This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.

Recommender systems have become essential in modern entertainment platforms, aiding users in discovering movies and TV shows tailored to their preferences. Traditional movie recommendation systems often rely on collaborative filtering or content-based methods. However, supervised learning offers an alternative approach by learning from labeled data, leveraging classification or regression models to predict user preferences. In this paper, we explore the implementation of a movie recommender system using supervised learning techniques, such as decision trees, random forests, and (...) support vector machines. We discuss the dataset used, feature extraction techniques, model training, and evaluation metrics. The proposed system predicts user ratings and recommends movies based on historical data, user features, and movie characteristics. We demonstrate how supervised learning models can outperform traditional methods by integrating both user and item data in a structured manner. (shrink)

In recent years, the integration of machine learning (ML) into healthcare has opened new frontiers in disease diagnosis and personalized medicine. This project presents a dual-purpose system that leverages machine learning algorithms for disease prediction and drug recommendation based on patient symptoms and medical history. The system is designed to analyze user inputs such as symptoms, demographic information, and prior medical conditions and predict the most probable disease using classification algorithms like Decision Trees, Random Forest, and Support Vector Machines. Following (...) the disease prediction, the system intelligently recommends appropriate drugs by analyzing historical treatment data and drug effectiveness. Collaborative filtering and content based filtering techniques are employed to build a robust drug recommendation engine. The model is trained and validated on publicly available datasets (e.g., Disease-Symptom and Drug-Disease datasets) to ensure accuracy and relevance. (shrink)

This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Following the most common approach in the literature, we assume a consequentialist framework to introduce the main concepts of multistakeholder recommendation. We then consider three research questions: who are the stakeholders in a RS? How are their interests taken into account when formulating a recommendation? And, what is the scientific paradigm underlying RSs? Our main finding is that multistakeholder RSs (MRSs) are designed and theorised, methodologically, according to neoclassical (...) welfare economics. We consider and reply to some methodological objections to MRSs on this basis, concluding that the multistakeholder approach offers the resources to understand the normative social dimension of RSs. (shrink)

YouTube has been implicated in the transformation of users into extremists and conspiracy theorists. The alleged mechanism for this radicalizing process is YouTube’s recommender system, which is optimized to amplify and promote clips that users are likely to watch through to the end. YouTube optimizes for watch-through for economic reasons: people who watch a video through to the end are likely to then watch the next recommended video as well, which means that more advertisements can be served to them. (...) This is a seemingly innocuous design choice, but it has a troubling side-effect. Critics of YouTube have alleged that the recommender system tends to recommend extremist content and conspiracy theories, as such videos are especially likely to capture and keep users’ attention. To date, the problem of radicalization via the YouTube recommender system has been a matter of speculation. The current study represents the first systematic, pre-registered attempt to establish whether and to what extent the recommender system tends to promote such content. We begin by contextualizing our study in the framework of technological seduction. Next, we explain our methodology. After that, we present our results, which are consistent with the radicalization hypothesis. Finally, we discuss our findings, as well as directions for future research and recommendations for users, industry, and policy-makers. (shrink)

E-commerce platforms increasingly leverage machine learning to enhance user experience through personalized product recommendations. While traditional static systems often fail to adapt to changing user behavior, machine learning models can dynamically analyze user interactions, purchase history, and browsing patterns to deliver tailored suggestions. This project implements collaborative filtering, content-based filtering, and hybrid recommendation models to generate accurate and relevant product recommendations. The system is designed to improve customer engagement, boost sales, and enhance overall user satisfaction. The ultimate goal is (...) to develop an intelligent recommendation engine capable of understanding individual user preferences and providing real-time, context-aware product suggestions. (shrink)

With advanced NLP, AI has transformed how software specifications and validation are made. Ambiguity, inconsistency, and inefficiency are the enemies of most traditional methods, causing delays and unneeded project expenses. These issues are resolved in AI by automatically extracting, validating, prioritizing, and classifying requirements from documents. NLP helps AI understand unstructured texts to simplify communication, avoid errors, and match requirements with business goals and regulatory standards. It further allows organizations to predict changes and optimize their resources. Integrating AI in DevOps (...) and agile production environments reduces the software development lifecycle by providing real-time documentation updates, offering true automation of risk assessments, and even facilitating the process of negotiation of requirements through intelligent methods. Of course, AI chatbots and virtual assistants also help developers, project managers, and clients interact without any complications. Although requirements engineering with an AI can be challenging regarding data quality, interpretability, and ethics, and there are no good quality AI tools, AI continues to evolve, as with deep learning and contextual understanding, which will result in better requirements engineering. As AI becomes more integrated, businesses can develop high quality software faster and more accurately, increasing project success. (shrink)

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 trust in these (...) systems, albeit a “guarded trust” in which individuals actively seek information about system foibles and analyze the reputations of participants. (shrink)

By allocating their attention to pieces of content, algorithmic filtering shapes the daily behavior of billions of users when they interact with a digital platform. Beyond conditioning what we do, can recommendation algorithms influence who we are? This article suggests that they do. Specifically, I contend that recommender systems affect users’ capacity to be their authentic selves in both positive and negative ways. I start by offering an account of authenticity that builds on two central concepts: volitional alignment (...) and self-understanding. I then explain how algorithmic filtering works and impacts authenticity. While recommender systems frustrate users’ second-order desires by relying on uninformative behavioral signals, they also facilitate self-understanding by inciting users to question their identity. I end by discussing how controllable and explainable recommenders would best enable users to be authentic. (shrink)

Recommender systems are artificial intelligence technologies, deployed by online platforms, that model our individual preferences and direct our attention to content we’re likely to engage with. As the digital world has become increasingly saturated with information, we’ve become ever more reliant on these tools to efficiently allocate our attention. And our reliance on algorithmic recommendation may, in turn, reshape us as moral agents. While recommender systems could in principle enhance our moral agency by enabling us to (...) cut through the information saturation of the internet and focus on things that matter, as they’re currently designed and implemented they’re apt to interfere with our ability to attend appropriately to morally relevant factors. In order to analyze the distinctive moral problems algorithmic recommendation poses, we develop a framework for the ethics of attention and an account of judicious attention allocation as a moral skill. We then discuss empirical evidence suggesting that attentional moral skill can be thwarted and undermined in various ways by algorithmic recommendation and related affordances of online platforms, as well as economic and technical considerations that support this concern. Finally, we consider how emerging technologies might overcome the problems we identify. (shrink)

In the age of streaming, we face a pressing problem of aesthetic choice: how are we to navigate the overwhelming quantity of content to which we now have access? Streaming platforms like Spotify and Netflix apply sophisticated machine learning tools to recommend personalized content to individual users. These recommender systems are presented to users as a technological solution to the problem of aesthetic choice, promising to help us discover new opportunities for engagement with aesthetic value. However, overreliance on (...) algorithmic recommendation can lead to diminished aesthetic autonomy, reduced aesthetic exploration, and an overall reduction in the satisfaction we take in aesthetic engagement. This is largely due to the fact that, in their most popular implementations, recommender systems are optimized to captivate users. They aim to maximize our engagement by recommending both content and modes of engagement which are initially attractive and frictionless, but which ultimately reshape our aesthetic personalities in ways that anchor us to streaming platforms. This paper explores these concerns before concluding with an assessment of whether it’s possible to use recommender systems in ways more conducive to our aesthetic flourishing. (shrink)

This is the third draft of a paper that aims to clarify the apparent contradictions in the views presented in certain standards and other specifications of health informatics systems, contradictions which come to light when the latter are evaluated from the perspective of realist philosophy. One of the origins of this document was Klein’s discussion paper of 2005-07-02 entitled “Conceptology vs Reality” and the responses from Smith, as well as the several hours of discussions during the 2005 MIE meeting (...) in Geneva. (shrink)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

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 (...) neither straightforward nor consistent, and are complicated by commercial interests and tensions around compulsive overuse. This multi-layered reality requires an analysis that is itself multidimensional and that takes into account human experience at various levels of resolution. We borrow from HCI and psychological research to apply a model (“METUX”) that identifies six distinct spheres of technology experience. We demonstrate the value of the model for understanding human autonomy in a technology ethics context at multiple levels by applying it to the real-world case study of an AI-enhanced video recommender system. In the process we argue for the following three claims: 1) There are autonomy-related consequences to algorithms representing the interests of third parties, and they are not impartial and rational extensions of the self, as is often perceived; 2) Designing for autonomy is an ethical imperative critical to the future design of responsible AI; and 3) Autonomy-support must be analysed from at least six spheres of experience in order to approriately capture contradictory and downstream effects. (shrink)

People are increasingly subject to algorithmic decisions, and it is generally agreed that end-users should be provided an explanation or rationale for these decisions. There are different purposes that explanations can have, such as increasing user trust in the system or allowing users to contest the decision. One specific purpose that is gaining more traction is algorithmic recourse. We first pro- pose that recourse should be viewed as a recommendation problem, not an explanation problem. Then, we argue that the capability (...) approach provides plausible and fruitful ethical standards for re- course. We illustrate by considering the case of diversity constraints on algorithmic recourse. Finally, we discuss the significance and implications of adopting the capability approach for algorithmic recourse research. (shrink)

Cultivation Advisor may be the single most significant feature of precision farming. Prescription farming attempts to establish these parameters on a case-by-case basis in an attempt to solve the crop selection problems. Although the "site-specific" approach has enhanced performance, there remains the necessity to oversee the results of the system. Precision farming systems are not equal to one another. But in agriculture, it is important that the suggestions given are accurate and precise because a single mistake can lead to (...) a lot of material and capital loss. This application will help farmers boost agricultural productivity. A crop requires sufficient soil and atmospheric conditions for the crop to yield well. So, if we provide the values that define soil and atmospheric conditions to this application it informs us about the crop that can be cultivated for the specified conditions. This online application will assist the farmers by determining the kind of disease the crop is undergoing with the help of the machine learning algorithm and even recommending to the farmers the kind of medicine that needs to be utilized to rectify the situation in both text and image of the medicine and pesticides that need to be applied. (shrink)

Abstract This paper examines whether a proposed shift to a federal parliamentary system in the Philippines would reduce or entrench political dynasties. Drawing on comparative experiences from other parliamentary-federal countries (India, Malaysia, Canada, Germany), the analysis concludes that without strong institutional safeguards, political dynasties could be further strengthened. A model Anti-Dynasty Law is proposed as a necessary reform, alongside party strengthening, campaign finance regulation, and holistic civic education. -/- .

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms of concept (...) combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

This paper aims to identify computerized management information systems resources and their relationship to the development of performance in the Electricity Distribution Company in Gaza. This research used two dimensions. The first dimension is computerized management information systems and the second dimension the Development of Performance. The control sample was (063). (360) questioners were distributed and (306) were retrieved back with a percentage of (85%). Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation (...) using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggested the presence of a statistically significant relationship between resources (physical, software, and human and organizational) for the computerized management information systems and the development of performance in the Electricity Distribution Company in Gaza. The study recommended the following: The need to strengthen the company's management interest in the potential of computerized management information systems and using them in the computerization of all the company's activities. And the need to involve workers and users in the design of computerized management information systems and assessment and development process. And strengthen the relationship between users and information systems personnel in the department responsible for the system. And it is essential that the company is developing the infrastructure for information technology in general, and computerized management information systems, in particular for the development of performance. And increase interest in providing resources (physical, software, and human and organizational) for the computerized management information systems. The current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first study at Electricity Distribution Company in Gaza resources explores the status of Computerized management information systems and their relationship to the development of performance in the Electricity Distribution Company in Gaza increasing interest in Computerized management information systems through continuity, keeping pace with technological means and modern techniques. (shrink)

The growing use of smart technology in personal grooming has resulted in novel uses such as smart mirrors to analyze the skin health and offer skincare advice. Here is a machine learning-based smart mirror framework that inspects facial skin conditions and gives individualized skincare advice. The framework employs computer vision and deep learning methods to identify and evaluate typical skin issues like acne, wrinkles, pigmentation, dryness, oiliness, and dark circles. By taking facial images with high resolution, the smart mirror derives (...) dermatological attributes and identifies skin conditions based on a CNN-driven model. The analysis is then tuned using image processing techniques and predictive analytics powered by artificial intelligence, providing high accuracy in the assessment of skin. Depending on the identified condition of the skin, the system recommends individualized skincare regimens involving appropriate products, lifestyle changes, and home remedies. The suggestions are based on a knowledge base learned on dermatological databases, skin care literature, and user-dependent considerations like age, skin type, climatic conditions, and past skin care. The intelligent mirror includes IoT sensors that sense environmental parameters like humidity, temperature, and UV index that impact skin well-being. Users interact with the intelligent mirror through voice recognition, touchpad controls, or gesture sensors, so it can be a seamless and convenient user interface. Progress tracking can be provided by the system too, where users get to track changes in the skin over a period of time and accordingly adjust their regimens. Besides, it ties in with cloud platforms and mobile apps, allowing consumers to access their skincare information online and receive professional advice. (shrink)

This paper examines the systemic vulnerabilities in the governance of the United Kingdom’s higher education sector, identifying a convergence of market fragility, fiscal exposure, and entrenched governance opacity. Drawing on policy analysis, statutory interpretation, and documentary evidence, it argues that these weaknesses constitute a governance crisis with significant economic and political implications. The case study of the Higher Education Policy Institute (HEPI) illustrates how incomplete statutory records, nepotism, and trustee entrenchment mirror patterns of network capture and epistemic gatekeeping found across (...) the sector. The paper advances the normative framework of ‘Directors’ Epistemic Duties and Fiduciary Openness’ {Kahl 2025}, proposing statutory reforms to embed active inquiry, independent verification, and proactive disclosure into governance practice. Recommendations include establishing a Higher Education Prudential Authority, mandatory sector-wide stress testing, conflict-proofed parliamentary oversight, and transparent fee structures. The analysis situates higher education alongside other sectors of critical national infrastructure, arguing for comparable standards of prudential regulation to protect public trust and systemic stability. (shrink)

Brain-computer interfaces (BCIs) offer significant therapeutic opportunities for a variety of neurophysiological and neuropsychiatric disorders and may perhaps one day lead to augmenting the cognition and decision-making of the healthy brain. However, existing regulatory frameworks designed for implantable medical devices (IMDs) are inadequate to address the unique ethical, legal, and social risks associated with next-generation networked brain-computer interfaces (BCIs). In this article, we make nine recommendations to support developers in the design of BCIs and nine recommendations to support policymakers in (...) the application of BCIs, drawing insights from the regulatory history of IMDs and principles from AI ethics. We begin by outlining the historical development of IMDs and the regulatory milestones that have shaped their oversight. Next, we summarize similarities between IMDs and emerging implantable BCIs, identifying existing provisions for their regulation. We then use two case studies of emerging cutting-edge BCIs-the HALO (Hardware Architecture for LOw-power BCIs) and SCALO (SCalable Architecture for LOw-power BCIs) computer systems-to highlight distinctive features in the design and application of nextgeneration BCIs arising from contemporary chip architectures, which necessitate reevaluating regulatory approaches. We identify critical ethical considerations for these BCIs, including unique conceptions of autonomy, identity, and mental privacy. Based on these insights, we suggest potential avenues for the ethical regulation of BCIs, emphasizing the importance of interdisciplinary collaboration and proactive mitigation of potential harms. The goal is to support the responsible design and application of new BCIs, ensuring their safe and ethical integration into medical practice. (shrink)

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 and strategic management in (...) the Islamic University in Gaza, and this shows that there is a role for decision support systems in strategic management development. The senior management is convinced of the importance of strategic management of the organization, and this conviction paid to clearly understand the process of the development of strategic management and thus led to a commitment to this process to improve its performance. There is an impact on the strategic management of the capabilities available for the use of decision support systems, and the type of decision support systems used, while there is little effect of top management support for the use of decision support systems. Also, the results showed that there were no statistically significant differences between the averages of the respondents answers attributed to personal data. The research also concluded a series of recommendations: The Islamic University of Gaza need to develop its infrastructure of decision support systems when it develops the strategic management. It should increase its interest in organizational potential through the necessity of a separate unit for decision support systems. As well as increased interest in the physical and technical capabilities available to decision support systems through continuity in keeping pace with technological means and techniques, continued support of senior management in the organization of strategic management for its positive role on decision support systems, that senior management will continue in the organization in creating a culture of strategic management, and it should encourage employees to participate in the strategic management process. (shrink)

This work describes an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework.

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 (...) Language Integrated Production System) framework. The expert system utilizes a rule-based inference engine to analyze patient-reported symptoms and provide reliable diagnoses or probability scores indicating the likelihood of migraine. The knowledge base of the expert system is designed based on expert knowledge obtained from medical professionals specializing in migraines. The collected knowledge is translated into a structured format suitable for the CLIPS inference engine, incorporating rules and facts to represent the diagnostic criteria and associated symptoms. The system prompts users to provide relevant information about their symptoms, medical history, and potential triggers. It applies the defined rules and facts to evaluate the likelihood of migraine and generate accurate diagnoses or probability scores. Preliminary evaluation results demonstrate the potential of the expert system as a valuable tool for diagnosing migraines. A dataset of anonymized patient records with confirmed migraine cases was used to test the system. The diagnoses generated by the expert system were compared against the known diagnoses, and a high level of accuracy was observed, with 90% of cases correctly diagnosed as migraines. These results highlight the effectiveness and reliability of the system in assisting medical professionals in the diagnosis of migraines. The proposed expert system offers several advantages for migraine diagnosis. It leverages the collective knowledge and expertise of experienced migraine specialists, providing a standardized and consistent approach to diagnosis. The system can handle large amounts of patient data and effectively analyse complex relationships between symptoms, risk factors, and diagnostic criteria. Furthermore, it offers real-time feedback and recommendations, supporting medical professionals in their clinical decision-making process. Future work involves refining the expert system based on feedback from medical experts, expanding the knowledge base to encompass a wider range of symptoms and risk factors, and conducting further evaluations to enhance its accuracy and applicability in clinical settings. The development of an expert system for migraine diagnosis has the potential to improve the diagnostic process, leading to more effective management and treatment strategies for individuals suffering from migraines. (shrink)

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. By employing (...) an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

The digitalization of human society continues at a relentless rate. However, to develop modern information technologies, the increasing complexity of the real-world must be modeled, suggesting the general need to reconsider how to carry out conceptual modeling. This research proposes that the often-overlooked notion of ‘‘system’’ should be a separate, and core, conceptual modeling construct and argues for incorporating it and related concepts, such as emergence, into existing approaches to conceptual modeling. The work conducts a synthesis of the ontology of (...) systems and general systems theory. These modeling foundations are then used to propose a CESM+ template for conducing systems-grounded conceptual modeling. Several new conceptual modeling notations are introduced. The systemist modeling is then applied to a case study on the development of a citizen science platform. The case demonstrates the potential contributions of the systemist approach and identifies specific implications of explicit modeling with systems for theory and practice. The paper provides recommendations for how to incorporate systems into existing projects and suggests fruitful opportunities for future conceptual modeling research. (shrink)

Artificial intelligence (AI) and Machine learning (ML) systems in medicine are poised to significantly improve health care, for example, by offering earlier diagnoses of diseases or recommending optimally individualized treatment plans. However, the emergence of AI/ML in medicine also creates challenges, which regulators must pay attention to. Which medical AI/ML-based products should be reviewed by regulators? What evidence should be required to permit marketing for AI/ML-based software as a medical device (SaMD)? How can we ensure the safety and effectiveness (...) of AI/ML-based SaMD that may change over time as they are applied to new data? The U.S. Food and Drug Administration (FDA), for example, has recently proposed a discussion paper to address some of these issues. But it misses an important point: we argue that regulators like the FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective—from a product view to a system view—is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies like the FDA who are used to regulating products, not systems. We offer several suggestions for regulators to make this challenging but important transition. (shrink)

A lot of infants have significant food-related problems, as well as spitting up, rejecting new foods, or not accepting to eat at specific times. These issues are frequently ordinary and are not a sign that the baby is unwell. According to the National Institutes of Health, 25% of generally developing infants and 35% of babies with neurodevelopmental disabilities are tormented by some sort of feeding problem. Some, for example rejecting to eat specific foods or being overly finicky, are momentary and (...) don’t cause any health dangers. This paper proposes an expert system that can be used to successfully diagnose Feeding problems in infants and children. The suggested systems were found to be beneficial approach in addition to existing impartial ones. So far as the authors are aware, this is the initial effort of using an expert system in attaining good performance in a real world application. This expert system was designed and implemented to help parents diagnose these problems and get a recommendation of how to deal with infants and children. (shrink)

Today e-commerce has had tremendous growth in the past years primarily due to changes in technology and customer’s buying behavior. One of the big shifts in the process has been the use of ML in advertising which has the capability to transform the marketing domain together with consumer interactions. This paper discusses the viability of using machine learning for designing realistic models of advertising to increase effectiveness of target and personalized advertising, as well as conversion rates in e-commerce. Several techniques (...) are explored in the study, such as supervised and unsupervised learning, recommender systems, and content optimization with natural language processing. By using case studies and experimental models, we discuss how and to what extent ML is beneficial in e-commerce advertising transformation. The results presented in this paper indicate that using machine learning in advertising has a potential of dramatically improving the customer experience while simultaneously increasing brand recognition and sales. (shrink)

Many individuals often struggle to identify the type of music they truly want to listen to based on their current mood. These challenges can lead to significant time wasted in searching for the "perfect" song that aligns with their emotional state. In this era of rapid technological advancements, particularly in the domain of Artificial Intelligence, leveraging AI in song recommendation systems can bridge this gap, creating a seamless fusion of technology and user needs. This paper aims to develop an (...) emotion-based song suggestion system that suggests songs based on the user's emotional state. The process begins with the user capturing a photo of themselves using their laptop's webcam—an action undertaken only with their explicit consent. Using a Convolutional Neural Network (CNN), the system analyzes the image to detect the users current emotional state. Once the emotion is identified, the system matches it to a curated playlist or category of songs that correspond to the detected mood. The selected song is then played automatically, fulfilling the user's musical preferences effortlessly. The proposed system enhances user engagement by dynamically adapting to their emotions, making it a promising approach for next-generation music recommendation platforms. (shrink)

Although patterns of human activity show a large degree of freedom, they exhibit structural patterns subjected by geographic and social constraints. Aiming at various problems of personalized recommendation in mobile networks, a social network recommendation algorithm is proposed with a variety of context-aware information and combined with a series of social network analysis methods.Based on geographical location and temporal information, potential social relations among users are mined deeply to find the most similar set of users for the target user, then (...) recommendations are carried out incorporating with social relations of the mobile users to effectively solve the problem of recommendation precision. The above study can not only help LBSN designers and developers to better understand their users and grasp their want, but also help to refine the design of their system to provide users with more appropriate applications and services.The experimental results on the real-world dataset verify the feasibility and effectiveness of the proposed algorithm, and it has higher prediction accuracy compared with existing recommendation algorithms. (shrink)

Modern AI systems based on deep learning are neither traditional tools nor full-blown agents. Rather, they are characterised by idiosyncratic agential profiles, i.e., combinations of agency-relevant properties. Modern AI systems lack superficial features which enable people to recognise agents but possess sophisticated information processing capabilities which can undermine human goals. I argue that systems fitting this description, when they are adversarial with respect to human users, pose particular risks to those users. To explicate my argument, I provide (...) conditions under which agential profiles are explanatorily relevant to harms caused. I then contend that the role of recommender systems in producing harmful outcomes like digital addiction satisfies these conditions. (shrink)

This study developed a disaster risk assessment system that integrates the Support Vector Machine (SVM) algorithm and risk indicators derived from social media data and official sources. Employing the Rational Unified Process (RUP) for system development and a mixed-methods design for evaluation, the study was conducted in the disaster-prone province of Sorsogon, Philippines. The system utilized a linear kernel SVM classifier to categorize social media posts as disaster-related or not and computed a Disaster Risk Index (DRI) using five key indicators: (...) hazard, exposure, vulnerability, and capacity (hard and soft countermeasures). System features included data extraction modules, GIS-based visualization, and a security layer employing SHA-256 encryption. Usability testing using the USE questionnaire and qualitative interviews showed high levels of perceived usefulness, ease of use, and user satisfaction among disaster management personnel. The results identified Juban, Sta. Magdalena and Bulan as the municipalities with the highest disaster risk levels. The study concludes that the proposed system is an effective tool for enhancing disaster preparedness and recommends its future deployment with real-time data integration and expanded geographic coverage. (shrink)

This study was conducted with the aim of developing the academic work in the Palestinian universities. No one can deny the technological stage that we are witnessing in the present era. Our mission is to use this development to develop the educational process. The Artificial Intelligence of the most important branches of computer science, which is interested in the development of computer software in order to make them simulate intelligent human, recently it emerged promised based on artificial intelligence applications are (...) intelligent tutoring system one of the most prominent of these applications is the most useful in the field of education. Intelligent tutoring system are programs that are helping the student and the teacher in the educational process, so that the student exploits these systems to increase his education and the acquisition of scientific skills, and we are not exaggerating if we say that the future of the development of the educational process is through the development of intelligent private teaching systems because it adapts to me intellectual level of the student as well as easy to use and available 24 hours every day. In this study, a smart tutor was designed using the ITSB tool developed by Prof. Sami Abu Nasser to develop the process of teaching the computer skills course. This course is a university course that teaches students of Israa University on different samples of students. After completion of the course, and evaluate the special lecturers who studied the course and used the system in the process of teaching and arrived at a set of conclusions and recommendations make sure that the use of the tutor Smart smartphone is important in the development of laboratory teaching has positive results in improving the level of scientific student . (shrink)

This article briefly summarizes the key characteristics and social philosophies in Japan’s vision of Society 5.0. Then it discusses why Vietnam, as a developing country, can learn from the experiences of Japan in establishing its vision for an AI-powered human-centric society. The paper finally provides five concrete recommendations for Vietnam toward a harmonic and human-centric coexistence with increasingly competent and prevalent AI systems, including: Human-centric AI vision; Multidimensional, pluralistic understanding of human-technology relation; AI as a driving force for socio-economic (...) development; Bottom-up, participatory approach for building the vision; and Sustainability and inclusion in the adoption of AI. (shrink)

This study was conducted with the aim of developing the academic work in the Palestinian universities. No one can deny the technological stage that we are witnessing in the present era. Our mission is to use this development to develop the educational process. The Artificial Intelligence of the most important branches of computer science, which is interested in the development of computer software in order to make them simulate intelligent human, recently it emerged promised based on artificial intelligence applications are (...) intelligent tutoring system one of the most prominent of these applications is the most useful in the field of education. Intelligent tutoring system are programs that are helping the student and the teacher in the educational process, so that the student exploits these systems to increase his education and the acquisition of scientific skills, and we are not exaggerating if we say that the future of the development of the educational process is through the development of intelligent private teaching systems because it adapts to me intellectual level of the student as well as easy to use and available 24 hours every day. In this study, a smart tutor was designed using the ITSB tool developed by Prof. Sami Abu Nasser to develop the process of teaching the computer skills course. This course is a university course that teaches students of Israa University on different samples of students. After completion of the course, and evaluate the special lecturers who studied the course and used the system in the process of teaching and arrived at a set of conclusions and recommendations make sure that the use of the tutor Smart smartphone is important in the development of laboratory teaching has positive results in improving the level of scientific student . (shrink)

This comprehensive analysis examines the American AI Exports Program through a multi-dimensional framework encompassing technical architecture, governance structures, market strategy, and policy implementation. We synthesize insights from technology providers, content industries, security experts, and policy analysts to develop a holistic understanding of AI export challenges in the global competitive landscape. The paper presents a multi-layer framework architecture with strategic, governance, technical, and market layers, supported by detailed visualizations including architectural diagrams, decision matrices, risk assessment frameworks, and implementation roadmaps. We analyze (...) the Federal Register requirements for full-stack AI technology packages and industry-led consortia, addressing tensions between export promotion, national security, intellectual property protection, and competitive fairness. Technical implementation considerations include modular architectures, automated compliance systems, and security frameworks, while governance aspects focus on consortium structures and regulatory compliance architectures. Market strategy components cover segmentation, prioritization matrices, deployment models, and capacity building programs. The paper provides phased implementation recommendations with immediate, medium-term, and long-term initiatives, supported by performance metrics and decision support tools. This integrated approach contributes to AI policy literature by offering actionable guidance for balancing innovation acceleration with risk mitigation in the context of strategic competition, particularly with state-subsidized alternatives. (shrink)

Coronavirus is a viral irresistible sickness brought about by SARS- COV2. Its clinical signs and side effects are on an expansive range going from asymptomatic to serious confusions like multi-organ disappointment, thromboembolism, and extreme pneumonia with respiratory disappointment. More awful results and higher death rates have been accounted for in the old, individuals with co-morbidities, and malnourished people. Sustenance is central to acceptable wellbeing and safe capacity. It frames an essential segment of therapy modalities for different intense and persistent infections, (...) particularly where a causative therapy isn't yet perceived. Despite the fact that reviews tending to the part of explicit supplements in COVID-19 are still at a beginning phase, accessible proof recommends that addressing the necessities of a variety of large scale and miniature supplements (energy, proteins, fats, nutrients A, D, E, C, B nutrients, iron, selenium, zinc, and so forth) Additionally, supplements are Immune System Might Promote Recovery for Mild COVID-19 Patients Impact of Coronavirus on Education in India Review 466 determinants of the sythesis of the gut microbiota that thusly impacts the attributes of safe reactions in the body. (shrink)

This paper explores some of the factors that make complex systems complex. We first examine the history of complex systems. It was Aristotle’s insight that how elements are joined together helps determine the properties of the resulting whole. We find (a) that scientific reductionism does not provide a sufficient explanation; (b) that to understand complex systems, one must identify and trace energy flows; and (c) that disproportionate causality, including global tipping points, are all around us. Disproportionate causality (...) results from the wide availability of energy stores. We discuss three categories of emergent phenomena—static, dynamic, and adaptive—and recommend retiring the term emergent, except perhaps as a synonym for creative. Finally, we find that virtually all communication is stigmergic. (shrink)

What does aesthetic life look like in the digital age? This chapter explores the impact that AI, algorithms, social networking, and other technological innovations have had on the ways that we create, consume, and commune. We’ll divide our focus across each one of the three c’s listed above – creativity, consumption, and community. In each section, we’ll also be zooming in on one technological development, highlighting its specific impact on our aesthetic lives. The first section focuses on the emergence of (...) AI-generated art and its impacts on creativity; the second section concerns the impact of algorithmic recommendation systems on our consumption; and in the final section, I discuss the ways in which the internet has affected our ability to form and maintain aesthetic communities. (shrink)

Imagine you are casually browsing an online bookstore, looking for an interesting novel. Suppose the store predicts you will want to buy a particular novel: the one most chosen by people of your same age, gender, location, and occupational status. The store recommends the book, it appeals to you, and so you choose it. Central to this scenario is an automated prediction of what you desire. This article raises moral concerns about such predictions. More generally, this article examines the ethics (...) of artificial social cognition—the ethical dimensions of attribution of mental states to humans by artificial systems. The focus is presumptuous aim attributions, which are defined here as aim attributions based crucially on the premise that the person in question will have aims like superficially similar people. Several everyday examples demonstrate that this sort of presumptuousness is already a familiar moral concern. The scope of this moral concern is extended by new technologies. In particular, recommender systems based on collaborative filtering are now commonly used to automatically recommend products and information to humans. Examination of these systems demonstrates that they naturally attribute aims presumptuously. This article presents two reservations about the widespread adoption of such systems. First, the severity of our antecedent moral concern about presumptuousness increases when aim attribution processes are automated and accelerated. Second, a foreseeable consequence of reliance on these systems is an unwarranted inducement of interpersonal conformity. (shrink)

The aim of the research is to identify the role of policies and procedures for the electronic document management system in the success of the electronic document management system in the Palestinian Pension Agency. In order to achieve the objectives of the study, the researchers used the analytical descriptive method in which the tries to describe the phenomenon studied, analyze its data, the relationship between its components and the opinions that are raised around it, and use the comprehensive inventory method (...) due to the small size of the society. (108) questionnaires were distributed to the community of 65 employees in Gaza Strip and 43 employees in the West Bank. All the responses were retrieved. The research found that there is a clear adoption by the Commission of the policies and procedures put in place to implement the electronic management system of electronic documents. The study showed that there are no statistically significant differences between the responses of the study population regarding the role of policies and procedures for the electronic document management system in the success of the electronic document management system in the Palestinian Pension Agency due to variable (age, nature of job, specialization). And showed that there is a fundamental difference in the opinion of members of the study community on the role of policies and procedures for the electronic document management system in the success of the electronic document management system in the Palestinian Pension Agency attributed to the scientific qualification, and shows the difference in favor of the bachelor's degree. And years of service, and shows the difference in favor of the 11-15 year category. The research led to a number of recommendations, the most important of which is the increase of interest and awareness of the need to implement policies and procedures to ensure the success of the electronic document management system through access to and benefit from the experiences of other institutions and the private sector. And the need to focus on the attention to develop appropriate and clear plans and dissemination on the electronic document management system and specific to specific objectives and the Commission is committed to apply them, the need to pay attention to the development of strategic plans and policies and work mechanisms commensurate with the electronic document management system, and the need to define a policy in advance to form a team of different specialties of the staff of the Authority and cooperation with consultants from outside the body to work on the electronic document system. (shrink)

The research aims to identify the impact of the management requirements on operating of computerized management information systems to improve performance, and discuss the perceptions of respondents to develop the performance of employees in the Gaza Electricity Distribution Company, the researchers used the stratified sample method, (360) questionnaires were distributed on the study sample, (306) questionnaires were recoved with a percentage of (85%). The most important findings of the study: computerized MI have a positive impact on the development of (...) performance in the Gaza Electricity Distribution Company systems. The is statistical significance impact between “the physical, software supplies, human and organizational” requirements for the management and operation of computerized management information systems and performance development in the Gaza Electricity Distribution Company. -/- The research also concluded a series of recommendations: the need to strengthen the company's management interest in the use of computerized management information systems in all its components and elements of being an important variable which contributes to the effect on performance development. It's essential that we develop the infrastructure for information technology in general, and computerized management information systems, in particular for the development of performance. Increased interest in providing the material of equipment and devices used in the computerized management information system requirements. Interest in providing technical inputs to the computerized management information systems through keeping pace with technological means and modern techniques and work on the training of personnel to use those systems. And increased attention to human inputs of computerized management information systems "specialists technicians and end-users" through a variety of disciplines working in the field of computerized management information systems. (shrink)

The practicability of the comprehensive FSR concept is problematic. Contemporary FSR must be positioned at the point of overlap between the positivist and constructivist paradigms, which are both grounded in a continual identification with the rational-empirical consciousness, in thinking -being.Spirituality, defined as the process in which one systematically trains the receptivity to gain regular access to transcendental consciousness, emphasizes the experience of just being, of consciousness-as-such. It is an experiential spirituality, which is not based on dogmas, but on do-it-yourself techniques (...) to break the continuous spell of the rational-empirical consciousness. Such a spirituality facilitates the cultivation of societally and environmentally friendly behavior. Sustainability can be defined as the integrative 'emergent property' of experiential spirituality and rational morality based on negotiated agreements.In addition to the outward-oriented approaches of the positivist and constructivist paradigms, an inward-oriented approach, focusing on consciousness development, is recommended. Language-mediated interaction must be supported by consciousness-mediated interaction. (shrink)

Research engagement in Philippine Higher Education Institutions (HEIs) is a pressing challenge. Despite its recognized importance for instructional innovations and institutional development, many faculty members avoid research, even when incentives are available. This qualitative-transcendental phenomenology explores and describes the experiences and insights of instructors on the factors affecting their research engagement. Through purposive sampling, specifically the criterion sampling technique, thirty-two (32) participants were selected from the four branches of Davao de Oro State College (DdOSC). The validated interview guide questions were (...) used as the primary instrument in obtaining data through in-depth interviews and focus-group discussion, and the responses were thoroughly analyzed using thematic analysis. The significant factors identified by faculty were graduate studies and work responsibilities. Additionally, their lack of technical research writing knowledge contributed to their research limitations. Faculty members emphasized the need for ongoing research guidance, mentorship, and a wider range of incentives, such as integrating research into teaching loads, salary increases, and travel opportunities. Communication gaps between faculty and institutional research policies were evident, as some faculty members were unaware of the college's support. This study's implications stress the need for institutions to reconsider faculty workloads, offer additional training, and establish support systems that create a more research-friendly environment. Addressing these factors and expanding incentives can inspire faculty to participate in research activities, fostering a vibrant research culture and advancing knowledge within the academic community. (shrink)

Abstract The modern state faces rising expectations for efficiency, transparency, and responsiveness. Traditional bureaucratic systems often struggle to meet these demands, resulting in calls for reforms that borrow from private-sector management practices. This paper explores how government systems can be redesigned using private company rules while safeguarding public accountability and equity. Through case studies of Estonia, Singapore, charter cities, and public–private partnerships (PPPs), the paper presents a framework for blending corporate efficiency with democratic values. Recommendations include performance-based governance, (...) citizen-centric service design, competitive contracting, and transparent oversight mechanisms. -/- . (shrink)

Abstract: Low vision is a significant global health issue that affects millions of individuals, limiting their daily activities and reducing their quality of life. Accurate and early diagnosis is essential for effective management and treatment, yet existing diagnostic methods often fall short due to various limitations in precision and accessibility. This paper proposes an innovative and accurate system for diagnosing low vision, leveraging advanced technologies such as artificial intelligence and expert systems. The proposed system integrates patient history, vision test (...) results, and imaging data to provide precise diagnoses and tailored recommendations. Designed with a user-friendly interface, the system is intended to assist ophthalmologists, optometrists, and general practitioners in diagnosing a wide range of low vision conditions efficiently. Initial evaluations suggest the system’s potential to significantly enhance diagnostic accuracy and patient outcomes, while also reducing the burden on healthcare professionals. This work represents a step forward in bridging the gap between technology and accessible eye care for patients worldwide. (shrink)

The Next-Gen Medication Guidance System is a cutting-edge healthcare tool designed to streamline the process of drug selection and optimize therapeutic outcomes by providing personalized medication recommendations. The system utilizes an advanced combination of artificial intelligence (AI), natural language processing (NLP), and machine learning algorithms to analyze a wide array of patient-specific data, including medical history, symptoms, lab results, demographic factors, and past medication responses. By processing this data, NMGS generates customized drug suggestions that are tailored to the individual needs (...) of each patient, ensuring that the prescribed treatments are not only effective but also safe. Key features of the NMGS include real-time drug interaction checking, adverse event prediction, and automated identification of potential contraindications, which help clinicians make informed decisions and minimize the risk of harmful drug interactions. The system is designed to integrate seamlessly with Electronic Health Records (EHR) systems, allowing healthcare professionals to access drug recommendations directly from their existing workflows, thus saving time and reducing the potential for errors. The system’s decision support is based on a dynamic, continually updated database of pharmaceutical information, clinical guidelines, and evidence-based research. This allows the NMGS to recommend the most current and relevant drug therapies, incorporating the latest advances in medicine and evolving medical standards. Additionally, the system can adapt to different healthcare environments, supporting both individual clinicians in private practice and large healthcare institutions. By enhancing clinical decision-making, the Integrated Drug Suggestion System aims to improve patient outcomes, reduce the incidence of adverse drug events, and promote the rational use of medications. The implementation of NMGS represents a significant advancement in the field of clinical informatics, contributing to the shift towards more precise, personalized, and efficient healthcare deliver. (shrink)

The main aim of this article is to reflect on the impact of biases related to artificial intelligence (AI) systems developed to tackle issues arising from the COVID-19 pandemic, with special focus on those developed for triage and risk prediction. A secondary aim is to review assessment tools that have been developed to prevent biases in AI systems. In addition, we provide a conceptual clarification for some terms related to biases in this particular context. We focus mainly on (...) nonracial biases that may be less considered when addressing biases in AI systems in the existing literature. In the manuscript, we found that the existence of bias in AI systems used for COVID-19 can result in algorithmic justice and that the legal frameworks and strategies developed to prevent the apparition of bias have failed to adequately consider social determinants of health. Finally, we make some recommendations on how to include more diverse professional profiles in order to develop AI systems that increase the epistemic diversity needed to tackle AI biases during the COVID-19 pandemic and beyond. (shrink)