artificial intelligence

Trust under threat: how AI vs. human mistakes in disaster alerts shape public perception and response

As artificial intelligence (AI) becomes increasingly integrated into disaster communication systems, understanding public responses to AI-led alerts is critical for designing trustworthy and effective crisis messaging. In line with an emerging line of inquiry, this study represents early empirical efforts to examine how the public responds to disaster alerts generated and delivered by AI, addressing a critical and timely gap in the disaster communication literature. Across two experiments (N = 599), we investigate how the attribution of disaster alerts (AI vs. human expert) shapes perceptions of message credibility, trust, and disaster coping outcomes. Study 1 finds that AI-led alerts are perceived as significantly less credible than expert-led alerts, although no significant differences emerge in coping outcomes such as self-efficacy, collective efficacy, or behavioral intentions. Study 2 extends these findings by introducing a factual error in the alert, revealing that AI sources suffer greater credibility and trust losses than human sources, despite being blamed less. Across both conditions, participants held human actors, such as experts, developers, and deploying organizations, more responsible than AI, yet consistently rated AI as less credible and trustworthy, even when greater responsibility predicted lower trust. Notably, errors made by human experts also diminished future interest in AI-based alerts, suggesting an interesting and complex shift in cross-source trust. These findings offer new insights into AI as a social actor within the disaster communication ecology and highlight the need for transparent, human-in-the-loop designs when deploying AI in public crisis messaging.

Few-shot neuromorphic vision in a nonlinear photonic network laser

With the growing prevalence of artificial intelligence (AI), demand increases for hardware that mimics the brain’s ability to extract structure from limited data. In the retina, ganglion cells detect features from sparse inputs via lateral inhibition, where neurons antagonistically suppress activity of neighboring cells. Biological neurons exhibit diverse heterogeneous nonlinear responses, linked to robust learning and strong performance in low-data regimes. Here, we introduce a retinally inspired photonic computing system where spatially competing lasing modes in a random network laser act as heterogeneous, inhibitively coupled neurons, enabling feature detection, few-shot classification, and segmentation. This silicon-compatible scheme harnesses heterogeneous excitatory and inhibitory nonlinear physical dynamics, which give rise to emergent photonic computing behavior, including parallel feature detection and strong performance when training data are scarce. We report 98.05 and 87.85% accuracy on MNIST and Fashion-MNIST, and 90.12% on BreakHis cancer diagnosis, outperforming software convolutional neural networks including EfficientNetV2 and the vision transformer ViT in few-shot and class-imbalanced regimes with training sets of up to several hundred images. We demonstrate combined segmentation and classification on the HAM10k skin lesion dataset, achieving DICE and Jaccard scores of 84.49 and 74.80%. These results demonstrate the potential of random lasing networks as nonlinear photonic learning systems and highlight the ability of heterogeneous nonlinear dynamics to support strong learning in challenging low-data scenarios.

Architectural Design: Crafting Ideas, Shaping Place Principles, Methods, and Contemporary Design Strategies part 3.

This part of the book examines the intellectual, methodological, and technological transformations that have reshaped contemporary architectural design through three interconnected themes: contemporary architecture and its environmental and digital directions; design evaluation as a transition from impression-based judgment to evidence-informed decision-making; and the integrated architectural project methodology as a framework that brings together knowledge, analysis, generation, evaluation, and implementation within a coherent design process. The book adopts the view that architecture is no longer an isolated formal activity but a multidimensional process in which environmental, economic, social, cultural, functional, and technological considerations interact continuously. The eight chapter addresses the main features of contemporary architecture, with particular emphasis on sustainability, environmental and climatic design, digital architecture, computational and parametric design, and the growing role of artificial intelligence and generative design in exploring alternatives, analyzing performance, and improving design decisions. It argues that digital tools do not replace architectural expertise or critical judgment; rather, they enhance both when applied within a framework that remains attentive to human experience, cultural context, data quality, and limitations of algorithms. The second chapter examines design evaluation as an integral component of the design process rather than as a subsequent and isolated procedure. It discusses the functional, formal, spatial, environmental, economic, and structural dimensions of evaluation, together with digital simulation, multi-criteria assessment, and post-occupancy evaluation. This chapter demonstrates that effective evaluation is not limited to measuring performance. Its primary value lies in transforming analytical results into applicable knowledge that supports the development of alternatives, improves project quality, reduces risks, and strengthens the feasibility. The ten chapter presents an integrated methodology for architectural projects. The methodology begins by defining the problem and objectives, collecting data, and analyzing the context and users. It then proceeds to formulate the vision, concept, and design strategy; generate alternatives; organize functions and spaces; develop massing and form; integrate environmental considerations and digital technologies; test performance; and finally develop, document, present, and defend the design decisions. The methodology emphasizes the iterative nature of design, in which the architect moves between different stages in response to evaluation findings and emerging information, thereby achieving genuine integration among understanding, generation, formal development, evaluation, documentation and communication. This section concludes that the quality of contemporary architectural design depends on its ability to balance creativity with methodological rigor, technology with human needs, environmental responsiveness with spatial identity, and the rapid generation of alternatives with the accurate verification of their performance. Accordingly, an integrated architectural project should not be understood merely as a final product but as a conscious, evidence-informed, and continuously developing professional practice that respects the uniqueness and context of every project. Keywords: contemporary architectural design, sustainability, environmental and climatic design, digital architecture, generative design, artificial intelligence, design evaluation, digital simulation, multi-criteria assessment, integrated architectural project.

From Social Media to Empathic Artificial Intelligence

Social technologies have profoundly transformed how people communicate, form relationships, and experience social connection. This chapter synthesizes two decades of research on social media and messaging platforms to extract lessons for new forms of social technology, such as empathic artificial intelligence. We propose that prior attempts to identify universal effects of social technology on connection are largely uninformative due to substantial heterogeneity across studies. We highlight and briefly review three key sources of heterogeneity: (1) the type and features of the technology, (2) how it is used, and (3) who is using it. We recommend that future research explicitly consider these sources of heterogeneity to better understand how technological advances will affect social life – and how they can be better designed to promote connection.

Architectural Design: Crafting Ideas, Shaping Place Principles, Methods, and Contemporary Design Strategies part 3.

This part of the book examines the intellectual, methodological, and technological transformations that have reshaped contemporary architectural design through three interconnected themes: contemporary architecture and its environmental and digital directions; design evaluation as a transition from impression-based judgment to evidence-informed decision-making; and the integrated architectural project methodology as a framework that brings together knowledge, analysis, generation, evaluation, and implementation within a coherent design process. The book adopts the view that architecture is no longer an isolated formal activity but a multidimensional process in which environmental, economic, social, cultural, functional, and technological considerations interact continuously. The eight chapter addresses the main features of contemporary architecture, with particular emphasis on sustainability, environmental and climatic design, digital architecture, computational and parametric design, and the growing role of artificial intelligence and generative design in exploring alternatives, analyzing performance, and improving design decisions. It argues that digital tools do not replace architectural expertise or critical judgment; rather, they enhance both when applied within a framework that remains attentive to human experience, cultural context, data quality, and limitations of algorithms. The second chapter examines design evaluation as an integral component of the design process rather than as a subsequent and isolated procedure. It discusses the functional, formal, spatial, environmental, economic, and structural dimensions of evaluation, together with digital simulation, multi-criteria assessment, and post-occupancy evaluation. This chapter demonstrates that effective evaluation is not limited to measuring performance. Its primary value lies in transforming analytical results into applicable knowledge that supports the development of alternatives, improves project quality, reduces risks, and strengthens the feasibility. The ten chapter presents an integrated methodology for architectural projects. The methodology begins by defining the problem and objectives, collecting data, and analyzing the context and users. It then proceeds to formulate the vision, concept, and design strategy; generate alternatives; organize functions and spaces; develop massing and form; integrate environmental considerations and digital technologies; test performance; and finally develop, document, present, and defend the design decisions. The methodology emphasizes the iterative nature of design, in which the architect moves between different stages in response to evaluation findings and emerging information, thereby achieving genuine integration among understanding, generation, formal development, evaluation, documentation and communication. This section concludes that the quality of contemporary architectural design depends on its ability to balance creativity with methodological rigor, technology with human needs, environmental responsiveness with spatial identity, and the rapid generation of alternatives with the accurate verification of their performance. Accordingly, an integrated architectural project should not be understood merely as a final product but as a conscious, evidence-informed, and continuously developing professional practice that respects the uniqueness and context of every project. Keywords: contemporary architectural design, sustainability, environmental and climatic design, digital architecture, generative design, artificial intelligence, design evaluation, digital simulation, multi-criteria assessment, integrated architectural project.

Karakteristik Guru Profesional Yang Tidak Tergantikan Oleh Artificial Intelligence

Perkembangan pesat teknologi kecerdasan buatan (Artificial Intelligence/AI) memberikan dampak besar dalam dunia pendidikan melalui penyediaan materi adaptif, efisiensi informasi, dan evaluasi pembelajaran otomatis. Namun, kemajuan ini memunculkan kekhawatiran terkait potensi pengikisan peran pendidik serta batas kemampuan teknologi dalam menggantikan fungsi mendasar guru, khususnya pada aspek pembentukan karakter, moral, dan nilai kemanusiaan peserta didik. Penelitian ini bertujuan untuk mengidentifikasi serta menganalisis karakteristik utama guru profesional yang tidak dapat digantikan oleh keberadaan AI. Metodologi yang digunakan adalah pendekatan kualitatif dengan jenis studi pustaka (library research) dan teknik analisis isi (content analysis) terhadap 16 sumber literatur berupa buku dan artikel ilmiah bereputasi terbitan tahun 2016–2026 yang relevan dengan profesionalisme guru, pembentukan karakter, dan teknologi AI. Hasil sintesis menemukan enam karakteristik utama guru profesional yang tidak tergantikan oleh AI, yaitu empati dan kepedulian terhadap peserta didik, keteladanan moral dan karakter, kemampuan membangun hubungan sosial, kreativitas dan inovasi pembelajaran, kemampuan menanamkan nilai dan budaya, serta kemampuan membimbing dan memotivasi peserta didik. Keterbatasan utama AI terletak pada ketiadaan pengalaman emosional, ikatan sosial timbal balik, pemahaman konteks kebudayaan yang mendalam, dan keteladanan nyata. Penelitian ini menyimpulkan bahwa AI tidak dapat menggantikan peran sentral guru profesional karena pendidikan tidak hanya berfokus pada efisiensi pemrosesan data, melainkan melibatkan dimensi relasional, moral, sosial, dan perkembangan manusia. AI sejatinya berfungsi sebagai teknologi pendukung untuk membantu tugas teknis-informasional. Sebagai rekomendasi, guru disarankan untuk terus mengasah literasi AI secara kritis dan etis guna mempermudah administrasi pembelajaran, sembari memperkuat kompetensi pedagogik, sosial, dan kepribadian. Selain itu, lembaga pendidikan dan pembuat kebijakan perlu memfasilitasi pelatihan integrasi teknologi yang berorientasi pada etika serta penguatan karakter pendidik.

Artificial Intelligence and tourism in APEC economies

The Impact of Artificial Intelligence (AI) in Content Personalization on Customer Experience and Purchase Intention among Generation Z Users of Shopee Indonesia: A Study of Aerostreet Footwear Consumers

The advancement of digital technologies and the adoption of artificial intelligence (AI) on e-commerce platforms have transformed consumer–business interactions through increasingly personalized content delivery. However, the effectiveness of AI-driven personalization in enhancing customer experience and stimulating purchase intention among Generation Z e-commerce users in Indonesia remains insufficiently understood. This study examines the influence of AI-based content personalization on customer experience and purchase intention and investigates the mediating role of customer experience in this relationship. A quantitative approach with a causal-associative research design was employed. Data were collected through questionnaires administered to 384 Generation Z users of Shopee Indonesia who had interacted with Aerostreet footwear products and were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings indicate that AI-based content personalization positively influences both customer experience and purchase intention. Customer experience also positively influences purchase intention and mediates the relationship between AI-based content personalization and purchase intention. These findings demonstrate that customer experience represents an important mechanism through which AI-driven personalization shapes consumers’ purchase intentions. The study contributes to the digital marketing literature by clarifying the relationship among AI-based content personalization, customer experience, and purchase intention in the context of Generation Z consumers on an Indonesian e-commerce platform. Practically, the findings highlight the importance of relevant product recommendations and customer experience optimization in developing effective AI-driven digital marketing strategies.

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality

Artificial intelligence in cellular senescence research: a systematic review assessing methodological quality and reporting standards using PROBAST + AI and TRIPOD + AI

Cellular senescence is a fundamental mechanism of biological ageing that has emerged as a critical target for therapeutic intervention in age related diseases. The coalesce of artificial intelligence and senescence research provides unprecedented opportunities in advancing our knowledge and treatment approaches. This systematic review study addresses the gap across diverse AI model and the heterogeneity in senescence, by conducting the extensive evaluation of the performance outcomes and methodological rigor of AI models using Prediction model Risk of Bias Assessment Tool + Artificial Intelligence (PROBAST + AI) and reporting completeness using Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis + Artificial Intelligence extension (TRIPOD + AI), providing the insights into AI models robustness and generalizability. For the articles, released between 2019 to 2025, across major databases 18 eligible studies was used for review, following PRISMA guideline. Quality and applicability were assessed by PROBAST + AI (4 domain) and reporting via TRIPOD + AI (27 items). The quantitative synthesis indicates that deep learning architectures, especially Convolutional Neural Networks (CNNs), are dominant which appeared in about 50% of the studies. These CNNs consistently outperform traditional machine learning methods in the analysis of morphological heterogeneity. While reported performance metrics were high, with accuracy ranging from 83.55% to 99.79%, the PROBAST + AI assessment indicates a high risk of bias in 83.33% (15/18) of studies, primarily driven by Analysis domain due to improper data splitting (data leakage) and lack of external validation. As well as adherence to TRIPOD + AI reporting standards was suboptimal with average of 62% ‘YES’; notably, with the major gap in 0% of studies pre-registered a protocol and only 44.4% made analytical code publicly available, severely limiting reproducibility. Evidently AI demonstrates immense potential to accelerate biomarker discovery and senolytic drug screening, particularly through label-free morphological analysis by DL models, despite of high quality concern and poor reproducibility limit reliability; also standardization, shared benchmarks, multi-omics integration, and explainable AI are essential concerns for clinical translation in aging research.

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality

Empathy and Artificial Intelligence

As artificial intelligence chatbots offer increasingly sophisticated emotional support, society faces a profound question: can a machine truly empathize? Empathy and Artificial Intelligence provides the first comprehensive roadmap for this pivotal moment. Moving beyond simple binaries of 'hype' or 'doom,' this interdisciplinary volume unites leading psychologists, philosophers, and engineers to explore the tangled web of synthetic care. Key chapters investigate the 'AI Advantage' – where machines often outperform humans in perceived empathy – alongside the 'AI Penalty,' where discovering the artifice corrodes trust. The text navigates the distinct landscapes of text-based LLMs and embodied robots, addressing urgent ethical dilemmas and exploring whether reliance on AI risks the atrophy of our moral capacities or enables synthetic agents to scaffold stronger human relationships. Essential for researchers, students, and curious observers, this book investigates whether outsourcing our emotional labor saves us time, or costs us our humanity.