Silver et al did not consider in their paper, namely, that aspect of intelligence involved in designing RL agents. If that is within human reach, then it should also be within AGI's reach. This raises the question: is there an RL environment which incentivises RL (...)
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  27. Learning to apply theory of mind.Rineke Verbrugge & Lisette Mol - 2008 - Journal of Logic, Language and Information 17 (4):489-511.
    In everyday life it is often important to have a mental model of the knowledge, beliefs, desires, and intentions of other people. Sometimes it is even useful to to have a correct model of their model of our own mental states: a second-order Theory of Mind. In order to investigate to what extent adults use and acquire complex skills and strategies in the domains of Theory of Mind and the related skill of natural language use, we conducted an experiment. It (...)
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  28. Student Privacy in Learning Analytics: An Information Ethics Perspective.Alan Rubel & Kyle M. L. Jones - 2016 - The Information Society 32 (2):143-159.
    In recent years, educational institutions have started using the tools of commercial data analytics in higher education. By gathering information about students as they navigate campus information systems, learning analytics “uses analytic techniques to help target instructional, curricular, and support resources” to examine student learning behaviors and change students’ learning environments. As a result, the information educators and educational institutions have at their disposal is no longer demarcated by course content and assessments, and old boundaries between information (...)
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  29. Learning to Read: A Problem for Adam Smith and a Solution from Jane Austen.Lauren Kopajtic - 2022 - In Garry L. Hagberg (ed.), Fictional Worlds and Philosophical Reflection. pp. 49-78.
    What might Adam Smith have learned from Jane Austen and other novelists of his moment? This paper finds and examines a serious problem at the center of Adam Smith’s moral psychology, stemming from an unacknowledged tension between the effort of the spectator to sympathize with the feelings of the agent and that of the agent to moderate her feelings. The agent’s efforts will result in her opacity to spectators, blocking their attempts to read her emotions. I argue that we can (...)
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  30. Enkrasia or evidentialism? Learning to love mismatch.Maria Lasonen-Aarnio - 2020 - Philosophical Studies 177 (3):597-632.
    I formulate a resilient paradox about epistemic rationality, discuss and reject various solutions, and sketch a way out. The paradox exemplifies a tension between a wide range of views of epistemic justification, on the one hand, and enkratic requirements on rationality, on the other. According to the enkratic requirements, certain mismatched doxastic states are irrational, such as believing p, while believing that it is irrational for one to believe p. I focus on an evidentialist view of justification on which a (...)
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  31.  43
    The plight of Modified Work and Study Program (MWSP) students in learning mathematics.Ervin Jay Salera, Orville J. Evardo Jr & Ivy Lyt Abina - 2023 - Contemporary Educational Researches Journal 13 (4):240-250.
    The Philippine educational system established alternative delivery modes of education, such as the Modified Work and Study Program, to eradicate student dropout incidence. This phenomenological study aims to probe the challenges and explore the coping mechanism of MWSP students in studying mathematics. The study was conducted at a public high school offering the program. Six students were chosen to participate in the study. Focus group discussion was utilized for the data gathering of the study. Results showed that mediocrity of resources (...)
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  32. Comparative Analysis of Deep Learning and Naïve Bayes for Language Processing Task.Olalere Abiodun - forthcoming - International Journal of Research and Innovation in Applied Sciences.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance (...)
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  33. Machine Learning Application to Predict The Quality of Watermelon Using JustNN.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):1-8.
    In this paper, a predictive artificial neural network (ANN) model was developed and validated for the purpose of prediction whether a watermelon is good or bad, the model was developed using JUSTNN software environment. Prediction is done based on some watermelon attributes that are chosen to be input data to the ANN. Attributes like color, density, sugar rate, and some others. The model went through multiple learning-validation cycles until the error is zero, so the model is 100% percent (...)
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  34. Science and Enlightenment: Two Great Problems of Learning.Nicholas Maxwell - 2019 - Cham, Switzerland: Springer Verlag.
    Two great problems of learning confront humanity: learning about the nature of the universe and about ourselves and other living things as a part of the universe, and learning how to become civilized or enlightened. The first problem was solved, in essence, in the 17th century, with the creation of modern science. But the second problem has not yet been solved. Solving the first problem without also solving the second puts us in a situation of great danger. (...)
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  35. Extending Environments To Measure Self-Reflection In Reinforcement Learning.Samuel Allen Alexander, Michael Castaneda, Kevin Compher & Oscar Martinez - 2022 - Journal of Artificial General Intelligence 13 (1).
    We consider an extended notion of reinforcement learning in which the environment can simulate the agent and base its outputs on the agent's hypothetical behavior. Since good performance usually requires paying attention to whatever things the environment's outputs are based on, we argue that for an agent to achieve on-average good performance across many such extended environments, it is necessary for the agent to self-reflect. Thus weighted-average performance over the space of all suitably well-behaved extended environments could (...)
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  36. Predicting students’ multidimensional learning outcomes in public secondary schools: The roles of school facilities, administrative expenses and curriculum.Valentine Joseph Owan, John Asuquo Ekpenyong, Usen Friday Mbon, Kingsley Bekom Abang, Nse Nkereuwen Ukpong, Maria Ofie Sunday, Samuel Okpon Ekaette, Michael Ekpenyong Asuquo, Victor Ubugha Agama, Garieth Omorobi Omorobi & John Atewhoble Undie - 2023 - Journal of Applied Learning and Teaching 6 (2):1-17.
    Previous research has assessed school facilities, administrative expenditures and curriculum and their relative contributions to students’ cognitive learning outcomes. This suggested the need to investigate further how these predictors may impact students’ affective and psychomotor outcomes. The current research studied the combined and relative prediction of school facilities, administrative expenses and curriculum on students’ overall cognitive, affective and psychomotor learning outcomes in public secondary schools. A cross-sectional research design was employed in this study, involving 87 school administrators and (...)
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  37. Diagonalization & Forcing FLEX: From Cantor to Cohen and Beyond. Learning from Leibniz, Cantor, Turing, Gödel, and Cohen; crawling towards AGI.Elan Moritz - manuscript
    The paper continues my earlier Chat with OpenAI’s ChatGPT with a Focused LLM Experiment (FLEX). The idea is to conduct Large Language Model (LLM) based explorations of certain areas or concepts. The approach is based on crafting initial guiding prompts and then follow up with user prompts based on the LLMs’ responses. The goals include improving understanding of LLM capabilities and their limitations culminating in optimized prompts. The specific subjects explored as research subject matter include a) diagonalization techniques as practiced (...)
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  38. Breaking Good: Moral Agency, Neuroethics, and the Spontaneity of Compassion.Christian Coseru - 2017 - In Jake H. Davis (ed.), A Mirror is for Reflection: Understanding Buddhist Ethics. New York, NY: Oxford University Press. pp. 109-128.
    This paper addresses two specific and related questions the Buddhist neuroethics program raises for our traditional understanding of Buddhist ethics: Does affective neuroscience supply enough evidence that contempla- tive practices such as compassion meditation can enhance normal cognitive functioning? Can such an account advance the philosophical debate concerning freedom and determinism in a profitable direction? In response to the first question, I argue that dispositions such as empathy and altruism can in effect be understood in terms of the mechanisms that (...)
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  39. Good Legal Thought: What Wordsworth Can Teach Langdell About Forms, Frames, Choices, and Aims.Harold Anthony Lloyd - 2016 - Vermont Law Review 41 (1):1-22.
    Langdellian “science” and its “formalism” ignore ways form permits and even creates freedom of choice. For example, as Wordsworth notes, though the weaver is restricted by what his form of loom can weave, the weaver may nonetheless choose what and how he weaves. Furthermore, the loom creates weaving possibilities that do not exist without it. Such freedom alongside form is often lost on lawyers, judges, and teachers trained primarily in Langdellian redacted appellate cases where “facts” and other framed matters often (...)
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  40. The Transmission of Cumulative Cultural Knowledge — Towards a Social Epistemology of Non-Testimonial Cultural Learning.Müller Basil - forthcoming - Social Epistemology.
    Cumulative cultural knowledge [CCK], the knowledge we acquire via social learning and has been refined by previous generations, is of central importance to our species’ flourishing. Considering its importance, we should expect that our best epistemological theories can account for how this happens. Perhaps surprisingly, CCK and how we acquire it via cultural learning has only received little attention from social epistemologists. Here, I focus on how we should epistemically evaluate how agents acquire CCK. After sampling some reasons (...)
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  41. Norms of Inquiry, Student-Led Learning, and Epistemic Paternalism.Robert Mark Simpson - 2021 - In Jonathan Matheson & Kirk Lougheed (eds.), Epistemic Autonomy. New York, NY: Routledge. pp. 95-112.
    Should we implement epistemically paternalistic measures outside of the narrow range of cases, like legal trials, in which their benefits and justifiability seem clear-cut? In this chapter I draw on theories of student-led pedagogy, and Jane Friedman’s work on norms of inquiry, to argue against this prospect. The key contention in the chapter is that facts about an inquirer’s interests and temperament have a bearing on whether it is better for her to, at any given moment, pursue epistemic goods via (...)
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  42. Personal Discernment and Dialogue. Learning from ‘the Other’.Michael Barnes Sj - 2020 - European Journal for Philosophy of Religion 12 (4):27-43.
    This article considers the theme of discernment in the tradition of Ignatian spirituality emanating from the Spiritual Exercises of St Ignatius of Loyola, the founder of the Society of Jesus. After a brief introduction which addresses the central problematic of bad influences that manifest themselves as good, the article turns to the life and work of two Jesuits, the 16th C English missionary to India, Thomas Stephens and the 20th C French historian and cultural critic, Michel de Certeau. Both (...)
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  43. The idea of shan 善 (goodness): A neglected philosophical relation between Guodian’s ‘Wu xing’ and Xunzi.Fan He - 2024 - Asian Philosophy 34 (1):16-31.
    The ‘Wu xing’ belongs to Guodian bamboo slips texts, which were buried around 300 BCE and excavated in 1993. Its relation with Mengzi is widely investigated. Yet how it is philosophically related to Xunzi receives little attention. In this article, I illustrate a neglected relation between ‘Wu xing’ and Xunzi, by elucidating how shan 善 (goodness) is first raised in ‘Wu xing’ and developed by Xunzi into a concrete idea. Both ‘Wu xing’ and Xunzi propose that shan exists in action, (...)
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  44. Mapping Value Sensitive Design onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1 (3):283–296.
    Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, (...)
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  45. (1 other version)THE INFLUENCE OF IMPLEMENTATION BRAIN-FRIENDLY LEARNING THROUGH THE WHOLE BRAIN TEACHING TO STUDENTS’ RESPONSE AND CREATIVE CHARACTER IN LEARNING MATHEMATICS.Widodo Winarso & Siti Asri Karimah - 2017 - Jurnal Pendidikan Dan Pengajaran 50 (1):10-19.
    his study aims to determine whether the application of brain-friendly learning through whole brain teaching gives a positive effect on the creative character of students, to know the response of the students against the application of brain-friendly learning through whole brain teaching, and to find out if the student response against the application of brain-friendly learning through whole brain teaching correlates positively with the creative character of students in learning mathematics. The research method used that is (...)
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  46. Educating Judgment: Learning from the didactics of philosophy and sloyd.Birgit Schaffar & Camilla Kronqvist - 2017 - Revista Española de Educación Comparada 29:110–128.
    Teachers in vocational education face two problems. (1) Learning involves the ability to transcend and modify learned knowledge to new circumstances. How should vocational education prepare students for future, unknown tasks? (2) Students should strive to produce work of good quality. How does vocational education help them develop their faculty of judgment to differentiate between better and worse quality? These two ques- tions are tightly interwoven. The paper compares the didactics of philosophy and sloyd. Both developed independently, but (...)
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  47. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to 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 (...)
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  48. Implants and Ethnocide: learning from the Cochlear implant controversy.Robert Sparrow - 2010 - Disability and Society 25 (4):455-466.
    This paper uses the fictional case of the ‘Babel fish’ to explore and illustrate the issues involved in the controversy about the use of cochlear implants in prelinguistically deaf children. Analysis of this controversy suggests that the development of genetic tests for deafness poses a serious threat to the continued flourishing of Deaf culture. I argue that the relationships between Deaf and hearing cultures that are revealed and constructed in debates about genetic testing are themselves deserving of ethical evaluation. Making (...)
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  49. Implementation and Comparison of Deep Learning with Naïve Bayes for Language Processing (4th edition).Abiodun Olalere - 2024 - Internation Journal of Research and Innovation in Appliad Science:1-6.
    Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance (...)
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  50. The Ethics of Narrative Art: philosophy in schools, compassion and learning from stories.Laura D’Olimpio & Andrew Peterson - 2018 - Journal of Philosophy in Schools 5 (1):92-110.
    Following neo-Aristotelians Alasdair MacIntyre and Martha Nussbaum, we claim that humans are story-telling animals who learn from the stories of diverse others. Moral agents use rational emotions, such as compassion which is our focus here, to imaginatively reconstruct others’ thoughts, feelings and goals. In turn, this imaginative reconstruction plays a crucial role in deliberating and discerning how to act. A body of literature has developed in support of the role narrative artworks (i.e. novels and films) can play in allowing us (...)
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