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explainable ai

2,278 papers

#explainable ai Sep 2026

Affective AI ethics in tourism: Extending the SOR framework with indigenous relational constructs

An indigenous relational construct-based culturally informed framework on the ethics of affective AI in tourism that incorporates indigenous constructs into the stimulus–organism–response framework is presented, demonstrating explanatory power beyond universalist ethics and fast trust models.

Abhijit Pandit, Saugata Chakraborty, Tiny Tanushree Gohain · 0 citations
#explainable ai Sep 2026

Is AI a moral expert?

It is concluded that, while AI may be considered a valuable tool for supporting human moral deliberation, it cannot by itself serve as an expert moral decision-maker.

Lane DesAutels · 0 citations
#explainable ai Open access Sep 2026

Artificial Intelligence for Drug-Likeness Prediction: An Intelligent Framework for Chemical Compound Screening

An AI-based framework for predicting drug-likeness using molecular descriptors derived from chemical structures is proposed that integrates data preprocessing, feature selection, machine learning model development, and performance evaluation using metrics such as accuracy, precision, recall, F1-score, and AUROC.

Manharan Yadav · 0 citations
#explainable ai Review Open access Sep 2026

The Role of AI in Enhancing Financial Decision-Making in Commerce

Financial decisions in commerce—whom to lend to, what to stock and at what price, when to hedge, which transactions to flag—have always been made under uncertainty, time pressure and cognitive limitation. Artificial intelligence (AI) alters this situation by sharply reducing the cost of prediction and by extracting sig...

Prof. (Dr.) Smruti Ranjan Rath, Dr. Madhabi Mehta, Ejim Kenneth Ejimne³, Ram Prakash Yadav · 0 citations
#explainable ai Open access Sep 2026

Quantum sovereignty and constitutional asymmetry: mapping the sovereignty gap in Puerto Rico and the Dominican Republic

Quantum technologies are advancing faster than the institutional capacities of most small island jurisdictions, creating a structural vulnerability that remains largely unaddressed. This article introduces the Quantum Sovereignty Gap (QSG) to explain why Puerto Rico (PR) and the Dominican Republic (DR) risk entering th...

Karen L. Orengo-Serra · 0 citations
#explainable ai Open access Sep 2026

An XGBoost–logistic regression hybrid stacking model for breast cancer outcome prediction

Accurate prediction of breast cancer outcomes remains challenging due to high-dimensional, imbalanced clinical datasets and the need to balance predictive performance, calibration, interpretability, and model simplicity. We propose an AICc-guided hybrid stacking framework that integrates Logistic Regression...

Oyetayo Oyebisi, W. Chacha, F. Amoyedo · 0 citations
#explainable ai Open access Sep 2026

A context-aware and human-centered framework for road safety assessment using semantic scene understanding

The proposed framework provides a reliable and explainable approach for assessing perceived road safety by integrating semantic scene understanding with contextual reasoning and establishes a reproducible foundation for future research in interpretable transportation systems, human–AI alignment analysis, and road scene...

Imad Tbaileh, Ahmed Radwan, Oroob Yaseen et al. · 0 citations
#diffusion models Review Open access Sep 2026

AI Driven Multidomain Research: New Frontiers in Science, Business and Technology

Artificial intelligence (AI) is no longer confined to computer science. The same families of learning algorithms now predict protein structures, price financial assets, design semiconductor layouts and personalise customer journeys. This diffusion has created a new kind of scholarship in which methods, data and problem...

Devanand Ch E. B. Khedkar, Chetan Khedkar, Dasharath Suryavanshi Sapna R. Chavan · 0 citations

From tech blogs

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Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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