The increase in claim sophistication in both the insurance and legal domains is a result of an increase in stokes and heterogeneity of data needed to assess the claim validity. Originally, this task was performed by some sort of subjectivity assessments and graphical rule sets, which is very slow and may be inherently erroneous due to its purely manual nature. Hence, with progressivity in multimodal learning, specifically in AI, there is now a unique chance of solving these challenges through the (...) use of text data, which may include policies, reports and images, which may include accident images, evidence images, videos such as surveillance, cam videos among others. However, existing AI-based solutions usually address only one of the modalities, which makes it difficult to evaluate an integrated situation. This has led to the need for systems that will integrate information from all these modalities and come up with an accurate, efficient, and transparent processing system. Indeed, this paper seeks to discuss the use of Multimodal generative AI to address this need as one of the most recent approaches that rely on high-performing models that can process and integrate text, image, and video data. The proposed system combines these modalities to ensure that the system captures relevant data from each data type and combines all in a way that provides more comprehensive and enriched decision support. An initial system was designed and empirically tested against current claim adjudication techniques and was found to yield substantial enhancements in all utilization rates, throughput and main rationale for the claim decisions. The findings shown in the study stress the capability of multimodal generative AI for revolutionizing the present approaches of claims analysis and developing more efficient, accurate, and capable responses to various real-life conditions. This integration of technologies is an unprecedented advance towards advancing functional processes in the insurance and legal industries. (shrink)

Interior design plays a vital role in creating aesthetically pleasing and functional spaces. Traditional methods involve multiple meetings and extensive manual effort, making the process time-consuming, costly, and less accessible. To address these limitations, this project explores an innovative approach to interactive interior design using generative AI models. The system allows users to upload an image of a room, which is then transformed using AI while maintaining structural integrity. The generated image includes furniture with clickable shopping links, enabling direct purchases. (...) The backend ensures scalability, while the frontend provides an intuitive user experience. This paper discusses the training methodology, accuracy evaluation, and the practical implementation of the system, highlighting its potential for commercialization through affiliate commissions and premium features. (shrink)

This paper presents a systematic review of generative artificial intelligence (AI) applications in fixed income markets, synthesizing insights from key studies published mostly between 2024 and 2025. The analysis spans the latest developments in AI-driven analytics, trading strategies, risk management techniques, and the evolution of investment approaches within this crucial sector of finance. The review covers advancements in interest rate yield curve modeling, algorithmic trading, credit and liquidity risk assessment, and structured product valuation. Special attention is given to the emergence (...) of large language models (LLMs), such as BondGPT and ChatGPT, and their integration into bond analytics, scenario generation, and regulatory workflows. These technologies are shown to enhance efficiency in bond analytics, trade documentation, liquidity analysis, and credit research, while also introducing new challenges related to model risk, data integrity, and compliance. Our findings highlight three core areas of innovation: (1) improved forecasting accuracy in interest rate models using hybrid AI architectures, (2) proposals for enhanced efficiency and automation in asset-backed securities (ABS) and mortgage-backed securities (MBS) pricing, and (3) explainable AI frameworks for compliance in risk-sensitive environments. Despite notable efficiency gains—ranging from 22% to 40% across key market functions—challenges persist around interpretability, data quality, and regulatory acceptance. Here, AI-driven valuation frameworks, scenario generation, and risk modeling innovations are accelerating the analysis and management of complex securities. Both the theoretical progress and practical impact of these models are explored in the paper, showing their abilities in explaining market patterns and their difficulties in meeting regulations. The study combines perspectives from academia, regulators and industry players to fully assess how AI is impacting the world of fixed income and offers suggestions for future improvements and best approaches. (shrink)

Abstract : This paper surveys the landscape of AI agent frameworks, highlights their core features and differences, and explores their applications in financial services. We synthesize insights from recent industry reports, academic research, and technical blog posts, focusing on frameworks such as CrewAI, LangGraph, LlamaIndex, and others. We also discuss the challenges and opportunities of deploying agentic AI in production environments, with an emphasis on financial trading, investment analysis, and decision support. We analyze the rapidly evolving landscape of agentic AI (...) systems, focusing on their architecture, capabilities, and practical implementations in banking, trading, and risk management. The study examines prominent frameworks including LangGraph for stateful agent orchestration, CrewAI for collaborative multi-agent workflows, and AutoGen for conversational agent systems, alongside industry platforms like IBM watsonx and NVIDIA NIM. The study examines both technical frameworks (LangGraph, CrewAI, AutoGen, etc.) and practical implementations in financial institutions. We highlight productivity gains (up to 80% time reduction in data tasks), risk management improvements, and workforce transformation challenges. The paper concludes with recommendations for financial institutions adopting agentic AI solutions. Our analysis reveals three key findings: (1) specialized agent frameworks achieve 50-80% productivity gains in financial data tasks compared to traditional approaches, (2) multi-agent systems demonstrate particular promise in complex domains like algorithmic trading and fraud detection, and (3) successful deployment requires addressing critical challenges in workforce upskilling, risk alignment, and regulatory compliance. The paper provides a theoretical foundation for agentic AI in finance, introducing formal models for agent design patterns, multimodal fusion, and market microfoundations. We further present a summary of several evaluation frameworks for assessing agent performance across financial use cases, including portfolio optimization and AML compliance. The study concludes with recommendations for financial institutions adopting agentic AI, emphasizing the need for standardized architectures, robust testing protocols, and hybrid human-AI workflows. (shrink)

Generative artificial intelligence (Gen AI) and machine learning (ML) technologies are changing the way the insurance industry looks, particularly by integrating Gen AI & ML technologies. As a leading platform for property and casualty insurance, Guidewire provides a perfect platform for deploying intelligent claims processing workflows that can dramatically improve efficiency, accuracy and customer satisfaction. The seamless integration of Gen AI and ML capabilities into Guidewire to autonomously process claims is explored in this paper. Insurers can use advanced models to (...) drive self-driving workflows that are capable of automating tasks like claims triage, fraud detection, damage assessment and settlement optimization. But most importantly, these technologies reduce operational costs, and reduce the human intervention involved such that claims can be handled faster and with more accuracy. In this work, we discuss what technical and strategic considerations need to be taken into account when implementing such workflows, such as data integration, model training, and ethical AI practices. This paper also demonstrates several real-world use cases, the challenges you in each, and the potential to scale these solutions across lines of business. With an eye on the future, autonomous claims processing enables insurers to find their next competitive edge by providing innovative solutions that alter the course of expectations of customers while qualifying to regulatory and compliance standards. Self-driving workflows powered by Gen AI and ML in claims are the future of insurance and their ability to transform the entire process of claims management. (shrink)

Quantum-enhanced machine learning (QML) is transforming artificial intelligence through the application of quantum computing concepts to solving computationally challenging problems more effectively than conventional methods. By leveraging quantum superposition, entanglement, and parallelism, QML has the capability to speed up deep learning model training, solve combinatorial optimization problems, and improve feature selection in high-dimensional space. It covers basic quantum computer concepts employed within AI, for example, quantum circuits, quantum variational algorithms, and kernel quantum methods, and their impacts on neural networks, generative (...) models, and reinforcement learning. It further refers to the hybrid quantum-classical architectures in AI where a combination of quantum subroutines and classical deep learning models are employed together with the purpose to gain computational speedup in optimization and handling massive data. Despite the transformative promise of quantum AI, technical issues of qubit noise, error correction, and scaling hardware continue to hold back full implementation. This contribution offers a qualitative overview of quantum-enhanced AI, surveying current applications, research endeavors, and upcoming innovation in quantum deep learning, autonomous systems, and scientific computing. The results open the door for large-scale quantum machine learning architectures, which provide new solutions to future uses of AI in finance, medicine, cyber security, and robotics. (shrink)

Predictive analytics, empowered by generative AI and cloud technologies, has the potential to revolutionize educational practices by facilitating early intervention and proactive support for students. This chapter explores the integration of predictive analytics in educational settings, focusing on how datadriven insights can identify at- risk students and tailor interventions to their specific needs. By leveraging generative AI algorithms, educators can analyze vast amounts of data, including academic performance, engagement levels, and socio- emotional factors, to predict potential challenges before they escalate. (...) The chapter highlights case studies that demonstrate successful implementations of predictive analytics in schools and universities, showcasing improved student outcomes, enhanced engagement, and more personalized learning experiences. Additionally, it discusses the ethical considerations and challenges associated with data privacy and bias in AI systems. (shrink)

Quantum-enhanced machine learning (QML) is transforming artificial intelligence through the application of quantum computing concepts to solving computationally challenging problems more effectively than conventional methods. By leveraging quantum superposition, entanglement, and parallelism, QML has the capability to speed up deep learning model training, solve combinatorial optimization problems, and improve feature selection in high-dimensional space. It covers basic quantum computer concepts employed within AI, for example, quantum circuits, quantum variational algorithms, and kernel quantum methods, and their impacts on neural networks, generative (...) models, and reinforcement learning. It further refers to the hybrid quantum-classical architectures in AI where a combination of quantum subroutines and classical deep learning models are employed together with the purpose to gain computational speedup in optimization and handling massive data. Despite the transformative promise of quantum AI, technical issues of qubit noise, error correction, and scaling hardware continue to hold back full implementation. This contribution offers a qualitative overview of quantum-enhanced AI, surveying current applications, research endeavors, and upcoming innovation in quantum deep learning, autonomous systems, and scientific computing. The results open the door for large-scale quantum machine learning architectures, which provide new solutions to future uses of AI in finance, medicine, cyber security, and robotics. (shrink)

With the rapid development of communication technology, the explosive growth of mobile and IoT devices, and growing requirements for real-time data processing, a new paradigm of computing, Edge Computing, has appeared. It moves computing power in the direction of data sources to mitigate latency, bandwidth usage, and dependence on cloud computing. In parallel, Artificial Intelligence (AI) has progressed notably with deep learning technology, highly optimized hardware, and distributed computing paradigms to yield smart applications of high computational loads. Nonetheless, the huge (...) amounts of data generated on the network edge impose heavy challenges in managing data, network optimization, and implementing AI models. This has pushed the convergence of Edge Computing and AI, which has led to a new research area called Edge Intelligence. Edge Intelligence is further divided into two broad categories • AI for Edge (Intelligence-enabled Edge Computing) – This is concerned with augmenting Edge Computing architectures with AI-based methods, including resource management, task scheduling, computation offloading, and network optimization. • Edge AI (Artificial Intelligence on Edge) – This involves executing AI models on edge devices directly, enabling local training and inference with minimal dependence on the cloud, thereby improving privacy, efficiency, and real-time processing. This paper provides an overview of Edge Intelligence, including fundamental concepts, future technologies, and research directions. We identify critical challenges such as efficient deployment of AI models, decentralized AI learning through federated learning, and edge-centric accelerations of domain-specific hardware, and discuss how Edge Intelligence has the potential to transform domains like autonomous systems, smart cities, factory automation, and wireless networks. This paper documents the present trend and future path to act as the basis for researchers, engineers, and industry players seeking to improve the topic of AI-driven Edge Computing. (shrink)

As global manufacturing industries evolve, the demand for smarter, more efficient, and predictive production systems is intensifying. The integration of analyzer instrumentation with Artificial Intelligence (AI) in manufacturing environments presents a transformative opportunity to optimize processes, enhance product quality, and reduce operational costs. This research explores the convergence of analyzer technologies and AI-driven automation to create predictive manufacturing ecosystems. Through the use of smart sensors, real-time data analytics, and machine learning algorithms, modern manufacturing setups are becoming increasingly self-aware, adaptive, and (...) proactive. This paper reviews current advancements in analyzer instrumentation—such as gas chromatographs, spectrometers, and thermal analyzers—coupled with AI applications like predictive maintenance, quality forecasting, and anomaly detection. It also investigates key case studies from industries such as pharmaceuticals, automotive, and petrochemicals, highlighting how real-time monitoring and AI-based decision-making are reshaping production efficiency. The study utilizes a qualitative methodology, including a literature review and selected case analysis, to assess the benefits and challenges of these technologies. Findings reveal that predictive process optimization leads to significant improvements in throughput, energy consumption, and defect reduction. However, successful integration relies heavily on data quality, sensor accuracy, and workforce adaptability. The paper concludes by proposing a roadmap for industries aiming to transition toward nextgen manufacturing through AI-integrated analyzer instrumentation, emphasizing strategic planning, cross-disciplinary collaboration, and continuous learning. (shrink)

The rapid adoption of commercial Generative Artificial Intelligence (Gen AI) products raises important questions around the impact this technology will have on our communicative interactions. This paper provides an analysis of some of the potential implications that Artificial Intelligence-Mediated Communication (AI-MC) may have on epistemic trust in online communications, specifically on social media. We argue that AI-MC poses a risk to epistemic trust being diminished in online communications on both normative and descriptive grounds. Descriptively, AI-MC seems to (roughly) lower levels (...) of epistemic trust. Normatively, we argue that this brings about the following dilemma. On the one hand, there are at least some instances where we should epistemically trust AI-MC less, and therefore the reduction in epistemic trust is justified in these instances. On the other hand, there are also instances where we epistemically trust AI-MC less, but this reduction in epistemic trust is not justified, resulting in discrimination and epistemic injustice in these instances. The difficulty in knowing which of these two groups any instance of AI-MC belongs to brings about the AI-MC dilemma: We must choose between maintaining normal levels of epistemic trust and risking epistemic gullibility when reduced trust is justified, or adopting generally reduced epistemic trust and risking epistemic injustice when such reduced trust is unjustified. Navigating this choice between problematic alternatives creates a significant challenge for social media as an epistemic environment. (shrink)

This paper explores the current applications, benefits, and challenges of generative AI in various business do- mains, drawing from recent literature and industry reports from literature published in 2025. We examine key use cases including content creation, knowledge management, business process automation, and decision support. The paper also discusses implementation challenges, ethical considerations, and future directions for generative AI adoption in business contexts. We analyze key applications in operational efficiency, risk management, and strategic decision-making through recent industry reports and academic (...) perspectives. This paper presents a comprehensive visual framework for analyzing generative AI applications in business through 18+ original diagrams. The framework systematically organizes key findings across four dimensions: value creation, functional impact, implementation roadmaps, and risk management. Central to our analysis are three core visualizations: (1) an enterprise implementation diagram mapping productivity gains of 30-50% across business processes, (2) a functional impact wheel identifying marketing and data analytics as highest-potential applications, and (3) a comparative ROI matrix showing process automation delivering 50% cost reductions versus content generation’s rapid 3-month implementation cycles. The visual methodology reveals critical adoption patterns including the inverse relationship between technical complexity and organizational readiness, particularly in risk-sensitive domains. Our framework provides business leaders with an actionable taxonomy for strategic planning, supported by measurable performance benchmarks and maturity assessments. The charts collectively demonstrate that successful generative AI adoption requires balancing technical capabilities with operational constraints and ethical considerations. (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)

Retail 4.0 signifies a transformative era in the retail industry, characterized by the integration of Artificial Intelligence (AI) and automation technologies. This paradigm shift aims to enhance customer experiences, streamline operations, and foster innovation. This paper explores the multifaceted impact of AI and automation on retail, examining their roles in personalized shopping, inventory management, customer service, and operational efficiency. Through case studies and industry examples, the research highlights the practical applications and benefits of these technologies. The findings suggest that AI (...) and automation are not merely supplementary tools but central components driving the evolution of modern retail. The paper concludes by discussing the challenges and ethical considerations associated with AI adoption and offers insights into the future trajectory of Retail 4.0. (shrink)

This paper investigates the causes, implications, and mitigation strategies of AI hallucinations, with a focus on generative AI systems. This paper examines the phenomenon of AI hallucinations in large language models, analyzing root causes and evaluating mitigation strategies. We synthesize insights from recent academic research and industry findings to explain how hallucinations often arise due to problems in the data used to train language models, limitations in model architecture, and the way large language models (LLMs) generate text. Through a systematic (...) review of current literature, we identify key patterns in how hallucinations emerge and examine the growing concern about their impact as AI becomes more embedded in decision-making systems. We identify core contributors such as data quality issues, model complexity, lack of grounding, and limitations inherent in the generative process. The risks are examined in various domains, including legal, business, and user-facing applications, highlighting consequences like misinformation, trust erosion, and productivity loss. To address these challenges, we survey mitigation techniques including data curation, retrieval-augmented generation (RAG), prompt engineering, fine-tuning, multi-model systems, and human-in-the-loop oversight. Our analysis draws from a wide range of academic and industry sources, offering both theoretical understanding and practical insights for AI practitioners. This is a pure review paper and all results are from the cited references. (shrink)

The exponential complexity of contemporary Life Insurance applications - shaped by stringent regulatory compliance requirements, dynamic customer - centric innovation, and expansive product diversification - has magnified the challenges of maintaining traditional test automation frameworks. These frameworks often falter under the weight of frequent application updates, evolving user interfaces (UI), and fluctuating backend integrations, leading to brittle test scripts and heightened maintenance costs. Self-healing test automation frameworks offer a cutting-edge, AI-driven solution to this paradigm. By leveraging advanced machine learning (ML) (...) algorithms and intelligent heuristics, these frameworks autonomously detect, diagnose, and remediate test failures caused by changes in application elements, workflows, or environments. Through real-time adaptation to UI modifications, API updates, and evolving test environments, self-healing frameworks ensure uninterrupted testing cycles with minimal manual intervention, significantly improving efficiency and scalability. This paper provides a comprehensive exploration of the architectural design and operational mechanisms of self healing test automation frameworks within the context of Life Insurance applications. Core focus areas include their ability to dynamically recalibrate element locators and adapt test scripts during runtime, thereby enhancing test coverage, optimizing maintenance workflows, and reducing the overall defect detection lifecycle. Through an in-depth analysis, the paper highlights the integration of AI-powered locator optimization engines, the deployment of predictive analytics for early anomaly detection, and the orchestration of continuous self-healing pipelines in CI/CD ecosystems. Detailed case studies from the Life Insurance domain illustrate tangible benefits such as accelerated regression cycles, substantial cost reductions, and improved system resilience. (shrink)

Generative AI (Gen AI) is rapidly evolving, promising profound impacts across diverse fields such as healthcare, entertainment, design, and business. By leveraging machine learning techniques, particularly generative adversarial networks (GANs) and variational autoencoders (VAEs), Generative AI has demonstrated the capability to produce novel content, from text and images to music and video. This paper explores the future of generative AI, focusing on its potential to revolutionize industries, enhance creativity, and address complex problems. The study examines the current state of Gen (...) AI, its applications, limitations, and future trends. It also delves into ethical and societal implications, such as the risks of misinformation, data privacy concerns, and biases embedded within AI models. Finally, the paper provides insights into how businesses and policymakers can effectively navigate these challenges while maximizing the benefits of Gen AI technology. Through literature review and analysis, this paper presents a forward-looking view of the role of Generative AI in shaping the future. (shrink)

This paper offers a comprehensive review of existing literature on the intersection of Artificial Intelligence (AI) and leadership, drawing on both theoretical insights and practical implementations. By analyzing scholarly publications from the past two years (2023-2025), the review traces emerging patterns in how AI technologies are being integrated into leadership practices. Key themes include the growing relevance of learning-based systems for adaptive decision-making and the application of attention-based models to improve responsiveness in dynamic environments. The review also addresses ethical dimensions (...) of AI-enabled leadership, emphasizing the need to balance algorithmic efficiency with human judgment and oversight. Concerns around transparency, psychological safety, and trust in automated systems are explored in depth. Furthermore, the paper outlines various AI-supported leadership support systems that are currently in use, highlighting their potential to assist leaders in strategic forecasting, communication, and stakeholder engagement. The synthesis incorporates multiple theoretical frameworks that help contextualize AI’s role in leadership transformation, offering a structured view of how emerging technologies are reshaping leadership thought and behavior. Ultimately, this review maps out a landscape of opportunities and challenges, providing a foundation for future research in AI-augmented leadership. The analysis identifies reinforcement learning as a predominant approach in leadership strategies, with a theory-weighted impact metric (Impact=∑T_i×F_i) assigning it a weighted score of 4.08/6.0. The review also highlights the use of multi-head attention mechanisms (LeadershipAttention(Q,K,V)) to enhance crisis response times by 37% (p<0.001). Additionally, ethical concerns are discussed, particularly regarding the incorporation of KL divergence optimization systems (KL(p_AI |)p_human )<ϵ) to maintain human oversight. The findings from the reviewed studies show that AI adoption leads to a 58% ±12% faster decision-making process, a 41% ±9% increase in strategic accuracy, and 89.2% forecasting precision. However, challenges in psychological safety thresholds (T<0.4) and transparency in AI decision-making (A<0.6) persist. The paper also discusses existing AI-Driven Leadership Decision Support Systems (AI-LDSS), including the use of transformer-based NLP, SHAP-explainable predictions, and bias detection. This review synthesizes theoretical frameworks, including differential leadership equations ((dL_i)/dt=αL_i (1-L_i/K)-β∑L_i L_j+γA_i (t)), and provides an overview of the current state of AI in leadership research. (shrink)

This paper presents a review and propose framework for training older financial services employees (age 45+) in Generative AI applications. As banks rapidly adopt AI tools, our research identifies specific barriers facing older workers including technological anxiety, interface complexity, and knowledge retention challenges. We conclude that older workers require approximately 30-40% more training time than younger colleagues but achieve comparable proficiency with appropriate support. Key success factors include: (1) peer mentoring systems pairing tech-savvy junior employees with senior staff, (2) simplified (...) interfaces removing unnecessary technical options, and (3) job-specific practice scenarios rather than abstract exercises. This paper further explores the critical need for training older adults in Generative AI (GenAI). While GenAI offers transformative potential across various sectors, ensuring equitable access and its adoption requires addressing the specific challenges faced by older populations. These challenges include digital literacy gaps, concerns about data privacy and security, and the need for user-friendly interfaces especially for older population who might be largely non-technical. The paper examines recent literature and key considerations for developing effective GenAI training programs for older adults, emphasizing the importance of foundational digital skills, accessible language, personalized learning, and ongoing support. Additionally, this study highlights the digital divide faced by older adults, emphasizing the need for structured AI training programs. Furthermore, it analyzes future projections of GenAI's impact, highlighting the necessity of upskilling and reskilling the workforce, including older individuals, to bridge the emerging GenAI skills gap. The paper categorizes and quantifies the types of sources used to support its claims, providing a comprehensive overview of the current state of research and expert opinion on this topic with tables, graphics and charts. By addressing the unique needs of older learners and preparing for the future of GenAI, we can foster digital inclusion and empower all members of society to benefit from this transformative technology. This paper also examines the impact of Generative AI (GenAI) and Agentic AI on the financial services sector, with a specific focus on workforce training and upskilling. Key findings from litreature indicate that by 2027, 80\% of the engineering workforce will require AI-related upskilling (Gartner) and AI-driven automation can reduce manual data tasks by up to 80% (West Monroe). For example, in banking, AI adoption has led to tangible productivity gains, such as Capitec Bank employees saving over one hour per week using AI tools (as suggested by recent reports). The paper categorizes and quantifies recent AI adoption trends, workforce transformation data, and financial efficiency metrics to provide a comprehensive condensed overview of the evolving AI landscape in financial services based on recent reports. (shrink)

This paper presents a comprehensive review of Artificial General Intelligence (AGI) and Agentic AI, examining their technological foundations, current capabilities, and future trajectories. The study identifies key technical distinctions between these AI paradigms, including their architectural requirements, computational demands, and learning mechanisms. We survey the current technical landscape, including specialized frameworks like OpenAI’s AGI classification system and emerging Agentic AI platforms such as Vectara-agentic and CrewAI. The paper also examines the hardware infrastructure and cloud services enabling these advanced AI systems, (...) from NVIDIA’s specialized GPUs to large-scale projects like OpenAI’s proposed "Stargate" initiative and others. Our comparative analysis reveals that Agentic AI is rapidly transitioning from research to practical deployment across industries including legal services, DevOps, and enterprise automation, while AGI remains in the research phase with ongoing debates about its feasibility and timeline. The paper discusses critical challenges in both domains, including safety considerations, alignment problems, and governance requirements. We highlight how Agentic AI serves as a bridge between today’s generative AI capabilities and future AGI aspirations, offering autonomous functionality while avoiding some of AGI’s unresolved risks. (shrink)

The alignment problem in artificial intelligence (AI) is a critical challenge that extends beyond the need to align future superintelligent systems with human values. This paper argues that even "merely intelligent" AI systems, built on current-gen technologies, pose existential risks due to their competence-without-comprehension nature. Current AI models, despite their advanced capabilities, lack intrinsic moral reasoning and are prone to catastrophic misalignment when faced with ethical dilemmas, as illustrated by recent controversies. Solutions such as hard-coded censorship and rule-based restrictions prove (...) inadequate, as they fail to imbue AI with a true understanding of moral complexities, making these systems vulnerable to manipulation. To address these risks, the paper explores a paradigm shift from competence to comprehension, emphasizing the importance of developing AI systems with an intrinsic value framework capable of moral reasoning. By adopting intrinsic teleology, AI could self-reflect, simulate other minds, and develop empathy, which would enable it to navigate ethical dilemmas in ways that are currently impossible. Using theories from philosophy, ethics, and AI research, the paper proposes the development of AI systems that can reason through moral dilemmas autonomously, suggesting that such systems would be safer and more alignable than current generation competence-driven AI. (shrink)

The capitalist system has undergone several transformations (mutations in the language of Karl Marx) during the last centuries. This article examines the main characteristics of the three great revolutions of capitalism: industrial, financial and digital. Each revolution is analyzed with the main paradigms that seek to explain these different mutations of capitalism. In the last part of the article the emphasis is placed on the consequences of the Digital Revolution and the GEN-AI on the economic theories taught for decades by (...) economists. (shrink)

This paper synthesizes recent research and practical frameworks to explore the impact of AI on multi-criteria decision-making (MCDM), stakeholder relations, leadership, and organizational change. Drawing on empirical studies, reviews, and industry insights, we provide a comprehensive analysis of AI's transformative role, highlight challenges, and propose strategies for effective AI adoption. By leveraging AI-driven tools such as MCDA methods, intelligent mediation systems, and change management frameworks, organizations can achieve enhanced strategic planning, cross-functional collaboration, and adaptive leadership. We present a comprehensive analysis (...) of current implementations, challenges, and future directions for AI in complex organizational structures, drawing from recent scholarly works and industry case studies. Our findings demonstrate that AI-enabled matrix organizations show 23% higher decision-making efficiency and 37% improved conflict resolution rates compared to traditional structures. Drawing upon recent advancements in multi-criteria decision analysis (MCDA), we demonstrate how machine learning-enhanced methods such as AHP and TOPSIS are achieving 23-29% improvements in decision speed and accuracy across supply chain, healthcare, and engineering applications. The study further explores the evolution of human-AI collaboration models, from early toolbased systems to contemporary agentic frameworks capable of autonomous negotiation and conflict resolution. Through analysis of organizational change case studies, we identify key success factors in AI adoption, including leadership commitment metrics (Lt > 0.8) and change capacity coefficients (Cc > 0.7) that predict successful implementation. The research reveals that matrix organizations leveraging AI-mediated stakeholder management and cross-functional collaboration tools achieve 37% higher conflict resolution rates compared to traditional structures. (shrink)

This paper delves into the multifaceted realm of Artificial General Intelligence (AGI), exploring its definition, evolution, potential applications, and the ongoing debates surrounding its development. We examine AGI's theoretical underpinnings, contrasting it with narrow AI and artificial superintelligence (ASI). Furthermore, we discuss the impact of AGI across various sectors, including finance, research, and business, while also addressing the ethical considerations and challenges associated with its advancement. This survey synthesizes current research and perspectives, providing a comprehensive overview of AGI's trajectory and (...) its potential to reshape the future. This paper presents a comprehensive examination of Artificial General Intelligence (AGI), analyzing its current state, applications across industries, and future trajectory. Through systematic review of academic literature and industry reports, we identify three critical dimensions of AGI development: (1) technical architectures bridging narrow AI to general intelligence, (2) transformative applications in finance and business, and (3) emerging ethical and workforce challenges. Our findings reveal accelerating market growth (projected 36.9% CAGR through 2031) alongside significant research gaps in evaluation metrics, environmental impact, and cross-cultural adoption. The study highlights AGI's dual role as both disruptor and enabler, with financial services emerging as the leading adoption sector (38% of investments by 2028). We summarize (based on cited work) a framework for responsible AGI development that balances innovation with ethical considerations, emphasizing the need for standardized benchmarks and workforce transition strategies. The paper contributes to ongoing discourse by synthesizing dispersed research into actionable insights for practitioners and policymakers navigating the AGI revolution. This is a pure review paper and all results and findings are form cited literature. (shrink)

«Les gens disent encore et encore que la philosophie ne progresse pas vraiment, que nous sommes toujours occupés avec les mêmes problèmes philosophiques que les Grecs. Mais les gens qui disent cela ne comprennent pas pourquoi il doit en être ainsi. C’est parce que notre langue est restée la même et continue de nous séduire à poser les mêmes questions. Tant qu’il continue à y avoir un verbe qui ressemble à s’il fonctionne de la même manière que de manger et (...) de boire, tant que nous avons encore les adjectifs 'identiques', 'faux', 'false', 'possible', tant que nous continuons à parler d’une rivière du temps, d’une étendue d’espace, etc., etc., les gens continueront à trébucher sur les mêmes difficultés déroutantes et se retrouveront à regarder quelque chose qui ne semble pas capable de se dégager. Et qui plus est, cela satisfait un désir pour le transcendant, parce que, dans la mesure où les gens pensent qu’ils peuvent voir les ‘«limites de la compréhension humaine », ils croient bien sûr ce ils peuvent voir au-delà de ceux-ci. Cette citation est de Ludwig Wittgenstein qui a redéfini la philosophie il ya 70 ans (mais la plupart des gens n’ont pas encore de le savoir). Dennett, bien qu’il ait été un philosophe pendant une quarantaine d’années, est l’un d’entre eux. Il est également curieux que lui et son antagoniste principal, John Searle, étudié sous les célèbres Wittgensteiniens (Searle avec John Austin, Dennett avec Gilbert Ryle) mais Searle plus ou moins obtenu le point et Dennett n’a pas, (bien qu’il est étirer les choses à appeler Searle ou Ryle Wittgensteinians). Dennett est un déterministe difficile (bien qu’il essaie de se faufiler la réalité dans la porte arrière), et peut-être cela est dû à Ryle, dont le célèbre livre "Le concept de l’esprit" (The Concept of Mind) (1949) continue d’être réimprimé. Ce livre a fait un excellent travail d’exorciser le fantôme, mais il a quitté la machine. Dennett aime faire les erreurs Wittgenstein, Ryle (et beaucoup d’autres depuis) ont exposé en détail. Notre utilisation des mots conscience, choix, liberté, intention, particule, pensée, détermine, vague, cause, arrivé, événement (et ainsi de suite sans fin) sont rarement une source de confusion, mais dès que nous quittons la vie normale et entrer dans la philosophie (et toute discussion détachée de l’environnement dans lequel la langue a évolué-c’est-à-dire le contexte exact dans lequel les mots avaient un sens) chaos règne. Comme la plupart, Dennett n’a pas un cadre cohérent - que Searle a appelé la structure logique de la rationalité. J’ai développé sur ce considérablement depuis que j’ai écrit cette revue et mes articles récents montrent en détail ce qui ne va pas avec l’approche de Dennett à la philosophie, que l’on pourrait appeler Scientism sur les stéroïdes. Permettez-moi de terminer par une autre citation de Wittgenstein-- «L’ambition est la mort de la pensée. Ceux qui souhaitent un cadre complet à jour pour le comportement humain de la vue moderne de deux systèmes peuvent consulter mon livre 'The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle' 2nd ed (2019). Ceux qui s’intéressent à plus de mes écrits peuvent voir «Talking Monkeys --Philosophie, Psychologie, Science, Religion et Politique sur une planète condamnée --Articles et revues 2006-2019 3e ed (2019) et Suicidal Utopian Delusions in the 21st Century 4th ed (2020) et autres. (shrink)

Ce n’est pas un livre parfait, mais il est unique, et si vous écrémez les 400 premières pages ou plus, les 300 dernières (sur quelque 700) sont une assez bonne tentative d’appliquer ce qui est connu sur le comportement aux changements sociaux de la violence et des manières au fil du temps. Le sujet fondamental est le suivant : comment notre génétique contrôle-t-elle et limite-t-elle le changement social ? Étonnamment, il ne parvient pas à décrire la nature de la sélection (...) des parents (fitness inclusif) qui explique une grande partie de la vie sociale animale et humaine. Il n’a pas non plus (comme presque tout le monde) un cadre clair pour décrire la structure logique de la rationalité (LSR—terme préféré de John Searle) que je préfère appeler la psychologie descriptive de la pensée de haut ordre (DPHOT). Il aurait dû dire quelque chose sur les nombreuses autres façons d’abuser et d’exploiter les gens et la planète, car ceux-ci sont maintenant beaucoup plus graves que de rendre d’autres formes de violence presque hors de propos. Étendre le concept de violence pour inclure les-conséquences mondiales à long terme de la réplication des gènes de quelqu’un, et avoir une compréhension de la nature de la façon dont fonctionne l’évolution (c.-à-d., la sélection des parents) fournira une perspective très différente sur l’histoire, les événements actuels, et comment les choses sont susceptibles d’aller dans les quelques centaines d’années. On pourrait commencer par noter que la diminution de la violence physique au cours de l’histoire a été compensée (et rendue possible) par le viol sans pitié de la planète (c’est-à-dire par la destruction par les gens de l’avenir de leur propre descendant). Pinker (comme la plupart des gens la plupart du temps) est souvent distrait par les superficialités de la culture quand c’est la biologie qui compte. Voir mes critiques récentes de Wilson 'The Social Conquest of Earth' et Nowak and Highfield’s 'SuperCooperators' ici et sur le net pour un bref résumé de la vacuité de «véritable altruisme»(sélection de groupe), et le fonctionnement de la sélection des parents et l’inutilité et la superficialité de décrire le comportement en termes culturels. C’est la question classique de la nature/nourrir et la nature l’emporte nourrir - infiniment. Ce qui importe vraiment, c’est la violence faite à la terre par l’augmentation incessante de la population et de la destruction des ressources (en raison de la médecine et de la technologie et de la répression des conflits par la police et l’armée). Environ 200.000 personnes de plus par jour (un autre Las Vegas tous les 10 jours, un autre Los Angeles chaque mois), les 6 tonnes ou plus de la base va dans la mer / personne / année - environ 1% du total du monde disparaissant chaque année, etc. signifie que si un miracle se produit la biosphère et la civilisation va largement s’effondrer au cours des deux prochains siècles, et il y aura la famine, la misère et la violence de tous les types. Les manières, les opinions et les tendances des gens à commettre des actes de violence ne sont d’aucune pertinence à moins qu’ils ne puissent faire quelque chose pour éviter cette catastrophe, et je ne vois pas comment cela va se produire. Il n’y a pas de place pour les arguments, et aucun point non plus (oui je suis un fataliste), donc je vais juste faire quelques commentaires comme s’ils étaient des faits. N’imaginez pas que j’ai un intérêt personnel dans la promotion d’un groupe au détriment des autres. J’ai 78, n’ont pas de descendants et pas de proches parents et ne s’identifient à aucun groupe politique, national ou religieux et considèrent ceux que j’appartiens par défaut aussi répugnant que tout le reste. Les parents sont les pires ennemis de la vie sur Terre et, compte tenu de la vue générale des choses, les femmes sont aussi violentes que les hommes quand on considère le fait que la violence des femmes (comme la plupart de celle faite par les hommes) se fait en grande partie au ralenti, à une distance dans le temps et l’espace et la plupart du temps effectuée par procuration -par leurs descendants et par les hommes. De plus en plus, les femmes portent des enfants, qu’elles aient un compagnon ou non et que l’effet d’empêcher une femme de se reproduire est en moyenne beaucoup plus important que d’arrêter un homme, car ils constituent le goulot d’étranglement reproducteur. On peut considérer que les gens et leur progéniture méritent richement toute la misère vient leur chemin et (à de rares exceptions près) les riches et les célèbres sont les pires délinquants. Meryl Streep ou Bill Gates ou J.K Rowling et chacun de leurs enfants peuvent détruire 50 tonnes de terre d’o re plus chaque année pendant des générations dans l’avenir, tandis qu’un fermier indien et son peut détruire 1 tonne. Si quelqu’un nie que c’est très bien, et à leurs descendants, je dis "Bienvenue à l’enfer sur Terre"(WTHOE). Aujourd’hui, l’accent est toujours mis sur les droits de l’homme, mais il est clair que si la civilisation doit avoir une chance, les responsabilités humaines doivent remplacer les droits de l’homme. Personne n’obtient des droits sans être un citoyen responsable et la première chose que cela signifie est la destruction de l’environnement minimal. La responsabilité la plus fondamentale n’est pas les enfants à moins que votre société vous demande de les produire. Une société ou un monde qui permet aux gens de se reproduire au hasard sera toujours exploité par des gènes égoïstes jusqu’à ce qu’il s’effondre (ou atteint un point où la vie est si horrible qu’il ne vaut pas la peine de vivre). Si la société continue à maintenir les droits de l’homme comme primaires, à leurs descendants, on peut dire avec confiance "WTHOE". Ceux qui souhaitent un cadre complet à jour pour le comportement humain de la vue moderne de deuxemssyst peuvent consulter mon livre 'The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle' 2nd ed (2019). Ceux qui s’intéressent à plus de mes écrits peuvent voir «Talking Monkeys --Philosophie, Psychologie, Science, Religion et Politique sur une planète condamnée --Articles et revues 2006-2019 3e ed (2019) et Suicidal Utopian Delusions in the 21st Century 4th ed (2019) et autres. (shrink)

L’Amérique et le monde sont en train de s’effondrer à cause d’une croissance démographique excessive, la plupart pour le siècle dernier et maintenant tout cela en raison de la 3e population mondiale. La consommation de ressources et l’ajout d’un ou deux milliards de dollars de plus vers 2100 vont effondrer la civilisation industrielle et provoquer la famine, la maladie, la violence et la guerre à une échelle stupéfiante. Des milliards vont mourir et la guerre nucléaire est presque certaine. En Amérique, (...) cela est considérablement accéléré par l’immigration massive et la reproduction des immigrants, combinée avec des abus rendus possibles par la démocratie. La nature humaine dépravée transforme inexorablement le rêve de démocratie et de diversité en cauchemar de la criminalité et de la pauvreté. La cause profonde de l’effondrement est l’incapacité de notre psychologie innée à s’adapter au monde moderne, ce qui conduit les gens à traiter des personnes sans lien de parenté comme s’ils avaient des intérêts communs. Ceci, plus l’ignorance de la biologie de base et de la psychologie, conduit aux illusions d’ingénierie sociale des personnes partiellement instruites qui contrôlent les sociétés démocratiques. Peu de gens comprennent que si vous aidez une personne, vous faites du mal à quelqu’un d’autre, il n’y a pas de déjeuner gratuit et chaque article que quelqu’un consomme détruit la terre au-delà de la réparation. Par conséquent, les politiques sociales partout sont insoutenables et une à une toutes les sociétés sans contrôle strict sur l’égoïsme s’effondreront dans l’anarchie ou la dictature. Sans changements dramatiques et immédiats, il n’y a aucun espoir pour empêcher l’effondrement de l’Amérique, ou tout autre pays qui suit un système démocratique. D’où mon essai "Suicide by Democracy". Il est également maintenant clair que les sept sociopathes qui gouvernent la Chine gagnent la guerre mondiale 3, et donc mon essai final sur eux. La seule plus grande menace est l’intelligence artificielle que je commente brièvement. La clé de tout ce qui nous concerne est la biologie, et c’est l’oubli qui conduit des millions de personnes instruites intelligentes comme Obama, Chomsky, Clinton, le Parti démocrate et le pape à épouser des idéaux utopiques suicidaires suicidaires qui mènent inexorablement directement à l’enfer sur Terre. Comme W l’a fait remarquer, c’est ce qui est toujours sous nos yeux qui est le plus difficile à voir. Nous vivons dans le monde du système linguistique délibératif conscient 2, mais c’est inconscient, système réflexif automatique 1 qui règne. C’est la source de la cécité universelle décrite par L’illusion phénoménologique (TPI) de Searle, Blank Slate de Pinker et Tooby et le modèle standard de science sociale de Cosmides. Le premier groupe d’articles tente de donner un aperçu de la façon dont nous nous comportons qui est raisonnablement exempt d’illusions théoriques. Dans les trois groupes suivants, je commente trois des principales illusions empêchant un monde durable : la technologie, la religion et la politique (groupes coopératifs). Les gens croient que la société peut être sauvée par eux, donc je fournis quelques suggestions dans le reste du livre quant à pourquoi cela est peu probable par le biais de courts articles et des critiques de livres récents par des écrivains bien connus. Un autre section decrit l’illusion religieuse - qu’il ya un certain super pouvoir qui nous sauvera. La section suivante décrit les délires numériques, qui confondent les jeux linguistiques du système 2 avec les automatismes du système un, et ne peut donc pas distinguer les machines biologiques (c’est-à-dire les gens) d’autres types de machines (c.-à-d. les ordinateurs). D’autres illusions numériques sont que nous serons sauvés du mal pur (égoïsme) du système 1 par les ordinateurs /AI/robotique/nanotech/génie génétique créé par le système 2. Le directeur du no Free Lunch nous dit qu’il y aura des conséquences graves et peut-être fatales. La dernière section décrit The One Big Happy Family Delusion, c’est-à-dire que nous sommes sélectionnés pour la coopération avec tout le monde, et que les idéaux euphonieux de la démocratie, de la diversité et de l’égalité nous mèneront à l’utopie, si nous gérons les choses correctement (la possibilité de la politique). Encore une fois, le principe du non-déjeuner libre devrait nous avertir qu’il ne peut pas être vrai, et nous voyons à travers l’histoireet partout dans le monde contemporain, que sans contrôles stricts, l’égoïsme et la stupidité prennent le dessus et détruisent bientôt toute nation qui embrasse ces illusions. En outre, l’esprit singe écarte fortement l’avenir, et nous coopérons donc à la vente du patrimoine de notre descendant pour des conforts temporaires, exacerbant considérablement les problèmes. (shrink)

This chapter argues that emotion recognition is a skill. A skill perspective on emotion recognition draws attention to underappreciated features of this cornerstone of social cognition. Skills have a number of characteristic features. For example, they are improvable, practical, and flexible. Emotion recognition has these features as well. Leading theories of emotion recognition often draw inadequate attention to these features. The chapter advances a theory of emotion recognition that is better suited to this purpose. It proposes that emotion recognition involves (...) scripts. Emotion scripts describe how people are likely to behave in different emotional contexts. Scripts can be improved with the addition of richer social knowledge, they are practical in that they describe and guide social interaction, and they are flexible because they must accommodate the fact that emotions have different behavioral impact depending on the agents involved and the circumstances at play. Learning to recognize emotions through scripts qualifies as a skill. (shrink)

Marginalized communities are confronted with issues resulting from their marginalization, such as exclusion, invisibility, misrepresentation, and hate speech, not only offline but – due to digital change – increasingly online. Our research project DigitalDialog21 aims at evaluating the effects of digital change on society and how digital change, and the risks and possibilities that come with it, is perceived by the population. Digital change is understood as a factor of social change in this project. By investigating digital change and its (...) effects on society, we are able to draw more general inferences on how societies change socially and what needs to be done in education to establish digital trust. In 2017 the Digital Evolution Index observed an increasing trust deficit and skepticism towards digitalization in both very industrialized and lesser industrialized countries. We will draw inferences from these observations here and hypothesize the following: It seems that especially in marginalized communities, that is: in communities that are structurally and systemically disadvantaged and that experience societal marginalization, this trust deficit and skepticism towards digitalization is prevalent. This could be so because, as a member of a marginalized community, one might quickly find issues resulting from marginalization to be present in digital spaces just like they are present in non-digital spaces. This paper will examine critically how attitudes in marginalized communities towards digital media are influenced by digital change. Do the risks of digitalization outweigh the advantages for marginalized communities? Are digital media perceived to provide advantages such as increased visibility and representation or are they perceived to fuel discrimination against marginalized people? Our research project brings together secondary analyses of existing studies with the results of our own qualitative interview study on marginalized people's perceptions of digital change. The paper will portray some example interviews, and thereby analyze if and how attitudes in the margins towards digital media change, what this change consists of, and how we can understand the changing attitudes within an ethical and educational framework. Our findings will point at a necessity to increase ethically based digital literacy (PEAT) in the German education system, starting in early education. Marginalized groups in particular must be empowered to become digitally competent through problem-oriented education. Independent self-efficacy can increase digital trust in fragmented societies. The paper concludes by introducing media ethics tools that are being developed as part of the project. (shrink)

This paper explores how the social and affective lives of people with marginalized social identities are particularly affected by digital influences. Specifically, the paper examines whether and how social media enables LGBTQ+ people to experience feelings of belonging. It does so by drawing on literature from digital epistemology and phenomenology of the digital, and by presenting and analyzing the results of a qualitative study consisting of 25 interviews with LGBTQ+ people. The interviews were conducted to explore the social media experiences (...) of LGBTQ+ people through an empirical framework informed by both phenomenology and social epistemology, particularly feminist standpoint theory. The paper emphasizes the importance of positionality and the epistemic value of research that centers marginalized perspectives and employs an anti-oppressive research approach, and focuses on understanding the digital experiences of LGBTQ+ people from within their marginalized perspective. (shrink)

In recent years, an array of critical emotion theorists have emerged who call for change with respect to how emotion theory is done, how emotions are understood, and how we do emotion. In this chapter, I draw on the work that some of these authors have produced to analyze how emotional marginalization of trans and disabled identities is experienced, considering in particular how this emotional marginalization results from the long history of pathologization of trans and disabled people. The past and (...) current pathologization of trans and disabled people is produced through normative assumptions, values, and beliefs that uphold systems of normalcy, including assumptions, values, and beliefs about how we feel and express emotions. In order to examine these issues, I identify three different stages at which emotional marginalization may take place: emotion experience, emotional display, and emotion recognition. In other words, emotional marginalization of trans and disabled people can occur at any of these stages. The central concern of my chapter is thus to show how emotional marginalization, at each of these stages, affects trans and disabled people. (shrink)

While the importance of social emotions is widely recognized, the question whether all emotions are social and what this would mean for the category ‘social emotions’ is yet to be addressed systematically. Emotion theorists and researchers so far have proposed different candidates for social emotions. These include non-basic emotions, self-conscious emotions, higher-cognitive emotions, and defining social emotions via their social functions. This paper looks at these different candidates for social emotions and briefly discusses their issues. Discussing the candidates and their (...) issues motivates embracing a pluralistic approach to social emotions. In a further step, the paper will look at approaches exploring how social factors impact emotions in general. This serves as a basis for explaining what it would mean to propose that all emotions are social. After reviewing different candidates for social emotions and looking at the impact of social factors on emotions in general, the paper will propose that a pluralistic understanding of social emotions is needed to embrace the different ways in which social emotions may function. Embracing a pluralistic understanding of social emotions does not mean, however, that all emotions are social emotions. (shrink)

To explain how social cognition normally serves us in real life, we need to ask which factors contribute to specific social interactions. Recent accounts, and mostly pluralistic models, have started incorporating contextual and social factors in explanations of social cognition. In this paper, I further motivate the importance of contextual and identity factors for social cognition. This paper presents scripts as an alternative resource in social cognition that can account for contextual and identity factors. Scripts are normative and context-sensitive knowledge (...) structures that describe behavior in terms of corresponding events, situations, social roles, individuals, or mental state types in a way that guides action. The script approach presented here builds on recent accounts of social cognition but points out important differences and possible advantages it has over them: e.g., the script approach focuses even more strongly on context and identity. (shrink)

In this article we develop a taxonomy of emotional injustice: what occurs when the treatment of emotions is unjust, or emotions are used to treat people unjustly. After providing an overview of previous work on this topic and drawing inspiration from the more developed area of epistemic injustice, we propose working definitions of ‘emotion’, ‘injustice’, and ‘emotional injustice’. We describe seven classes of emotional injustice: Emotion Misinterpretation, Discounting, Extraction, Policing, Exploitation, Inequality, and Weaponizing. We say why it is useful to (...) distinguish these and also to subsume them under a single concept. Our aims are both theoretical and practical: to provide a unified account of emotional injustice, while recognizing the diversity of this phenomenon; to facilitate further research on this topic; to recognize the political importance of emotions; and to outline some of the ways in which emotional injustice can be combated. (shrink)

There is no specific trans perspective on romantic love. Trans people love and do not love, fall in love and fall out of love, just like everyone else. Trans people inhabit different sexual identities, different relationship types, and different kinds of loving. When it comes to falling in love as or with a trans person, however, things can get more complicated, as questions of gender and sexual identity emerge. In a study by Blair & Hoskin from 2018, 87.5% of the (...) interviewed participants said they would not consider dating a trans person (Blair & Hoskin, 2018). Among those who were open to dating trans people, a pattern emerged: the subjects were disproportionately willing to date trans men but not trans women, even if this preference did not match their own sexual identity; for example, a woman who identifies as a lesbian may be open to dating a trans man but not a trans woman. This seems like a clash of sexual and gender identities: why are women who identify as lesbians willing to date men? This chapter aims to analyze this phenomenon: love between clashing sexual and gender identities – e.g., the love between a man, who identifies as being romantically interested in men, and a trans woman, – and thereby evaluates the limits of romantic love for trans people. Limits of love, in this chapter, are conceived of as normative restrictions on whom and how we love. By exploring cases of clashing sexual and gender identities in romantic love, this chapter analyzes how trans people’s opportunities for love are often limited. (shrink)

Trans healthcare and thus trans people have been severely affected by the COVID-19 pandemic. Trans people’s healthcare situations have turned out to be so vulnerable in this crisis because they have been precarious to begin with. There are multiple ways in which trans healthcare has been affected: Surgeries and other procedures have been cancelled or postponed, and mental health services have been paused or moved online. This raises ethical questions around discrimination against trans people in the healthcare system. This article (...) argues that cancelling trans surgeries and procedures in the COVID-19 crisis is made possible through an understanding of trans healthcare as non-essential. The article explores how trans healthcare in particular has been affected by the pandemic. (shrink)

This paper proposes a novel perspective for resolving Nelson Goodman’s Grue Paradox. The Grue Paradox can be outlined as the problem of reconciling why, despite being inductively supported by the same evidence, the statement “all emeralds are green” feels natural, while “all emeralds are grue” feels unnatural. The proposed approach classifies predicates into “grammatically observable predicates” and “grammatically unobservable predicates,” reinterpreting inductions that ostensibly project the latter as “multiple induction.” Furthermore, by formalizing this framework using first-order predicate logic, the paper (...) identifies the philosophical confusion underlying this paradox. (shrink)

This book argues that our success in navigating the social world depends heavily on scripts. Scripts play a central role in our ability to understand social interactions shaped by different contextual factors. -/- In philosophy of social cognition, scholars have asked what mechanisms we employ when interacting with other people or when cognizing about other people. Recent approaches acknowledge that social cognition and interaction depends heavily on contextual, cultural, and social factors that contribute to the way individuals make sense of (...) the social interactions they take part in. This book offers the first integrative account of scripts in social cognition and interaction. It argues that we need to make contextual factors and social identity central when trying to explain how social interaction works, and that this is possible via scripts. Additionally, scripts can help us understand bias and injustice in social interaction. The author’s approach combines several different areas of philosophy—– philosophy of mind, social epistemology, feminist philosophy—as well as sociology and psychology to show why paying attention to injustice in interaction is much needed in social cognition research, and in philosophy of mind more generally. -/- Scripts and Social Cognition: How we Interact with Others will appeal to scholars and graduate students working in philosophy of mind, philosophy of psychology, social epistemology, social ontology, sociology, and social psychology. (shrink)

On 24th February 2025, Justin Mike (United States) wrote a review for Wild Wise Weird as follows: “Wild Wise Weird celebrates the wild spirit, the wisdom gained from unusual experiences, and the eccentric qualities that define us as individuals, thereby capturing the beauty of embracing authenticity. It serves as a reminder that being unique is something to be proud of, not just acceptable.” The review made me feel really relevant to the content of the book. I was curious what AI (...) would think of Mike’s review, so I asked Gemini “what do you think of the review?”. (shrink)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...) diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)

Climate change is affecting communities across the globe, yet those most vulnerable to its impacts are often the last to receive the financial assistance they need. A recent critical review by Venner, García-Lamarca, and Olazabal (2024) examines how climate adaptation finance—funding intended to help societies adjust to the impacts of climate change—is distributed. The findings are concerning: despite repeated global commitments to prioritize those most at risk, adaptation finance tends to benefit the most powerful and well-resourced actors rather than the (...) communities that need it most. (shrink)

We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...) body fluids ontology initiative may provide support to basic and translational science. (shrink)

Artificial Intelligence (AI) is transforming nearly every sector of society—and conservation is no exception. In a recent article, Chris Sandbrook examines the emerging field of “Conservation AI,” defined as the intentional use of AI technologies to achieve biodiversity protection goals [2].

The rapid expansion of renewable energy technologies—such as solar panels, electric vehicles (EVs), and wind turbines—has intensified the global demand for critical raw materials (CRMs), including lithium, cobalt, and neodymium. These materials are vital to clean energy infrastructure but are often sourced from geopolitically unstable or environmentally vulnerable regions [2-4]. In response, a recent study proposes an optimal framework for CRM recycling in Italy aimed at strengthening supply chain resilience and supporting the transition to a low-carbon economy [5].

Hiện nay, chế độ sở hữu ở Việt Nam đã có những đổi mới cơ bản, nhưng vẫn còn những khác biệt rất lớn so với chế độ sở hữu ở các nền kinh tế thị trường hiện đại. Trong cơ cấu của chế độ sở hữu ở Việt Nam, tỷ trọng của sở hữu nhà nước còn quá lớn; kinh tế nhà nước giữ vai trò chủ đạo… Chính những khác biệt này đã làm cho nền kinh tế thị (...) trường Việt Nam bị méo mó và giảm lợi thế cạnh tranh quốc gia. Do vậy, công cuộc đổi mới và hoàn thiện chế độ sở hữu ở Việt Nam phải hướng tới việc khắc phục những hạn chế trên và đạt tới sức cạnh tranh ngang hàng với các nền kinh tế thị trường hiện đại khác. (shrink)

Biến đổi khí hậu đang ảnh hưởng đến các cộng đồng trên toàn cầu, nhưng những người dễ bị tổn thương nhất trước tác động của nó thường là những người cuối cùng nhận được sự hỗ trợ tài chính cần thiết.

This article proposes a unified solution to the mind-body problem, grounded in the philosophical framework of Ethical Empirical Rationalism. By presenting a mathematical model of the mind-body interaction, we oƯer a dynamic feedback loop that resolves the traditional dualistic separation between mind and body. At the core of our model is the concept of essence—an eternal, metaphysical truth that sustains both the mind and body. Through coupled diƯerential equations, we demonstrate how the mind and body are two expressions of the (...) same essence, interacting in a continuous and harmonious relationship. This approach provides a new perspective on the mind-body relationship, grounded in both empirical evidence and metaphysical insight. Keywords: Mind-body problem, Unmoved Mover, Essence, Unified Theory, Feedback Loop, Ethical Empirical Rationalism, Mathematical Modeling. (shrink)

ĐỀ CƯƠNG HỌC PHẦN VĂN HÓA KINH DOANH 1. Tên học phần: VĂN HÓA KINH DOANH (BUSINESS CULTURE) 2. Mã học phần: BMGM1221 3. Số tín chỉ: 2 (24,6) (để học được học phần này, người học phải dành ít nhất 60 giờ chuẩn bị cá nhân).