Results for 'Ai-Ling Hsu'

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  1. Does Communicative Retributivism Necessarily Negate Capital Punishment?Jimmy Chia-Shin Hsu - 2015 - Criminal Law and Philosophy 9 (4):603-617.
    Does communicative retributivism necessarily negate capital punishment? My answer is no. I argue that there is a place, though a very limited and unsettled one, for capital punishment within the theoretical vision of communicative retributivism. The death penalty, when reserved for extravagantly evil murderers for the most heinous crimes, is justifiable by communicative retributive ideals. I argue that punishment as censure is a response to the preceding message sent by the offender through his criminal act. The gravity of punishment should (...)
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  2. Saliva Ontology: An ontology-based framework for a Salivaomics Knowledge Base.Jiye Ai, Barry Smith & David Wong - 2010 - BMC Bioinformatics 11 (1):302.
    The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...)
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  3. Depressive rumination is correlated with brain responses during self-related processing.Tzu-Yu Hsu & Timothy J. Lane - 2021 - Journal of Psychiatry and Neuroscience 46:E518-E527.
    Background: Rumination, a tendency to focus on negative self-related thoughts, is a central symptom of depression. Studying the self-related aspect of such symptoms is challenging because of the need to distinguish self effects from the emotional content of task stimuli. This study employed an emotionally neutral self-related paradigm to investigate possible altered self-processing in depression and its link to rumination. Methods: People with major depressive disorder (n = 25) and controls (n = 25) underwent task-based electro-encephalogram recording. We studied late (...)
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  4. Clinical data wrangling using Ontological Realism and Referent Tracking.Werner Ceusters, Chiun Yu Hsu & Barry Smith - 2014 - In Ceusters Werner, Hsu Chiun Yu & Smith Barry (eds.), Proceedings of the Fifth International Conference on Biomedical Ontology (ICBO), Houston, 2014, (CEUR, 1327). pp. 27-32.
    Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (b) (...)
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  5. Alternative Protection of Intellectual Property Rights in Vaccine Production and Use under Covid-19.Ling Jin - 2022 - Journal of Education, Humanities and Social Sciences 1 (1):147-153.
    For the past three years, Coronavirus-19 (Covid-19) has become one of the major global health problems. Unlike any previous virus in the past decades, Covid-19 has shown its unprecedented spreading speed, infection rate, fatality rate, etc. Under this urgent disease outbursting event, scientists around the globe, through the myriad of research and experiments, successfully developed effective vaccines. However, like many other medical innovations, Covid-19 vaccines are categorized as intellectual properties and a scarce resource. As a consequence, the citizens of developed (...)
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  6. Bioinformatics advances in saliva diagnostics.Ji-Ye Ai, Barry Smith & David T. W. Wong - 2012 - International Journal of Oral Science 4 (2):85--87.
    There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...)
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  7. Towards a Body Fluids Ontology: A unified application ontology for basic and translational science.Jiye Ai, Mauricio Barcellos Almeida, André Queiroz De Andrade, Alan Ruttenberg, David Tai Wai Wong & Barry Smith - 2011 - Second International Conference on Biomedical Ontology , Buffalo, Ny 833:227-229.
    We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...)
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  8. Heavy Metals Contamination in Greenhouse Soils and Vegetables in Guanzhong, China.Ling Liu - 2014 - Journal of Encapsulation and Adsorption Sciences 4:80-88.
    This study used a flame atomic absorption spectrometer (FAAS) and atomic fluorescence spec-trophotometer (AFS) to detect the concentrations of chromium (Cr), cadmium (Cd), lead (Pb), hy-drargyrum (Hg) and arsenic (As) in soils and three genotypes of vegetables in greenhouse, as well as analyzed the physical and chemical properties of soils, including soil pH, soil organic matter (OM), basic nutrients, electrical conductivity (EC) and cation exchange capacity (CEC) in Guan- zhong areas, Shaanxi province, China. The results showed that comparing to subsoil, (...)
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  9. An Empirical Study on the Development of Global Mindset Through Learning.Yong Suhk Pak & Mon Yee Hsu - 2018 - Korean Management Review 47 (2):481 - 503.
    This study aims to examine the development of global mindset, which is rarely addressed in a Korean international business journal. We investigate whether the global mindset is a static state that is difficult to change or a dynamically changeable competence. Based on the global mindset literature, we categorize the global mindset into three dimensions - cognition, skills and attitudes - and analyze the nature (static or dynamic) of each dimension. We collect survey questions from 269 undergraduate students. We use paired (...)
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  10. The Complexity Of Individual And Socio-Cultural Ecology: Interaction Of Genes And Attachments On Intercultural Experience.Phua Yee Ling Desiree - 2016 - Dissertation, Nanyang Business School
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  11. A Presuppositional Approach to Conceptual Schemes.Xinli Wang & Ling Xu - 2010 - South African Journal of Philosophy 29 (4):404-421.
    The current discussions of conceptual schemes and related topics are misguided; for they have been focused too much on the truth-conditional notions of meaning/concepts and translation/interpretation in Tarski's style. It is exactly due to such a Quinean interpretation of the notion of conceptual schemes that the very notion of conceptual schemes falls prey to Davidson's attack. We argue that what should concern us in the discussions of conceptual schemes and related issues, following the initiatives of I. Hacking, T. Kuhn, and (...)
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  12. Uma história da educação química brasileira: sobre seu início discutível apenas a partir dos conquistadores.Ai Chassot - 1996 - Episteme 1 (2):129-145.
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  13. The Propositional vs. Hermeneutic Models of Cross-Cultural Understanding.Xinli Wang & Ling Xu - 2009 - South African Journal of Philosophy 28 (3):312-331.
    What the authors attempt to address in this paper is a Kantian question: not whether, but how is cross -cultural understanding possible? And specifically, what is a more effective approach for cross -cultural understanding? The answer lies in an analysis of two different models of cross -cultural understanding, that is, propositional and hermeneutic understanding. To begin with, the author presents a linguistic interpretation of culture, i.e., a culture as a linguistically formulated and transmitted symbolic system with its conceptual core as (...)
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  14. Logical thinking education to combat plagiarism.Wai Ling Lai & Chad Nilep - 2014 - Gengo bunka ronshu 36 (1):179-193.
    Plagiarism, which Indiana University’s Writing Tutorial Service defines as "using others' ideas and words without clearly acknowledging the source of that information", is often described as a major problem. However, standard definitions such as this one suggest only limited solutions to the problem: acknowledging sources or forbidding reuse. Since all scholarship involves engaging with the ideas of others and academic writing tends to reuse certain expressions, these solutions – though important – are of limited utility. This paper examines a type (...)
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  15. Đổi mới chế độ sở hữu trong nền kinh tế thị trường định hướng xã hội chủ nghĩa ở Việt Nam.Võ Đại Lược - 2021 - Tạp Chí Khoa Học Xã Hội Việt Nam 7:3-13.
    Hiện nay, chế độ sở hữu ở Việt Nam đã có những đổi mới cơ bản, nhưng vẫn còn những khác biệt rất lớn so với chế độ sở hữu ở các nền kinh tế thị trường hiện đại. Trong cơ cấu của chế độ sở hữu ở Việt Nam, tỷ trọng của sở hữu nhà nước còn quá lớn; kinh tế nhà nước giữ vai trò chủ đạo… Chính những khác biệt này đã làm cho nền kinh tế thị (...)
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  16. A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.Yongqun He, Hong Yu, Anthony Huffman, Asiyah Yu Lin, Darren A. Natale, John Beverley, Ling Zheng, Yehoshua Perl, Zhigang Wang, Yingtong Liu, Edison Ong, Yang Wang, Philip Huang, Long Tran, Jinyang Du, Zalan Shah, Easheta Shah, Roshan Desai, Hsin-hui Huang, Yujia Tian, Eric Merrell, William D. Duncan, Sivaram Arabandi, Lynn M. Schriml, Jie Zheng, Anna Maria Masci, Liwei Wang, Hongfang Liu, Fatima Zohra Smaili, Robert Hoehndorf, Zoë May Pendlington, Paola Roncaglia, Xianwei Ye, Jiangan Xie, Yi-Wei Tang, Xiaolin Yang, Suyuan Peng, Luxia Zhang, Luonan Chen, Junguk Hur, Gilbert S. Omenn, Brian Athey & Barry Smith - 2022 - Journal of Biomedical Semantics 13 (1):25.
    The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...)
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  17. The impacts of value, disconfirmation and satisfaction on loyalty: Evidence from international higher education setting.Hiep-Hung Pham, Sue Ling Lai & Quan-Hoang Vuong - manuscript
    Relationships with international students can be beneficial to higher education in terms of financial and human resources. For this reason, establishing and maintaining such relationships are usually pre-eminent concerns. In this study, we extended the application of the disconfirmation expectation model by incorporating components from subjective task value to predict the loyalty of international students toward their host countries. On a sample of 410 Vietnamese students enrolled in establishments of higher education in over 15 countries across the globe, we employed (...)
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  18.  77
    Đề cương học phần Văn hóa kinh doanh.Đại học Thuongmai - 2012 - Thuongmai University Portal.
    ĐỀ CƯƠNG HỌC PHẦN VĂN HÓA KINH DOANH 1. Tên học phần: VĂN HÓA KINH DOANH (BUSINESS CULTURE) 2. Mã học phần: BMGM1221 3. Số tín chỉ: 2 (24,6) (để học được học phần này, người học phải dành ít nhất 60 giờ chuẩn bị cá nhân).
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  19. Đổi mới chế độ sở hữu trong nền kinh tế thị trường định hướng xã hội chủ nghĩa ở Việt Nam.Võ Đại Lược - 2021 - Khoa Học Xã Hội Việt Nam 2021 (7):3-13.
    Hiện nay, chế độ sở hữu ở Việt Nam đã có những đổi mới cơ bản, nhưng vẫn còn những khác biệt rất lớn so với chế độ sở hữu ở các nền kinh tế thị trường hiện đại. Trong cơ cấu của chế độ sở hữu ở Việt Nam, tỷ trọng của sở hữu nhà nước còn quá lớn; kinh tế nhà nước giữ vai trò chủ đạo… Chính những khác biệt này đã làm cho nền kinh tế thị (...)
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  20. Tiếp tục đổi mới, hoàn thiện chế độ sở hữu trong nền kinh tế thị trường định hướng XHCN ở Việt Nam.Võ Đại Lược - 2021 - Tạp Chí Mặt Trận 2021 (8):1-7.
    (Mặt trận) - Chế độ sở hữu trong nền kinh tế thị trường định hướng xã hội chủ nghĩa Việt Nam trước hết phải tuân theo các nguyên tắc của nền kinh tế thị trường hiện đại. Trong các nguyên tắc của nền kinh tế thị trường hiện đại, nguyên tắc sở hữu tư nhân là nền tảng của nền kinh tế thị trường - là nguyên tắc quan trọng. Xa rời nguyên tắc này, dù chúng ta cố gắng xây (...)
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  21. The Blood Ontology: An ontology in the domain of hematology.Almeida Mauricio Barcellos, Proietti Anna Barbara de Freitas Carneiro, Ai Jiye & Barry Smith - 2011 - In Barcellos Almeida Mauricio, Carneiro Proietti Anna Barbara de Freitas, Jiye Ai & Smith Barry (eds.), Proceedings of the Second International Conference on Biomedical Ontology, Buffalo, NY, July 28-30, 2011 (CEUR 883). pp. (CEUR Workshop Proceedings, 833).
    Despite the importance of human blood to clinical practice and research, hematology and blood transfusion data remain scattered throughout a range of disparate sources. This lack of systematization concerning the use and definition of terms poses problems for physicians and biomedical professionals. We are introducing here the Blood Ontology, an ongoing initiative designed to serve as a controlled vocabulary for use in organizing information about blood. The paper describes the scope of the Blood Ontology, its stage of development and some (...)
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  22. Why AIs Cannot Play Games.David Koepsell - manuscript
    This paper explores the human experience of game-playing and its implications for artificial intelligence. The author uses phenomenology to examine game-playing from a human-centered perspective and applies it to language games played by artificial intelligences and humans. The paper argues that AI cannot truly play games because it lacks the intentionality, embodied experience, and social interaction that are fundamental to human game-playing. Furthermore, current AI lacks the ability to converse, which is argued to be equivalent to Wittgenstein’s view of engaging (...)
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  23. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  24. AI and the expert; a blueprint for the ethical use of opaque AI.Amber Ross - forthcoming - AI and Society:1-12.
    The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...)
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  25.  48
    AI training data, model success likelihood, and informational entropy-based value.Quan-Hoang Vuong, Viet-Phuong La & Minh-Hoang Nguyen - manuscript
    Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...)
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  26. Medical AI: is trust really the issue?Jakob Thrane Mainz - 2024 - Journal of Medical Ethics 50 (5):349-350.
    I discuss an influential argument put forward by Hatherley in theJournal of Medical Ethics. Drawing on influential philosophical accounts of interpersonal trust, Hatherley claims that medical artificial intelligence is capable of being reliable, but not trustworthy. Furthermore, Hatherley argues that trust generates moral obligations on behalf of the trustee. For instance, when a patient trusts a clinician, it generates certain moral obligations on behalf of the clinician for her to do what she is entrusted to do. I make three objections (...)
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  27. Taking AI Risks Seriously: a New Assessment Model for the AI Act.Claudio Novelli, Casolari Federico, Antonino Rotolo, Mariarosaria Taddeo & Luciano Floridi - 2023 - AI and Society 38 (3):1-5.
    The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, (...)
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  28. AI Wellbeing.Simon Goldstein & Cameron Domenico Kirk-Giannini - manuscript
    Under what conditions would an artificially intelligent system have wellbeing? Despite its obvious bearing on the ethics of human interactions with artificial systems, this question has received little attention. Because all major theories of wellbeing hold that an individual’s welfare level is partially determined by their mental life, we begin by considering whether artificial systems have mental states. We show that a wide range of theories of mental states, when combined with leading theories of wellbeing, predict that certain existing artificial (...)
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  29. How AI’s Self-Prolongation Influences People’s Perceptions of Its Autonomous Mind: The Case of U.S. Residents.Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Ruining Jin, Minh-Khanh La & Tam-Tri Le - 2023 - Behavioral Sciences 13 (6):470.
    The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI’s capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, (...)
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  30. AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act.Claudio Novelli, Federico Casolari, Antonino Rotolo, Mariarosaria Taddeo & Luciano Floridi - 2024 - Digital Society 3 (13):1-29.
    The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by (...)
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  31. AI-Related Misdirection Awareness in AIVR.Nadisha-Marie Aliman & Leon Kester - manuscript
    Recent AI progress led to a boost in beneficial applications from multiple research areas including VR. Simultaneously, in this newly unfolding deepfake era, ethically and security-relevant disagreements arose in the scientific community regarding the epistemic capabilities of present-day AI. However, given what is at stake, one can postulate that for a responsible approach, prior to engaging in a rigorous epistemic assessment of AI, humans may profit from a self-questioning strategy, an examination and calibration of the experience of their own epistemic (...)
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  32.  92
    AI Rights for Human Safety.Peter Salib & Simon Goldstein - manuscript
    AI companies are racing to create artificial general intelligence, or “AGI.” If they succeed, the result will be human-level AI systems that can independently pursue high-level goals by formulating and executing long-term plans in the real world. Leading AI researchers agree that some of these systems will likely be “misaligned”–pursuing goals that humans do not desire. This goal mismatch will put misaligned AIs and humans into strategic competition with one another. As with present-day strategic competition between nations with incompatible goals, (...)
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  33. AI Art is Theft: Labour, Extraction, and Exploitation, Or, On the Dangers of Stochastic Pollocks.Trystan S. Goetze - 2024 - Proceedings of the 2024 Acm Conference on Fairness, Accountability, and Transparency:186-196.
    Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues that AI (...)
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  34.  40
    (DRAFT) 如何藉由「以人為本」進路實現國科會AI科研發展倫理指南.Jr-Jiun Lian - 2024 - 2024科技與社會(Sts)年會年度學術研討會論文 ,國立臺東大學.
    本文深入探討人工智慧(AI)於實現共同福祉與幸福、公平與非歧視、理性公共討論及自主與控制之倫理與正義重要性與挑戰。以中央研究院LLM事件及國家科學技術委員會(NSTC)AI技術研發指導方針為基礎,本文 分析AI能否滿足人類共同利益與福祉。針對AI不公正,本文評估其於區域、產業及社會影響。並探討AI公平與非歧視挑戰,尤其偏差數據訓練問題,及後處理監管,強調理性公共討論之重要性。進而,本文探討理性公眾於 公共討論中之挑戰及應對,如STEM科學素養與技術能力教育之重要性。最後,本文提出“以人為本”方法,非僅依賴AI技術效用最大化,以實現AI正義。 -/- 關鍵詞:AI倫理與正義、公平與非歧視、偏差數據訓練、公共討論、自主性、以人為本的方法.
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  35. AI Methods in Bioethics.Joshua August Skorburg, Walter Sinnott-Armstrong & Vincent Conitzer - 2020 - American Journal of Bioethics: Empirical Bioethics 1 (11):37-39.
    Commentary about the role of AI in bioethics for the 10th anniversary issue of AJOB: Empirical Bioethics.
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  36. AI-aesthetics and the artificial author.Emanuele Arielli - forthcoming - Proceedings of the European Society for Aesthetics.
    ABSTRACT. Consider this scenario: you discover that an artwork you greatly admire, or a captivating novel that deeply moved you, is in fact the product of artificial intelligence, not a human’s work. Would your aesthetic judgment shift? Would you perceive the work differently? If so, why? The advent of artificial intelligence (AI) in the realm of art has sparked numerous philosophical questions related to the authorship and artistic intent behind AI-generated works. This paper explores the debate between viewing AI as (...)
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  37. Unjustified untrue "beliefs": AI hallucinations and justification logics.Kristina Šekrst - forthcoming - In Kordula Świętorzecka, Filip Grgić & Anna Brozek (eds.), Logic, Knowledge, and Tradition. Essays in Honor of Srecko Kovac.
    In artificial intelligence (AI), responses generated by machine-learning models (most often large language models) may be unfactual information presented as a fact. For example, a chatbot might state that the Mona Lisa was painted in 1815. Such phenomenon is called AI hallucinations, seeking inspiration from human psychology, with a great difference of AI ones being connected to unjustified beliefs (that is, AI “beliefs”) rather than perceptual failures). -/- AI hallucinations may have their source in the data itself, that is, the (...)
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  38. Ethical AI at work: the social contract for Artificial Intelligence and its implications for the workplace psychological contract.Sarah Bankins & Paul Formosa - 2021 - In Sarah Bankins & Paul Formosa (eds.), Ethical AI at Work: The Social Contract for Artificial Intelligence and Its Implications for the Workplace Psychological Contract. Cham, Switzerland: pp. 55-72.
    Artificially intelligent (AI) technologies are increasingly being used in many workplaces. It is recognised that there are ethical dimensions to the ways in which organisations implement AI alongside, or substituting for, their human workforces. How will these technologically driven disruptions impact the employee–employer exchange? We provide one way to explore this question by drawing on scholarship linking Integrative Social Contracts Theory (ISCT) to the psychological contract (PC). Using ISCT, we show that the macrosocial contract’s ethical AI norms of beneficence, non-maleficence, (...)
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  39. Ethical AI at Work: The Social Contract for Artificial Intelligence and Its Implications for the Workplace Psychological Contract.Sarah Bankins & Paul Formosa - 2021 - In Sarah Bankins & Paul Formosa (eds.), Ethical AI at Work: The Social Contract for Artificial Intelligence and Its Implications for the Workplace Psychological Contract. Cham, Switzerland:
    Artificially intelligent (AI) technologies are increasingly being used in many workplaces. It is recognised that there are ethical dimensions to the ways in which organisations implement AI alongside, or substituting for, their human workforces. How will these technologically driven disruptions impact the employee–employer exchange? We provide one way to explore this question by drawing on scholarship linking Integrative Social Contracts Theory (ISCT) to the psychological contract (PC). Using ISCT, we show that the macrosocial contract’s ethical AI norms of beneficence, non-maleficence, (...)
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  40. AI & democracy, and the importance of asking the right questions.Ognjen Arandjelović - 2021 - AI Ethics Journal 2 (1):2.
    Democracy is widely praised as a great achievement of humanity. However, in recent years there has been an increasing amount of concern that its functioning across the world may be eroding. In response, efforts to combat such change are emerging. Considering the pervasiveness of technology and its increasing capabilities, it is no surprise that there has been much focus on the use of artificial intelligence (AI) to this end. Questions as to how AI can be best utilized to extend the (...)
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  41. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  42.  56
    Can AI Achieve Common Good and Well-being? Implementing the NSTC's R&D Guidelines with a Human-Centered Ethical Approach.Jr-Jiun Lian - 2024 - 2024 Annual Conference on Science, Technology, and Society (Sts) Academic Paper, National Taitung University. Translated by Jr-Jiun Lian.
    This paper delves into the significance and challenges of Artificial Intelligence (AI) ethics and justice in terms of Common Good and Well-being, fairness and non-discrimination, rational public deliberation, and autonomy and control. Initially, the paper establishes the groundwork for subsequent discussions using the Academia Sinica LLM incident and the AI Technology R&D Guidelines of the National Science and Technology Council(NSTC) as a starting point. In terms of justice and ethics in AI, this research investigates whether AI can fulfill human common (...)
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  43. Extinction Risks from AI: Invisible to Science?Vojtech Kovarik, Christiaan van Merwijk & Ida Mattsson - manuscript
    In an effort to inform the discussion surrounding existential risks from AI, we formulate Extinction-level Goodhart’s Law as “Virtually any goal specification, pursued to the extreme, will result in the extinction of humanity”, and we aim to understand which formal models are suitable for investigating this hypothesis. Note that we remain agnostic as to whether Extinction-level Goodhart’s Law holds or not. As our key contribution, we identify a set of conditions that are necessary for a model that aims to be (...)
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  44. How AI can be a force for good.Mariarosaria Taddeo & Luciano Floridi - 2018 - Science Magazine 361 (6404):751-752.
    This article argues that an ethical framework will help to harness the potential of AI while keeping humans in control.
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  45. AI Human Impact: Toward a Model for Ethical Investing in AI-Intensive Companies.James Brusseau - manuscript
    Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technology’s human-centering. When summed, the scores convert into objective investment guidance. The strategy of incorporating ethics into financial decisions will be recognizable to participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks (...)
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  46. AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context.Sarah Bankins, Paul Formosa, Yannick Griep & Deborah Richards - forthcoming - Information Systems Frontiers.
    Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions of decision-maker role appropriate- (...)
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  47. AI Alignment vs. AI Ethical Treatment: Ten Challenges.Adam Bradley & Bradford Saad - manuscript
    A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching moral implications (...)
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  48. AI, Opacity, and Personal Autonomy.Bram Vaassen - 2022 - Philosophy and Technology 35 (4):1-20.
    Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive a (...)
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  49. Does AI Make It Impossible to Write an 'Original' Sentence (Is it Fair to Mechanically Test Originality).William M. Goodman - 2023 - The Toronto Star 2023 (September 28):A19.
    As a retired professor, I join in the growing concerns among educators, and others, about plagiarism, especially now that AI tools like ChatGPT are so readily available. However, I feel more caution is needed, regarding temptations to rely on supposed automatic detection tools, like Turnitin, to solve the problems. Students can be unfairly accused if such tools are used unreflectingly. The Toronto Star's online version of this published Op Ed is available at the link shown below. The version attached here (...)
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  50. As AIs get smarter, understand human-computer interactions with the following five premises.Manh-Tung Ho & Quan-Hoang Vuong - manuscript
    The hypergrowth and hyperconnectivity of networks of artificial intelligence (AI) systems and algorithms increasingly cause our interactions with the world, socially and environmentally, more technologically mediated. AI systems start interfering with our choices or making decisions on our behalf: what we see, what we buy, which contents or foods we consume, where we travel to, who we hire, etc. It is imperative to understand the dynamics of human-computer interaction in the age of progressively more competent AI. This essay presents five (...)
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