explainable ai

Capacity Degradation Estimation of Lithium-Ion Batteries Using Explainable Machine Learning

This research presents a machine learning approach to predict the capacity degradation of lithium-Ion battery, integrated with Explainable AI to improve model explainability and shows that charge time has the most impact on capacity degradation prediction.

Trust and the reliability of AI algorithms for clinical decision-making support in medicine: the MIRACLE case study

This paper distinguishes technical reliability from trust in AI-supported clinical decision-making, arguing that the two belong to distinct registers that current debates tend to elide and proposes replacing the expression "trustworthy AI" with "technically reliable AI," a distinction that relocates the conditions of t...

Problematisation and reconfiguration of knowledge in AI-embedded agile software development

An agility paradox linking reactive, efficiency-oriented AI adoption to potential constraints on proactive agile capabilities is developed, linking reactive, efficiency-oriented AI adoption to potential constraints on proactive agile capabilities.

Artificial Intelligence in Social Insurance: Administrative Promise, Legal Risk, and the Emerging Threat of Deepfake Fraud

Evaluating the potential of AI in social insurance and to identify the conditions under which it can enhance institutional capacity without compromising legality, procedural justice, and public trust finds AI can enhance communication, case triage, document management, workload forecasting, and fraud identification.

FAIRNESS-AWARE RECOMMENDER SYSTEMS IN PRACTICE: A SCOPING REVIEW OF MODELS, EVALUATION PROTOCOLS, AND OPEN CHALLENGES

The findings indicate that fairness-aware recommender systems increasingly integrate fairness objectives with recommendation performance, while highlighting persistent gaps in evaluation standardization, real-world deployment, scalability, interpretability, and cross-domain validation.

How Artificial Intelligence Facilitates Collaborative Governance? Research on Mechanisms and Multi‐Dimensional Effects Based on Triple Entities

A quantifiable multi‐stakeholder governance framework and actionable policy insights for China and the Global South are offered and econometric evidence from difference‐in‐differences, threshold regressions, and spatial econometric models robustly addresses concerns about AI.

ARTIFICIAL INTELLIGENCE-ENABLED REGTECH FOR KYC, FINANCIAL COMPLIANCE, AND REGULATORY REPORTING: APPLICATIONS, RISKS, AND FUTURE DIRECTIONS

This narrative review explains the technical architecture of artificial intelligence-enabled RegTech systems and examines their use in know-your-customer procedures, financial compliance monitoring, investigations, and regulatory reporting.

Is AI Becoming the New Manager?

This blog examines how AI-based advice seeking may affect managerial legitimacy and manager-employee relationships and argues that the important issue is not whether AI will formally replace managers, but whether increasing dependence on AI for workplace advice will change how employees perceive and use human managers.

Artificial intelligence capability and project performance: integrating dynamic capabilities theory and the knowledge-based view

The findings indicate that AI capability positively influences knowledge integration, project agility, and project performance, and that AI capability improves project performance by strengthening knowledge integration, which subsequently enhances project agility.

Explainable AI for evaluating hospitalization outcomes based on electronic health records for chronic disease patients

Learning human aligned explanations through supervised aggregation of XAI methods for Arabic sentiment analysis

This study provides the first investigation of human-supervised XAI aggregation in Arabic, offering new insights into balancing faithfulness and plausibility in explainable NLP.

Structural links between AI-art literacy, VR presence, visual-language proficiency, and experimental imaging performance among university students.

Novelty lies in a production-centered, theory-consistent pathway from domain-specific AI-art literacy to an authentic, rubric-and-logs outcome via visual-language proficiency, with VR presence as a boundary condition, delivered through a reflective-formative PLS-SEM architecture and a large, multi-city Chinese sample.