explainable ai

The Responsibility Gap in Explainable AI

This paper critically examines the persistent responsibility gap in explainable artificial intelligence (XAI), arguing that current approaches fail to adequately bridge it. While XAI is often promoted as a remedy for the opacity of AI systems—the so-called “black box problem”—and as a way to enable human accountability...

AI-Generated Evidence and the Future of Digital Justice: An Empirical Study of Legal Acceptance, Forensic Reliability, and Regulatory Challenges

Diagnosing and correcting OpenET satellite evapotranspiration across U.S. climate zones: Error decomposition, explainable AI, and uncertainty quantification

BRISA Project Brochure

Innovation for Safer Industrial Workplaces Discover BRISA (Breakthrough Research on Industrial Safety Against Airborne Carcinogens and Emerging Pollutants), a Horizon Europe-funded research and innovation project working to improve air quality, reduce exposure to hazardous airborne substances and protect workers in ene...

Translators’ language competence in technology-mediated contexts: Building on past conceptualizations and charting future directions

Language competence is the driving force behind and the basis for advanced translation competence, yet rapid technological change requires it to be reconsidered in light of current professional realities. Against this backdrop, the article discusses the past and present conceptualizations, definitions, and changing man...

Leakage-Aware Explainable AI for Credit Risk Assessment of Perishable Food Supply-Chain SMEs Using Food Shelf-Life, Postharvest Loss and Digital Banking Data in Nigeria

Small and medium-sized enterprises (SMEs) operating in perishable food supply chains face intertwined operational and financial risks: inventory can deteriorate before sale, postharvest losses reduce cash available for repayment, and many firms have thin or irregular formal credit histories. This study proposes a leaka...

A Vectorium v5.0 Operator Model of Saturn's Polar Hexagon as a Mode‑6 Curvature–Holonomy Limit Cycle (v2.0)

This technical note presents a geometric toy model that illustrates how Saturn’s north‑polar hexagon can arise from the interaction between curvature patterns and holonomy transport inside a neutral manifold. The model is intentionally non‑physical: it does not attempt to simulate atmospheric dynamics. Instead, it prov...

Natural Resources for Human Health Original Research Explainable Machine Learning for Crop Yield Forecasting within an Agentic AI Decision Support System Natural Resources for Human Health

Data Analytics and AI

Data analytics and artificial intelligence (AI) are transforming geotechnical monitoring by extracting insights from large sensor datasets. This chapter covers analytics objectives (trend detection, anomaly identification, and prediction) and data types (time-series, spatial, imagery, and point clouds). We discuss prep...

Beyond access: AI literacy, instructional design and perceived autonomous learning among students in Indian higher education

Universities are rapidly adopting artificial intelligence, yet access to AI tools does not guarantee that students experience greater ownership of their learning. This study examines how three learner side factors, AI literacy, AI readiness and perceived value of AI tools, and one pedagogy side factor, AI enhanced inst...

Concept-Based Explainable AI in Retinal Imaging: Core Concepts, Techniques, and Challenges

Abstract In high-stakes domains like healthcare, establishing trust in AI-assisted decisions is critical for fostering confidence among experts and researchers. However, standard explanation methods may not fully meet clinical needs, offering raw data, such as saliency maps, rather than human-readable text and auditabl...

An explainable AI framework using wearable IMU-based motion sensing for estimating and explaining motor skill improvement in school-based Baduanjin education