explainable ai

Reliability-Audited Explainable AI for Multi-Class Skin-Lesion 2 Triage Under Cross-Device Domain Shift

Background/Objectives: Reliable skin-lesion AI requires evaluation beyond the development distribution. This study assessed whether a source-developed multi-class system preserves discrimination and reliability when transferred to an unseen smartphone-acquired domain. Methods: A source-only multimodal four-class classi...

Key Data Analytics Trends to Explore Before Choosing a Data Analytics

Data analytics is changing how organisations operate, plan, and compete. Businesses use data to understand customer behaviour, improve services, reduce costs, and identify new opportunities. As digital systems expand, companies collect information from websites, applications, transactions, supply chains, and customer i...

A System Dynamics Approach to Modeling Trust Dynamics in Conversational AI

Abstract Trust plays a central role in how users adopt and rely on conversational AI systems. Research shows that trust does not develop linearly or remains stable over time. Although initially it often increases, it can fluctuate, decline, and even collapse over time, even when the AI’s performance remains constant. B...

AI still has a vocabulary problem: toward terminological accountability in artificial intelligence

Navigating the Legal Architecture of AI

A state that ignores a 95.6% accurate landslide prediction and then invokes force majeure is not applying a legal doctrine it is abusing one. Force majeure and the Act of God defence share a single operative requirement. Machine learning has destroyed that requirement. AUC values for flood and landslide prediction rout...

Practical Business Negotiation

Known for its practical approach and real-life examples, the third edition of Practical Business Negotiation continues to equip readers with the necessary knowledge and tools to negotiate well in business. This latest edition comes with a refreshed set of case studies and addresses the topic of Artificial Intelligence...

E8 Lattice Coherence Threshold for Live-Trading Signal Emergence — E8 Intelligence Research

We propose a critical coherence threshold at 132 × φ² ≈ 344 Hz where E8 root vector alignment crosses from statistical noise into deterministic signal structure within live AI trading ecosystems. The 240 E8 roots map directly to a 240-dimensional feature space in which market microstructure states achieve phase-locked...

A Human-Centered Multi-agent Architecture Framework for AI-Based Hybrid Decision Support in Product Engineering

ХЛОПКОВАЯ СТРАТЕГИЯ ТАДЖИКИСТАНА: ГЛОБАЛЬНЫЕ ТРЕНДЫ, ЯВНЫЕ И ЛАТЕНТНЫЕ РАЗРЫВЫ И ИНТЕЛЛЕКТУАЛЬНАЯ ЭКОСИСТЕМА АГРОЭКСПЕРТА

This study examines the strategic transformation of Tajikistan’s cotton economy in the context of global market trends, declining production capabilities, institutional constraints, and the need to improve farmers’ economic incentives. Drawing on USDA data for 15 cotton-producing countries, Tajikistan’s national statis...

When information is not enough: AI-enabled advisory and the fragile pathways of low-carbon transitions under system constraints

CONTEXT Low-carbon rice farming is widely recognized as a key strategy for agricultural decarbonization, yet adoption remains limited among smallholder farmers despite expanding AI-enabled advisory and increasing awareness of climate risks. Existing adoption-based models provide limited explanation for why improved inf...

Learning the world: A Critical Survey of World Models for Physical AI

A world model is a learned system that predicts what will happen next under a candidate action, given what an agent has observed and done. With one, an agent can compare actions before it commits, practice skills in imagination and notice when the world surprises it. The idea dates to 1990 and now sits at the center of...

ADMP-GCN: Interpretable Adaptive Message Passing Graph Learning for Patient-specific EEG Seizure Prediction with Human-in-the-Loop Validation

Automated seizure prediction based on multichannel Electroencephalography (EEG) using Artificial Intelligence (AI) is a challenging task that mandates accurate and interpretable results for improved clinical decisionmaking.However, brain connectivity modelling on the evolving patient-specific and seizure-dynamic EEG si...