Results for 'Intelligent decision-support systems'

976 found
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  1. The impact of intelligent decision-support systems on humans’ ethical decision-making: A systematic literature review and an integrated framework.Franziska Poszler & Benjamin Lange - forthcoming - Technological Forecasting and Social Change.
    With the rise and public accessibility of AI-enabled decision-support systems, individuals outsource increasingly more of their decisions, even those that carry ethical dimensions. Considering this trend, scholars have highlighted that uncritical deference to these systems would be problematic and consequently called for investigations of the impact of pertinent technology on humans’ ethical decision-making. To this end, this article conducts a systematic review of existing scholarship and derives an integrated framework that demonstrates how intelligent (...)-support systems (IDSSs) shape humans’ ethical decision-making. In particular, we identify resulting consequences on an individual level (i.e., deliberation enhancement, motivation enhancement, autonomy enhancement and action enhancement) and on a societal level (i.e., moral deskilling, restricted moral progress and moral responsibility gaps). We carve out two distinct methods/operation types (i.e., processoriented and outcome-oriented navigation) that decision-support systems can deploy and postulate that these determine to what extent the previously stated consequences materialize. Overall, this study holds important theoretical and practical implications by establishing clarity in the conceptions, underlying mechanisms and (directions of) influences that can be expected when using particular IDSSs for ethical decisions. (shrink)
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  2. Decision support systems and its role in developing the universities strategic management: Islamic university in Gaza as a case study.Mazen J. Al Shobaki & Samy S. Abu Naser - 2016 - International Journal of Advanced Research and Development 1 (10):33-47.
    This paper aims to identify the decision support systems and their role on the strategic management development in the Universities- Case Study: Islamic University of Gaza. The descriptive approach was used where a questionnaire was developed and distributed to a stratified random sample. (230) questionnaires were distributed and (204) were returned with response rate (88.7%). The most important findings of the study: The presence of a statistically significant positive correlation between the decision support systems (...)
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  3. Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
    Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of (...)
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  4. Decision Support Systems and Their Impact on the Development of the Organizational Structure in Palestinian Higher Education Institutions.Al Shobaki Mazen J. - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (7):1-22.
    The aim of the research is to identify decision support systems and their impact on the development of the organizational structure in Palestinian higher education institutions. The research was applied to four Palestinian universities (Al-Aqsa University, the Islamic University, Al-Azhar University, the University of Palestine), and a sample of academics with an administrative position. The analytical descriptive approach was used and secondary data was obtained through a survey list distributed to the research community of academics in an (...)
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  5. Artificial Intelligence and Organizational Evolution: Reshaping Workflows in the Modern Era.Ahmed S. Sabah, Ahmed A. Hamouda, Yasmeen Emad Helles, Sami M. Okasha, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Pedagogical Research (IJAPR) 8 (9):16-19.
    Abstract: Artificial Intelligence (AI) is transforming organizational dynamics by reshaping both structures and processes. This paper examines how AI-driven innovations are redefining organizational frameworks, ranging from shifts in hierarchical models to the adoption of decentralized decision-making. It explores AI's impact on key processes, including workflow automation, data analysis, and decision support systems. Through case studies and empirical research, the paper illustrates the advantages of AI in enhancing efficiency, driving innovation, and fostering agility within organizations. Additionally, it (...)
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  6. Enhancing the use of Decision Support Systems for Re-engineering of Operations and Business- Applied Study on the Palestinian Universities.Samy S. Abu Naser & Mazen J. Al Shobaki - 2016 - Journal of Multidisciplinary Engineering Science Studies 2 (5):505--512.
    This research aims to identify the use of decision support systems as an entry point for operations of re-engineering in the Palestinian universities in Gaza Strip. The researchers used the method of questionnaire to collect data, and the researchers used a sample stratified random way, were (350) questionnaire distributed on the research sample and (312) questionnaire were collected back (89.1%). The study results showed that the most important ones are: there exists statistically significant impact at the level (...)
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  7. The relationship between the decision support systems and re-engineering in the Palestinian universities in Gaza Strip.Mazen J. Al Shobaki, Samy S. Abu Naser & Ramez A. Bedair - 2010 - Dissertation, Al-Azhar University, Gaza
    The aim of this study is to explore the relationship between the decision support systems and re-engineering in the Palestinian universities in Gaza Strip. A descriptive approach was used where a questionnaire was developed and distributed to a stratified random Sample. (500) questionnaires were distributed and (449) were returned, response rate (89.8%). The study reached many results such as: There is A statistically significant relationship at a significant level (α ≤ 0.04) between the decision support (...)
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  8. Rule by Automation: How Automated Decision Systems Promote Freedom and Equality.Athmeya Jayaram & Jacob Sparks - 2022 - Moral Philosophy and Politics 9 (2):201-218.
    Using automated systems to avoid the need for human discretion in government contexts – a scenario we call ‘rule by automation’ – can help us achieve the ideal of a free and equal society. Drawing on relational theories of freedom and equality, we explain how rule by automation is a more complete realization of the rule of law and why thinkers in these traditions have strong reasons to support it. Relational theories are based on the absence of human (...)
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  9. AI-Driven Organizational Change: Transforming Structures and Processes in the Modern Workplace.Mohammed Elkahlout, Mohammed B. Karaja, Abeer A. Elsharif, Ibtesam M. Dheir, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (8):38-45.
    Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the (...)
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  10. A Proposed Expert System for Diagnosis of Migraine.Malak S. Hammad, Raja E. N. Altarazi, Rawan N. Al Banna, Dina F. Al Borno & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (6):1-8.
    Migraine is a complex neurological disorder characterized by recurrent moderate to severe headaches, accompanied by additional symptoms such as nausea, sensitivity to light and sound, and visual disturbances. Accurate and timely diagnosis of migraines is crucial for effective management and treatment. However, the diverse range of symptoms and overlapping characteristics with other headache disorders pose challenges in the diagnostic process. In this research, we propose the development of an expert system for migraine diagnosis using artificial intelligence and the CLIPS (C (...)
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  11. What decision theory provides the best procedure for identifying the best action available to a given artificially intelligent system?Samuel A. Barnett - 2018 - Dissertation, University of Oxford
    Decision theory has had a long-standing history in the behavioural and social sciences as a tool for constructing good approximations of human behaviour. Yet as artificially intelligent systems (AIs) grow in intellectual capacity and eventually outpace humans, decision theory becomes evermore important as a model of AI behaviour. What sort of decision procedure might an AI employ? In this work, I propose that policy-based causal decision theory (PCDT), which places a primacy on the (...)-relevance of predictors and simulations of agent behaviour, may be such a procedure. I compare this account to the recently-developed functional decision theory (FDT), which is motivated by similar concerns. I also address potentially counterintuitive features of PCDT, such as its refusal to condition on observations made at certain times. (shrink)
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  12. The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems.Kathleen Creel & Deborah Hellman - 2022 - Canadian Journal of Philosophy 52 (1):26-43.
    This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to explain (...)
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  13. The Ethical Gravity Thesis: Marrian Levels and the Persistence of Bias in Automated Decision-making Systems.Atoosa Kasirzadeh & Colin Klein - 2021 - Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES '21).
    Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not (...)
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  14. A multi-INT semantic reasoning framework for intelligence analysis support.Janssen Terry, Basik Herbert, Dean Mike & Barry Smith - 2010 - In L. Obrst, Janssen Terry & W. Ceusters (eds.), Ontologies and Semantic Technologies for the Intelligence Community. Amsterdam, The Netherlands: IOS Press. pp. 57-69.
    Lockheed Martin Corp. has funded research to generate a framework and methodology for developing semantic reasoning applications to support the discipline oflntelligence Analysis. This chapter outlines that framework, discusses how it may be used to advance the information sharing and integrated analytic needs of the Intelligence Community, and suggests a system I software architecture for such applications.
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  15. Intelligent Neurtosophic Diagnostic System for Cardiotcography data.Belal Amin, A. A. Salama, Mona G. Gafar & Khaled Mahfouz, - 2021 - Computational Intelligence and Neuroscience 2021:15-21.
    Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Constructing good and efficient classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. *e proposed neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural networks but also to achieve a better performance than the (...)
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  16. Decisions and the Evolution of Memory: Multiple Systems, Multiple Functions.Stan Klein, Leda Cosmides, John Tooby & Sarah Chance - 2002 - Psychological Review 109:306-329.
    Memory evolved to supply useful, timely information to the organism’s decision-making systems. Therefore, decision rules, multiple memory systems, and the search engines that link them should have coevolved to mesh in a coadapted, functionally interlocking way. This adaptationist perspective suggested the scope hypothesis: When a generalization is retrieved from semantic memory, episodic memories that are inconsistent with it should be retrieved in tandem to place boundary conditions on the scope of the generalization. Using a priming paradigm (...)
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  17. CSS-Tutor: An Intelligent Tutoring System for CSS and HTML.Mariam W. Alawar & Samy S. Abu Naser - 2017 - International Journal of Academic Research and Development 2 (1):94-99.
    In this paper we show how a student can learn the basics of the system databases using (W3school CSS) which was built as intelligent tutoring educational system by using the authoring tool called (ITSB). The learning material contains CSS and HTML. We divided the material in a group of lessons for novice learner which combines relational system and lessons in the process of learning. The student can learn using example of CSS, and types of CSS color. Furthermore, the (...) tutoring system supports not only lessons; but exercises of different difficult levels for each lesson. When a student finish successfully the first difficulty level in a lesson, the student is allowed to move to the next difficulty level of the exercises of the lesson. (shrink)
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  18. Usage Degree of the Capabilities of DSS in Al-Aqsa University of Gaza.Mazen J. Al-Shobaki & Samy S. Abu-Naser - 2017 - International Journal of Engineering and Information Systems (IJEAIS) 1 (2):33-47.
    Abstract— This study aimed to identify the degree of use of the capabilities of decision-support systems in Palestinian institutions higher education, Aqsa University in Gaza - a case study. The study used a analytical descriptive approach, and the researchers used the of questionnaire tool to collect the data, the researchers using stratified random sample distributed (150) questioners to the study population and (126) was obtained back with rate of 84%. The study showed that the most important results (...)
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  19. Supporting human autonomy in AI systems.Rafael Calvo, Dorian Peters, Karina Vold & Richard M. Ryan - 2020 - In Christopher Burr & Luciano Floridi (eds.), Ethics of digital well-being: a multidisciplinary approach. Springer.
    Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of digital experiences are (...)
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  20.  73
    Intelligent Driver Drowsiness Detection System Using Optimized Machine Learning Models.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):397-405.
    : Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as (...)
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  21. Leveraging Artificial Intelligence for Strategic Business Decision-Making: Opportunities and Challenges.Mohammed Hazem M. Hamadaqa, Mohammad Alnajjar, Mohammed N. Ayyad, Mohammed A. Al-Nakhal, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):16-23.
    Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in (...)
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  22. (1 other version)Ethics-based auditing to develop trustworthy AI.Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines 31 (2):323–327.
    A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, (...)
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  23. أثر الأبعاد الإدارية لأنظمة مساندة القرارات في إعادة هندسة النظم للجامعات الفلسطينية بقطاع غزة من وجهه نظر العاملين فيها.Al Shobaki Mazen J. - 2017 - Arab Journal for Quality Assurance in Higher Education 10:155-175.
    the paper aimed to identify the impact of the dimensions of the administrative decision support systems on the re-engineering of the systems of the Palestinian universities in Gaza Strip from the standpoint of employees. A descriptive approach was used through which a questionnaire was developed and distributed to a stratified random sample. (500) questionnaires were distributed and (449) were returned, with (89.8 %) response rate.
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  24. Development and Evaluation of the Oracle Intelligent Tutoring System (OITS).Rami Aldahdooh & Samy S. Abu Naser - 2017 - European Academic Research 4 (10).
    This paper presents the design and development of intelligent tutoring system for teaching Oracle. The Oracle Intelligent Tutoring System (OITS) examined the power of a new methodology to supporting students in Oracle programming. The system presents the topic of Introduction to Oracle with automatically generated problems for the students to solve. The system is dynamically adapted at run time to the student’s individual progress. An initial evaluation study was done to investigate the effect of using the intelligent (...)
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  25. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on (...)
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  26. Trusting in others’ biases: Fostering guarded trust in collaborative filtering and recommender systems.Jo Ann Oravec - 2004 - Knowledge, Technology & Policy 17 (3):106-123.
    Collaborative filtering is being used within organizations and in community contexts for knowledge management and decision support as well as the facilitation of interactions among individuals. This article analyzes rhetorical and technical efforts to establish trust in the constructions of individual opinions, reputations, and tastes provided by these systems. These initiatives have some important parallels with early efforts to support quantitative opinion polling and construct the notion of “public opinion.” The article explores specific ways to increase (...)
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  27. Design and Development of an Intelligent Tutoring System for C# Language.Bashar G. Al-Bastami & Samy S. Abu Naser - 2017 - European Academic Research 4 (10).
    Learning programming is thought to be troublesome. One doable reason why students don’t do well in programming is expounded to the very fact that traditional way of learning within the lecture hall adds more stress on students in understanding the Material rather than applying the Material to a true application. For a few students, this teaching model might not catch their interest. As a result, they'll not offer their best effort to grasp the Material given. Seeing however the information is (...)
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  28. The paradox of the artificial intelligence system development process: the use case of corporate wellness programs using smart wearables.Alessandra Angelucci, Ziyue Li, Niya Stoimenova & Stefano Canali - forthcoming - AI and Society:1-11.
    Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will (...)
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  29. What we owe to decision-subjects: beyond transparency and explanation in automated decision-making.David Gray Grant, Jeff Behrends & John Basl - 2023 - Philosophical Studies 2003:1-31.
    The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to (...)
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  30. Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - International Data Privacy Law 1 (2):76-99.
    Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In (...)
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  31. 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 (...)
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  32. Smart Walking System based on Artificial Intelligence.Vanita Babanne, Simranjeet Kaur, Tejal Mehta, Divya Mulay & Rachana Nagarkar - 2018 - International Journal of Research in Engineering, Science and Management 1 (12).
    This paper shows the smart walking stick based on ultrasonic sensors and Arduino for outwardly debilitated individuals. There are roughly 37 million individuals over the globe who are visually impaired as indicated by the World Health Organization. Individuals with visual inabilities are regularly subjected to outer help which can be given by people, trained dogs, or electronic gadgets as supportive networks for basic assistance. Thus, this played as the motivation to develop a smart cane white stick to survive these restrictions (...)
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  33. For a Pluralism of Climate Modelling Strategies.Baldissera Pacchetti Marina, Julie Jebeile & Erica Thompson - 2024 - Bulletin of the American Meteorological Society.
    The continued development of General Circulation Models (GCMs) towards increasing resolution and complexity is a predominantly chosen strategy to advance climate science, resulting in channelling of research and funding to meet this aspiration. Yet many other modelling strategies have also been developed and can be used to understand past and present climates, to project future climates and ultimately to support decision-making. We argue that a plurality of climate modelling strategies and an equitable distribution of funding among them would (...)
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  34. The Requirements of Computerized Management Information Systems and Their Role in Improving the Quality of Administrative Decisions in the Palestinian Ministry of Education and Higher Education.Mazen J. Al Shobaki & Samy S. Abu-Naser - 2017 - International Journal of Information Technology and Electrical Engineering 6 (6):7-35.
    The purpose of this study is to identify the requirements of computerized Management Information Systems and their role in improving the quality of administrative decisions in the Palestinian Ministry of Education and Higher Education. The authors used the descriptive analytical method and the questionnaire method to collect the data. (247) questionnaires were distributed on the study sample and (175) questionnaires were collected back with a recovery rate of (70.8). The study showed a number of results, the most important of (...)
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  35. Algorithms and Autonomy: The Ethics of Automated Decision Systems.Alan Rubel, Clinton Castro & Adam Pham - 2021 - Cambridge University Press.
    Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. Using these (...)
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  36.  47
    The Comprehensive Human Decision-Making Equation and Holistic Free Will.Juan Chavez - manuscript
    The Comprehensive Human Decision-Making Equation presents a robust model for understanding Holistic Free Will (HFW), conceptualizing decision-making as an autonomous, non-deterministic process within a complex network of influences. This model addresses the Infinite Regress issue by portraying free will as an emergent property of interacting layers, including internal beliefs, external contexts, emotional responses, cognitive biases, and habitual tendencies. Departing from traditional linear models, the equation adopts a systemic framework where each choice reflects a cumulative utility, integrating multiple components (...)
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  37. Command and Control Ontology.Andreas Tolk & Barry Smith - 2011 - International Journal of Intelligent Defence Support Systems (Special Issue) 4 (3).
    Intelligent defence support systems are confronted with the need to manage ever-increasing floods of data in a way that raises significant challenges because the data are described and presented using different terminologies and formats. How, on this basis, is it possible to reach a common understanding of the information content of these data among people and software agents? How is it possible to ensure that domain knowledge is reused in consistent fashion in a way that makes this (...)
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  38. Preparing undergraduates for visual analytics.Ronald A. Rensink - 2015 - IEEE Computer Graphics and Applications 35 (2):16-20.
    Visual analytics (VA) combines the strengths of human and machine intelligence to enable the discovery of interesting patterns in challenging datasets. Historically, most attention has been given to developing the machine component—for example, machine learning or the human-computer interface. However, it is also essential to develop the abilities of the analysts themselves, especially at the beginning of their careers. -/- For the past several years, we at the University of British Columbia (UBC)—with the support of The Boeing Company—have experimented (...)
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  39. Toward Modeling and Automating Ethical Decision Making: Design, Implementation, Limitations, and Responsibilities.Gregory S. Reed & Nicholaos Jones - 2013 - Topoi 32 (2):237-250.
    One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a (...)
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  40. Plato’s Metaphysical Development before Middle Period Dialogues.Mohammad Bagher Ghomi - manuscript
    Regarding the relation of Plato’s early and middle period dialogues, scholars have been divided to two opposing groups: unitarists and developmentalists. While developmentalists try to prove that there are some noticeable and even fundamental differences between Plato’s early and middle period dialogues, the unitarists assert that there is no essential difference in there. The main goal of this article is to suggest that some of Plato’s ontological as well as epistemological principles change, both radically and fundamentally, between the early and (...)
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  41. Enhanced Artificial Intelligence System for Diagnosing and Predicting Breast Cancer Using Deep Learning.Mona Alfifi, Mohamad Shady Alrahhal, Samir Bataineh & Mohammad Mezher - 2020 - International Journal of Advanced Computer Science and Applications 11 (7):1-17.
    Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional (...)
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  42. Intelligent Plagiarism Detection for Electronic Documents.Mohran H. J. Al-Bayed - 2017 - Dissertation, Al-Azhar University, Gaza
    Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will be done with (...)
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  43. Management of socio-economic transformations of business processes: current realities, global challenges, forecast scenarios and development prospects.Maksym Bezpartochnyi, Igor Britchenko & Olesia Bezpartochna - 2023 - Sofia: Professor Marin Drinov Publishing House of Bulgarian Academy of Sciences.
    The authors of the scientific monograph have come to the conclusion that мanagement of socio-economic transformations of business processes requires the use of mechanisms to support of entrepreneurship, sectors of the national economy, the financial system, and critical infrastructure. Basic research focuses on assessment the state of social service provision, analysing economic security, implementing innovation and introducing digital technologies. The research results have been implemented in the different models of costing, credit risk and capital management, tax control, use of (...)
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  44.  85
    Artificial Intelligence and Universal Values.Jay Friedenberg - 2024 - UK: Ethics Press.
    The field of value alignment, or more broadly machine ethics, is becoming increasingly important as artificial intelligence developments accelerate. By ‘alignment’ we mean giving a generally intelligent software system the capability to act in ways that are beneficial, or at least minimally harmful, to humans. There are a large number of techniques that are being experimented with, but this work often fails to specify what values exactly we should be aligning. When making a decision, an agent is supposed (...)
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  45. Explainable AI lacks regulative reasons: why AI and human decision‑making are not equally opaque.Uwe Peters - forthcoming - AI and Ethics.
    Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. (...)
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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 (...)
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  47. Ontological Support for Living Plan Specification, Execution and Evaluation.Erik Thomsen, Fred Read, William Duncan, Tatiana Malyuta & Barry Smith - 2014 - In Erik Thomsen, Fred Read, William Duncan, Tatiana Malyuta & Barry Smith (eds.), Semantic Technology in Intelligence, Defense and Security (STIDS), CEUR vol. 1304. pp. 10-17.
    Maintaining systems of military plans is critical for military effectiveness, but is also challenging. Plans will become obsolete as the world diverges from the assumptions on which they rest. If too many ad hoc changes are made to intermeshed plans, the ensemble may no longer lead to well-synchronized and coordinated operations, resulting in the system of plans becoming itself incoherent. We describe in what follows an Adaptive Planning process that we are developing on behalf of the Air Force Research (...)
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  48. Shared decision-making and maternity care in the deep learning age: Acknowledging and overcoming inherited defeaters.Keith Begley, Cecily Begley & Valerie Smith - 2021 - Journal of Evaluation in Clinical Practice 27 (3):497–503.
    In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in (...)
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  49. A hybrid Automated Intelligent COVID-19 Classification System Based on Neutrosophic Logic and Machine Learning Techniques Using Chest X-ray Images.Ibrahim Yasser, Aya A. Abd El-Khalek, A. A. Salama, Abeer Twakol, Mohy-Eldin Abo-Elsoud & Fahmi Khalifa - forthcoming - In Ibrahim Yasser, Aya A. Abd El-Khalek, A. A. Salama, Abeer Twakol, Mohy-Eldin Abo-Elsoud & Fahmi Khalifa (eds.), Advances in Data Science and Intelligent Data Communication Technologies for COVID-19 Pandemic (DSIDC-COVID-19) ,Studies in Systems, Decision and Control.
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  50.  93
    A Proposed Taxonomy for the Evolutionary Stages of Artificial Intelligence: Towards a Periodisation of the Machine Intellect Era.Demetrius Floudas - manuscript
    As artificial intelligence (AI) systems continue their rapid advancement, a framework for contextualising the major transitional phases in the development of machine intellect becomes increasingly vital. This paper proposes a novel chronological classification scheme to characterise the key temporal stages in AI evolution. The Prenoëtic era, spanning all of history prior to the year 2020, is defined as the preliminary phase before substantive artificial intellect manifestations. The Protonoëtic period, which humanity has recently entered, denotes the initial emergence of advanced (...)
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