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2,868 papers
It is demonstrated that multimodal sensing with explainable AI improves operational visibility and educational analytics and the smart lab framework is proposed, supporting safer, more efficient, and data-driven learning across engineering disciplines.
Evidence is provided that ensemble-based frameworks currently offer the most effective balance between predictive accuracy, robustness, and clinical feasibility, and future research should emphasize multi-center external validation and explainable AI frameworks.
The study presents one of the first regional mappings of the adoption of generative AI in South American journalism and proposes an analytical model that explains how the technology is being institutionalized in news organizations within the South American context.
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This study investigates the influence of Artificial Intelligence-driven administrative practices on principals’ effectiveness in public senior secondary schools in Bauchi State, Nigeria and provides empirical evidence on the role of emerging AI technologies in improving principals’ administrative effectiveness.
The Human-Centric and Trustworthy Machine Learning (HCT-ML) framework is developed as an operational decision-support profile for ITS and provides an evidence-informed and reproducible protocol that can be tested through stakeholder studies, simulations, and field deployments.
The study suggests that explainable AI is a crucial factor in building intelligent, reliable, accountable, transparent, and effective AI-powered systems that can be deployed in realistic environments for decision making.
The widespread adoption of generative artificial intelligence (AI) has significantly transformed the way people acquire knowledge, solve problems, and make decisions in both academic and professional settings. While these technologies improve efficiency and accessibility, their growing use has raised important psycholo...
This research introduces a tiered multi-agent architecture grounded in Human-Centered eXplainable AI principles that contributes an adaptable and generalizable framework and foundational artifacts for trustworthy AI teammates.
SmartCrop AI is proposed as a practical digital platform that brings machine-learning based crop and yield prediction, soil-suitability assessment, an AI advisory component, simulated IoT data, mandi-price information and farmer-oriented reporting.
Results showed that topic-specific classifiers reduced subgroup disparity compared to the topic-general classifier, and a factorization approach to decompose complex data into simpler components by reducing topic dimensions of clinical transcripts was proposed.
A Blog post by Dharma-AI on Hugging Face
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
· gpt-lab.eu
Nov 3, 2026
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.
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
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