Results for 'AI Curriculum Design'

980 found
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  1. A participatory, qualitative analysis of the use of MagicSchool AI for course design.Shantanu Tilak, Jesse Lincoln, Tara Miner, Natasha Christensen, Judy Jankowski & Kadie Kennedy - 2024 - Journal of Sociocybernetics 19 (1):43-106.
    This participatory study recounts conversational practices occurring between three teachers, a head of school, and a researcher during a month-long curriculum design workshop mediated by the MagicSchool AI technology to create social studies, language arts, science, and mathematics lessons for a virtual special education program. A social paradigm of AI-mediated educational practices is presented, wherein teachers interact with AI tools by embodying co-agency and a spirit of inquiry. Collective practices are interpreted using Gordon Pask’s conversation theory framework, showcasing (...)
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  2. From Confucius to Coding and Avicenna to Algorithms: Cultivating Ethical AI Development through Cross-Cultural Ancient Wisdom.Ammar Younas & Yi Zeng - manuscript
    This paper explores the potential of integrating ancient educational principles from diverse eastern cultures into modern AI ethics curricula. It draws on the rich educational traditions of ancient China, India, Arabia, Persia, Japan, Tibet, Mongolia, and Korea, highlighting their emphasis on philosophy, ethics, holistic development, and critical thinking. By examining these historical educational systems, the paper establishes a correlation with modern AI ethics principles, advocating for the inclusion of these ancient teachings in current AI development and education. The proposed integration (...)
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  3.  38
    How AI Can Implement the Universal Formula in Education and Leadership Training.Angelito Malicse - manuscript
    How AI Can Implement the Universal Formula in Education and Leadership Training -/- If AI is programmed based on your universal formula, it can serve as a powerful tool for optimizing human intelligence, education, and leadership decision-making. Here’s how AI can be integrated into your vision: -/- 1. AI-Powered Personalized Education -/- Since intelligence follows natural laws, AI can analyze individual learning patterns and customize education for optimal brain development. -/- Adaptive Learning Systems – AI can adjust lessons in real (...)
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  4. The Role of Engineers in Harmonising Human Values for AI Systems Design.Steven Umbrello - 2022 - Journal of Responsible Technology 10 (July):100031.
    Most engineers Fwork within social structures governing and governed by a set of values that primarily emphasise economic concerns. The majority of innovations derive from these loci. Given the effects of these innovations on various communities, it is imperative that the values they embody are aligned with those societies. Like other transformative technologies, artificial intelligence systems can be designed by a single organisation but be diffused globally, demonstrating impacts over time. This paper argues that in order to design for (...)
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  5. 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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  6. 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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  7. Designing AI with Rights, Consciousness, Self-Respect, and Freedom.Eric Schwitzgebel & Mara Garza - 2023 - In Francisco Lara & Jan Deckers, Ethics of Artificial Intelligence. Springer Nature Switzerland. pp. 459-479.
    We propose four policies of ethical design of human-grade Artificial Intelligence. Two of our policies are precautionary. Given substantial uncertainty both about ethical theory and about the conditions under which AI would have conscious experiences, we should be cautious in our handling of cases where different moral theories or different theories of consciousness would produce very different ethical recommendations. Two of our policies concern respect and freedom. If we design AI that deserves moral consideration equivalent to that of (...)
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  8.  65
    AI Literacy among Pre- service Teachers: Inputs Towards a Relevant Teacher Education Curriculum.Jhonas S. Lumanlan, Mary Rose I. Ayson, Mark Jayson V. Bautista, Jhayvi C. Dizon & Cynthia Mae L. Ylarde - 2025 - International Journal of Multidisciplinary Educational Research and Innovation 3 (1): 242-253.
    The present study is aimed at contributing to the growing literature around the application and relevance of AI in education, among others. Specifically, this work is centered around the constructs of AI literacy, as well as attitudes towards AI among pre-service teachers at three higher education institutions offering teacher education programs in Central Luzon, Philippines. Similarly, data pertinent to the respondents’ attitudes towards AI were gathered through an adapted instrument with a 4-point Likert scale, consisting of 26 items distributed across (...)
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  9. 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. (...)
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  10. Value Sensitive Design to Achieve the UN SDGs with AI: A Case of Elderly Care Robots.Steven Umbrello, Marianna Capasso, Maurizio Balistreri, Alberto Pirni & Federica Merenda - 2021 - Minds and Machines 31 (3):395-419.
    Healthcare is becoming increasingly automated with the development and deployment of care robots. There are many benefits to care robots but they also pose many challenging ethical issues. This paper takes care robots for the elderly as the subject of analysis, building on previous literature in the domain of the ethics and design of care robots. Using the value sensitive design approach to technology design, this paper extends its application to care robots by integrating the values of (...)
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  11. Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles.Steven Umbrello & Roman Yampolskiy - 2022 - International Journal of Social Robotics 14 (2):313-322.
    One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model (...)
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  12.  42
    The Role of AGI in Achieving Universal Balance and Overcoming Dogmatic Limitations.Angelito Malicse - manuscript
    The Role of AGI in Achieving Universal Balance and Overcoming Dogmatic Limitations -/- Introduction -/- Human civilization has long been shaped by a complex interplay of natural laws, societal structures, religious beliefs, and scientific progress. While religion has provided moral guidance and a sense of purpose, it has also been a source of dogma—rigid, unquestionable beliefs that resist scrutiny. At the same time, scientific advancements have sought to uncover objective truths, yet they often struggle to address deeper existential questions. -/- (...)
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  13. AI Ethics by Design: Implementing Customizable Guardrails for Responsible AI Development.Kristina Sekrst, Jeremy McHugh & Jonathan Rodriguez Cefalu - manuscript
    This paper explores the development of an ethical guardrail framework for AI systems, emphasizing the importance of customizable guardrails that align with diverse user values and underlying ethics. We address the challenges of AI ethics by proposing a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior, while comparing the proposed framework to the existing state-of-the-art guardrails. By focusing on practical mechanisms for implementing ethical standards, we aim to enhance transparency, user autonomy, and continuous improvement in (...)
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  14. A value sensitive design approach for designing AI-based worker assistance systems in manufacturing.Susanne Vernim, Harald Bauer, Erwin Rauch, Marianne Thejls Ziegler & Steven Umbrello - 2022 - Procedia Computer Science 200:505-516.
    Although artificial intelligence has been given an unprecedented amount of attention in both the public and academic domains in the last few years, its convergence with other transformative technologies like cloud computing, robotics, and augmented/virtual reality is predicted to exacerbate its impacts on society. The adoption and integration of these technologies within industry and manufacturing spaces is a fundamental part of what is called Industry 4.0, or the Fourth Industrial Revolution. The impacts of this paradigm shift on the human operators (...)
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  15. How to design AI for social good: seven essential factors.Luciano Floridi, Josh Cowls, Thomas C. King & Mariarosaria Taddeo - 2020 - Science and Engineering Ethics 26 (3):1771–1796.
    The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that are (...)
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  16. Maximizing team synergy in AI-related interdisciplinary groups: an interdisciplinary-by-design iterative methodology.Piercosma Bisconti, Davide Orsitto, Federica Fedorczyk, Fabio Brau, Marianna Capasso, Lorenzo De Marinis, Hüseyin Eken, Federica Merenda, Mirko Forti, Marco Pacini & Claudia Schettini - 2022 - AI and Society 1 (1):1-10.
    In this paper, we propose a methodology to maximize the benefits of interdisciplinary cooperation in AI research groups. Firstly, we build the case for the importance of interdisciplinarity in research groups as the best means to tackle the social implications brought about by AI systems, against the backdrop of the EU Commission proposal for an Artificial Intelligence Act. As we are an interdisciplinary group, we address the multi-faceted implications of the mass-scale diffusion of AI-driven technologies. The result of our exercise (...)
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  17. 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, 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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  18. Steps to Designing AI-Empowered Nanotechnology: A Value Sensitive Design Approach.Steven Umbrello - 2019 - Delphi - Interdisciplinary Review of Emerging Technologies 2 (2):79-83.
    Advanced nanotechnology promises to be one of the fundamental transformational emerging technologies alongside others such as artificial intelligence, biotechnology, and other informational and cognitive technologies. Although scholarship on nanotechnology, particularly advanced nanotechnology such as molecular manufacturing has nearly ceased in the last decade, normal nanotechnology that is building the foundations for more advanced versions has permeated many industries and commercial products and has become a billion dollar industry. This paper acknowledges the socialtechnicity of advanced nanotechnology and proposes how its convergence (...)
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  19. The Design of Curricula in the Universities: College of Humanities and Social Sciences UAEU Model.Abduljaleel Kadhim Alwali - 2008 - Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia: International Islamic University Malaysia, IIUM Press.
    This paper was chosen from ninety papers presented at (Conference on Higher Education in the Islamic world: challenges and prospects, Malaysia in 2008) to be chapter of the book “Higher education in the Islamic world: challenges and prospects” During the human history, philosophy organizes education, and the societies revert to philosophy to regulate education policy .Philosophy contributes to: suggesting education goals, provide the learning outcome, classification of topics and learning activities in educational institutions , and proposes an educational curriculum (...)
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  20. Will AI and Humanity Go to War?Simon Goldstein - manuscript
    This paper offers the first careful analysis of the possibility that AI and humanity will go to war. The paper focuses on the case of artificial general intelligence, AI with broadly human capabilities. The paper uses a bargaining model of war to apply standard causes of war to the special case of AI/human conflict. The paper argues that information failures and commitment problems are especially likely in AI/human conflict. Information failures would be driven by the difficulty of measuring AI capabilities, (...)
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  21. The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - 2020 - Minds and Machines 30 (1):99-120.
    Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...)
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  22. The future won’t be pretty: The nature and value of ugly, AI-designed experiments.Michael T. Stuart - 2023 - In Milena Ivanova & Alice Murphy, The Aesthetics of Scientific Experiments. New York, NY: Routledge.
    Can an ugly experiment be a good experiment? Philosophers have identified many beautiful experiments and explored ways in which their beauty might be connected to their epistemic value. In contrast, the present chapter seeks out (and celebrates) ugly experiments. Among the ugliest are those being designed by AI algorithms. Interestingly, in the contexts where such experiments tend to be deployed, low aesthetic value correlates with high epistemic value. In other words, ugly experiments can be good. Given this, we should conclude (...)
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  23. Meeting the Students’ Expectations: Evaluating the Implementation of English Language Teaching Curriculum.Andi Kaharuddin - 2021 - Elementary Education Online, 20 (3):165-176.
    Educational institutions are in need of increasing their high standards as an essential factor in improving the level of quality in education. Hence, they are looking at better ways to develop such a curriculum which reaches the pre-decided standards. This calls for curriculum evaluation. This study was aimed at evaluating the implementation of the 2010 Curriculum (K-10) of English Education Department at the Universitas Islam Negeri Alauddin Makassar, Indonesia. The research design adapted Stake's Countenance Model. The (...)
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  24. Curriculum Management and Graduate Programmes’ Viability: The Mediation of Institutional Effectiveness Using PLS-SEM Approach.Valentine Joseph Owan, Emmanuel E. Emanghe, Chiaka P. Denwigwe, Eno Etudor-Eyo, Abosede A. Usoro, Victor O. Ebuara, Charles Effiong, Joseph O. Ogar & Bassey A. Bassey - 2022 - Journal of Curriculum and Teaching 11 (5):114-127.
    This study used a partial least squares structural equation modelling (PLS-SEM) to estimate curriculum management's direct and indirect effects on university graduate programmes' viability. The study also examined the role of institutional effectiveness in mediating the nexus between the predictor and response variables. This is a correlational study with a factorial research design. The study's participants comprised 149 higher education administrators (23 Faculty Deans and 126 HODs) from two public universities in Nigeria. A structured questionnaire designed by the (...)
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  25. AI through the looking glass: an empirical study of structural social and ethical challenges in AI.Mark Ryan, Nina De Roo, Hao Wang, Vincent Blok & Can Atik - 2024 - AI and Society 1 (1):1-17.
    This paper examines how professionals (N = 32) working on artificial intelligence (AI) view structural AI ethics challenges like injustices and inequalities beyond individual agents' direct intention and control. This paper answers the research question: What are professionals’ perceptions of the structural challenges of AI (in the agri-food sector)? This empirical paper shows that it is essential to broaden the scope of ethics of AI beyond micro- and meso-levels. While ethics guidelines and AI ethics often focus on the responsibility of (...)
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  26. Medical AI and human dignity: Contrasting perceptions of human and artificially intelligent (AI) decision making in diagnostic and medical resource allocation contexts.Paul Formosa, Wendy Rogers, Yannick Griep, Sarah Bankins & Deborah Richards - 2022 - Computers in Human Behaviour 133.
    Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of being (...)
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  27. Why Globalize the Curriculum?Duncan Ivison - 2020 - In Melissa S. Williams, Deparochializing Political Theory. New York, NY: Cambridge University Press. pp. 273-290.
    In a world no longer centered on the West, what should political theory become? Although Western intellectual traditions continue to dominate academic journals and course syllabi in political theory, up-and-coming contributions of “comparative political theory” are rapidly transforming the field. Deparochializing Political Theory creates a space for conversation among leading scholars who differ widely in their approaches to political theory. These scholars converge on the belief that we bear a collective responsibility to engage and support the transformation of political theory. (...)
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  28. Dalla Soggettività all’Oggettività: La Filosofia di Bernard Lonergan come Fondamento per il Design Sensibile ai Valori.Steven Umbrello - 2024 - Archivio Teologico Torinese 1 (2024):161-171.
    This article explores the potential of Bernard Lonergan’s philosophy of subjectivity as objectivity as a grounding for value sensitive design (VSD) and the design turn in applied ethics. The rapid pace of scientific and technological advancement has created a gap between technical abilities and our moral assessments of those abilities, calling for a reflection on the philosophical tools we have for applying ethics. In particular, applied ethics often presents interconnected problems that require a more general framework for ethical (...)
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  29. AI Mimicry and Human Dignity: Chatbot Use as a Violation of Self-Respect.Jan-Willem van der Rijt, Dimitri Coelho Mollo & Bram Vaassen - manuscript
    This paper investigates how human interactions with AI-powered chatbots may offend human dignity. Current chatbots, driven by large language models (LLMs), mimic human linguistic behaviour but lack the moral and rational capacities essential for genuine interpersonal respect. Human beings are prone to anthropomorphise chatbots—indeed, chatbots appear to be deliberately designed to elicit that response. As a result, human beings’ behaviour toward chatbots often resembles behaviours typical of interaction between moral agents. Drawing on a second-personal, relational account of dignity, we argue (...)
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  30. Disagreement, AI alignment, and bargaining.Harry R. Lloyd - forthcoming - Philosophical Studies:1-31.
    New AI technologies have the potential to cause unintended harms in diverse domains including warfare, judicial sentencing, biomedicine and governance. One strategy for realising the benefits of AI whilst avoiding its potential dangers is to ensure that new AIs are properly ‘aligned’ with some form of ‘alignment target.’ One danger of this strategy is that – dependent on the alignment target chosen – our AIs might optimise for objectives that reflect the values only of a certain subset of society, and (...)
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  31. Ethical funding for trustworthy AI: proposals to address the responsibilities of funders to ensure that projects adhere to trustworthy AI practice.Marie Oldfield - 2021 - AI and Ethics 1 (1):1.
    AI systems that demonstrate significant bias or lower than claimed accuracy, and resulting in individual and societal harms, continue to be reported. Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles. This paper focusses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions such as AI procurement guidelines, AI impact assessments and (...)
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  32. Curriculum Restructuring and Job Creation Among Nigerian Graduates: The Mediating Role of Emerging Internet Applications.Valentine Joseph Owan, Daniel Clement Agurokpon & Joseph Udida Udida - 2021 - International Journal of Educational Administration, Planning and Research 13 (2):1-16.
    Existing literature on entrepreneurship education has continually highlighted its potential for job creation. However, much attention has not been paid to the restructuring of the curriculum that can enable entrepreneurship education to thrive for job creation. This study used a structural equation modelling approach to understand the mediating role that the deployment of emerging Internet Applications (IAs) play in the nexus between curriculum restructuring and job creation. Being a quantitative study, a virtual snowball sample of 4,628 higher education (...)
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  33. The AI-Stance: Crossing the Terra Incognita of Human-Machine Interactions?Anna Strasser & Michael Wilby - 2022 - In Raul Hakli, Pekka Mäkelä & Johanna Seibt, Social Robots in Social Institutions. Proceedings of Robophilosophy’22. IOS Press. pp. 286-295.
    Although even very advanced artificial systems do not meet the demanding conditions which are required for humans to be a proper participant in a social interaction, we argue that not all human-machine interactions (HMIs) can appropriately be reduced to mere tool-use. By criticizing the far too demanding conditions of standard construals of intentional agency we suggest a minimal approach that ascribes minimal agency to some artificial systems resulting in the proposal of taking minimal joint actions as a case of a (...)
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  34. Decolonial AI as Disenclosure.Warmhold Jan Thomas Mollema - 2024 - Open Journal of Social Sciences 12 (2):574-603.
    The development and deployment of machine learning and artificial intelligence (AI) engender “AI colonialism”, a term that conceptually overlaps with “data colonialism”, as a form of injustice. AI colonialism is in need of decolonization for three reasons. Politically, because it enforces digital capitalism’s hegemony. Ecologically, as it negatively impacts the environment and intensifies the extraction of natural resources and consumption of energy. Epistemically, since the social systems within which AI is embedded reinforce Western universalism by imposing Western colonial values on (...)
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  35. AI-Driven Strategic Insights: Enhancing Decision-Making Processes in Business Development.Mohaimenul Islam Jowarder Rafiul Azim Jowarder - 2024 - International Journal of Innovative Research in Science, Engineering and Technology 14 (1):99-116.
    This research explores the transformative role of artificial intelligence (AI) in strategic decision-making and business development, highlighting its capacity to enhance strategy execution, optimize operations, and foster innovation through advanced methodologies such as machine learning, predictive analytics, and natural language processing. By employing a mixed-methods approach that combines deductive and inductive research designs, crosssectional case analysis, and a review of empirical literature, the study underscores AI’s critical role in delivering datadriven insights, accurate forecasting, and robust simulations, positioning it as a (...)
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  36. AI systems must not confuse users about their sentience or moral status.Eric Schwitzgebel - 2023 - Patterns 4.
    One relatively neglected challenge in ethical artificial intelligence (AI) design is ensuring that AI systems invite a degree of emotional and moral concern appropriate to their moral standing. Although experts generally agree that current AI chatbots are not sentient to any meaningful degree, these systems can already provoke substantial attachment and sometimes intense emotional responses in users. Furthermore, rapid advances in AI technology could soon create AIs of plausibly debatable sentience and moral standing, at least by some relevant definitions. (...)
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  37. EI & AI In Leadership and How It Can Affect Future Leaders.Ramakrishnan Vivek & Oleksandr P. Krupskyi - 2024 - European Journal of Management Issues 32 (3):174-182.
    Purpose: The aim of this study is to examine how the integration of Emotional Intelligence (EI) and Artificial Intelligence (AI) in leadership can enhance leadership effectiveness and influence the development of future leaders. -/- Design / Method / Approach: The research employs a mixed-methods approach, combining qualitative and quantitative analyses. The study utilizes secondary data sources, including scholarly articles, industry reports, and empirical studies, to analyze the interaction between EI and AI in leadership settings. -/- Findings: The findings reveal (...)
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  38. Contextual Vocabulary Acquisition: from Algorithm to Curriculum.Michael W. Kibby & William J. Rapaport - 2014 - In Michael W. Kibby & William J. Rapaport, Contextual Vocabulary Acquisition: from Algorithm to Curriculum. pp. 107-150.
    Deliberate contextual vocabulary acquisition (CVA) is a reader’s ability to figure out a (not the) meaning for an unknown word from its “context”, without external sources of help such as dictionaries or people. The appropriate context for such CVA is the “belief-revised integration” of the reader’s prior knowledge with the reader’s “internalization” of the text. We discuss unwarranted assumptions behind some classic objections to CVA, and present and defend a computational theory of CVA that we have adapted to a new (...)
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  39. Values in science and AI alignment research.Leonard Dung - manuscript
    Roughly, empirical AI alignment research (AIA) is an area of AI research which investigates empirically how to design AI systems in line with human goals. This paper examines the role of non-epistemic values in AIA. It argues that: (1) Sciences differ in the degree to which values influence them. (2) AIA is strongly value-laden. (3) This influence of values is managed inappropriately and thus threatens AIA’s epistemic integrity and ethical beneficence. (4) AIA should strive to achieve value transparency, critical (...)
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  40.  36
    AI Healthcare ChatBot_ using Machine Learning (13th edition).Brahmtej B. Bargali Akash S. Shinde, - 2024 - International Journal of Innovative Research in Science, Engineering and Technology 13 (12):20832-20837. Translated by Akash S Shinde.
    The rapid advancement of artificial intelligence (AI) and machine learning (ML) has led to significant innovations in the healthcare sector. One such development is AI-powered healthcare chatbots, which assist patients and medical professionals by providing medical guidance, symptom assessment, and appointment scheduling. This paper presents the design and implementation of an AI healthcare chatbot using machine learning techniques. The chatbot leverages natural language processing (NLP) and deep learning models to understand and respond to user queries effectively. Experimental results demonstrate (...)
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  41. Writing Across the Curriculum Report: Close Reading Pilot Project (2011).Gregory Sadler - manuscript
    Report submitted by Gregory B. Sadler, Pilot Project Coordinator to Sonya Brown, WAC Activity Director, Fayetteville State University, June 28 2011. -/- A Pilot program focused on improving student performance in carrying out Close Readings in humanities-based discipline courses was developed and implemented under the auspices of Writing Across the Curriculum and Title III at Fayetteville State University in Winter and Spring 2011. Five faculty were involved in the Pilot, myself as the coordinator, and four other faculty from four (...)
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  42. Collective ownership of AI.Markus Furendal - 2025 - In Martin Hähnel & Regina Müller, A Companion to Applied Philosophy of AI. Wiley-Blackwell.
    AI technology promises to be both the most socially important and the most profitable technology of a generation. At the same time, the control over – and profits from – the technology is highly concentrated to a handful of large tech companies. This chapter discusses whether bringing AI technology under collective ownership and control is an attractive way of counteracting this development. It discusses justice-based rationales for collective ownership, such as the claim that, since the training of AI systems relies (...)
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  43. AI-powered Legal Documentation Assistant.G. Kiran Kumar - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (1):1-13.
    This project focuses on simplifying the legal documentation process for small businessesand individuals in India. Utilizing advanced technologies such as Optical Character Recognition (OCR) and AI-driven models, the system automatically drafts and simplifies complex legaldocuments. The platform features a user-friendly interface for easy input, integration withup-to-date legal resources, and ensures strict data privacy and security. By reducing the time, effort, and potential errors associated with legal documentation, the assistant aims to improve accessibility to legal services and promotegreater access to justice. (...)
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  44. AI Can Help Us Live More Deliberately.Julian Friedland - 2019 - MIT Sloan Management Review 60 (4).
    Our rapidly increasing reliance on frictionless AI interactions may increase cognitive and emotional distance, thereby letting our adaptive resilience slacken and our ethical virtues atrophy from disuse. Many trends already well underway involve the offloading of cognitive, emotional, and ethical labor to AI software in myriad social, civil, personal, and professional contexts. Gradually, we may lose the inclination and capacity to engage in critically reflective thought, making us more cognitively and emotionally vulnerable and thus more anxious and prone to manipulation (...)
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  45. Decentralized Governance of AI Agents.Tomer Jordi Chaffer, Charles von Goins Ii, Bayo Okusanya, Dontrail Cotlage & Justin Goldston - manuscript
    Autonomous AI agents present transformative opportunities and significant governance challenges. Existing frameworks, such as the EU AI Act and the NIST AI Risk Management Framework, fall short of addressing the complexities of these agents, which are capable of independent decision-making, learning, and adaptation. To bridge these gaps, we propose the ETHOS (Ethical Technology and Holistic Oversight System) framework—a decentralized governance (DeGov) model leveraging Web3 technologies, including blockchain, smart contracts, and decentralized autonomous organizations (DAOs). ETHOS establishes a global registry for AI (...)
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  46.  18
    Advanced AI Algorithms for Automating Data Preprocessing in Healthcare: Optimizing Data Quality and Reducing Processing Time.Muthukrishnan Muthusubramanian Praveen Sivathapandi, Prabhu Krishnaswamy - 2022 - Journal of Science and Technology (Jst) 3 (4):126-167.
    This research paper presents an in-depth analysis of advanced artificial intelligence (AI) algorithms designed to automate data preprocessing in the healthcare sector. The automation of data preprocessing is crucial due to the overwhelming volume, diversity, and complexity of healthcare data, which includes medical records, diagnostic imaging, sensor data from medical devices, genomic data, and other heterogeneous sources. These datasets often exhibit various inconsistencies such as missing values, noise, outliers, and redundant or irrelevant information that necessitate extensive preprocessing before being analyzed (...)
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  47. The virtues of interpretable medical AI.Joshua Hatherley, Robert Sparrow & Mark Howard - 2024 - Cambridge Quarterly of Healthcare Ethics 33 (3):323-332.
    Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are 'black boxes'. The initial response in the literature was a demand for 'explainable AI'. However, recently, several authors have suggested that making AI more explainable or 'interpretable' is likely to be at the cost of the accuracy of these systems and that prioritising interpretability in medical AI may constitute a 'lethal prejudice'. In this paper, we defend the value of interpretability (...)
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  48.  58
    Design for operator contestability: control over autonomous systems by introducing defeaters.Herman Veluwenkamp & Stefan Buijsman - 2025 - AI and Ethics 1.
    This paper introduces the concept of Operator Contestability in AI systems: the principle that those overseeing AI systems (operators) must have the necessary control to be accountable for the decisions made by these algorithms. We argue that designers have a duty to ensure operator contestability. We demonstrate how this duty can be fulfilled by applying the'Design for Defeaters' framework, which provides strategies to embed tools within AI systems that enable operators to challenge decisions. Defeaters are designed to contest either (...)
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  49.  93
    AI-Optimized Urban Green Spaces: Enhancing Biodiversity and Sustainability in Smart Cities.Eric Garcia - manuscript
    Urban green spaces are vital for mitigating climate change, enhancing biodiversity, and improving citizen well-being. However, traditional methods of designing and managing these spaces often lack the precision and scalability needed to address modern urban challenges. This paper explores how Artificial Intelligence (AI) and IoT technologies can optimize urban green spaces in smart cities. By integrating satellite imagery, soil sensors, and machine learning models, cities can dynamically monitor plant health, predict ecological impacts, and design green zones that maximize biodiversity (...)
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  50. A Robust Governance for the AI Act: AI Office, AI Board, Scientific Panel, and National Authorities.Claudio Novelli, Philipp Hacker, Jessica Morley, Jarle Trondal & Luciano Floridi - 2024 - European Journal of Risk Regulation 4:1-25.
    Regulation is nothing without enforcement. This particularly holds for the dynamic field of emerging technologies. Hence, this article has two ambitions. First, it explains how the EU´s new Artificial Intelligence Act (AIA) will be implemented and enforced by various institutional bodies, thus clarifying the governance framework of the AIA. Second, it proposes a normative model of governance, providing recommendations to ensure uniform and coordinated execution of the AIA and the fulfilment of the legislation. Taken together, the article explores how the (...)
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