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explainable ai

2,878 papers

#artificial intelligence Open access Sep 2026

Analysis Capability Dynamics of E-Commerce MSMEs in Adopting Generative AI Technology for Content Strategy Efficiency Creative

The findings show that detecting capability develops organically through a bottom-up process, with creative staff acting as information gatekeepers, and transforming capability emerges by restructuring conventional workflows into a human–AI hybrid model, in which AI generates ideas and drafts, while creative staff perf...

Anthonius S. Hutabarat, Dewi Tamara, Irawan R. D. Budianto et al. · 0 citations
#explainable ai Sep 2026

Semantic Layer-Enabled AI

This article explains how ontology-based semantic layers work and advocates for their use as versatile enterprise tools. They add shared meaning, context, and governance to data, improving integration, analytics, oversight, and AI reliability across organizational systems.

Sally Hubbard, Elena Loukoianova, Hsiao-Ying Lin · 0 citations
#explainable ai Open access Aug 2026

Analisis Sentimen Berbasis SHAP untuk Mendukung Perencanaan Strategis Sistem Layanan M-Paspor

Transformasi digital layanan publik melalui aplikasi M-Paspor menghadapi tantangan signifikan terkait stabilitas sistem dan kepuasan pengguna. Melalui pendekatan Explainable AI, metode SHAP diimplementasikan untuk membongkar mekanisme internal algoritma XGBoost, untuk mengidentifikasi kontributor utama sentimen negatif...

Hagi Semara, Putera, Made Lanang et al. · 0 citations
#explainable ai Open access Aug 2026

Autonomous Enterprise Platforms: A Framework for AI-Guided Decision Loops, Predictive Intelligence, and Continuous Organizational Adaptation

A conceptual Autonomous Enterprise Platform based on continuous AI-guided decision loops integrating enterprise sensing, contextual intelligence, predictive analytics, decision intelligence, prescriptive policies, autonomous execution, learning, and governance is proposed.

Shekar Vollem · 0 citations
#explainable ai Open access Aug 2026

Ethical data governance for sensitive document classification under the LGPD

The findings indicate the feasibility of the BERT model as an initial, human-in-the-loop screening stage for ethical data governance in the public sector.

Gomes Braz Ingrit dos Anjos, Luiz Augusto de Oliveira Almeida, Ueuder Castro Do Nascimentoa et al. · 0 citations
#explainable ai Open access Aug 2026

KORA: A Knowledge-Oriented Open Reference Architecture for GovTech and Trustworthy Public AI.

KORA proposes the concept of Data Space Lite: lightweight semantic infrastructures based on W3C standards and Data Spaces principles for rapidly deploying reusable interoperability layers in GovTech environments.

Mélida López, Francisco Sáez, Bárbara Ribeiro et al. · 0 citations
#explainable ai Aug 2026

A Cryptographically Secure and Explainable AI Framework for Automated Health Insurance Claim Processing Using the Insurefusionnet

InureFusionNet is proposed, a hybrid explainable structured ensemble framework integrating heterogeneous models of deep feature learning, uncertainty-aware prediction, interpretable boosting mechanisms, and high-performance gradient- boosting classifiers through a fusion strategy for robust health insurance claim appro...

Indirakumar Rajendiran, Sam Cherub Hameem Pillay · 0 citations
#explainable ai Open access Aug 2026

The Effect of AI Skin Diagnosis Service Quality on AI Source Credibility, Brand Trust, and Purchase Intention: Focusing on a Trust Transfer-Based Serial Mediation Model

The findings reveal that service quality positively affected AI source credibility, brand trust, and purchase intention, and suggest that trust in AI systems can be transferred to brand trust.

Nameun Kim, Hyojin Jo · 0 citations
#machine learning Preprint Sep 2026

CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN

CRAFT, which stands for Cold-start Reasoning Alignment Alignment via Fine-Tuning, is proposed, a data-centric method to autonomously generate a verified dataset of (input, trace, label) triplets, requiring substantially less compute and wall-clock time than GRPO-based methods.

Pranshav Gajjar, V. K. Shah · 0 citations
#artificial intelligence Preprint Sep 2026

Causal Evidentiary Governance for High-Risk Machine Learning Systems

Evaluation on the German Credit dataset shows that harm associated with specific causal pathways can be substantially understated by associational fairness metrics, and a proof-of-concept implementation demonstrates operationally plausible throughput and highlights relevant performance tradeoffs.

Sama L. Kareem, B. Celiktas · 0 citations

From tech blogs

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Microsoft Research Blog Nov 5, 2026

Formally verifying agent-written full-stack web apps with PDD Kit

AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…

Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

GPT-Lab Nov 3, 2026

Sovereignty Is the Option to Leave

Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.

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