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· SN Business & Economics· 0 citations
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.
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· International Journal of Adv...· 0 citations
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· International Journal of Adv...· 0 citations
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· Frontiers in Human Dynamics· 0 citations
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· Frontiers in Applied Mathema...· 0 citations
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.· Frontiers in Future Transpor...· 0 citations
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· International Journal of Adv...· 0 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
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.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
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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