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explainable ai

2,590 papers

#explainable ai Open access Oct 2026

Fairness, Trust and Understanding As Preconditions and Predictors for Industry 5.0 AI Adoption

Background Workplace adoption of AI technologies depends, not only on technical performance, but also on whether people perceive these systems as fair, trustworthy, and understandable. Existing research utilises varied definitions for these concepts, impeding our understanding of how these factors contribute to AI adop...

Siobhan B O’Neill, Padraigh Jarvis, Kenneth N. Brown · 0 citations
#explainable ai Oct 2026

From Rules to Autonomous Agents: The Evolution of Artificial Intelligence, Human-AI Integration, and the Governance of Agentic Systems-A Review

Artificial intelligence has evolved from rule-based symbolic systems into learning architectures capable of perception, prediction, content generation, reasoning, planning, tool use, and increasingly autonomous action. This qualitative literature review examines this transition as more than a technological chronology....

Loso Judijanto · 0 citations
#explainable ai Open access Oct 2026

Kummer congruences for the values b^r E_r(a/b) of the Euler polynomials at rational points, and

Let E_r(x) be the Euler polynomials and let p be an odd prime. We prove that for every rational a/b with p not dividing b the numbers f_r = b^r E_r(a/b) are p-integral and satisfy f_r == f_r' (mod p^k) whenever r == r' (mod (p-1) p^(k-1)) and r, r' >= k; this is the only hypothesis. The proof is elementary: f_r is the...

Roberto Blanco Gómez · 0 citations
#explainable ai Open access Oct 2026

Counterexamples and corrections concerning a 2025 paper on Ulam stability of a fractional boundary-value problem

This independent mathematical comment examines the published formulations in I. Nasrallah, R. Aouafi and S. Kouachi, Mathematics 13 (2025), 157, DOI: 10.3390/math13010157. An explicit example satisfies the printed hypotheses of the uniqueness theorem while admitting infinitely many solutions because the stated Green co...

Zeraoulia Rafik · 0 citations
#explainable ai Open access Oct 2026

An AI- and IoT-Enabled Smart Food Donation Management System with Explainable Food-Risk Prediction, Safe-Time Forecasting and Automated NGO Assignment

Surplus cooked food from restaurants, hotels and cafés is often discarded because donors cannot verify its safety or reach an NGO in time. This paper presents a Smart Food Donation Management System that combines low-cost IoT sensing, explainable machine learning and automated NGO allocation in one web platform. An ESP...

Dr. Manoj Singh S. Mathavencie Sudhakar · 0 citations
#explainable ai Open access Oct 2026

From Compliance Burden to Organizational Resilience: A System Dynamics Model of AI Risk Governance in SMEs

The paper provides a system dynamics model that would explain the way in which small and medium-sized enterprises (SMEs) can use AI compliance as an administrative burden, rather than an organizational resilience capacity. Based on the dynamic capabilities theory, organizational resilience studies, AI risk management p...

Osman Angeles Conteh, Alimamy Kamara, Aminata Kera Conteh · 0 citations
#explainable ai Open access Oct 2026

LUCID: Lipid-featured Urine Cytology with Intelligent Detection for Non-Invasive Early Diagnosis of Bladder Cancer

Leveraging its non-invasive and convenient nature, urinary cytology offers a way for the early diagnosis and surveillance of bladder cancer (BCa). However, its sensitivity remains substantially inferior to the histopathological gold standard, rendering it inadequate to support precise clinical diagnosis. Here, we devel...

Zhe Hao, Jianlin Liu, Tinghe Fang et al. · 0 citations
#explainable ai Open access Oct 2026

CanaryCap-Stego: Steganographic Capability Canaries for Detecting Agentic-AI Tool Misuse and Hidden Retrieval Abuse

The final CanaryCap-Stego research package includes the original manuscript and supplementary materials, alongside an implementation. Its documentation provides: A quick-start guide for installation, configuration, and execution. An inventory of the original research files, with checksums to verify their integrity. Tec...

Mohammad Nassar · 0 citations
#explainable ai Open access Oct 2026

Beyond AI Tutors: A Human-Centred Framework for Goal-Driven Learning Agents in Education

Artificial intelligence is changing education by offering new ways to explain concepts, support teachers, and personalise student learning. However, many conventional educational chatbots focus on answering individual questions rather than coordinating the complete learning process. Students often need more than an ans...

Ghodakhe Keshav, Prof. Y.G.Suryawanshi, Dr. H.B.Jadhav · 0 citations
#explainable ai Open access Oct 2026

Multilayer Transparent Electrodes: Design, Fabrication, Performance, and Applications

Indium tin oxide (ITO) is the benchmark transparent conductor for displays and for electrochemical and optical sensors, but its brittleness, cost, and indium supply risk limit its use in flexible, large-area devices. Oxide/metal/oxide multilayers, namely transparent conducting oxide (TCO)/metal/TCO stacks such as ITO/m...

Edmunds Zutis, Ainārs Ozols, Ilmārs Sekacis et al. · 0 citations
#explainable ai Book Oct 2026

Balancing Innovation with Ethical Values: A Bibliometric Analysis of Ethical AI Research Trends

The ethical aspect of artificial intelligence (AI) has received a lot of academic interest as AI technologies continue to draw societies, economies, and systems of governance. The bibliometric survey provides a systematic assessment of the research trend, the topic development, and an impactful contribution to the rese...

Dhanashree Nagar, Dr. Kshama Ganjiwale, Amrita Baid More et al. · 0 citations
#explainable ai Open access Oct 2026

Why Enterprise AI Projects Fail: Platform-First Thinking

A $2.3M AI platform launch resulted in zero adoption after 90 days. David Ohnstad explains the critical mistake: building infrastructure before understanding what problems it actually solves. The real roadmap starts with user demand, not infrastructure. Full article: https://davidohnstad.net/why-enterprise-ai-projects-...

David Ohnstad · 0 citations

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MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

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