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2,810 papers
EASCI (Experience, Articulation, Structuring, Consolidation, Innovation), a five-stage framework that separates cognitive tasks and restricts AI involvement, is introduced, to mitigate working-memory overload.
A sequential political-economy model in which an AI vendor chooses auditability and substantive mitigation, a deployer monitors after adoption while facing switching costs, and enforcement depends on verifiable evidence is developed.
This work contributes longitudinal evidence on sustaining 4DWW in agile software development and proposes two conceptual artifacts: a lifecycle model of the 4DWW and a 4DWW survival matrix, explaining how external pressures and management rationale rollback risk.
This work provides a conceptual foundation for governance-aware, adaptable, and AI-first software engineering methods by proposing a metamodel that treats autonomy not as a fixed property of an actor, but as a derived, situation-dependent authority assignment determined by task, context, and collaboration pattern.
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This review critically evaluates the role of AI throughout the cancer theranostic workflow, with a focus on its potential to address the key clinical and technical challenges that continue to limit the routine implementation of personalized radiopharmaceutical therapy.
The developed XAI framework, together with the pathogen-specific predictive models, the pathogen-selective fragment lists, and their mapping onto the chemical structures, is able to provide a highly valuable and practical guide to the rational design of new antimicrobial agents.
Artificial intelligence has intensified ethical, legal, and social inquiry, but generative systems expose a domain-specific limit in the conventional ELSI framework. This article argues that when AI operates as a cultural producer or perceptual mediator, aesthetics constitutes an analytically distinct dimension. AI-gen...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22734670. What the paper claims This is an evidence map of 11,628 PubMed-indexed records on generative language models in healthcare, January 2023 to June 2026, built to answer one...
With its high design freedom, wide material compatibility, and versatile processes, 3D printing technology has emerged as a revolutionary approach to the fabrication of flexible electronic devices, and has been shown to have tremendous applications in smart wearables, healthcare monitoring systems and soft robots. But...
This repository contains the extraction dataset, the explanation-evaluation reclassification, and the association analysis supporting the systematic mapping study of explainable artificial intelligence (XAI) in medicine (383 studies from Q1/Q2-indexed journals, 2020–2025).
Communication education increasingly requires students to work across two linked capabilities: critically evaluating professional communication materials and using generative AI (GenAI) with judgment, transparency, and ethical care. This article presents a “Broken and Repair” case-study assessment, developed in a postg...
Artificial intelligence (AI) models, particularly deep learning and machine learning approaches, are increasingly developed for endodontic tasks, including detection of periapical pathosis, identification of vertical root fractures, characterisation of root canal morphology, and prediction of treatment outcomes. Most h...
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.
Google DeepMind and UK government work together to reduce planning assessment times
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
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